5 Ways to Know Your Site Has Been Penalized By Google

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seoHave 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

  1. 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.
  2. 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.
  3. 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.
  4. PageRank
    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.
  5. 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!

August 16th 2013 Google, Search Engine Marketing, SEO

AdWords Editor Update Brings Upgraded Sitelink Management And More

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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.

August 14th 2013 PPC, Search Engine Marketing

Multi-Channel Attribution Modeling: The Good, Bad and Ugly Models

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balance 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:

~ Three Unique Attribution Challenges.

~ Do You Have an Attribution Problem?

~ The Best Next Steps/The First Best Steps.

~ Multi-Channel Attribution Models.

~ Multi-Channel Attribution Analysis.
~ In Closing, Five Quick Tips/Reality Checks.


Excited? Grab a Red Bull. Let's go!

Three Unique Attribution Challenges.

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-AMS covers the challenge of attributing accurate impact of our marketing and advertising efforts across multiple devices (desktop, laptop, mobile, TV).

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).

digital marketing path to conversion1

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.

Do You Have an Attribution Problem?


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.

path length multi channel conversion visualizer

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 Best Next Steps/The First Best Steps.

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.

top conversion paths

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.

Multi-Channel Attribution Models.

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?

last click vs linear attribution model

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!

OMG! Really?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).

digital marketing path to conversion1

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?

last click attribution modeling 1

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.

last non direct click attribution model

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.

last adwords click attribution model

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.

first interaction click attribution model

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."

Eschew irrationality.

linear attribution model

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.

time decay attribution model

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?

time decay attribution model adjust half life

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.

position based attribution model

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.

custom 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…

custom attribution model step one baseline

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."

custom attribution model step two look back window

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.

custom attribution model step three user engagement

Time on Site is always a tricky computation. In all Web Analytics tools, unless you apply custom code, time on site is not computed for bounce visits or for the last page viewed in a visit.

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.

custom attribution model step four custom credit rules

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 ….

market motive custom 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.

Multi-Channel Attribution Analysis.

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.

multi channel attribution analysis

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.

In Closing, Five Quick Tips/Reality Checks.

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.

Thank you.

Multi-Channel Attribution Modeling: The Good, Bad and Ugly Models is a post from: Occam's Razor by Avinash Kaushik

Does an In-House SEO Have a Fool for a Client?

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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 

When I ran the search marketing at IBM, I think I was a bit unusual in a few ways. First, I had a deep knowledge of search technology going back 15 years at the time, so a lot of the concepts were easy to me. Also, I had an education in marketing, including direct marketing, so I understood the business side, too. In addition, I had worked at IBM for over 20 years at that time, so I intimately understood the products and services as well as the potential clients, being an IT person myself. Looking back on it, I was an ideal candidate for the job. 
But I didn’t do it all by myself. I not only attended conferences and read up on everything I could find, I also hired a search consultancy to tutor me in everything that I did not know. That is how I met Bil Hunt and how we ended up writing a book together. 
So, you might also be an ideal candidate for your own in-house SEO, but it would probably help you to take advantage of whatever help you can afford. And it’s worth asking if SEO is even your biggest problem at the moment. 
So when that lawyer told me he was a newbie at Web sites who had a lousy experience with an SEO consultant, and then asked if it was a “pipe dream” for him to do his own SEO, this is part of what I told him:
I don’t think that doing your own SEO is a pipe dream if you have enough technical skills to maintain your Web site. If you don’t, then your goal needs to be to get someone who does. But you need to ask yourself whether you are ready for SEO. I’d focus first on the Web site itself and later on the SEO. It’s not the advice that I would give to everyone, but there are so many skills that you are trying to pick up at once that I think you need to set priorities. I think that the two places to start are analytics and site building. Pick a site builder and create your site, enabling it with the analytics to see what people are actually doing. Start to tweak your site to improve the number of people converting and track that it is really happening. At that point, it makes sense to focus on SEO, so that you attract more people to come to your site. I know that you are in a hurry, but that is the order I would prescribe. If you are in a big hurry, you are probably better off trying again to hire someone to do things for you while you bone up on your new skills. It all depends on how expensive it is to get the work done vs. the opportunity cost of taking six months or more to have everything done by doing it yourself.
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.

Two Amazing Bar Charts: % Content Consumption, % Share of Search

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two of a kind 3Would you believe me when I say that your digital analytics data, from Google Analytics or WebTrends et. al., might be hindering your ability to make some important strategic decisions?

