In 2012 we introduced you to the Digital Marketing Makeover . A bid by us and a team of experienced Bing Ads Accredited Professionals to help small businesses thrive in economical challenging times by offering digital marketing advice. So far we’ve helped very creative chef from Cheshire , a Scottish entrepreneur and a catering business . Today we’re casting an analytical and creative eye on a manufacturing business – The Paper Cup Company .
As you expect from a business that…(read more)
In 2012 we introduced you to the Digital Marketing Makeover . A bid by us and a team of experienced Bing Ads Accredited Professionals to help small businesses thrive in economical challenging times by offering digital marketing advice. So far we’ve helped very creative chef from Cheshire , a Scottish entrepreneur and a catering business . Today we’re casting an analytical and creative eye on a manufacturing business – The Paper Cup Company .
You’ve seen the headlines. Google is rolling out secure search for everyone. Marketers shouldn’t fear this change though; this is just another step towards progress in the ever-changing world of search. Instead of burying ourselves in organic keyword lists, we must start taking a more holistic approach to search marketing and begin taking steps towards seamlessly combining paid and organic search data. With developing products and concepts like Google Now and One Microsoft, the future of search is thrilling. Content strategies and social marketing must complement and integrate with every aspect of search; this is only the beginning of the next chapter of search in which keywords are only a small part of the puzzle.
Two years ago Google started encrypting their data by defaulting any search by a user signed into Google to Secure Sockets Layer, more commonly known as SSL. Expecting to lose around 10% of search referral data, some digital marketers were upset but accepting and understanding. After all, they could still get a general idea of how users were getting to their site and if a user is signed into Google then encrypting via SSL makes sense for privacy reasons. Releasing a statement on their blog, it was hard to argue with the logic:
“As search becomes an increasingly customized experience, we recognize the growing importance of protecting the personalized search results we deliver. As a result, we’re enhancing our default search experience for signed-in users.”
After Google made the change, a precedent was set and less than a year after Google made the first change, Firefox released a version of their browser that defaulted to Google’s secure search. A few months after that, Safari in iOS 6 began using Google’s secure search. And a few months after that, the latest release of Chrome began encrypting all searches submitted via its omnibox. All of these changes contributed to the steadily increasing percentage of search referral data that was being shown as “not provided.”
With privacy becoming increasingly important, it should be no surprise that this move was made. Not only is a niche being carved out for privacy-focused products, Google has always placed a high emphasis on improving the security of their searches. Their awareness of this rising consumer value is evidenced by the statement they released in the wake of the change:
“We added SSL encryption for our signed-in search users in 2011, as well as searches from the Chrome omnibox earlier this year. We’re now working to bring this extra protection to more users who are not signed in.”
Fortunately, there are still ways for you to understand search referral data. By using carefully orchestrated Google AdWords campaigns in concert with Compete PRO, you will have access to both organic and paid search referrals. In a search environment that will soon be dominated by encrypted search, not only will this put you ahead of the competition, but it will continually offer you insights into how customers are getting to your site and what you should focus your efforts on optimizing.
How can you still see your organic search referral data with 100% “Not Provided”
With Compete PRO, not only can you see the search volume that a certain search term brings to your site, you can see other search-related data as well:
- Keyword & Referral Share: Obviously the most important and the most valuable, the actual search queries (and the share of the total search referral visits that each query makes up) that are bringing visitors to your site.
- Paid & Natural Share: For each search term, you can see how much of the traffic is natural and how much is paid. If you are bidding on the terms then you probably already have a good idea of these numbers already. However, this data can prove to be invaluable when looking at your competitors.
- Time Index: Along with search referral share and paid/natural share, we also offer two different time indexes for each search term. The first, Average Time Index, is an engagement metric found in Site and Category Search Referral Reports. This metric is indexed to 100, with 100 representing the keyword term that resulted in the most average time per visit being spent on the site. The other metric, Total Time Index, is also indexed to 100, with 100 representing the keyword term that resulted in the most total time spent on the site.
- Search Insights: Compete PRO also offers seven different search insights which are preset filter configurations based on common data use cases for Search marketing. They call out valuable insights in the data by automatically setting the filters to predefined ranges, reducing the noise in large data sets. You can see the following search insights within Compete PRO: Highly engaging keywords, high traffic keywords, paid keywords, natural keywords, engaging long tail keywords, enthusiast keywords, and long tail keywords.
Not only are all of these data sets crucial to have for your own site, using Compete PRO also allows you to gather data from your competitors’ sites as well. This information was valuable before, but now that the day “Not Provided” makes up 100% of your competitors’ search referral data is right around the corner, and the only way to see it is through Compete PRO, it is invaluable. Not convinced? Try out a free trial of Compete PRO today or contact us if you have any questions.
If you want more advanced keyword analysis features, check out Ascend, which provides marketers with visibility into crucial data on the search engine results page (SERP) to help reduce overall spend, pinpoint and mitigate competitive exposure, optimize share of voice, and align search with the shoppers path-to-purchase.
In late 2011, Google announced an effort to make search behavior more secure. Logged-in users were switched to using httpS from http. This encrypted their search queries from any prying eyes, and kept from being passed on to websites the users visits after seeing search results.
This led to the problem we, Marketers, SEOs, Analysts, fondly refer to as not provided .
Following revelations of NSA activities via Mr. Snowden, Google has now switched almost all users to secure search, resulting in even more user search queries showing up as not provided in all web analytics tools.
At the moment it is not clear whether Bing, Baidu, Yandex and others will move to similarly protect users’ search privacy; if and when they do, the result will be loss of even more keyword-level user behavior data.
Initially, I was a little conflicted about the whole not provided affair.
As an analyst, I was upset that this change would hurt my ability to analyze the effectiveness of my beloved search engine optimization (SEO) efforts – which are really all about finding the right users using optimal content strategies.
But it is difficult to not look at the wider picture. Repressive (and some not-overtly repressive) regimes around the world aggressively monitor user search behavior (and more). This can place many of our peer citizens in grave danger. As a citizen of the world, I was happy that Google and Yahoo! want to protect user privacy.
I'm a lot less conflicted now. I've gone through the five stages in the Kubler-Ross model. Besides, I've also come to realize that there is a lot I can still do!
In this post I want to share four angles on secure search:
2. What Is Not Going Away. #silverlinings
While not provided is not an optimal scenario, you'll see that things are not as bad as initial impressions might indicate, yes there are new challenges, but we also have some alternative solutions, and realize that the SEO industry is not done innovating. Ready?
No keyword data in analytics tools.
We are headed towards having zero referring keywords from Google and, perhaps, other search engines.
Depending on the mobile device and browser you are using (for example, Safari since iOS 6), you have already been using secure search for a while regardless of the search engine you use. So that data has been missing for some time.
There are a number of "hacks" out there with promises of getting close enough keyword data, or for marrying not provided with some of the remaining data and landing pages. These are well meaning, but almost always yield zero value or worse drive you in a sub-optimal direction. Please been careful if you choose to use them.
No keyword data in competitive intelligence/SEO tools.
Perhaps you (like me) use competitive intelligence or SEO tools to monitor keyword performance. For example, for L'Oreal:
Secure Search will also impact data in these tools. It will be increasingly distorted because it will reflect only traffic from the small audience of visitors who are not yet using secure search or are using other non-secure search engines or only the type of people who allow their behavior to be 100% monitored – including SSL/httpS. Sample and sampling bias.
You can read this post to learn how these tools collect data: The Definitive Guide To (8) Competitive Intelligence Data Sources.
I really loved having this data. It was such a great way to see what competitors were doing or where I was beating them on paid or organic or brand or category terms. Sadly, it does not matter which tool you use. These tools will only show you a more distorted view of reality. Please be very careful about what you do with keyword data from these tools (though they provide a lot of other data, all of which was of the same quality as in the past).
These changes impact my AdWords spend sub-optimally. A lot of the keywords I used to add to my campaigns came from the long, long tail I saw in my organic search data (I would take the best performers there and use PPC to get more traffic) and from competitive intelligence research. With both of these sources gone, my AdWords spend may take a dive because I can't find these surprising keywords — even using the tools you'll see me mention below! How is this in Google's interest?
No keyword-level conversion analysis.
We have a lot of wonderful detailed data at a keyword level when we log into SiteCatalyst or WebTrends or Google Analytics. Bounce Rates, % New Visits, Visit Duration, Goal Conversions, Average Order Value.
All this data will no longer be available for organic search keywords.
As hinted above, our ability to understand the long tail — often as much as 80% of search traffic — will be curtailed. We can guess our brand terms and product keywords, but the wonderful harvest of category-type, and beyond, keywords is gone.
Current keyword data is only temporarily helpful.
Remember: On a daily basis 15% of the queries on Google have never been seen before by the search engine. Daily! For all 15 years of Google's existence!
That is one reason the data we have for the last year or so, even as not provided ramped up, might only be temporarily helpful in our analysis.
Another important reason historical data becomes stale pretty quickly is that any nominally functioning business will have new products, new content, new business priorities, and all that impacts your search strategy.
Finally, with every change in the search engine interface the way people use search changes. This in turn mandates new SEO (and PPC) strategies, if we don't want to fail.
So, use the data you have today for a little while to guesstimate your SEO performance or optimize your website. But know that the view you have will become stale and provide a distorted view of reality pretty soon.
While we are losing our ability to do detailed keyword analysis, we are retaining our ability to do strategic analysis. Search engine optimization continues to be important, and can still get a macro understanding of performance and identify potentially valuable keywords.
Aggregated search engine level analysis.
The Multi-Channel Funnels folder in Google Analytics contains the Top Conversion Paths report. At the highest level, across visits by focusing on unique people, the report shows the role search plays in driving conversions.
You can see how frequently it is the starting point for a later conversion, you can see how frequently it is in the middle, and you can see how frequently it is the last click.
