Excellent Analytics Tip #26: Every Critical Metric Should Have A BFF!

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yellowThere is unlimited amount of data thrown off our digital existences. (Or to use sexy term du jour , we have big data!)

Our leaders (companies, agencies, teams) have to deal with an incredibly complex landscape, and they don't have enough time.

The very natural outcomes is this ask of us: "Can you make it simple? What's the one thing I should care about?"

And we oblige: "Conversion Rate, that's it." Or "don't worry about anything except Facebook Likes." Or, "I read this blog, Bounce Rate is the only one!" Or, "Profitability, it is so sexy, just focus on Customer Lifetime Value, no, sorry, I mean Profitability."

To be fair, it is not just our leaders. Because the combination of complexity, limited time and available time, everywhere in the organization people want the one thing to watch for.

Honestly, who can blame them.

But the problem is that single golden metrics hide valuable insights and, more often than not, drive bad behavior. Especially in medium and large size organization because responsibility gets fragmented pretty quickly. (In small organizations there is a lot more end-to-end ownership amongst the few employees, and if something is going awry things hit the fan pretty fast. This is a great behavior correcting mechanism.)

So, how do we fix this problem in a responsible manner?

Here's my proposal: If you are pushed to have a single golden metric, give it a partner. For each metric deemed to be critically important, identify an immediately adjacent contextual / OMG we are on the right track metric that will give more context while incentivizing the right behavior.

The key is the immediately adjacent part. The BFF metric you find should not be one that is very far away. It should be immediately adjacent.

The reason is that it is easy for every discussion to come down to: "Well, all we care about is Profit. Why not just measure Profit?" That is right, we will measure it. But as we strive to improve the many things that result in a massive digital success, we need to look at multiple facets of our existence and we need to look at a cluster of critical few metrics. For many of them, Profit is not the metric that will give valuable context.

You'll see this in action in this post.

Let's look through ten specific strategic and tactical examples that will help internalize the value of the approach I'm recommending. The examples cover elements we optimize for in our acquisition (what are we doing to attract traffic), behavior (what happens once they land on our website) and outcomes (did we end up making money, were the customers satisfied) strategies.

1. Click-through Rate <-> Bounce Rate.

There are many good acquisition metrics including impressions, clicks, delivery rate, share of voice, and on and on. One of my favorites is Click-through Rate (CTR).

I like it because CTR it immediately discourages spray and pray strategies so prevalent in our industry (particularly in display advertising). It says, you must also get clicks at a certain rate. That incentivizes a focus on the targeting strategy, the content in the ad, recency and frequency capping, and other such things. Better, more relevant ads will get more clicks.

So, great metric. Dare I say, a key performance indicator.

The problem is that it does not provide any incentive to the marketing team to ensure the rest of the experience for the user is great. How do we get them to care and not just dump people on your site (mobile or desktop)?

Simple. Give CTR a BFF. Find it the immediately adjacent contextual metric. I suggest Bounce Rate.

click thru rate bounce rate 2

So the marketer is now incentivized to get lots of the right people to the site (better more relevant ads!) and get them to the right landing page that deliver on the promise made in the ad.

If users are sent to the right page, and they don't bounce, the Marketer should get her bonus.

See the magic? The BFF fixes a gap in the incentive/org structure.

Let's try another one.

2. Visits <-> Visitors.

(Or Sessions – Users)

You definitely want a lot of Visits. It delivers happiness!

But an obsession purely with Visits drives very short term thinking. You can get lots of terrible Visits on your site. Get a bit number. Up and to the right. But is the business really doing well? Are we adding value with our efforts?

That is unclear with Visits.

So. What's the immediately adjacent contextual metric? Visitors.

How many people did we manage to get to our site? Now things get interesting.

Consider this scenario: 50,000 Visits, 50,000 Visitors. And 50,000 Visits, 10,000 Visitors.

The people who see the data will ask very different questions.

For the first set perhaps they will ask… How come each person only visited once? Is that what we are solving for? How will our business survive?

For the second set perhaps they will ask… Wow, that is cool, each person visited five times on average. I wonder what the distribution looks like? Are there some outliers? What did the people who come back most consume?

Think of this scenario: 50,000, 60,000, 70,000 Visits.

How intriguing would be with the immediately adjacent contextual metric… 50,000 Visits and 50,000 Visitors, 60,000 Visits and 50,000 Visitors, 70,000 Visits and 50,000 Visitors.

Cool right?

visits visitors

The numbers could go either way, but having them together allows the recipient to just see the right amount of complexity. That is great.

Let's consider a more controversial, and behavioral, metric.

3. Time on Site <-> Page Views per Visit.

Time on Site is not a great metric in almost all circumstances. Time on the last page of a visit is not recorded (that also means time for bounced visits is not recorded).

But I still see it used, so let's get off that topic. (But think carefully before you use Time on Page or Time on Site .)

Say you communicate that the Average Time on Site is 60 seconds, 150 seconds, 98 seconds in the last three weeks (/months/days/years).