Would you believe me if I said that even leveraging cool features like custom reporting and smart advanced segments might be insufficient in some cases?

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.

Two stories.

#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?

texas instruments 11

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)…..

content consumption content creation balance 1

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?

search overview report google analytics

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….

search opportunity analysis

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…

adwords keyword tool keyword ideas

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:

Ad Share
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.

Search Share
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.

compete search 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)….

click share of search

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.

Thank you.

Two Amazing Bar Charts: % Content Consumption, % Share of Search is a post from: Occam's Razor by Avinash Kaushik

July 1st 2013 Search Engine Marketing

In Search Marketing, Focus on What’s Important

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by Mike Moran

Search marketing seems like it changes every minute, and it’s hard to blame anyone who is worried about falling behind. With big news such as Google Instant seemingly coming every instant, anyone might be concerned that their SEO knowledge is becoming outdated and that their search rankings will be the next thing to drop. I got a Facebook message from someone in just such a predicament and I decided to share my answer to him with you all.

Quick question. I hope you can help me. With so much change from Google in the recent months and weekly algorithm changes I am sure to come… and so much info in the blogosphere… I am wondering… what is the best way to keep up with it all? I have both your SEO books… first and second editions. If I stayed focused with all that you teach in the books and not pay attention to all the info out there… will I still be OK and ranking organically? Thanks Mike!

Well, Larry, no one can guarantee that you’ll be OK no matter what you do. But I am sure that you do not need to keep up with every algorithm change to succeed in organic search marketing.

There are some people who can follow every twist and turn of Google’s algorithm (and Bing’s too, for that matter), but if that describes you, then why are you reading my blog? No, my readers need advice that won’t change next week, which is what I give you.

The basics of search marketing don’t change:

  • You must know what searchers are looking for. Every keyword they use, every piece of content, they’ll be watching you. Or they won’t. It all depends on whether you know what they want.
  • You must have a better answer than other people do. If you’ve really got a good answer for their question–better than what almost everyone else has, then you’ll be found. If not, not.
  • You must be able to sell something related to the answer. Sometimes, that’s easy because they are searching for the exact thing that you make. But other times, they are looking for the solution to a problem, so you need to sell what solves it for them.

In many ways, search marketing is much more complicated than that. (Hey, Bill Hunt and I wrote a 600-page book on it, so it better be.) But in some ways, it is just that simple. Keep your eye on what’s important and ignore the rest. Sure, sometimes you might feel like others are gaming the system, but most of the time it works out in the long run. Best of luck to you.

I’m focusing on what’s important, too. I have been threatening to write my third book for two years but I haven’t had the time. So I am taking most of next week off to take another chunk out of that effort. I am staying off Twitter and not posting to my blog either. I’ll see you again on October 25. You, my readers, are very important to me, but when I need to focus on something, sometimes I need to take a break from social media for a while. I believe that I come back fresher, with more ideas when I do that. Thanks for understanding.
Originally Posted on Biznology Blog

Be sure and visit our small business news site.

Your Guide to Local SEO 2013

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by Chris Warden

The importance of local search on the future of your
business can’t be understated. Google, Yahoo, Bing and now Facebook have all
placed an emphasis on being able to find, review and recommend local
businesses. If the four biggest websites on the Internet are all pointing in
the same direction, isn’t it about time you took the idea seriously?

Not only is local search traffic more apt to buy, and buy
quickly, it’s the traffic that you’re often paying a fortune to reach when
using other marketing channels (ads, direct mail, commercials, etc.).

It’s time to get serious about local SEO, and this guide
should be just what you need to get you started. 

Local SEO – “Why is it important?”

Local SEO – “Optimization and Understanding Your Users”

Local SEO – “Rank Factors: Places Listing and Social Media”

Local SEO – “Rank Factors: Review Sites”

Local SEO – “Citations & Linking”

Local SEO – “Analytics and Tracking”

Be sure and visit our small business news site.

Confessions Of A $100/Month SEO Client

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Are you an agency trying to sell super cheap search marketing services to SMBs? If so, here’s some free market research! Last week, I got my kitchen counters resurfaced. Inevitably the service guy asked me what I did for a living. When I told him I did SEO, the conversation quickly turned to…

Please visit Search Engine Land for the full article.

June 10th 2013 Search Engine Marketing

Excellent Analytics Tip #25: Decrapify Search, Social Compound Metrics

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off centerEveryone likes chasing big shiny objects all the time. What's not to like. They are big. They are shiny. :)

But a lot of progress in life comes from doing the everyday small things better. A small improvement, every single day, to move the ball a little more forward.