I like starting with this report because it allows us to have a smarter beyond-the-last-click discussion and answer these questions: What is the complete role of Search in the conversion process? How does paid search interplay with organic search?
From there, jump to my personal favorite report in MCF, Assisted Conversions.
We can now look at organic and paid search differently, and we are able to see the complete value of both. We can see how often search is the last click prior to conversions, and how often it assists with other conversions.
The reason I love the above view is that for each channel, I'm able to present our management team a simple, yet powerful, understanding of the contribution of our marketing channels – including search.
Selfishly, now we can show the complete value, in dollars and cents, we deliver via SEO.
[Bonus: For more on next steps and attribution modeling please see: Multi-Channel Attribution Modeling: The Good, Bad and Ugly Models.]
If you are interested in only the last-click view of activities (please don't be interested in this!), you can of course look at your normal Channels or All Traffic reports in Google Analytics.
This is a simple custom report I use to look at the aggregated view:
As the report above demonstrates, you can still report on your other metrics, like Unique Visitors, Bounce Rates, Per Visit Value and many others, at an aggregated level. You can see how Google is doing, and you can see how Google Paid and Organic are doing.
So from the perspective of reporting organic search performance to senior management, you are all set. Where we are out of luck is taking things down from here to the keyword level. Yes, there will still be some data in the keyword report, but since not provided is an unknown unknown, you have no idea what that segment represents.
Organic landing pages report.
Search engine optimization is all about pages and the content in those pages.
The top landing pages getting traffic from organic search. And of course our Acquisition, Behavior, Outcome metrics.
See Page Value there? Now you also know how much value is delivered when each of these pages is viewed by someone who came from organic search.
So let's say you spent the last few weeks optimizing pages #2, #3 and #5; well, now you can be sad that they are delivering the lowest page value from organic search. Feel sad.
Or, just tell your boss/client: "No, no, no, you misunderstood. I was optimizing page #4!" : )
The custom landing pages report also includes the ability drill down to keyword level, just click on the page you are interested in and you'll see this:
With every passing day this drilldown will become more and more useless. But for now, it is there if you want to see it.
Let me repeat a point. I've noticed some of our peer SEOs making strong recommendations to take action based on the keywords you are able to see beyond not provided. I'm afraid that is a career-limiting move. You have no idea what these words represent – head, mid, tail, something else – or what is in the blank not provided bucket. Be very careful.
Paid search keyword analysis report.
We all of course still have access to keyword level analysis for our paid search spend.
There is one really interesting bit in the paid search reports that you can use for SEO purposes.
When you submit your keywords and bids, the search engine will match them against user search queries. In Google Analytics you have Keyword, in your AdWords report, as above, but if you create a custom report you can drill down from Keyword to Matched Search Query. The latter is what people actually type. So for "chrome notebook," above, if I look at the Matched Search Query I can see all 25 variations the users typed. This is very useful for SEO.
You can download my custom report, it is #2 in this post: Paid Search/AdWords Custom Reports
Beyond this, be judicious about what inferences you draw from your paid search performance. Some distinguished SEO experts have advocated that you should use the distribution of visits/conversions/profits of your AdWords keywords and use that to make decisions about effectiveness of your SEO efforts. Others are advising you to bid on AdWords and guesstimate various things about SEO performance. Sadly these are also career-limiting moves.
When you look at your AdWords data, you have no idea which of these four scenarios is true for your business:
And if you don't know which is true — and you really won't with not provided in your way — is it prudent to use your AdWords performance to judge SEO? I would humbly suggest not.
If you want to stress test this,…. go back to your 2011 (pre-not provided) data for paid and organic and see what you can find. And remember since then Google has made sixteen trillion changes to how both paid and organic search work, and your business has at least made 25.
Don't assume that your SEO strategy should reflect the prioritizations implied by your AdWords keyword data. The reason SEO worked so well is that you would get traffic you might not have known/guessed/realized you wanted/deserved.
With not provided eliminating almost all of our keyword data, initially for some search engines/browsers and likely soon from all, we face challenges in understanding performance. Luckily we can avail ourselves of a couple of alternative, if imperfect/incomplete, options.
Here are the challenges Google's Webmaster Tools solves: Which search queries does my website show up for, and what does my click-through rate look like?
I know this might sound depressing, but this is the only place you'll see any SEO performance data at a keyword level. Look at the CTR column. If you do lots of good SEO — you work on the page title, url, page excerpt, author image and all that wonderful stuff — this is where you can see whether that work is getting you more clicks. You work harder on SEO, you raise your rankings (remember don't focus on overall page rank, it is quite value-deficient), you'll see higher CTRs.
You will see approximately 2,000 search queries. These are not all the search queries for which your site shows up. (More on this in the bonus section below.)
There are a couple of important things to remember when you use this data.
If you go back in history and do comparative analysis for last year's data when not provided was low, you'll notice that your top 100 keywords in Google Analytics or Site Catalyst are not quite the same as those in WebMaster Tools. They use two completely different sources of data and data processing.
Be aware that even if you sort by Clicks (and always sort by clicks), the order in which these queries appear is not a true indication of their importance (in GA when I could see it, I would see a different top 25 as an example). The numbers are also soft or directional. For example, even with 90% not provided Google Analytics told me I had 500 visits from "avinash kaushik" and not 150 clicks as shown above.
Despite these two caveats, Webmaster Tools should be a key part of your SEO performance analysis.
It is my hope that if this is how search engines are comfortable sharing keyword level data, that over time they will invest resources in this tool to increase the number of keywords and improve the data processing algorithms
1. Google's Webmaster Tools only stores your data for 90 days. If you would like to have this data for a longer time period, you can download it as a csv. Another alternative is to download it automatically using Python. Please see this post for instructions: Automatically download webmaster tools search queries data
2. GWT only shows you data for approximately 2,000 queries which returned your site in search results. Hence it only displays a sub-set of your query behavior data. The impact of this is in the top part of the table above, Impressions and Clicks. During this time period my site received 1,800k Impressions in search results, but GWT is only showing data for 140k of those impressions because it is only displaying 2,574 user queries. Ditto for Clicks. If I download all the data for the 2k queries shown in GWT, that will show behavior for just 8,000 of the 50,000 clicks my site received from Google in this time period. Data for 42,000 clicks is not shown because those queries are beyond the 2k limit in GWT.
Update: 3. In his comment below Jeff Smith shares a tip on how to structure your GWT account to possibly expanding the dataset to get more information. Please check it out.
Update: 4. Another great tip. Kartik's comment highlights that you can link your GWT account with your AdWords account and get paid and organic click data for the same keyword right inside AdWords. Click to read a how-to guide and available metrics.
Google Keyword Planner.
The challenge Google Keyword Planner solves: What keywords (user search queries) should my search engine optimization program focus on?
In the Keyword Planner you have several options to identify the most recent keywords — the most relevant keywords — to your website. The simplest way to start is to look for keyword recommendations for a specific keyword.
I choose the "search for new keyword and ad group ideas" section and in the landing page part type in the URL I'm interested in. Just as an example, I’m using the Macy's women's activewear page:
A quick click of the Get Ideas button gives us … the ideas!
I can choose to look at the Ad Group ideas or the Keyword Ideas.
There are several specific applications for this delightful data.
First, it tells me the keywords for which I should be optimizing this specific page. I can go and look at the words I'm focused on, see if I have all the ones recommended by the Keyword Planner, and if not, I can include them for the next round of search engine optimization efforts.
Second, I have some rough sense for how important each word is, as judged by Avg. Monthly Searches. The volume can help me prioritize which keywords to focus on first.
Third, if this is my website (and Macy's is not!), I can also see my Ad Impression Share. Knowing how often my ad shows up for each keyword helps me prioritize my search engine optimization efforts.
It would be difficult to do this analysis for all your website pages. I recommend the top 100 landing pages (check that the 100 include your top product pages and your top brand landing pages — if not, add them to the list).
With the advent of not provided we lost our ability to know which keywords we should focus on for which page; the Google Keyword Planner helps solve that problem to an extent.
You don't have to do your analysis just by landing pages. If you would like, you can have the tool give you data for specific keywords you are interested in. Beyond landing pages, my other favorite option is to use the Product Category to get data for a whole area of my business.
For example, suppose I'm assisting a non-profit hospital with its analytics and optimization efforts. I'll just drill down to the Health category, then the Health Care Service sub-category and finally the Hospitals & Health Clinics sub-sub-category:
Press Get Ideas button and — boom! — I have my keywords. In this case, I've further refined the list to only focus on a particular part of the US:
I have the keyword list I need to focus my search engine optimization efforts. Not based on what the Hospital CEO wants or what a random page analysis or your mom suggested, but rather based on what users in our geographic area are actually typing into a search engine!
A quick note of caution: As you play with the Keyword Planner, you'll bump into a graph like this one for your selected keyword or ad group ideas. It shows Google's estimate of how many possible clicks you could get at a particular cost per click.
Other than giving you some sense for traffic, this is not a relevant graph. I include it here just to show you that it is out there and I don't want you to read too much into it.
The challenge Google Trends tool solves: What related and fastest-rising keywords should I focus on for my SEO program?
Webmaster tools focuses us on clicks and the Keyword Planner helps us with keywords to target by landing pages. Google Trends is valuable because it helps expand our keyword portfolio (top searches) and the keywords under which we should be lighting a fire (rising searches).
Here's an example. I'm running the SEO program for Liberty Mutual, Geico, AAA or State Farm. My most important query is car insurance (surprise!). I can create a report in Google Trends for the query "car insurance" and look at the past 12 months of data for the United States.
The results are really valuable:
I can see which brand shows up at the top (sadly it’s not me, it’s Progressive), I can see the queries people are typing, and I can see the fastest-rising queries and realize I should worry about Safeco and Arbella. I can also see that Liberty Mutual's massive TV blitz is having an impact in increasing brand awareness and Geico seems to be having support problems with so many people looking for its phone number.