How much context is there to be able to separate the good from the bad? Not a whole lot.

What's the immediate adjacent contextual metric we can use? Why not use Page Views per Visit? Another indicator of activity during the Visit!

Now you might see 60 secs and 5 PVV, 150 secs and 20 PVV, 98 secs and 5 PVV.

OMG! What happened?

Try different combinations above and you'll see how these two BFFs works very nicely together.

From an incentive perspective, this is also pretty cool. Is a lot of time spent on the site good? Is very little time good? It is a difficult question to answer, but having the number of pages seen during the visit gives us immediate enough context to understand what is going on and where your initial focus should be.

That's it. That's all we are solving for.

[Bonus: While these are not as apparently adjacent, if you use Time on Page as you metric, try Page Value as its BFF. They are particularly good together!]

Let's switch to some outcomes metrics.

4. Conversion Rate <-> Average Order Value.

Our returning champion, Conversion Rate! Everyone loves Conversion Rate!!!

And they should. Conversion Rate is money, sometimes directly as revenue and other times indirectly via Leads collected.

But a pure obsession with Conversion Rate can incentivize sub-optimal behavior (not on purpose, but people react to incentives).

For example, a Marketer can focus on getting lots of simple, lower value, conversions because that will boost the rate up. Or they might prioritize fixes in the site design or experience that get people to a particular cluster decisions that will make Conversion Rate looks better but not solve for the longer term for the business.

conversion rate average order value

One simple way to solve this is to use of my favorite immediately adjacent contextual metric, Average Order Value.

2% Conversion Rate, AOV = $26. 2.5% Conversion Rate, AOV = $14. Ouch.

2% Conversion Rate, AOV = $26. 2.5% Conversion Rate, AOV = $40. Goodness, bonuses all around!

Simple fix, right?

The purists amongst you might notice that I'm really using Revenue as the BFF. You are right.

5. Conversion Rate <-> Task Completion Rate.

Two lessons.

The immediately adjacent contextual metric you choose will really depend not just on the type of business you have, but also the people you have, the size of your company, the incentives currently in place, and a number of such factors. So this blog post should simply serve as inspiration. Take the spirit, apply it to your unique circumstances.

Your immediately adjacent contextual metric can be a qualitative metric. At least some of the times, it likely should be!

Where I've implemented a simple where you able to complete your task qualitative data collection mechanism, I always pair Conversion Rate with Task Completion Rate.

Two simple reasons.

Conversion Rate solves for the company and Task Completion Rate solves for the customer. Such a delightfully nice approach to take.

Conversion Rate only tells you how a very small fraction of your users, who came to buy, did. Task Completion Rate shows you how 100% of your audience did, were they all successful regardless of why they came to the site.

When you see 2% Conversion Rate and 14% Task Completion Rate you will cry. Everyone in the company will cry. And they they will ask how come only 14% of the users completed their task! That will lead to a broader obsession by the digital team, almost always leading to big wins.

6. Revenue <-> Profitability

I have to admit this is a hard one.

None of the digital analytics tools make it easy to measure true profitability. And if you can pass that barrier (with, say, dimension widening using universal analytics), it is very hard to find this data inside the company (Finance department?), at a level of aggregation or granularity you need, and send it into your digital analytics tools.

The whole thing is so painful. But it is incredibly rewarding and if you want your digital analytics practice to reach the analytics.ninja state you need to do it. (Ask an authorized consultant to help you, you will get there faster: www.bit.ly/gaac).

Revenue is the ultimate goal. Lots and lots of Revenue!

But of course it is entirely possible for you to make lots of Revenue and go bankrupt. Simply sell products that are loss leaders or don't cross high enough above the hurdle of the Cost of Goods Sold.

The immediately adjacent contextual metric for us is Profitability.

Now when you report at a business/site level you can show that $54 mil in Revenue resulted in $40k in Profit. Or, at a campaign level you can show that while Twitter brings $5 mil in Revenue, that only results in $5k in Profit and while the Email Revenue is $1 mil the Profit from those campaigns is $700k because how how remarkably your campaigns are targeted.

As long as there is even $1 in Profit you should spend all the money on Twitter, but when it comes to making strategic decisions for the company, you might make different ones now that you know the profitability of email, and other acquisition efforts.

Think of how much fun it will be have this pair for the products you sell, the geographic locations of your customers, and so much more.

Revenue, meet your new BFF Profit!

[Bonus: Another sign you are an analysis.ninja is that you not only measure Profitability - session-level short-term metric - but pair it up with the immediately adjacent contextual metric of Customer Lifetime Value - person-level long-term metric. Shoot for the above first, then, if you are successful, get to this one because it is, obviously, much harder even if it is disproportionately more impactful.]

Let's step outside our owned platforms and on to rented platforms .

7. Video Views <-> Subscribers

Raise your hand if you've heard this: "How can we make our video viral?" Too often, right? And you know the moment those words are uttered you are dealing with a video/effort that is most definitely never going to become "viral."

Sad, but true.