A best practice I've developed is to take a step back and reflect on if I have a good balance between chasing shiny objects and making incremental progress on small every day things.

Today's post is from the latter category. It is a story about dealing with a complicated everyday challenge in an incrementally better way.

It is not quite about web analytics, not quite about data you can just get from WebTrends or Google Analytics, and not quite about just making yet another pretty chart. Rather it is about trying to step back and to think differently about a particular problem and, this is so scary, fighting to not simplify things to the point of uselessness.

I deeply wish that the problem we confront in this post did not exist at all. I wish we did not have this desire to pulpify a bunch of metrics to produce something recognizable. But it does exist, and so let us figure out how to incrementally improve the insights we can deliver.

Here's a summary of our journey in this delightful post…

~ What are Compound Metrics?
~ The Challenge with Compound Metrics: Social Media Edition
~ Compound Metrics "Decrapification" Strategy: Social: Standard Approach
~ Compound Metrics "Decrapification" Strategy: Social: Awesome Approach
~ Compound Metrics "Decrapification" Strategy: Search: Awesome Approach

Ready? Let's go…

What are Compound Metrics?

Compound metrics are everywhere. An example from the world of sports is the NFL Passer Rating (don't worry, no one really understands what it is). In a government context, Consumer Confidence Index and Consumer Price Index are good examples. One that you likely care about a lot is your FICO credit score. Perhaps the most famous digital compound metric is PageRank .

In a digital analytics context a compound metric might be…

Visit Quality = [(% of downloads + % of visits with more than 68 pageviews - % of visits with less 2 pages + % visits with Facebook shares + % of visits with store searches)/5)*1476]

The goal would be to communicate, perhaps, the quality of the site or the quality of each visit or quality of the outcomes, to the Dear Leader in your company using an "one simple easy metric."

I understand why people want to create compound metrics.

We have too much data on the web. We can measure way too much nuance, and sub-nuance and sub-sub-nuance. Because there is so much, and so much of our leadership is full of simple minds (not a ding, we should not expect them to be Analysts), the instinct is to "make it all simple, make it into one simple number" in the hope that they'll understand what's going on.

The intent behind creating compound metrics is good, sadly the outcome never is.

The Challenge with Compound Metrics: Social Media Edition

Go back and look at the Visit Quality compound metric someone's defined above. Do you see the problem? Do you see why it would be nearly impossible for you to look at the number that get's spit out every day/week/month and learn almost nothing from it – even if the number moves every time ?

For a bit more on the other reasons please see: Actively avoid insights: Use Compound Metrics

Here's a summary: When you cross-breed a bunch of metrics to produce a, I'm being charitable here, hybrid "simple number," the process, by design, hides insights, hinders the ability to understand performance and almost never allows the management team to identify root-causes.

Let's look at a practical example that demonstrates why I'm allergic to compound metrics.

Tool X below computes a social influence score for me. I'm a 83.

(Even if you can recognize this tool can I please request that you not name it in comments? They are hardly unique in creating compound metrics in the social analytics space. Thank you.)

social score avinash

So what does that 83 mean?


I just know that I'm 83 and a peer of mine is 87 and another one is 76. So what? More importantly, what do I do now?

There is a trend in the image. I can see it goes up and down.

Why does it do that? Not clear at all.

What contributes to 83 that causes the trend to go up and down, or for that matter what causes the 87?

No clarity.

So what do we do with the 83? Well… It depends on what you are measuring. Oh, it's not clear what it is measuring. Hmm… so it is useless?

They do share how much of this influence is from my presence on Twitter, Google+, Facebook and Wikipedia. Oh… Maybe that helps?

social influence breakdown

No. Not really.

So what's the 83 and what can you do with it?


This is the problem with compound metrics. You don't know what causes the final number to happen. You don't know the focusing factors, hence you are blind to why things go up/down and what actions you can take to improve.

In this case this Tool X is deliberately hiding all the focusing factors because they don't want you to game the system. I respect that. But for me as the recipient of this "boiled down from all the complexity simple metric that anyone can understand" it is a little less than useless.

Compound metrics. #arrrrhhhh

Let's look at another example and bring the problem closer to a company level challenge.

(Again, I just pulled a random example. If you know the tool or the provider, please do not mention it in comments. They are not unique in being guilty. Thank you.)

Tool Y shares this comparison of two companies.