I can click on the gear icon at the top right and download a bunch more data, beyond the top ten. I can also focus on different countries, or just certain US states, or filter for the last 90 days.
I can also focus on different countries, or just some of the states in the US or only for the last 90 days. The options are endless.
There are two specific uses for this data.
First, I get the top and rising queries to consider for my SEO program. Not just queries either, but deeper insights like brand awareness, etc.
Second, I can use this to figure out the priorities for the content I need to create on my website to take advantage of evolving consumer interests and preferences.
If you have an ability to react quickly (not real-time, just quickly) the Google Trends tool can be a boon to your SEO efforts.
Competitive Intelligence / SEO Tools.
Competitive intelligence tools solve the challenge of knowing: What are my competitors up to? What is happening in my product/industry category when it comes to search?
SEO tools solve the challenge of knowing: What can I do to improve my page ranks, inbound links, content focus, social x, link text y, etc.?
There are many good competitive intelligence tools out there. They will continue to be useful for other analysis (referring domains, top pages, display ads, overall traffic etc.), but as I mentioned at the top of this post, the search keyword level data will attain a even lower quality. Here's a report I ran for L'Oreal:
If you see any keyword level data in these tools, you should assume that you are getting a distorted view of reality. Remember, all other data in these tools is fine. Just not any of the keyword level data.
There are many good SEO tools out there that provide a wide set of reports and data. As in the case of the CI tools, many other reports in these SEO tools will remain valuable but not the keyword level reports. As not provided moves toward 100% due to search switching to https, they will also lose their ability to monitor referring keywords (along with aforementioned repressive and sometimes not-so-overtly repressive regimes).
When the keywords are missing, the SEO tools will have to figure out if the recommendations they are making about "how to rank better with Bing/Google/Yahoo!" or "do a, b, c and you will get more keyword traffic" are still valid. At a search engine level they will remain valid, but at a keyword level they might become invalid very soon (if they’re not already)
Even at a search engine level, causality (in other words, “do x and y money will come to you”) will become tenuous and the tools might switch to correlations. That is hard and poses a whole new set of challenges.
Some of the analysis these tools start to provide might take on the spirit of: "We don't know whether factors m, n, and q that we are analyzing/recommending, or all this link analysis and link text and brand mentions and keyword density, specifically impact your search engine optimization/ranking at a keyword level, or if our recommendations move revenue, but we believe they do and so you should do them."
There is nothing earth-shatteringly wrong about it. It introduces a fudge factor, a risky variable. I just want you to be aware of it. And if you want to feel better about this, just think of how you make decisions about offline media – that is entirely based on faith!
Just be aware of the implications outlined above, and use the tools/recommendations wisely.
Let's try to end on a hopeful note. Keyword data is almost all gone, what else could take its place in helping us understand the impact of our search engine optimization efforts? Just because the search engines are taking keywords away does not mean SEO is dead! If anything, it is even more important.
Here are a couple of ideas that come to my mind as future solutions/approaches. (Please add yours via comments below.)
Page "personality" analysis.
At the end of the day, what are we trying to do with SEO? We are simply trying to ensure that the content we have is crawled properly by search engines and that during that process the engines understand what our content stands for. We want the engines to understand our products, services, ideas, etc. and know that we are the perfect answer for a particular query.
I wonder if someone can create a tool that will crawl our site and tell us what the personality of each page represents. Some of this is manifested today as keyword density analysis (which is value-deficient, especially because search engines got over "density" nine hundred years ago). By personality, I mean what does the page stand for, what is the adjacent cluster of meaning that is around the page's purpose? Based on the words used, what attitude does the page reflect, and based on how others are talking about this page, what other meaning is being implied on a page?
If the Linguistic Inquiry and Word Count (LIWC) can analyze my email and tell me the 32 dimensions of my personality, why can't someone do that for my site’s pages beyond a dumb keyword density analysis?
If I knew the personality of the page, I could optimize for that and then the rest is up to the search engine.
Crazy idea? Or crazy like a fox idea? : )
Non-individualized (not tied to visits/cookies/people) keyword performance data.
A lot of the concern related to privacy is valid, and even urgent when these search queries are tied to a person. The implications can be grim in many parts of the world.
But, I wonder if Yahoo!/Bing/Google/Yandex would be open to creating a solution that delivers non-individualized keyword level performance data.
I would not know that you, let's say Kim, came to my website on the keyword "avinash rocks so much it is pretty darn awesome" and you, Kim, converted delivering an order of $45. But the engines could tell us that the keyword "avinash rocks so much it is pretty darn awesome" delivered 100 visits of which 2% converted and delivered $xx,xxx revenue.
Think of it as turbo-charged webmaster tools – take what it has today and connect it to a conversion tracking tag. This protects user privacy, but gives me (and you) a better glimpse of performance and hence better focus for our organic search optimization efforts.
Maybe the search engines can just give us all keywords searched more than 100 times (to protect privacy even more). Still non-individualized.
I don't know the chances of this happening, but I wanted to propose a solution.
Why not give up on the tools/data and learn from our brothers and sisters in TV/Print/Billboards land and use sophisticated controlled experiments to prove the value of our SEO efforts?
(Remember: Using the alternative data sources covered above, you already know which keywords to focus your efforts on.)
In the world of TV/Radio/Print we barely have any data – and what we do have is questionable – hence the smartest in the industry are using media mix modeling to determine the value delivered by an ad.
We can do the same now for our search optimization efforts.
Now its time for the SEO Consultant's awesomely awesome SEO strategy implementation.
Try not to go whole hog. Pick a part of the site to unleash the awesomely awesome SEO strategy. One product line. One entire directory or content. A section of solutions. A cleanly isolatable cluster of pages/products/services/solutions/things.
Implement. Measure the impact (remember you can measure at a Search Engine and Organic/Paid level). If it’s a winner, roll the strategy out to other pages. If not, the SEO God you hired might only be a seo god.
At some level, exactly as in the case of TV/Radio/Print, this is deeply dissatisfying because it takes time, it requires your team to step up their analytical skills and often you only understand what is happening and not why. But, it is is something.
I genuinely believe the smartest SEOs out there will go back to school and massively upgrade their experimentation and media mix modeling skills. A path to more money via enriching skills and reducing reliance on having perfect data.
There is no doubt that secure search, and the delightful result not provided, creates a tough challenge for all Marketers and Analysts. But it is here, and I believe here to stay.
My effort in this post has been to show that things are not as dire as you might have imagined (see the not going away and alternatives sections). We can fill some gaps, we can still bring focus to our strategy. I'm also cautiously optimistic that there will be future solutions that we have not yet imagined that will address the void of keyword level performance analysis. And I know for a fact that many of us will embrace controlled experimentation and thereby rock more and charge more for our services or get promoted.
As always, it is your turn now.
I'm sure you have thoughts/questions on why not provided happened. You might not have made it through all the five stages Kubler-Ross model yet. That is OK, I respect your questions and your place in the model. Sadly I'm not in a position to answer your questions about that specifically. So, to the meat of the post …
Is there an implication of not having keyword level data that I missed covering? From the data we do have access to, search engine level, is there a particular type of analysis that is proving to be insightful? Are there other alternative data sources you have found to be of value? If you were the queen of the world and could create a future solution, what would it do?
Please share your feedback, incredible ideas, practical solutions and OMG you totally forgot that thing thoughts via comments.
PS: Here's my post on how to analyze keyword performance in a world where only a part of the data was in not provided bucket: Smarter Data Analysis of Google's https (not provided) change: 5 Steps. For all the reasons outlined in the above post this smarter data analysis option might not work any more. But if only a small part of your data, for any reason, is not provided, please check out the link.
A few months back, I wrote an article for Marketing Land called “Is The Art Of Paid Search Marketing Dead?” in which I foolishly suggested there was still a small bit of art left in search marketing. Art? Are you kidding me? Ugh. I haven’t been so wrong or felt so foolish in a long […]
Please visit Search Engine Land for the full article.
Two things I love a lot:
1. Frameworks, because if I can teach someone a new mental model, a different way of thinking, they can be incredibly successful.
2. Visuals, because if I can paint a simple picture about something complex it means I understand it and in turn I can explain it to others.
This post is at the intersection of those two lovely things.
Each of the six visuals re-frames a unique facet of the digital opportunity/challenge, and shares how to optimally take advantage of the opportunity/challenge.
We'll start with digital at the highest strategic level, which leads us into content marketing, from there it is a quick hop over to the challenge of metrics and silos, followed by a recommendation to optimize for the global maxima, and we end with the last two visuals that cover social investment and social content strategy.
A vast expanse of our current existence.
All of the visuals are in the form of a venn diagram, though, as you'll see, I do take enormous liberties with the format.
Ready to learn, smile and cry (just a little)?
Let's do this!
#1: How to Win, Really Win, at Digital: One-Time PLUS Many-Time Relationships.
The most intense amount of effort companies put into their site happens at site launch or the yearly new product launch. Everyone gets excited, agencies are hired, content is scraped from product box-shots, prettiness is sprinkled everywhere and much happiness, represented by a gigantic sigh of relief, occurs.
All of that is good.
The challenge is that this annual, or semi-annual, update of the content or the website design, is a terrible way to win at digital.
All the stuff you've launched is great for showcasing your company and its products. It delivers conversions when I visit your site once and buy something. But beyond that engagement, that one-time relationship if you will, there is no reason for me to ever come back. Because you don't have anything updated on your website. If I remember everything you sell, I might come back the next time I need something from that everything. Or due to some incredible co-incidence if I bump into your brand when I'm thinking of buying something from your everything.
A secondary, under-appreciated, challenge is that search engines value freshness of content. Once you launch your site, it becomes stale in due course (from a organic search signal perspective). It impacts your organic rankings (even if there are tons and tons of factors that influence SEO results).