And yet, the number of Video Views is a metric often elevated as the thing to solve for, the single golden metric for video powered digital initiatives. You won't be able to get away from reporting views, so why not find a partner for it?

The immediately adjacent contextual metric that works marvelously well is the number of new Subscribers.

youtube rsa subscribers

You can solve for the short-term with Views, but if you are not converting them into Subscribers you are not really building an owned audience that you can engage with over time. If your last one million Views video got you only 25 new Subscribers, was it really a success? Even if you got a temporary bump in publicity?

[Bonus: While Subscribers is my ultimate success metric for YouTube - I crave large owned audiences so that I can stop renting them from TV and/or Radio and/or Google and/or AOL - the other two that can also share key context are % Completes and Amplification Rate. Depending on your local circumstances, you could possibly consider those as well. Though if you want to make me happy, you'll choose Subscribers!]

8. Likes – ?

People who don't know anything about Social Media use Facebook Likes to measure success.

There are so many of them, including your boss! Let me give you a virtual hug. There, there, it gets better.

First, be sure to mention that Likes simply represent people walking by us on the street who smiled at us. They meant nothing more. We need to make sure that we are creating content that is incredible and of value. That is what causes people who gave us a passing Like to come back again, engage with us, give us their precious attention.

Then we have to think about how do we give our dear boss, still obsessed with Likes, the immediately adjacent contextual that will help her/him make smarter decisions.

I recommend two different ones.

Likes are most commonly used at a page-level. For example, my Facebook brand page where I post daily analysis on an interesting topic has 19,789 Likes. The best immediately adjacent contextual metric for the page-level Likes is Talking About This. At the moment that number is 1,203. It is a decent tentative way to understand the engagement on Facebook.

The 1,203 is great context to have for the 19,789 for your boss.

[Bonus: For later reading, when you are attempting to be an analysis.ninja, see this post: Excellent Analytics Tip #25: Decrapify Search, Social Compound Metrics]

Likes are also present at a post-level. For example, my Facebook post on how to stand out from the crowd during an interview has 62 Likes. That is insufficient to indicate success because I not only want you to Like it, I also want you to amplify it to others so that I wonderful content (!) can reach others I can't reach myself. The best metric for that is Amplification Rate.

The above post only has one Share (the key ingredient in Amplification Rate). That is super-lame (and for such a good post!).

While another post, Global Views on Morality: Homosexuality, has 72 Likes and 40 Shares. Much, much stronger Amplification.

When your boss looks at the two posts he/she will now be able to recognize that one was more successful in terms of what's important (reaching new audiences) than the other. That's exactly why you want your metrics to have BFFs!

9. Mobile: Installs – 30-day Active.

We looked at YouTube, we looked at social, and so mobile can't be too far behind! Let's look at a quick one for mobile apps.

The most important metric our leadership cares about when it comes to apps? Number of Installs.

And it is important.

But if 80 to 90 percent of all downloaded apps are used only once, should we have an immediate adjacent contextual metric that will be more insightful?

I recommend also reporting 30-day active, the number of unique users who have been active during a 30-day period. You have some flexibility in how exactly you define it, but as long as you stay consistent it does not matter.

Now your boss is focused both on getting more new customers, and on keeping the ones you already have. Balance. It is what makes the world go round!

10. [By channel] Conversions- Assisted Conversions.

Let's close with a pairing for all of you analysis.ninjas.

It is common to segment Conversions, our beloved key metric, by the source of traffic. Earned, owned, or paid. Or, Google, Email, AOL etc. It helps your boss understand how best to optimize your acquisition strategy.

The challenge is every single analytics tool reports single-session conversions only (also known as last-click attribution). This is absolutely silly and leads to awful decisions.

The immediate adjacent contextual metric you need is Assisted Conversions – the number of times that same acquisition channel (earned, owned, or paid) was present in the customer journey that lead to a conversion but that channel was not the last-click.

Essentially, how often did that channel help with a future conversion?

assisted conversions

Now you have excellent context for making smarter decisions about the full-value of each acquisition channel in your portfolio.

For example, Organic Search delivered 119k last-click Conversions and also assisted with another 73k Conversions that were delivered via other channels when looking at a last-click view.

[Bonus: For more awesome goodness on this yummy topic check out this post: Multi-Channel Attribution Modeling: The Good, Bad and Ugly Models.]

Ten short stories to help you internalize the incredible value of having an immediately adjacent contextual BFF for every critical metric you report to your management team.

Oh, and you can easily put all this together in a very simple dashboard…

digital analytics dashboard 1

Throw in your pretty pie charts (no!) and your stacked bar graphs and some lovely trend lines and you have yourself all the ingredients for creating an organization where data delivers the kind of insights that deliver big action!

Please consider the examples in this post, and the dashboard above, as a way of thinking I would love for you to embrace. The specific metrics you end up choosing will depend on many important factors. If you create your Digital Marketing and Measurement Model, you will know exactly what will go in the above dashboard for you and then all you have to do for each metric is find the BFF metric.