15 1

What can you learn from it? In their social presence each company wants more of the Engagement Rate, what insights can you derive about each company from Engagement Rate performance above?

Yes. One seems high and other other seems low, in extremely tiny percentage terms.

But can you learn anything about what Mercedes-Benz is doing right or wrong? How about Audi? What might they be doing right or wrong?

Nothing. Zip. Nada.

You don't even know if 0.670% is awesome or completely sucky. You might if you knew that the upper limit or benchmark for Engagement Rate is 100%. That would give you incredible context. But you don't get that above. That in turn implies you don't even know if Mercedes-Benz is just a little less than awesome or really totally completely sucky!

What if you were kindly told by Tool Y that this is the formula used to compute Engagement Rate…

facebook engagement score attempt 1

(Remember, don't mention the tool or the company in comments. EVERYONE does this, let's not single them out.)

Does it help?

Now can you tell me what 0.290% and 0.670% mean?

And, always more importantly, why 0.670% became 0.670%? What caused Audi's number to be higher than MB?

Let's say this was not Audi and MB.

In April your Website Engagement Rate (WER) was 29 and in May your WER was 67. Would the score of that compound metric be able to tell you anything about what you did better or worse? Would your management team know what action to take when you plonk this compound metric in a dashboard?

Extremely highly improbable. Hence my allergy to compound metrics.

[PS: The above formula is not even the most sub-optimal one. There are social/search/website engagement/quality/experience compound metrics that are much, much worse. Those exquisite beauties contain weights, multipliers and other sundry "values" attached to each element in the formula. "Values" that are sourced from nothing more than our biases and blind spots. The end result is unique type of awful that you have to experience to believe.]

Compound Metrics "Decrapification" Strategy: Social: Standard Approach

If you can avoid compound metrics, that is the optimal. Rather can creating unrecognizable pulp, use the Digital Marketing and Measurement Model process to identify the best direct key performance metric. Use them to deliver insights that directly drive ultimate business profitability.

In our social scenario above I'll take inspiration from the Digital Marketing and Measurement Model process to create an alternative simple approach to using compound metrics.

Rather than "simplify" things and put five metrics into a blender and puke out an "easy to understand" number, my strategy would be to expose the focusing factors in order to encourage our leadership to look a little deeper to understand performance.

Instead of calculating the "Average Social Engagement Rate," I would much rather (as recommended in the Best Social Media Metrics post) show the management team this…

best social media metrics 1

Four metrics, not "one simple easy metric."

The first three, Conversation Rate, Amplification Rate, Applause Rate, show, wait for it…. engagement (!) on the social channels. As you look across you can see how well or badly you are doing on individual channels and the last row beautifully shows how much money we make off each social visit to your digital existence.

Sweet, right?

[If you would like to get the above view for your social media efforts please checkout True Social Metrics.]

What about Audi and Mercedes-Benz?

Instead of the cute infographic compound metric view with two other value deficient metrics, number of fans and total "interactions," would it not be magnificently been better to show this…

alternative to social engagement rate compound metric 1

Yes, it is neither cute looking nor "one simple easy metric." It is also a little harder on the eyes. The recipient will have to think a little harder.

But would you agree that the above view makes it really, really, easy to understand social engagement AND social's impact on the business of each company?

So, if you are willing to trade a small amount of pain (the discussion you have to have with your Dear Leader that a "one simple easy metric" might actually not be so simple or easy or valuable, and that you'll show they a bit more data), then it is entirely possible to completely avoid having to use a compound metric. Imagine the waves of pleasure that will wash over your body because you no longer have to create a crazy formula based on little more than biases and blind spots (exemplified by the Engagement Rate formula above).

Oh, and this works beautifully even if you look at just one company and their performance over a period of time.

Let's say we work for Audi (hurray!) and want to show social performance. Rather than saying the Average Engagement Rate was 0.67%, 0.68%, 0.57%, we can just show this table….

alternative to social engagement rate compound metric 2

Yes, more data. But so much easier for the Dear Leader to understand performance, brainstorm on root-causes and discuss fixes with the leadership circle.

Progress. Prosperity.

Compound Metrics "Decrapification" Strategy: Social: Awesome Approach

What if you are in a situation where your good intentions are insufficient?

What if you are a little minion, but a poor humble soul, who no one cares about and who's being whipped into creating compound metrics?

It does happen. Sometimes you simply can't avoid it. There is too much pressure to "simplify" things.

What do you do? How to ensure that you still deliver something of value?