A final tertiary challenge is that in a world dominated by conversations and social, your static content rarely entices any new conversations. It is great that you've added a silly string of buttons to all your product pages, but there is hardly a reason for anyone to click on them. (Most of the time all they are is an ad for addthis or some other "free" provider of those buttons.)
If you want to truly rock digital, this is what your digital strategy should look like…
So do your periodic product launches/site refreshes. But almost all your content energy should be poured into fueling the creation of dynamic content! You should have an incredibly amazing blog for your company (more on this below). You should have a robust strategy to earn compelling product reviews. You should have a well defined strategy to create videos and how-to content (constantly updated with solutions to new pain points of customers). You should talk about how innovation works in your company. Your employees should tell their stories. And so on and so forth.
This constantly updated content provides me more reasons to visit your website and stay in touch with your brand. It is also immensely beneficial for search engine optimization (great content, delivered fresh, every day!). Finally it generates a constant stream of social amplification and social conversations!
So do you have a static AND dynamic strategy for your digital existence?
Patagonia is amazing at this. They have a fantastic website where I can buy fantastic stuff that I fantastically love. In addition to that they have amazing content like what you'll see at Patagonia Surfing, and they have a regularly updated awesome blog The Cleanest Line and so much more. As a result I have a one-time and a many-time relationship with the Patagonia brand.
Ditto for one of my favorite hotels in New York, The Standard. Great website for booking rooms and all that. But they also have a great blog/culture guide/all things cool and amazing sub-site called The Standard Culture. I have a time-to-time relationship with their brand (whenever I have to visit New York). I also have a many-time relationship with them because of all this amazing dynamic content – which ensures that I love the brand and that in turn always makes my hands type their url when I have to visit NYC! That is what you want.
I'll be remiss if I did not provide you with two examples of what magnificent product reviews look like.
I love the ones on Williams Sonoma, they are detailed and include a title, a rating, specification on cooking ability and length of ownership sections are my fave and an overall recommendation. They also have, for each review, social amplification buttons! I also love the reviews on Rent The Runway. Can't you just imagine how much value those 102 photos and huge number of reviews add? Not to mention how helpful they are to current or prospective customers!!
So what is your balance of static vs. dynamic? Is it as outsized as the second picture above? It should be.
It is the only way to win big.
#2: The Secret to Content Marketing Success.
Content marketing is all the rage these days. Everyone is contenting a lot of content about content marketing. There is even an institute about it.
On the surface it is hard to argue about the value of content. On paper, what could possibly go wrong with creating or curating content with an eye to driving sales or influencing current or future customers?
Except that most content deployed in the service of content marketing sucks. For two simple reasons: 1. It is actually really hard to create good content, you have to know a lot about the subject matter. 2. We simply can't help pimping ourselves/our products/our services.
When our current/potential customers encounter the fluff pieces which are glorified vehicles for our not so subtle pimping, they quickly see through both things leading to sub-optimal results. And depending on when you want to open your eyes and see reality, you end up realizing content marketing does not work.
Let me share with you my simple rule for creating content that markets itself.
When people ask me how I decide what I write about on this blog, my answer is that prior to launching this blog I'd decided a simple rule for myself. Only post content that is 1. incredible 2. of value to the audience and 3. sans pimping.
I've worked very hard to follow this rule every single time I post something. The content here – and you are the ultimate judge of this – represents what I consider to be something incredible that you will find to be of value. I have a lot of other incredible things to write, but if I believe you won't find them to be of value, it gets killed. (I wish you knew how many posts I've discarded because they did not meet that simple criteria!)
The rule impacts my work in other, big, ways. For example, if I did not have time to write something incredible of value, I've not written anything. The deadline comes and goes, if I have nothing, you get nothing. It is also the reason my posting schedule over the last five years has gone from twice a week to once a week to once every two weeks to once every three weeks. (Amazingly, the blog traffic has gone from 2k a month to 150k a month!)
Finally, I've never accepted ads on this blog. In the right nav you'll see two discreet sections with my books and my start up Market Motive. That could possibly be considered advertising. There are three posts out of 283 about my book, and just five that mention Market Motive. Very little pimping, because I respect your capability to see what I'm selling and buy it if you feel it is a fit for you. (And you have!)
I'm not unique in following the above visual. There are many, many others. People and companies. Waaaaay more successful than I can ever dream of becoming. If content marketing is their strategy, the common thread is always the same. Something incredible, of value, with the barest minimum pimping.
It is the only way to win big.
#3: Data, Data Everywhere and Yet We are an Abject Failure.
I work with many medium to large companies around the world. Every single one has an impressive array of tools, many of them even have an equally impressive array of analysts.
Yet a heartbreakingly huge number of them stink at a company level. By that I mean they might have some pockets of excellence, but overall their site stinks, their customer experience (end-to-end) is awful, and their digital strategy is, on the greatest possible day when every single star is aligned perfectly, adding 1/10th the value it should.
It is the simple combination of how each division/group of people inside, and sometimes outside (agencies, et. al.), the company are organized and incentivized (as in what metrics determine their bonus).
Acquisition is everything we do to attract traffic. Behavior covers everything that happens after the person lands on our mobile or desktop site. Outcomes are what happen just before the visitor leaves our site (money to us, satisfaction to them).
Companies have an Email team and an SEO team and a PPC team and a Social Media team and a Display team and…. many teams for acquisition. They are often measured on impressions (or worse, "connections") and clicks. Then that is all they optimize for. They take zero responsibility for crappy landing pages, or even 404s on landing pages.
Then there is the "site team." Euphemism for we will do anything to keep the site up but really all we do is launch pages that someone will ask us for and we really don't know who is coming to the site or what is driving them there and we rarely speak to marketing or agency but the site is pretty cool, we think.
Depending on other variables, there might be someone who looks at conversion rates (usually sans a lot of other context).
Each might work on their own little circle, there is no incentive to look end-to-end, or even at the overlaps/hand-offs.
So fix that.
Make sure your executive dashboards obsess about acquisition, behavior and outcome metrics. Make sure that every single report you create has acquisition, behavior and outcome metrics (download this example: Page Efficiency Analysis Report).
Force each team to think end-to-end and you will incentivize the right behavior across your company.
It is the only way to win big.
#4: Optimize for your Global Maxima: Obsess About Macro AND Micro Outcomes!
The average conversion rate for a typical top ecommerce site is around 2%. And sadly, we are not at the top, so we tend to do worse.
When we obsess only about conversion rates on our website, the problem is that that is an obsession with just 2% of the site outcomes. We end up looking at the world through a straw, and the best we can do is a lot less than the best we can actually accomplish.
This is not to say that you should not worry about conversion. You should. But when your strategy looks like the one above, powered by looking through a straw, you'll optimize for the local maxima.
That is not terrible. It is just not awesome. Your parents will always pat you on your head and say "Oh sweetie, you could have been something. Something so much more."
And who wants that? You want to live up to your fullest potential!
That means you'll have to care about your macro-outcome, the ecommerce conversion or your lead submitted conversion or donations made to your non-profit conversion. But you'll also have to care about your micro-outcomes!
Some of these micro-outcomes will directly lead to your macro-outcome. For example, people signing up for your email marketing list will convert in the near future. Or people who create wish lists, sign up for product alerts, watch product videos today etc. They are all signaling intent to convert.
But other micro-outcomes might not be directly related to a near future macro-outcome. For example, people who subscribe to your blog's RSS feed. Or people who follow you on social media or subscribe to your YouTube channel or sign-up to volunteer for your non-profit or download your utility marketing mobile app etc. All these outcomes bring people closer to your brand, an awesome outcome.
When you measure the success of your AdWords campaigns or your email blasts or your Facebook ads or any other acquisition initiative, make sure you report your macro-conversion rate. But don't stop there. Make sure you report your micro-conversion rate as well. Teach your company to optimize their digital strategy for a portfolio of outcomes, macro plus micro. And if you compute economic value of digital – the value of macro plus micro outcomes – your career will be on the fastest possible track to fame and happiness!
Best of all, this will mean you are optimizing for the global maxima.
It is the only way to win big.
#5: Rent or Own? The Optimal Social Media Investment Strategy.
This is a new trend amongst companies. Swept up in the fervor of Google+, Facebook, YouTube and other social platforms, they are massively shifting their resources (people, time, dineros) into their presence on these new platforms.
That in of itself is not a bad thing. Everyone knows there are a quadrillion people on Facebook. It is absolutely a valuable audience.
The bad thing is that all this seems to come at the cost of investing resources on efforts related to the company's website. So many companies have irrelevant posts by expensive employees on Facebook all day long (more on this below), and don't spent the little bit of money to create a mobile website. #arrrrrhhhhh
Remember, when you create a presence on Facebook, Google+, Sina Weibo, Vkontakte, you are renting.
You don't own the domain, you don't own the customer data, you don't create/own the rules, you can't influence changes, you don't have a say in how many characters you can type or how long your video can be or how much creativity you can express. You play by their rules (after all you are just renting).
This does not make those platforms any less valuable. But it is astounding silly to have your rented presence come at the cost of a platform you own!
Build your own magnificent platform first. Where you create the rules, you control the evolution, you own the customer data, you have a direct relationship with your audience, you get to decide what happens next (or if ever!), and there are no limits to your experimentation with creativity!
Once you nail your own existence, move on to nailing your rent existence.
And going forward, always forever remember the balance between own and rent. Outsized investment in own and an appropriate, demonstrated by the best social media metrics, investment in rent.
It is the only way to win big.
#6: The World's Greatest Social Media Strategy.
Why does L'Oreal Paris USA, a multi-billion dollar corporation with a marketing budget of hundreds of millions of dollars, have fewer followers than I do on Twitter?
Why is the talking about this brand metric for Avis rent-a-car less than half of what it is for my brand page (and I have 50,000 fewer Likes than they do!)? Remember, Avis is a corporation with thousands of employees in tons of countries.