Friends don't let their KPIs not have BFFs. : )

As always, it's your turn now.

Do your current critical few metrics have an immediate adjacent contextual metric? Do you agree with the metric recommend in this post as the BFF metric? Would you have chosen something different for Time on Site or Visits or Likes? Are there metrics you are struggling with when it comes to identifying the BFF metric? Does your company dashboard provide all the necessary context to aid smart decision making?

Please share your insightful feedback, tips, omg don't do thats, and stories.

Thank you.

Excellent Analytics Tip #26: Every Critical Metric Should Have A BFF! is a post from: Occam's Razor by Avinash Kaushik

Yeah, But… [My Cousin / Mom / Webmaster / Company X] Does SEO a Lot Cheaper

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by Stoney deGeyter

Everyone likes to bargain shop. We don’t like paying “full price” for anything. When we do, and find out later we could have gotten it cheaper somewhere else, it really burns us.

I’m no different. But one of the things I’ve realized over the years is that although I can get the “same thing” for less, rarely is it the “same thing.” I’m usually getting a whole lot less in value/product/return in exchange for a little less in cost/price.

apple to orange comparison.jpg

Your cousin might tell you he can manage your business, but is he capable? Your best friend might be able to unclog a sink, but can he remodel your bathroom? Your webmaster might offer “SEO services” but do they really have the education and skills
to bring you success?

Every once in a while we come across a Yeah, Butter who tells us that we are too expensive. Usually they are looking at a number of proposals all which supposedly to do the same thing we do, albeit for less money.

But do we all really do the same thing? That’s the million dollar question.

Comparing on Price Alone Only Work for DVDs

If you want to shop on price alone, go buy a DVD. I mean, you’re getting the same thing regardless of where you buy it. Unless you’re buying the special edition, director’s cut, extended version or the Blu-ray with DVD and digital combo. Oh crap, I think I just blew my own point!

Get what I’m saying? Here’s another analogy: A Ford Mustang, Toyota Yaris and Jeep Cherokee are all vehicles that we use for the same standard reasons (to get us to the grocery store, the movies, church, school, etc.) but no one would really try to compare them to each other. Yes, price is always a factor when shopping for a car, but more important than the price itself is what you get for the price.

This is where many who are shopping for web marketing services go wrong. They shop based on price alone, not on benefits, value, service, deliverables, or
the quality and history of the company providing the service.

You can get “SEO” for as little as a couple hundred dollars per month, but
I’ll bet my mother-in-law that it’s not the same SEO strategy that runs a couple thousand a month. And yes, I do love my mother-in-law; I’m that confident I won’t lose.

What’s the difference?

Obviously, the cost is a big difference. But you also have to consider the
performance level, which is probably similar to the performance differences between a Yaris and a Mustang. Or the difference between either of those and a Jeep’s ability to climb the side of a mountain!

For a couple hundred per month you might get your meta tags edited and some
search engine submissions. Not the makings of a truly successful web marketing campaign.

But what about the difference of a $2K and $5K per month campaign? Hard to say, but you have to look at more than just the services being offered. What is the value of those services? There is a big difference between someone getting you 50 links and 500 links. And it might not be what you think! The good companies are charging more for 50 links than the others charge for 500. That’s because it’s easy to get 500 links. It’s not so easy to get 50 quality links.

Same goes for other services. Anyone can edit title and meta tags, but can they write tags that get rankings and clicks from the search engine results

Anyone can add keywords into your page content, but do they know which keywords are the best to use, how to group keywords for effective on-page targeting and integrate them in a way that adds, not detracts, from the sales message?

Anyone can look at analytics, but can they decipher the data to produce actionable recommendations for improving your site’s performance?

I know, I’m wearing out the italics button as I write this post, but I want to make sure you’re getting it. Quality SEO is important.

Good SEO Doesn’t Grow on Trees

Sometimes you can’t tell the difference between what two SEO companies are
offering by looking at a proposal alone. But you usually will want to know more about the company you’re hiring. The price might be a good indicator of value–those doing SEO on the cheap are usually doing cheap SEO–but it certainly doesn’t tell the whole picture.  You have to look deeper at the specific offerings and understand what value each brings to the success of the campaign. Only then can you begin to
determine which service is going to bring you greater ROI.

We all know that if you want a cheaper car, buy a Yaris. If you want a rugged off-road vehicle, a Jeep would probably be a better choice. If you want performance on the highway choose the Mustang. If you want gas savings, buy a hybrid, or better yet, an all-electric vehicle. However most don’t know which SEO company is the Yaris, Mustang, Jeep, or hybrid just by looking at the price tag on the proposal.

That means you might have to check under the hood a bit. If you don’t, you can always “yeah, but” your way into a Yaris, but you’ll be severely disappointed when you
get it out on the road (or off the road) and find that it doesn’t deliver the performance you expected.

SEO isn’t cheap, and it doesn’t grow on trees. You can’t just pick out a winning online marketing campaign at the discount store. The success of your business is at stake. Don’t yeah, but yourself into cheap SEO–look at the ROI and think smart, not cheap.