Here's my suggestion: Give them want they want, but package with it what they need. Oh and while they are at it, include the one disruptive thing that will give them critical performance context!

Show them this….

audi social engagement score 1

We have the "one simple easy metric" up top. (Happy?) Then we have the focusing factors (contributing elements) clearly outlined. Further more we show them performance of each element.

But we don't stop there! We also include something that is incredibly valuable for Dear Leaders around the world in trying to understand performance: We include critical context to illustrate if the performance seen is good or bad.

For the last part (the big gray box) I've used 1. an available benchmark for the metric or 2. an upper limit I'm aware of or have computed from existing data or 3. a target we as a company are shooting for.

Now the Dear Leader has what they wanted, but we've also provided what they needed to go from data to action.

It should be quite obvious why your company will make smarter decisions now.

Oh, and you don't have to use my best social media metrics . You can use anything you want for your formula that computes your compound metric.

For example you can do this….

audi social engagement score 2

I don't think it's better. But what do you care. : )

The point is, you should embrace the framework. You can use any reasonably relevant collection of metrics, for the compound metric you are trying to create. Just make sure your focusing factors (metrics you use) are as complete as possible, and ideally independent from each other.

Switching back to my original four focusing factors… you can now see exactly how this would look like if we wanted to compare the Social Engagement Scores of Audi and Mercedes-Benz…

mercedes audi social media savvy comparison

So, so, so much better right?

Even though the compound metric is there on top, you'll deliver a deeper understanding of why Mercedes is at 0.290% and Audi is at 0.670%. Both companies can learn from the other and figure out how to fix their social strategy to rock more.

And remember the above visualization could be for the month of May and June for one company. Still works beautifully in explaining the performance of the "one simple easy metric."

Compound Metrics "Decrapification" Strategy: Search: Awesome Approach

As I'd mentioned earlier, this approach could work in other contexts as well – any time you end up with a compound metric.

You follow the same three step process for decrapification outlined above:

1. Show the compound metric.
2. Show the contributing metric's performance.
3. Show that against a benchmark or upper limit or target.

Step three above is something I've started to do a lot recently, my tiny incremental innovation if you will.

Let's look at one more example to really solidify this three step process for you. Since we've beaten Social to death already, let's look at another exiting area: Search.

This example is one where I was unable to run away from a compound metric. I had to create one. Boo!

The mandate was to try and figure out how to show any company their "overall Search performance" using a "one simple easy metric."

How is that even possible given the insane complexity that is the digital Search business? But mandates demand that we deliver, so off we go.

Here's my humble attempt at a Search Performance Index (SPI)…

zqi search performance index 3

It boils the entire complicated paid search business into four key levers (four focusing factors, four key metrics). Keyword Relevancy, Bid/Budget Savvy, Ad Creativity (copy, sitelinks, offers), and Geo/Targeting Smarts. It uses those levers to create an index (score on top).

I'll let your imagination run wild as to how the score itself is computed. (If there is interest, I'll share it in a future blog post.)

The cool part is not that there is an overall score that the Dear Leader can look at and be thrilled with. The cool part is that she/he will be forced to glance, even if for a moment, at the focusing factors that explain why the Search Performance Index is at 643. The coolest part is that they'll know which area needs more attention because of the distance between the current performance and what's possible (the benchmark/upper limit/target).

Now it is easy for them to prioritize where we should devote resources to improve the SPI. Action!

That is, dear blog readers, to borrow a phrase, priceless.

I'm sure you noticed that while there is a lot of data behind the simple visualization above, there is almost no data overtly present. Just a bunch of bars.

That is by design. Sharing a more nuanced view of reality does not have to be complicated. Take everything away, until you just have the things you absolutely need left.

Once you have that nailed the focusing factors and the compound metric formula, it is easy to do cool stuff with it (if you have access to the data).

You can look at the compound metric across competitors and smile (or cry)….

search performance index competitive indexing 1

I'm beating this to death, but how much more fun is it that you know why the SPI for each company is where it is? Rather than just know the number all by itself?

And even if you are ZQ Inc (643) you can see that you are at least good at one thing (ad creativity) and you can figure out how to use that strength – even as you fix the other focusing factors .

You can/should do this to understand your own performance over time. And you don't have to use my choices above. I want to stress the process and not prescribe the metrics you should use.

Internalize the process. Spend some time understanding your own unique business needs, get advice from experts out there and create an extra-special magical formula that you believe will deliver glorious insights. Remove the metric you don't need above, plonk in your new BFF.