Why does TravelZoo have 224k fewer Followers on Google+ than I do?
All these companies are big and magnificent, and I'm very small and inconsequential. So, why?
The answer is simple: this is their social media strategy…
They wake up everyday and, on the world's greatest channels for conversations, they shout at people. Every single post they write, every single tweet they send, is simply another variation of BUY IT NOW!
The challenge is, as the See Think Do framework emphasizes, a tiny, tiny, minority of the audience is there to buy anything. (If you need more proof, just see how poorly advertising performs on these platforms.)
Just because you are good at shouting on TV/Radio/Print/Display does not imply that that is what you do on social media. Even if you somehow manage to get a bunch of Likes/Followers/+1s, your conversation rate, amplification rate and applause rate will be pathetic.
So stop that.
These channels are awesome (also see visual #5 above). Here's the strategy that works…
Pimp your stuff sometimes – say twice a week. And if you can be clever about it, like getting your customers to pimp for you, even better.
Ninety-five percent of the time create conversations and try to add value to your customers/likers/+1ers.
Write about topics both of you are interested in. If you sell smoothies, talk about food, how to develop a great palette, travel, evolution, agriculture, the future of the planet… the topics are endless.
Provide utility. Share tips on how to make my life better. Share tips on a healthy lifestyles, exercise, wellness of children, latest relevant mobile apps…. the topics are endless.
Your customers have given you permission to interrupt their day. Don't suck at it. Be respectful of their attention. Create a warm space in their heart for your brand. Contribute something incredible, of value.
That is the only way to win big.
That's it. Six simple visualizations, and solutions, for complex marketing, analytics and life challenges.
As always, it is your turn now.
Is there a venn diagram that resonates more with you than others? Which one least reflects reality? What does your company's digital balance between static and dynamic content look like? What percent of your social contributions is BUY IT NOW? Does your company execute for visual number one or two for outcomes? How incredible and of value is your content marketing content?
Please share your wisdom, stories, critique, and praise via comments.
Have you noticed the amount of traffic for your site dropping unexpectedly over the past week or so? Maybe your sales have suddenly seemed to have frozen and stopped coming in completely?
If so, one possibility could be that your site has been penalized by Google and, as a result, your site has become unranked and pretty much excluded from the search engine search result pages. And it should come as no surprise that if people online can’t find you, you won’t get many visitors or sales.
So how can you be sure that you’ve been penalized by Google? Well, if it was a manual penalty, meaning that your site was marked to be penalized by a person at Google rather than an algorithm, you’ll get a message from them, which makes things pretty obvious. However, if you haven’t received a message, it’s still possible that your site has been automatically penalized. Here’s how you can tell:
5 Giveaways of Penalization
- Brand Name Ranking
Rankings can change frequently and fluctuations are not too uncommon. Significant drops in ranking over a short period of time is unsettling, but not entirely naturally impossible; especially in highly competitive keyword fields, this isn’t necessarily an indicator of being penalized by Google. However, the one keyword that you should be ranking well if not the best for is your brand name. If you search your brand name and still have a difficult time finding your page, there’s a good chance you’ve been penalized by Google.
- Cached Search Results
When Google penalizes a site, they usually will also make all of the cached pages of that site unavailable. If you can’t find any of your cached pages in search results, and they seem to have just disappeared for no reason, there’s a good chance that Google’s found something against you.
- Home Page Listing
At this point, you might be looking for your page, scrolling down the results pages, one after another, just out of curiosity. If and when you do finally find your page on Google, it likely won’t link to your home page if you’ve been penalized.
A sudden and rather drastic drop in your PageRank is also a good indicator of penalty. If your PageRank suddenly appears to be a 0 or 1 when it was a respectable 3 the week before, it’s a good idea to look into reasons you might have been penalized.
- Site Search
Finally, if you do a site search—that is, entering “site:www.mydomain.com” into the Google search box and your site does not come up, there’s clearly something wrong.
What to do
Whether you’ve been manually or automatically penalized by Google, you need to handle the situation in a professional, respectful, and honest way.
Take another look at your SEO strategies—could any of them be considered to be fraudulent or “black hat?” Review Google’s guidelines and see if there are any you might have overlooked. Try to discover why you might have been penalized if you were penalized automatically. Then get into contact with Google. Sometimes, the penalty can be lifted if everything is handled well; however, other times the penalty can be permanent. Whatever happens, be respectful and as honest and forthcoming as you can be if you hope to save both your site and your reputation.
In the future, to prevent being further penalized by Google or any other search engines, stay up to date with their rules and familiarize yourself with blackhat SEO techniques so that you know what practices to avoid. Sometimes ignorance may be your only fault, but alas it does not make you innocent.
Best of Luck!
Google released an update to AdWords Editor, version 10.2, that supports upgraded sitelink management and several other smaller feature updates. Apparently now dubbed upgraded sitelinks, these new sitelinks rolled out in June just prior to the enhanced campaign roll-out. They give advertisers the…
Please visit Search Engine Land for the full article.
There are few things more complicated in analytics (all analytics, big data and huge data!) than multi-channel attribution modeling.
We have fought valiant battles, paid expensive consultants, purchased a crazy amount of software, and achieved an implementation high that is quickly, followed by a " gosh darn it where is my return on investment from all this?" low.
A lot of that is because of all the stuff we don't know. There is lots of missing data. And as if that were not enough, there is lots of unknowable data. Neither of which has stopped Gurus and Masters and Agency High Priests from trumpeting here's the next thing directly from Lord Krishna that will solve all your problems.
So, let's apply Occam's Razor to this complicated challenge. Let's try to make some sense of it all.
By the time you are done with this post you'll have complete knowledge of what's ugly and bad when it comes to attribution modeling. You'll know how to use the good model, even if it is far from perfect. I'll close with a custom attribution model into which you can insert all your biases – sorry, I mean expertise – and get something better than good to make incremental progress from where you are today.
My macro goal is to make you dangerously informed. By the end of this post, if you pay attention, you'll know the often hidden nuances and you'll be dangerous to any analyst/consultant/vendor who walks into your cubicle/office with I've got the God's-gift-to-humanity, easy-to-implement solution with insights riding out to you on a Unicorn.
Here's the outline of our incredible multi-channel attribution modeling adventure:
Excited? Grab a Red Bull. Let's go!
In a recent post, Multi-Channel Attribution: Definitions, Models and a Reality Check, I outlined three distinct attribution challenges.
MCA-O2S covers the challenge of attributing the offline impact (revenue/brand value/butts in seats/phone calls/etc) driven by online marketing and advertising.
MCA-ADC covers the challenge of attributing credit to all digital marketing channels (Social, Display, YouTube, Referral, Email, Search, others) that contributed to a particular conversion (or multiple conversions).
In this post we are going to take a close look at MCA-ADC. Multi-channel attribution across digital channels. Looking at the picture above … we've spent money on Social, Direct, Search, and Referral efforts and received 767 conversions. But how do we distribute credit for the conversions across all those channels?
All three challenges are important. I strongly encourage you to read the post and deeply understand all three and what your marketing and measurement possibilities and limitations are.
Sorry, I meant to say it is highly likely that you do.
It is a pretty easy question to answer. I normally ask people to look at the Path Length report in the Multi-Channel Funnels standard report in Google Analytics (or equivalent tool if you are using SiteCatalyst or WebTrends or other web analytics tools).
If a significant percent of your conversions have a greater than one path length, you have an attribution problem. Combine that with the excellent multi-channel conversion visualize (in the Overview section) and you have yourself a view of your marketing that will freak you out.
It is also ok to weep a little at this point as you realize the extent to which every single decision you've made about allocating your marketing budget is awful. Weep a little for that inconsiderate "friend," last-click attribution.
[One of my favorite parts of this Venn -diagram is the implications on organization structure. Some CxOs see it immediately, other times I have to walk the horse to the water and force it to drink. The outcome in either scenario is a restructuring of the organization that is exquisitely geared towards taking advantage of portfolio optimization. Related implications of what you want to do in-house vs. out source to an Agency. Really fun stuff, really long- term strategic implications. From a Venn -diagram. Who would have thunk?]
The simplest way to start is to look at your Assisted Conversions report in Google Analytics. Look at the last column: Assisted/Last Click or Direct Conversions.
• If you see a value less than one, that channel has a higher tendency to drive last click conversions. Hurray, hurray!
• If you see a value greater than one, that channel has a propensity to be present earlier in the conversion cycle. These channels are getting zero credit in last click attribution platforms (read that as: all standard reports in all web analytics tools). O. U. C. H.
At this point you should educate your management team on this specificity. "Look we might not be valuing all the performance we get from our marketing channels. Here are the specific channels that we are undervaluing." (Where the ratio is greater than one.)
You can even use that column to adjust some of the budget allocation right now, without any attribution modeling, and measure the outcome. It is imperfect, but it is such a simple first step.
It is likely your CxO will want you to explain which channel comes first ("introduces our brand to the customer"), which channel comes second ("nurtures our potential customer"), which channel comes fourth, fifth … and last.
You can use the Top Conversion Paths report.
It is very important to point out that this is a completely foolish exercise to undertake. For the same reasons that path analysis is a waste of time. There are too many paths, and you can't actually control the path that a potential customer can take. Even if, and this is not possible, I said to you that the path is Direct, Social, PPC, Organic, Referral for 5% of the site traffic … what would you do? It is not possible to force people down that path!
But show the actual report. Let them arrive at the obvious conclusion. Be a hero.
The next question will be, what are the best ways for us to allocate credit to all our marketing channels properly?
I'm glad you asked, Ms. Executive.
There is a free tool inside Google Analytics called Model Comparison Tool. It is sweet. It allows you to attribute credit to all your digital marketing channels involved in conversions (macro and micro conversions). You can visualize the impact of applying three models at one time.
For example, what if we used a linear attribution model instead of last click?