Be sure and visit our small business news site.

April 25th 2014 Search Engine Marketing

How do you break into SEO?

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by Mike Moran

If you are in this business long enough, someone will come up and ask the question. To some of them, it is the most important question in their lives: “How do I break into SEO?” I honestly get this question several times a month. And each person that asks me is ready for my answer. Some seem ready to take notes. They expect that I am going to rattle off some kind of canned answer that will unlock the secret to their future career. But I don’t, because it isn’t that easy.

Some people readily accept that it isn’t that easy. If it were easy, they wouldn’t need to ask.

In fact many folks ask a longer question. “How do I break into SEO, because I don’t have…”

  • …a technical background. This is one of the most common worries. People believe that they need to know how to program or at least code HTML or else they are doomed.
  • …a marketing background. Yeah, people who actually have a technical background worry that they need something else.

The truth is that almost no one breaks into SEO with both a marketing and a technical background. So, no matter who you are, you probably don’t have all the skills required to optimize for organic search.

But as SEO grows, you don’t really need all those skills anymore. There are plenty of jobs out there for folks who are specialists. They don’t know everything about SEO–they just know enough SEO, that when coupled with other skills make them employable.

That’s why when people ask me the magic question, I always ask them a question back. What do you already know?

People are always struck by this question because they don’t expect the magic formula to have anything to do with them. But it does:

  • If you have a background in direct marketing, you can learn search analytics.
  • If you came from PR, you can come up with social media ideas or write blog posts.
  • If you understand copy writing, you can do content optimization or paid search copy writing.
  • If you are a programmer, you can fix infrastructure problems.

You probably get the idea.

SEO is no longer some kind of monolithic profession. where you must know every part of it to get a job. If you have any skills that border on organic search marketing, adding SEO skills to that mix makes you far more employable.  And that is always the right way to break into SEO, by building on what you already know. 

Originally posted on Biznology.

Be sure and visit our small business news site.

6 Steps To Boost The Profitability Of Your SEM Acquisition Program

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Imagine that your job is to stand outside a barber shop and bring in new customers. If a businessman with shaggy hair comes walking by, you give him a big wave and a hello. If a bald man walks by, not so much. This analogy is used by Google AdWords to describe its Enhanced cost-per-click […]



Please visit Search Engine Land for the full article.

Dear Developer: Building a Website Isn’t Good Enough, It Has To Be Marketable, Too

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by Stoney deGeyter

Dear Web Developer,

Let me start off by saying that I am simply amazed at your skills and abilities. The fact that you can take what appears to be random strings of letters, numbers and other strange keyboard characters and turn them into a great looking website is, quite simply, an amazing feat. I can’t do what you do, and I’m glad there are people like you who can.

And that’s why I’m writing this letter to you. I need you. As a web marketer, I can’t do my job without you. Without you there would be no website to market, and I wouldn’t be able to market my client’s site effectively without incorporating your skills and expertise. So, thank you for being there for me.

I do need to tell you something, and I hope you understand where I’m coming from. I just want us work together to deliver the best results for our clients. The truth is, I’m frustrated.

Sometimes it seems you know how to do your job, but you don’t understand why you’re doing it. Sure, someone paid you some money, told you what they want, and you figured out all the cool things the site is going to do. And you might have even talked to the client to get a better understanding of their needs so you can design, develop and program the site to do everything they want. But again, do you know why they want that?

I do. As a web marketer, it’s my job to understand and help the client fulfill the “why” part of the website. We don’t just want the client to have a solution, we want the solution to help them achieve their goals. And believe me, the goals are not always what the client says they are.

In truth, the client wants to succeed. They want their website to bring in business. Some of the websites you create are designed to do a job, but nobody thought about how that job is best achieved. The site functions “properly” but not necessarily in the best way possible.

See, a great-looking car can be great for transportation, but it does no good if you don’t get a driver behind the wheel to use the car for its intended purpose. A car can look sharp on the outside, but what’s under the hood and inside the cabin matters just as much. Driver experience is about much more than getting from point A to point B. (Heck, you could do that on a segway.) Design and functionality must come together to make the car marketable.

This is what I would like from the websites you create. Don’t just make websites that are pretty and functional; the marketability of the website must be a priority as well.

That means thinking about things that, perhaps, you hadn’t given much thought to in the past.

If you would permit me an indulgence, may I make a few suggestions?