The next time your Awesome Search Performance Agency is doing their quarterly review, ask them to open their presentation with this view of the SPI….

search performance index quarterly 2

Dear Leader is happy, she/he has the "one simple easy metric."

You are happy because you snuck in just enough information to make the index easier to understand.

Your Agency is delighted because you are asking for a much more sophisticated understanding of reality to show the value of your huge investment in the Agency and Search. Agencies want their feet held to the fire, they love accountability.

Win – win – win.


So often we report (puke) data, we diligently produce (puke) dashboards, we lovingly create (puke) slides. But it is rare that our efforts drive action. It's not because our puking was not great, it is simply because we are unable to succinctly bring forth the underlying focusing factors and present them in a way that is accretive to quick internalization of which of the focusing factors need killing and which need feeding.

Solve for that.

And now you know how.

Ok, it is your turn.

Do you agree that compound metrics are sub-optimal? Are there compound metrics your company uses that you've simply failed to kill? Or other compound metrics that are your favorite? How do you deal with the insights that delivery actionability challenge that mashing five metrics into one to produce a paste presents? Do you think showing the focusing factors beneath the "one simple easy metric" will work inside your company? How can I make the above approach even better?

Please share your ideas, critique, praise, improvements, examples in comments below.

Thank you.

Excellent Analytics Tip #25: Decrapify Search, Social Compound Metrics is a post from: Occam's Razor by Avinash Kaushik

Excellent Analytics Tip #24: Obsess About Real Business Profitability

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elegance The art of analysis often fails to deliver ginarmous success simply because of how limited our worldview is when we go about identifying bottom-line impacting insights.

Hence, this is a post on a simple concept that will drag you out of your current "what is happening on my website?" comfort zone, and out of your Google Analytics, Site Catalyst, WebTrends worldview silo.

Sounds like fun?

It is. And you end up becoming rich and famous. Not too shabby, right?

Macro Business Context: The Big Deal

Digital is an obsession for almost everyone who reads this blog. Part of the reason is that even if you work for a multi-channel company you are likely in the "web," "interactive," "internet," or "digital" division. That narrows your responsibilities, and in turn your worldview. Part of the reason is that the data you to which you have access narrows your worldview – "Hey, all I have is Google Analytics, so all I'll look at is Google Analytics data!"

Somewhere inside us we know that there is more to our business than digital; we are not stupid. But the two reasons above combine to narrow our focus. This does not mean you'll cause a huge disaster for your company. No. But it is very likely that you are not going to have the hugest possible impact. Your company will be, at best, just as good as others (since people at other companies also have conveniently narrow world views).

I don't like that.

We should shoot for the stars! We should shoot for magnificent glory!

Let's try to do that today with a very simple story, one that I hope will have much broader implications on your digital success measurement.

Macro Business Context: The Challenge

I was working with a company that runs a private college type system. Let's call them ZQI University.

At ZQI U, a vast number of students enroll into online-only courses (just like our analytics, PPC, mobile, and SEO Master Certification students at my awesome Market Motive). But ZQI U also has many real world campuses, so students can enroll online and attend in the real world.

Digital advertising and marketing is a key part of ZQI's multi-channel acquisition portfolio. They do everything.

digital advertising portfolio

The cloud above is a rough to-scale approximation of their current traffic sources. As is common in these types of educational companies, aggregators rule the roost. They are simply much better and way more aggressive than the educational companies themselves. They are also a lot less weighed down by legacy mental models than the educational companies, which enables them to think smarter and move faster.

So if you are ZQI, how should you measure success? How should you decide which one of these acquisition sources you should invest in more? How do you decide which one delivers higher value to the business?

Business As Usual

The answer to those questions might seem obvious.

Tell me how many people came to my website. Tell me how many of those converted into leads.

Well, that is quite easy. Just crack open your funnel in WebTrends, or the analytics tool you temporarily call your BFF.

visits to leads

Now that you have the macro view (don't expect your lead generation/conversion rate to look that good!), how can you figure out which acquisition channel is more important?

Again, easey peasey.

Apply advanced acquisition segments to your data, press a button here and press a button there and … boom!

advanced segments conversions

The above image only illustrates three segments and their conversions – search, referrals, and aggregators – purely for the sake for simplicity.

Back to the question, where should we invest more / which source is the best one for our business? Which fire should we add more fuel to?

The answer is simple: Aggregators.

They are the best drivers of traffic, they are the best generators of leads. Let's go find more aggregators / increase the bounty / be more aggressive in another way to get them to promote ZQI University.