OMG! OMG! OMG! So cool!
All I have to do is look at the very last column and look at the green and red arrows and get guidance about how I should shift my budgets?Yes!
And you are telling me that the Cost Per Acquisition for my display campaigns is not $201 but rather a lowly $155?Yes.
Get. Out. Of. Here! That is so cool. Finally my amazing blinking hit the monkey display ads are getting all the credit they deserve!
Time to burst your bubble just a little.
The tool is actually that good. Apply the right model and you will not only distribute conversions across multiple touch points, but you can also look at the impact on the CPA (this really is OMG, I peed in my pants a little cool). You can even get great first-step guidance about how to rebalance your portfolio from that last column.
But the weakest link in the chain is the attribution model you use. The recommendations you get are only as good as the model you use.
With that in mind, let's look at the standard models available inside Google Analytics (and some of the high-end analytics or attribution analysis tools).
Just so we have a visual guide through this learning process, let's use the above image as a reference. Look up, memorize the steps to conversion. Ready?
1. Last Interaction/Last Click Attribution model.
This is the standard attribution model in all web analytics tools. It is applied to all the standard reports you see.
[The only exception to this rule is Google Analytics which, and I deeply passionately hate this, applies the #2 model below in all its standard reports.]
You can see why this model is silly. If 767 people converted as a result of the above experience, saying that all the credit should go to the Direct channel is silly. [Bonus: Learn more about what direct traffic is: Make Love To Your Direct Traffic.]
Social, Organic and Referral were also involved. We should figure out some way to identify their contribution to the conversion process, because they were involved in some form.
Historically, all tools used last click attribution because the one thing they could confidently say is what drove the converting visit. And they did not have the technical horsepower to do Visitor-centric analysis. Both these problems are solved now.
The only use for last click attribution now is to get you fired. Avoid it.
2. Last Non-Direct Click Attribution Model.
Google Analytics is bipolar.
All standard reports in Google Analytics give 100% of conversion credit to the last "campaign" prior to the conversion. Campaign is defined as anything but Direct traffic. So, the campaign could be Social, Organic Search, Email, Display, Affiliate, Referring Site … anything really.
This deliberately understates the Direct visits that lead to a conversion. In our picture below this model would say all credit goes to Referral.
This is imprecise. Why give credit to a campaign if it took me another visit where I remembered your URL and typed it in and came to your site? Why should the visit where, say, I saw a great promo or you recommended something based on my prior visit not get some credit for the conversion?
Why undervalue Direct? Why undervalue a marketer's efforts to create brand recognition and brand value?
I believe this is a mistake. A historical legacy, perhaps. It should be courageously fixed.
Bonus: This model is also the irritating reason why none of your standard Google Analytics reports match your standard Multi-Channel Funnels reports, even if you look at conversions in the standard MCF Overview or Assisted Conversions reports.
3. Last AdWords Click Attribution Model.
My words for this model might get a little bit vitriolic, so I'm going to keep my mouth shut.
And to think you never thought that was possible. : )
This model is profoundly value-deficient. There. I can be nice.
4. First Interaction/First Click Attribution Model.
Reverse of last click. Rather than giving all the credit to the last click, give all the credit to the first click.
In our example above, switch 100% of the credit from Direct to Social.
This is a gigante mistake.
First click attribution is akin to giving my first girlfriend 100% of the credit for me marrying my wife.
Makes no sense, right?
If the first was so awesome, how come I needed #2, #3… to get to the most perfect person – I mean, campaign – for me?
With last click attribution there is at least some certainty that something about that campaign, something about that visit to the site, resulted in a conversion. With first click you just have faith. Or a HiPPOs (Highest Paid Person's Opinion) fervent "gut-feel."
5. Linear Attribution Model.
This is less wrong.
That's it. Just less wrong. Use it if you are shooting for that.
When my son was smaller he would go to competitions (sports or IQ) and everyone would get a participation certificate.
Life, it turns out, is not utopian. When there is a competition, someone gets a gold medal, someone gets a silver, and someone gets a bronze. Everyone else goes home a loser, motivated to work harder the next time and win.
You should not treat your marketing optimization program with the same level of outcome optimization that is applied to five-year-olds. You can, and should, do better.
If someone threatens your life, use this model. Give everyone who contributed a participation certificate. But if you are not in a life-threatening situation, other models might help you actually understand which channels are contributing more value and which are not. And two of those models are just one click away.
6. Time Decay Attribution Model.
Ohh …. much better!
The core premise of the time decay model is this: The media touch point closest to conversion gets most of the credit, and the touch point prior to that will get less credit based on a smart and simple algorithm.
You only have to think about it for five seconds to realize it passes the ultimate test for everything: Common sense.
We could argue about how much credit the last few should get and how much the rest and how much the first. (Or we could not.) But overall it does seem to make sense that the further back a media touch point is (Organic Search and Social in our example) the less credit it should get. After all, if the touch points were magnificent, why did they not convert?
One of the cool things about this model is that you can customize the half-life of decay and insert your own feelings into the attribution process. Notice I said feelings.
If you are going to start doing attribution modeling, the time decay model is a great, passes the common sense test, way to dip your toes. Go to the Model Comparison Tool, click on Select Model, choose Time Decay, and let thoughts be provoked!
Bonus: Adjust days prior to conversion on top of the tool based on your Time Lag report in the Multi-Channel Funnels folder.
7. Position Based Attribution Model.
In some ways I really like the position based model because I have opinions – sorry, I meant to say expertise – and it is so easy to insert those opinions into this model and do some cool stuff.
That is what makes it a dangerous first model to use. If you don't know what you are doing, it is GIGO very quickly.
By default, the Position Based model attributes 40% of the credit to the first and the last interaction and the remaining 20% is distributed evenly to all the interactions in the middle.
1. See my perspective on first click attribution model above. 2. Understand why I believe that as designed the default position based model is sub-optimal. 3. Promise me you won't ever use the default one. 4. Feel really great you dodged a bullet.
Of the six attribution models available, there is one that you can use with little thought and still get value (Time Decay). One is not great, but won't completely kill you (Position). Three are so weak that you should not acknowledge them if they pass you in the street (and actively warn your friends to avoid them!).
Why are there so many models? The known world is smaller than the unknown world. There are always corner cases, there are always weird scenarios, there is always someone who wants to do something odd. All these reasons are good reasons for all these models to exist. But do go into using any model with open eyes.
There is one more thing you can do after you are done with the first step, playing with and experimenting with the results of the Time Decay model. You can create a customized attribution model.
8. Customized/Personalized Attribution Model.
(I've said this twice already but let me say it again, don't go into this until you play with the Time Decay model and have spent a good few weeks learning the implications and trying to take some action. It is a very good learning experience.)
I love using the customized attribution model, and I'm grateful that the team at Google made it free for everyone rather than having it only for Google Analytics Premium. The Premium customers get an interesting Data Driven Attribution Model, small price for the rest of us to pay.
With the custom modeling tool you can use the Linear, First, Last, Time Decay and Position Based models as your starting point, and then layer in other factors you consider to be important for your business to create your own attribution model.
I spend a lot of time with the business leaders, marketers, understanding historical performance, current media-mix and spend patterns before I create a customized model for them. Among the questions I ask the leaders are:
+ What type of user behavior do you value?
+ Is there an optimal conversion window you are solving for?
+ What does the repeat purchase behavior look like historically?
+ Are there any micro-conversions defined with engagement type goals, tied to the economic value?
+ Are offline conversions being sent back into GA using Universal Analytics?
So on, and so forth. These provide important context in making the decisions that will go into a custom attribution model.
From my portfolio of custom models, let me share one that has often served as a starting point for many customers.
Setting aside all humility for a nanosecond, I call it the Market Motive Mindblowing Model!
Click on Select Model in the Model Comparison Tool. At the bottom of the drop-down you'll see Create new custom model, click it.
Step 1: Select the baseline model.
I start with the Position Based. Then specify the amount of conversion credit based on the position. Here's what I use…
If you've read this post carefully to this point, this distribution of credit should not come as a surprise to you. From all my experimentation I've found that taking out the last channel (whichever one it is) causes a material impact on the conversion process, so it gets a "good amount of credit." The middle channels have an important role in driving people to the last interaction, they are recognized for that. The first interaction deserves some credit for the conversion, but not as much as the middle or last – for obvious reasons.
My distribution above is a good starting point. It is also really easy for you, as I often do myself, to experiment with different distributions, note the impact and optimize.
Step 2: Select the lookback window.
My process for picking the optimal time period to look for campaigns/interactions/media touch points to distribute credit over is to use the Time Lag report in the Multi-channel Funnels folder. It gives you the distribution of typical behavior.
My rule for picking the lookback window is to pick "close to the upper limit of the number of days to conversion, excluding the outliers, plus a bit more."
In this case it was a B2B client, long conversion cycle that lasted around 65 days, ignoring the outliers, so I picked 75. Just to be conservative.
Look at your own Time Lag report, come up with your own number. I'm a big believer in not going back to every single campaign, no matter how far back, and dragging it in to give it credit. If it was so awesome, it would have kicked off a conversion cycle for us that falls within the upper limits indicated in the Time Lag report.
The next two steps are critical. They are both really cool. But more than that, they help us wash away some of the sub-optimal decisions we might have made in the above two steps. Pay attention.
Step 3: Select the engagement based credit option.
We now go in and apply a rather clever rule to adjust credit for our campaign based on the behavior of the user that came to our site. This is particularly important for the touch points prior to last click.
Hence, I prefer to use Page Depth as a proxy for site engagement.
In this step we are telling GA to give more credit to campaigns that deliver users that have a higher engagement with the site. So if a user from campaign X see five pages during the visit on my automotive website and campaign Y sends a user that bounces, campaign X will get more credit.
Only seems fair. And now you can see how some of your credit distributions in step one will be auto-corrected based on the type of engagement campaigns deliver.