  • Start with keyword research. Keyword research isn’t your job–you’re a designer and programmer. No problem. I’m a keyword researcher, so get me (or the SEO of the client’s choice) involved in this. I cannot stress how important this is to the process of developing a site correctly. Keywords provide the foundation for understanding what searchers are looking for on Google and Bing. It also then tells us how the site should be built to meet the searcher’s needs and expectations.
  • Organize the navigational architecture. You’re not just developing a home page and an internal page. You’re developing an entire marketing vehicle. This means you have to understand how the entire site will come together. The keyword research you did is helpful to ensuring you have a navigation that meets searchers needs and helps them find the information they need quickly. Again, this isn’t something you have to do. I’m happy to help, just ask.
  • Know what is needed on each page. There is more to the site than content. You really need to understand what goes on every page, or particular pages, before you begin your incredible design work. Sit down with both the client and the SEO to figure out what is required. Navigation? Check. Social symbols? Check. Calls to action? Check. I could go on, but there are hundreds of things that may or may not be necessary in different areas of the site. Jot them all down so you can make sure these make it into your design.
  • Develop wire frames. Before you jump into the design, take a step back and wire frame out all the elements. This is critical because I’m sure you’ll find that different pages or sections of the site will have different needs. No need to start doing design work before we know everyone is comfortable with the placement of all the elements. Just draw these out in a very simple format. Labeled boxes that show where each element will be placed is simple enough. But include as many boxes as is needed to be sure each page section is included. Also be sure to develop as many wire frames as needed for different pages or sections of the site, such as home page, standard internal pages, about us page, contact us page, blog home, blog posts, etc. Now, with the client’s approval of the wire frames you’re ready to start designing!
  • Produce a gray scale comp. Strange, right? I’m sure you think of this as something that’s only needed for brand or logo design, but they can be helpful here, too. I’ve seen clients throw out an entire design because they thought they didn’t like it. It turned out, they just didn’t like how the colors worked; the design was fine with a little tweaking. Gray scale comps, based on the previously approved wire frame, allow the client to see if the wire frame layout really works, without the interference that color can sometimes cause. Again, do this for every different type of page to ensure there will be no re-design surprises later.
  • Produce a color comp. With an approved gray scale design, you can now colorize the comp. By this time, if there are any objections, you’ll know that it’s just a color issue, not a layout or design issues. Simply changing the colors around can make a big difference and you can sail through approval, moving on to the coding and development stage. Again, do this for each of the different types of pages that you created wire frames for. Side note: Be sure your comps show how headings (h1-3 at a minimum) will look on the page, as well as visited and non-visited textual hyperlinks, navigational mouse-overs and active pages.

Those last two items don’t really have anything to do with SEO, but they are important. I can help you with the wire frame to ensure that everything we’re going to need to market the site is in a good place. I don’t claim to be a designer by any means, but remember, our goals are the same: to produce a website that lets the client achieve their business goals.

I have a few thoughts for you as well as you move the site from the design stage to the development phase. Unless the site is designed to be marketable, when the client comes to us later, we are very likely going to have to tell them they will need to spend even more money fixing the site they just just paid you to build. In my experience, that doesn’t go over very well, but it’s impossible for us to do our job otherwise.

But don’t worry, I’ll give you a few pointers so that doesn’t happen. You’ll come out looking like a hero, not just when you deliver the site, but a year later when the SEO campaign cost half as much and was twice as effective!

  • Pay attention to URLs. You may not know this, and by looking at some of the sites you created you don’t, but URLs are very important to SEO and social marketing. URLs with lots of parameters can create a whole host of problems, giving the SEO a whole lot more work to ensure only the right URLs get indexed and the wrong one’s don’t. That’s OK, it’s just part of the job, but a lot of this frustration for both the SEO and the client can be eliminated simply by making sure the site is developed using search friendly URLs. Just ask, I’ll let you know what they should look like. But please, don’t leave it to me. Once a site goes live, changing URLs is a mess. And since I’m not a programmer, I might not be able to do it easily, which means it will cost the client more money to have the old URLs redirected properly. It’s better to just do it right from the beginning.
  • Use proper Hx hierarchy. Forget everything they taught you in design school about how to code Hx tags into the site. Hx tags are not for segmenting sections of the site, they are for segmenting sections of the content! The logo should not be an h1, navigational elements should not be an h2 and product links should not be an h3. Please get that out of your head. If you absolutely need to use heading tags for the design architecture, then stick to h4-6. Leave h1-3 for content. Oh, and be sure to program the uppermost page heading as the h1!
  • Give us editing capabilities. SEO is about making the site more search and user friendly. This means we need to be able to edit things to incorporate keywords and calls to actions. Be sure you program this capability into the site. Don’t force product links to be the product name without the ability to customize. And page headings titles, breadcrumbs, ALT tags and navigation links should not pull from the same source. Each of these needs to be independently customizable. If it’s content, it needs to be editable from the rest. Make sure that’s built in.
  • Know what links should and should not be spidered by the search engines. Most links should be spidered by the search engines, but some absolutely should not. It’s a bit complicated to know the difference, but let’s say that navigation links that go to content and product pages should all be spiderable. Links to your shopping cart and social sites should be unspiderable. The search engines have no interest in adding products to or viewing the shopping cart, nor do they want to socialize my pages. Making these links unspiderable is a big help.

There are probably a few things I left out, but that’ll do for now. I’m not trying to tell you how to do your job. In fact, I want what is best for the client.