And that is where we normally stop. I'd be lying if I did not also say that at this point we also expect a pat on the back / bonus / promotion.

The Fly in the Ointment

The challenge, of course, is that getting leads adds zero value to the business. As digital practitioners, we forget that blunt truth. In this case some value comes only if the student completes an application.

So Site Catalyst is essentially showing you a limited funnel if all you look at is the above picture.

Even if you are the digital analyst you need to at the very minimum look at this funnel …

better visits to conversion view

At the moment you don't look at the third step for a very simple reason. That data is not in Google Analytics. It is in some ERP/CRM/Backend system inside your company. And you don't have access to it.

Go hit someone up. With a chat if that works. With a Facebook poke if that works. With a lovely smile if that works. With a threatening glare if you are good at that sort of a thing.

Because you need to know if you your earlier answer, that you should be pumping your precious marketing dollars to Aggregators, is the right answer.

Resist the instinct to go to the CFO with a massively parallel processed big data warehouse monkey dance business lack of intelligence tool to comprehensively measure everything and God.

It will take too long. It will cost too much. It will never have ROA (return on analytics).

You CFO might also laugh at you and shoo you out of her office.

Just get a quick dump of the completed applications into Excel. Join that data with your Site Catalyst / WebTrends data with the lead_id as your primary key.

Now apply your original segments to the funnel, and boom!

better conversion funnel view with segments


What happened to all those "valuable" leads from Aggregators? And your "analyst expert" recommendation was to invest more in Aggregators. Ouch. : )

That tiny sliver of traffic from Referrals is not looking so bad now, is it?

And just look at all that Search traffic from Bing!

Now, what's your recommendation to the business?

Different, right?

That is what I mean by measuring real end-to-end success, about obsessing about real business profitability.

Forget Digital Conversions, Obsess About Real Business Profitability

Wait, wait, wait. Simmer down. I know. I know what you are going to say, you smart, awesome person that you are.

I do know that real business profitability for ZQI U does not come from the number of successful applications submitted.

Here's the rest of the funnel that takes us down to the actual point of real business profitability:

complete university online offline conversion funnel 2

We only make the maximum amount of money as a business, after the student completes the course.

If they submit the application and are accepted, but don't enroll in the course, we don't make money.

If they enroll in the course but don't start the course, we don't make much money (maybe some cancellation fees, but come on, that is a pathetic revenue source).

If they start the course but don't complete it, we've not made the *complete* amount of money,

So when you head out to measure the success of your digital advertising and marketing, you need to know the conversion rate at step six, not just step two. Yes, in Google Analytics you can only see step two. Yes, you will have to wait for step six to be completed and it does take time – how do you feed the "real time optimization" monster (just remember, in real time if you optimize garbage, you still have garbage)?

For tactical optimization, maybe you can use step five as your success point (# of students that Started the course / # of Visits to the site). But when it comes to strategic media (ad/marketing) budget optimization, you need to look at step six (Completions).

And how do you know where to invest your ad dollars? Here you go…

real business profitability acquisition analysis

Aggregators send 40% of the traffic to your site. A lot of that traffic also submits leads that go to your normal sales process. But when it comes to the quality of students that aggregators send to ZQI U, the students that successfully complete the course (hurray for them!) and deliver real business profitability to us, aggregators fall short. Way short.

ZQI should be obsessing incessantly about Referral traffic. Even if it looks like a small referrer, we can see it delivers a good chunk of ultimate profitability. ZQI should obsess about Search because it delivers 40% of the ultimate business profitability, from just 20% of the site traffic.

This is how business practitioners become worthy of a ticker tape parade in downtown:

By not focusing on just the digital data. By not focusing on just the digital conversions. By not even focusing on false prophets masquerading as real offline conversions. But by focusing on the ultimate business point of profitability.

Here's a simple picture to illustrate the key concepts. On the left the area where the engagement happens, on the right the amount of profitability accrued to your business.

digital non digital real profitability 1

Explains so much about why so often digital analysts are not taken seriously, right? If you stop at the point where the company has made no money, why should you be taken seriously?

Let me repeat, you can do this using a massively parallel processed big data warehouse monkey dance business lack of intelligence tool to comprehensively measure everything and God. That would be almost a perfect boondoggle for digital analytics consulting companies, or your internal IT teams.

But you don't have to.

It is manual, hard and not long-term sustainable, but you can get by with Excel (and my pretty conversion of the Excel data into the above PowerPoint picture!) for a while. You can earn trust, credibility and impact the business. Then you can go on your boondoggle. That would be ok, and perhaps even necessary as you scale.