Step 4: Apply custom credit rules.
The last bit of mind-exploding fun. We are going to select some custom rules that apply uniquely to our company (remember the five business questions above?).
You can literally apply any custom rule you want. You can go in and say "for all bounced visits from rich media display campaigns give the campaign 2x the credit." You would not do that, but you can. You can do the reverse, "give every campaign with Bounced Visits zero times the credit of other interactions in the conversion path."
I take a simpler first step. I want to value my campaigns based on the interaction they deliver. If there is only an impression (people only see the ad), I value that a lot less than ads that get people to click on them.
To do that first I choose Interaction Type. Then I choose Click from the Exactly Matching drop down.
Finally, I would like to have ads that get clicks to be extra rewarded and, in this case, get 1.4 times the credit of other campaigns in the conversion paths (in comparison to ads that just get impressions).
Why 1.4? After some experimentation, that was determined to be the optimal amount of value for this business (remember the custom model questions above?). There is no way out, you have to experiment.
That's our last step.
Other ideas for this last step include the ability to give generic or brand keywords more or less credit. Or giving Direct or Social more or less credit. Or giving all Social visits that are the last click prior to conversion only half the credit compared to other interactions in the path (Include Position in Path Exactly Matching Last and Include Source Exactly Matching Social, where Social is your campaign tracking parameter).
Totally your call. Just remember to drag your common sense along when you sit down to do this.
[sidebar] Once again in step four you see how clever use of custom filters can auto-correct some of your earlier assumptions related to distributions of credit in step one. If campaigns in the middle, or the first one, don't have the optimal interaction they will automatically be penalized. [/sidebar]
Here's a complete view of the Market Motive Mindblowing Attribution Model ….
That is all it takes, four simple steps, a pinch of understanding your business and a sprinkling of common sense.
It should be completely obvious to you that this model is based on a specific client's business environment, my experience, and business priorities. While I believe it will serve as a good starting point for your very own custom attribution model, it might not be optimal for you.
Hence, more than anything else, I would love for you to follow the thought process and the reasons for making choice x or choice y. Then apply that level of critical thinking as you go about creating a model for your digital business.
Once you have your models sorted out, I recommend you get rid of the last click attribution model. It only ends up being a heavy useless anchor on your analysis. If you want to do comparative analysis, choose Time Decay for the first one (we know it is better than last click) and choose the Mindblowing Model (or your custom model).
Your view will look something like this.
Focus on that last column, % change in Conversions.
Use the guidance provided (essentially a positive or negative shift away from the reference model, in this case Time Decay) to make recommendations for a different allocation of funds/effort for each marketing channel. Comparing the two models, you can see where your previous model/belief was wrong. Try adjusting your budgets accordingly for better success. As an example, in the above analysis Referrals are performing much better than we would otherwise have credited them for.
For the most optimal outcome for your company follow this 3-step process:
1. Create a hypothesis based on above analysis for how to better allocate budget across marketing channels.
2. Test that hypothesis using a percent of your budget and measure results.
3. Be less wrong over time.
Multi-channel attribution modeling and analysis is not a one-time effort, it is something you'll do all the time. Not every day, but at least do an operational review every two weeks and a strategic review (with recommendation for changes) every month.
I want to leave with some insights from the front lines of solving the MCA-ADC, MCA-AMS, MCA-O2S challenges. Hopefully these will help you get a jump-start in your own efforts.
#1. For multi-channel attribution modeling to work, all your marketing campaigns (Search, Social, Email, Display, Affiliate, others) must be 100% tagged with campaign tracking parameters . Tag your Bing campaigns. Tag your Email campaigns. Tag your Social campaigns. Tag the campaigns your mom is running on leaflets handed out to neighbors.
#2. One of my favorite exercises is to do the above analysis based on Cost Per Acquisition, rather than just conversions. You may be getting a lot of conversions, but the CPA can kill you. Notice above I only have two CPA values. For the rest I need to upload cost data into GA for my Social, Referral, Organic Search (yes, it costs money), and Email campaigns. You do too.
#3.You don't have to do attribution analysis for all your conversions in aggregate. On top of the attribution Model Comparison Tool, you'll see a drop down under the word Conversion. Click. Choose any conversion you consider to be important. You can do attribution modeling uniquely and optimize your marketing efforts just for an ecommerce transaction. Or you can do it for email subscription signups, or downloads, or videos played or anything else you consider to be important.
#4. Remember all of the above just covers Multi-Channel Analysis-All Digital Channels (MCA-ADC). There are two other, even more complex, attribution analysis scenarios: MCA-O2S and MCA-AMS. You can learn more about them here: Three Types of Multi-Channel Attribution Problems.
Don't be disheartened that all this complexity exists. Take things one step at a time. Standard Time Decay model first. Then your own Mindblowing Custom Model. Then Experimentation. Then MCA-O2S. Then MCA-AMS (it is so ironic this is harder than O2S!). With every step, you are making your company smarter. Less wrong every day.
#5. If you spend more than $10 million on advertising/marketing, it might be well worth it for you to completely skip all the attribution analysis challenges and jump to media-mix modeling by leveraging controlled experiments.
Optimize for your online media-mix at the start, then move to optimizing your online and offline media-mix. Media-mix modeling is harder and more time-consuming (hence the $10 million bar), but the payoff is huge and can be a competitive advantage.
We are done! Attribution modeling mastered! Hurray!!
As always, it's your turn now.
Are you doing any attribution modeling at the moment? What frustrates you about it? What benefits have come from your credit re-allocation efforts? Run into any organizational/ego problems with senior leaders yet? Love First Click or Linear attribution, what am I missing in my thinking? Which model is your BFF? What are two fatally flawed choices in my Mindblowing Model? What would you do differently? Has it been easy to go from analysis, end of this post, to insights to action?
Please share your feedback, critique, brilliant new ideas and radical proposals via comments.
by Mike Moran
As a long-time in-house SEO, you’d probably expect that I did not consider myself a fool at the time I was doing that. But I have recently gotten that question from a lawyer who wonders if he should do his own SEO, which reminds me of the old joke that a lawyers who represents himself has a fool for a client. But is it a bad idea to do your SEO in-house? I think it depends on how you go about it. If you think you’ll pick up everything you don’t know without any help, you’re probably looking at a rough ride
Before becoming your own SEO client, you need to ask yourself whether you are the ideal candidate to do it yourself, and if you are, how you’ll get the help you need (because no one knows it all). If you are trying to pick up many skills at once, you need to prioritize which ones are most important, but also ask yourself whether this is really worth the time you’ll put into it, instead of doing a better job of getting an expert to do it.
Originally posted on Biznology Blog
Be sure and visit our small business news site.
Perhaps you are skeptical.
I understand. We do have A LOT of data in our analytics tools.
But sometimes going outside our analytics tools can yield non-normal insights that can deliver a competitive advantage.
I want to share two such examples in this post. Neither is an example of just site analytics. Rather, its all about beyond-the-site analytics. Or maybe, beyond-our-blinders analytics. Or omg-why-am-I-not-rocking-whats-clearly-rock-worthy analytics.
With all that set up, you'll be surprised to learn that both examples are bar charts! Both drop dead simple in their presentation but incredible in the insights that they can bring to fore.
In the first case one value will come from the site analytics tool, the other one from your CMS. In the second example there is no site analytics data, that bar chart will tell you that you might be celebrating success too early when it comes to Search while pinpointing for you how high the upper limit is.
Excited? Let's learn a couple interesting analytical approaches, and have some fun.
#1: Content Creation – Content Consumption Balance Analysis.
This is a very simple analysis of the tussle between what you are providing vs. what the customers actually want. Originally I'd recommended it for content, or B2B, sites, over time I've come to rely on it for pretty much any type of company.
Content marketing is all the rage, as you are well aware of. Consistently producing good content that is relevant to your users is very important. Your users are happier. But fresh relevant content is also of value in our search engine optimization efforts, keeps a pipeline of socially shareable assets going. Both of these things combine to attract new audiences for our business.
The challenge is what to produce, what content to market? In answering that question we often get trapped in our "top ten pages viewed" type reports in our digital analytics tools. They sadly show a narrow siloed viewed of any website.
Try this on your site… total the percentage of unique pageviews in the the ten rows of most viewed pages report. What's the total? I'm confident it will be a tiny percentage. I'm sure you are going to discover that an astonishing percent of consumption is in rows beyond the top ten or twenty.
So how do we escape the narrow view? How can we look at tens of thousands of rows of data? How do we find a better balance between producing content that we like producing and content that our audiences actually crave?
Think of how difficult those questions are for Texas Instruments (or your website) to answer. There is sooooo much content there. How do we focus, and prioritize?
Here's a very simple way to start.
Step One: Count the amount of content in each area of your site, the data will be in your CMS platform. For www.ti.com the content clusters might be: Products, Applications, Tools & Software, Support, Community, Sample & Buy etc. For my beloved www.nytimes.com it might be World, US, Politics, Business, DealBook, Technology, Sports, Science, Health, Arts and Style. For a shampoo company it might be represented by these clusters: Expert Access, Personal Consultation, Products, Looks & Trends, Science, Samples & Offers.
Step Two: Count the unique pageviews in each of those areas, the data will be in your web analytics tool.
Unique pageviews is a count of the number of visits where a page is viewed, and in this case it is our proxy for interest. [Unique pageviews essentially removes multiple views of the page in each visit.]
Step Three: Plot this amazingly insightful bar chart (in this case for the shampoo/beauty products company)…..
In blue is the percentage of content in each section, and in red are the unique pageviews.
You'll always find something delightful when you plot this for your own site. But the first thing you'll note are the big mis-matches.
In this case the business has a ton of content in Personal Consultation, Products and Looks & Trends areas and yet almost no one who visits your site seems to care about it (as intimated by how many people visit that section). The highest amount of content is in the Science area, yet it only accounts for 10% of consumption.