I’m no more a designer than you are an SEO. We know a bit about each others’ jobs, but ultimately we each have our areas of expertise. Let’s take advantage of that. After all, we have the same client, and our job is to help them achieve their business goals. It’s time we worked on the same team to make sure the client gets everything that they need, not just visually and programmatically, but also with the site’s ability to be marketed properly as well.

Thanks for hearing me out. All of this might require some additional work on your part, but we both know it’s worth every penny to blow a client away with an exceptional website! Let’s work together to make that happen.

Sincerely,

Stoney

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Does Internet Marketing need a business case?

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by Mike Moran

Don’t give me that look. Depending on where you work, that might sound like a silly question. Everything needs a business case in some places. And I understand that. I used to work for IBM, which is one of those places in love with justifications for how you spend money before you drop a dime. And you can put together business cases for Internet marketing projects, but there is another way, too. In fact, I actually started the IBM search marketing program without any business case at all. You might be able to follow my lead where you work, not just with search marketing, but with any kind of digital marketing.

How did I do it? It wasn’t easy, but there are a few things you can do to make it happen for you:

  • Don’t spend any money. At least at first. I know that rules out a lot of marketing ideas, such as paid search, but it still leaves you with plenty of marketing tactics to try, including organic search, social media, and more. Start with one of those.
  • Neutralize your boss. You might be lucky, as I was, and have a boss that you could just tell what you are planning and he would go along. (My boss, John Rosato at IBM, actually thought it was a great idea.) But not everyone is so lucky. Even if you spend no money, you’ll have to spend some time, so you might need to hide this work from your boss, or do it on off-hours. Somehow, some way, you need to be able to do enough of the work required so that you can show some results. In my case, I needed to make a few changes to some critical web pages to improve the search results.
  • Get help. You are unlikely to be able to do everything on your own, so you need co-conspirators. Find some allies who are willing to be equally stealthy as you are and enlist them in the cause. Some people are not the right ones to approach, but you probably know who they are. Find the others that are as excited about this idea as you are and get hem on board. In my case, I needed to find some people who controlled some important web pages at IBM and get them to make some changes so we could see the resulting search ranking improvements.
  • Keep score. Trying out your idea is great, but how will you know if it worked? Choose some tangible measure of success (higher search rankings, more traffic to the site from your social media content, higher conversions from your tactic–pick something) so that you can show the before and after picture. It is OK if it is not earth-shattering. After all, you did this with no money and no assigned resources, so let the powers-that-be think about how big this would be if they actually worked on it for real.

This might seem sneaky to you. It is. But it has a few redeeming qualities. First, it allows you to try a lot of ideas, because some of them won’t work. Second, it helps you make a good idea work that needs a few tries. If no one knows that you are doing it, then if it fails twice before you figure it out, you have the time to make it work. Third, it can change your relationship with your boss.

Why do you think my boss at IBM, John Rosato, allowed me to try these things? One reason is that he is a sharp guy that gives his people freedom to try things. But I think he gave me a bit more freedom than some other people because he had seen this approach work for us before. When your boss sees that you know how to make big improvements by experimenting with no money and little risk, you’ll get treated differently, too.

So, you might not have the kind of boss that I did, but if you succeed at this a couple of times, you might change the way your boss thinks about you. And then you might be able to try a lot of different kinds of Internet marketing with no business case at all. At least it’s worth a try, no?

Originally posted on Biznology Blog.

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7 Data Presentation Tips: Think, Focus, Simplify, Calibrate, Visualize++

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elegantThere are three elements to our "big data" efforts, or unhyped normal data efforts: Data Collection, Data Reporting, and Data Analysis.

(More on that here: DC-DR-DA: A Simple Framework For Smarter Decisions .)

We are all aware that the best companies in the world have an optimal DC-DR-DA allocation when it comes to time/money/people: 15%-20%-65%.

All well and good.

But there is one crucial part we often don't invest in sufficiently. The last mile. Data presentation! The actual output that is almost singularly responsible for driving the change we want in our organizations. The thing that is the difference between an organization that data pukes and the one that influences actions based on understandable insights.

I believe we should present our data as effectively as possible in order to first build our credibility, second to set ourselves apart from everyone else who can present complicated graphs/charts/tables, and third allow our leadership teams to understand the singular point we are trying to make so that the discussion moves off data very quickly and on to what to with the insights.

A vast majority of occasions where data is presented (reports, executive dashboards, conference presentations, or just plain here's a automated emailed thingy from Google Analytics ) end up being abject failures because most of the discussion is still about the data. And if you are sitting in a Nth level tactical meeting, that is ok. But if the occasion is a strategic discussion, any occasion about taking action on data, then you need to get off data as fast as you can.

It is hard to do. After all you spent so much time on collection, reporting and analysis. You want to show them all data stuff and how much you worked and how cool your technique was. But trust me, it is better for your career (and, this is a lot less important, but much better for your company/audience :) ) to get really, really good at data presentation.

This post shares eight before and after examples that illustrate seven data presentation tips that I hope will inspire you to look at your report/dashboard/PowerPoint slide in a new light. We will look at some simple errors, and some much more subtle ones that end up limiting our ability to communicate effectively with data.