And what metric should you focus on in this proper end-to-end view?

You can take any number of complicated paths. I try to keep things as simple as possible (Occam's Razor!).

complete conversion funnel abandonment rate

Start simply by measuring the abandonment rate of each step in the process. Where's the leakage? Prioritize fixes.

Even with this simple view you can quickly identify where there are overall issues, or just for particular segments. It helps bring focus, it helps identify actions that add business value.

The mental model is simple. It might be a little difficult to get abandonment rates at each steps, you might have to deal with people, process, politics. But, as advised earlier in the post, you start with aggregate data for just these segments, you might find smoother sailing. You can complicate things later.

Remember, the quest is simple. We are not going to accept stopping at where our job responsibility stops (digital). We are not going to accept stopping where our web analytics data stops. We are going all the way to the real point of business profitability!

Identify the Real Business Profitability Point: E-commerce

We've used a university to illustrate the incredible value of going all the way down to the real business point of profitability. But you can go through this process for any type of digital entity (for profit, non-profit).

Let's take an e-commerce company. It could be a pure-play (Amazon, Shopbop), or multi-channel (Macy's, Wal-Mart).

Typically, we measure success by analyzing where people come from, and how many of those place an order online. That is not bad. But we can make a very simple extension to our analytical/success view and look at returns as well.

ecommerce beter point of profitability

This makes us smarter in how we judge success. For example, Google could send you a ton of traffic via your pay-per-click campaigns. A bunch of them could also convert. But if the return rate for the orders is 10%, you may wipe out your entire profitability.

Now compare returns rate for Facebook and AOL and Email and … on and on.

You just have to stretch the time horizon you are looking at a bit more (look at the data 30 days after the order was fulfilled, typically the window for returns). And you have to stretch your data sources and not be limited by Adobe Analytics or whatever else you have.

If you want to be slightly more awesome (admit it, that sounds so tempting!), focus not on what happens 30 days after but rather what happens over a longer time horizon. Say three to six months after the original customer was acquired.

Your "funnel" would look like this …

ecommerce optimal point of profitability

Awesome, right? Now you are getting into the yummy customer lifetime value territory. You are getting in the delicious quality of customer territory.

From here you can go into online purchases and offline purchases (if you are omni-channel) and so much more.

And it all starts with a desire not to be limited by what your digital analytics solution can offer, and not to wait for God's perfect single source of all company data to come into existence five years from now, fifteen million dollars over budget.

Identify the Real Business Profitability Point: B2B.

What if you don't sell anything online? What if you don't sell anything to customers? What if almost all of influencing and conversions happen offline via a complicated process of meetings, dinners, RFPs and complex negotiations with multiple organizations?

You can still use the same mental model to identify the real point of business profitability and measure the success of your digital activity.

Let's say you are a company that belongs to one of my absolute favorite B2B entities, Danaher Corporation.

For each company in the Danaher portfolio, we could use the process outlined above to identify the real point of business profitability and identify the success of the company's investment in Google or Yahoo! or other digital channels …

b2b danaher real point of profitability

The specific description of each step will be a little different for each Danaher portfolio company. But going through this process will ensure that the next time Mr. Larry Culp asks a company what is digital doing for their business, the question will be infinitely easier to answer.

This is not easy work, especially in B2B companies. The muscle you need to pull this off has not been exercised for a while, if ever. But we simply don't have a choice. If we don't do this, digital will remain an afterthought, companies will not take full advantage of all the incredible possibilities the digital revolution offers, and they might even suffer in the medium to long term.

But when we do it, the aforementioned awesomeness follows.

So if you are a B2C, B2B, A2Z, company, if you sell everything digitally or non-digitally, if you sell underwear or tires or services or software or just people, obsess about identifying the real point of business profitability. Quantify how your digital efforts are delivering against that point.

Go, knock 'em dead!

Ok, as always, it is your turn now.

How far does your company go in tying effectiveness of online advertising to business profitability? What is your biggest challenge in trying to go beyond the limits of data in your web analytics platforms? Do you have success stories to share about following this process and winning? Speaking of the process, what's missing from the above picture? What can I do to improve it?

I would love to have your ideas, war stories, guidance, and suggestions for improvements.

Thank you.

Excellent Analytics Tip #24: Obsess About Real Business Profitability is a post from: Occam's Razor by Avinash Kaushik

May 20th 2013 Search Engine Marketing