The other side is not pretty either. There is a ton of interest in Expert Access, Samples & Offers and About your company. Yet you don't have nearly as much content in those areas. Not good either.
Now, be aware that we are not looking for a perfect straight line match. No siree, Bob! All the blue and red bars won't align, and perhaps they should not (after all we have to sell product! ).
But, you don't want vast mis-matches either.
What is the point in producing expensive videos on Looks & Trends when no one seems to care? And perhaps we need to figure out how to invest more in Expert Access because that seems to be the #1 thing people want.
[And can't you just see how this really deep understanding of customer interest, based on their data and not your opinions or, worse, an "expert's" opinion, will be incredible when it comes to fueling your social media strategy? Engagement will rain down from the sky in torrents!]
An amazingly simple, yet deeply insightful, analysis that raises valuable questions. All waiting for you at the intersection of your CMS data (% content) and your Digital Analytics platform (% unique pageviews).
This graph will just be the first important step.
I encourage a quick qualitative analysis of the content as well.
Is the content in Personal Consultation and Looks & Trends complete garbage? If it is then you want to raise the quality before you lay off the staff that is producing that content. And by layoff I mean lovingly reassign to productive areas.
Another cross-validation strategy I often use is to deploy the "greatest survey in the world ," and ask people the three golden questions: Why are you here? Where you able to complete your task? If not, why not?
The answers provide incredible context about why people really come to your site and deliver additional insights about where you invest in content production.
But it all starts with the graph.
Go do one for your own site. I promise it will be reveling. More than that, it will bring more customer-centricity to your digital efforts. And what do happier customers deliver? More revenue!
#2:Quantifying the Missed, Search, Opportunity.
Given current trends in how people seek out content online, how they look for answers to their problems, hunt for the next great product to solve their life problems…. it has become a benchmark that around half of your traffic should come via search engines like Bing, Google, Yandex, Baidu and others.
An obsession with SEO and PPC is pretty much warranted in most companies, across platforms (desktop, mobile – it is particularly heartbreaking how poor most companies do on mobile platforms).
All that said, it might surprise you that even today most companies don't know how profoundly they are missing the giganto opportunity that Search provides. There are many reasons for this. Management does not get it, they have no online products so why care, they are doing Facebook ads and really what else does anyone else need, yada, yada, yada.
I believe one of the most important reasons for under valuing the Search opportunity is: Data!
Data as in the source that a company uses to determine if their Search efforts are a success or failure. Data as in their web analytics tool of choice. Google Analytics. SiteCatalyst. WebTrends. Others.
What? Data you have is making you blind ? Yes. Let me explain.
When you log into Google Analytics and you see this graph for Search traffic (SEO + PPC) would you declare your Search efforts to be a resounding success and order champagne for everyone?
Most likely yes. And I would not fault you for doing that. This company has made impressive progress with acquiring ever more traffic via search engines.
Sadly this graph only reflects optimization of the local maxima .
What's missing from the celebration is the answer to this question: What does the global maxima look like?
In other words, what percentage of all the people you could possibly have captured at the search engine were you actually able to capture? What is the upper limit for what the above graph represents?
An amazing question, right?
If our search traffic was up 150% year-over-year, should it have been up 20,000% year-over-year because there is that much demand out there? And it is not up that much because our Search program is simply not ambitious enough? Or worse, because we stink?
Your web analytics tool can't answer that question because it does not have the data, hence you are unable to make the smartest possible decision about your Search success.
But fear not, this is a solveable problem.
This bar chart attempts to answer that question by showing you the demand that was at the search engine, and the percentage that you, in this case a travel company, captured….
If you were this travel company, the bar graph might take your breath away.
You are all about booking hotel rooms, selling airline tickets, renting cars, you've invested enormous sums in high margin activity like booking cruises (entire ships!) and up-selling lucrative activities and excursions.
Yet your magnificent search strategy (SEO + PPC) resulted in you capturing such a small percentage of the demand!
Remember these are not random people you target on TV or Radio whose intention/relevance you are utterly clueless about. These were actual people who are raising their hands and essentially saying "sell to me, I want something you have!" To think you just managed to get those little green bar's worth.
But, remember our blue Analytics graph above? According to that we are totally rocking Search!
Yes, that is true and you should be happy about that (local maxima). You should not be satisfied. In fact you should be downright hungry/angry/happy because of the orange bars (the global maxima!).
For every Search (or other media platform) at a strategic level you should ask yourself this question: Are we optimizing for a local maxima or a global maxima?
I would recommend that latter. It is harder, more fun and you get to deliver crazy business success!
Then the question becomes…. where do you get this valuable orange-green graph?
There are two ways to look at the data you see. Impression Share or Click Share.
In both cases you have to do a bunch of work, the good news is that this is strategic analysis and you don't do it every single day (unless you absolutely insist on wasting your time).
Search Impression Share.
Traditional marketers (especially those that grew up with TV, billboards, or digital display advertising) try to solve for impressions. "How many times did people search for xyz, of those how many times did my website show up on the search results page, paid plus organic?" How many impressions did our brand get?
Not a problem. For Google you can use the AdWords Keyword Tool to get the data you are looking for. (For other search engines please reach out to your Account Manager at that company, they'll share this with you in 20 seconds.)
Here's what the screen will look like…
The query you run, like I'm doing for Market Motive, my startup that offers certification courses in Analytics. SEO, PPC, Mobile marketing, will return Ad Group ideas and Keyword ideas.
You'll be able to see a lot of fun data, but we are interested in two columns: Ad Share and Search Share.
Here are the official definitions:
This statistic describes the percentage of time that your ad is triggered. This statistic is specific to Google search performance only for your targeted country or territory.
This statistic describes the percentage of time that your website appeared on the first page of organic results. This statistic is specific to Google search performance only for your targeted country or territory
Essentially your Impression Share for Paid and Organic search results for the last 30 days.
It would be really cool to get this data clustered in your business categories (example: Hotels, Airlines, Rental Cars, Travel Leisure Activities, etc). You can't. You'll get individual keywords or clustered by Ad Group ideas. Extra work for you to download the data and aggregate it, but it is very valuable data so put in the extra effort.
The Ad Groups view is pretty helpful from an aggregated perspective. For Market Motive for example it gives: Certification Programs, Training Courses, Training and Certification, Online Classes etc, etc. From there you can see how using Ad Share and Search Share I can create my own Orange-Green graph for Impression Share.
There are all kinds of filters you can explore in the AdWords Keyword Tool for mobile or desktop or language or countries etc.
The data is aggregated, but remember you are not trying to pinpoint the last click here. You are trying to get a very broad understanding of how much of the share of shelf you are successful in capturing from a strategic perspective.
Note: You'll only see Ad Share and Search Share data if your business' AdWords account is connected to your login. I.E. only proven owners of the data can see it.
Search Click Share.
For me personally this is a lot more fun.
My site could show up in search results a million times (so tons of impression on Google/Bing) and yet I might never get a single click. Even if I'm ranked #1 (Organic or Paid), I might have terrible copy in the SERPs or my Ad. Worse, my PPC ad might always be #8. Or my Organic result has not site links showing up or my Organic strategy is from 1969 and not yet adopted for Universal Search awesomeness.
So I like measuring Click Share, I don't like measuring impressions as a success of anything for my search strategy.
Of all the people who searched on www.bing.com for my specific keyword, or my specific business category, how many did I manage to attract to my website?
Really cool, right?
It will really put that blue graph from my web analytics tool in context. It will really help me understand my global maxima for search. Or something close to it.
You have two sub-choices to get your Search Click Share metric.
You can use a competitive intelligence tool like www.compete.com and run a Keyword Destinations report.
My query above is for airline tickets. I get a whole bunch of cool data, including how much I or my competitors are getting (Volume column), along with the distribution of Paid and Natural for the aforementioned volume of clicks.
You can create our orange-green graph from this data.
Compete is a competitive intelligence (CI) tool and you should spend some time understanding how CI tools collect data: 8 Competitive Intelligence Data Sources & Best Practices. Perhaps there is no greater place to remember GIGO than CI tools.
Another wonderful option for this data is to directly go to the source of the data, the search engine.
If you reach out to your Account Manager at Bing, Google, Yahoo! or other search engines, then they will be able to directly give you the Search Click Share orange-green graph.
The colors might look different and the data might be a visual representation rather than giving you a specific number down to the 45th decimal point (as I said earlier that is actually not that important)….
Usually the search engine will give you your Search Click Share, yellow bar above, for each of your business categories (a multi-channel retailer above). The overall size of the opportunity is represented by the light gray bar. Some of the sophisticated search engines will also index your performance against a peer leader (dark gray above).
The collection of these three elements will deliver the type of mind-blowing context that changes the way you think about Search, the size of the opportunity and the success you've achieved thus far.
Now you'll not only have my orange-green, you'll also know that while you and your category peer leader might think they are mortal enemies and fighting a zero sum game, the pie in reality is huge (represented by the light gray). Both of you need to internalize this new scale, identify who these new "enemies" are, and develop a new game plan to win.
This data, remember its strategic analysis, helps you re-imagine your Search strategy, your digital focus areas and how you define, measure and reward success, or recognize the scope of failure, by your digital marketing team / agency.
So if your search account has an assigned Account Manager request them to give you this view of Click Share for your business lines. If you don't have an assigned Account Manager, consider using a competitive intelligence source like Compete or looking at the impression share data from the AdWords Keyword tool.
If I had to summarize this entire post: Step outside your web analytics tool. Ask smarter questions. Win big.
As always, it is your turn now.
Does your company, or perhaps you, use either of these two bar charts? If yes, which one do you find more actionable? If no, what changes might they drive in your digital strategy? Do you have other examples of data from outside site analytics tools that you find incredibly insightful?
Please share your recommendations, wisdom, critique and experiences via comments.