Here's a quick summary:

#1. Don't be sloppy. Your data presentation is your brand.

#2. Bring insane focus, and simplify.

#3. Calibrate data altitude optimally.

#4. Eliminate distractions, make data the hero!

#5. Lines, bars, pies… stress… choose the best-fit.

#6. Consolidate data, be as honest as you can be.

#7. Ditch the text, visualize the story.

We are going to have a lot of fun, and learn some not-so-obvious lessons.

It's not the ink, it's the think.

An important point first.

This post is not about tufte'ing your work. It is not a post about expressing your inner Excel geek with the most advanced remastered sparklines or conditional scatter plots. Advanced, sophisticated visualizations are important. But I find that so many times people focus on the ink and not the think. Hence all the insights-free data visualizations floating around the web that are totally value-deficient, even as they are pretty.

In this post I simply want you to focus on the think and not the ink. What was the error in thinking? How can you ensure you never make that error? Then, go express your inner visualization beast. :)

[My inspiration for a focus on the think: Bob Mankoff]

Lesson 1: Don't be sloppy. Your data presentation is your brand.

This graph is from an article by the consulting company McKinsey.

It actually shows very interesting data. The article is a bit dry, but valuable.

Yet, I could not get over how sloppy the graph was. For me, and perhaps for others, the sloppiness made the data appear to be an amateurish effort (surprising, given the source) and took away from the deservedly mighty McKinsey brand.

Can you see what the problems are?

email over social media 1

The first problem is that the title is weirdly placed. Then the y-axis legend is even more weirdly placed. The most important part seems to be to get the names of the company, gigantic, over two lines and distracting.

Finally, this is picky, but why is most of the x-axis yearly and then suddenly just until Q2, 2013? And if it is only two quarters of data, why is it taking up the same distance as represented by one year?

Surprisingly sloppy from McKinsey, right?

Watch out for these errors. People in the room (in a small room or a board room or a conference auditorium) will know a lot less about the data than you will, their first impression, and often the lasting impression, might be how clean your data presentation is.

Even without access to the raw data (let's say I'm a busy McKinsey blog post writer), you can make a couple of simple changes to the graph to make it cleaner and less sloppy…

email over social media fixed 1

Clean up the title, rephrase it.

Move the y-axis description to the right place.

Make the source attribution much smaller. If the data is good, people will seek it out. If the data is stinky, no one cares. Either way, why make it intrusive?

Scroll back up. Then down. Much cleaner, right? 30 seconds of work.

If I had the raw data, I would also fix the x-axis and representation of the partial 2013 data. That is still bothering me. But at least you can see what 30 seconds can do.

When it comes to your work, take the 30 seconds.

[PS: The data in the graph is cool, you can see my brief analysis on my LinkedIn Influencer Channel: Email Still Rocks! Social, Surprisingly, Stinks!]

Lesson 2: Bring insane focus, and simplify.

I'm sure you've either seen someone present a slide that looks like, or you've created a slide/executive dashboard like this one. Or, both.

: )

Before you scroll any further, what errors, subtle or obvious, do you see? Don't rush. Give it some thought.

cpc trending brand non brand 2

[Minor Rant: Never, ever, never obsess this much about CPCs. Yes, cost per click is metric. But if you had to obsess about something, obsess about the value delivered to the business. You will never obsess about the cost per trade of your E-Trade portfolio, right? It could go down from $10 per trade to $1, and you could have completely gone bankrupt as a result of your trades. So, don't obsess about CPC. Focus on Economic Value from your search advertising. Focus on Profit from your search advertising. Focus on the outcome. As long as you make a profit, does it matter if your CPC is $1 or $200? And would it matter if your CPC went from $200 to $1 if you were making no profit?]

The metric CPC aside, we do present data like this all the time.

The first challenge is that there is too much of it. We have actuals and we have the YOY change. Then we have it for the company and its category. Finally, we have it segmented into desktop and mobile and as if that was not joyous enough, further segmented into Brand and Non-Brand.

As if that was not enough, the data presentation itself is a bit uninspired.

We can quickly fix it though.

First pick one primary thing to focus on. When you design dashboards this is absolutely critical.

In this case, I believe, the most interesting thing is the YOY change. I bring it center stage, and make the actual CPC as small as I possibly can (in case someone wants it that desperately).

Next I create a simpler data presentation, God bless Excel, by creating two big clusters next to each other. Now it's just a matter of two similar columns that we can distinguish with the use of color.

Here's the result…

cpc trending brand non brand fixed

Again, something very quick you can do. (I'm sure like me you have a favorite custom font you use to make your presentations really yours.)

The orange and purple are easy on the eyes, and distinguish the two clusters nicely. The size of the font used makes the things that should stand out, stand out easily.

Notice because the company performance is all in one row, it is much easier to see that their CPC year-over-year change is less than the category (something harder to see in the original version).

Bring insane focus to your data presentation. If you can, focus on a singular metric for each module/slide/element. Then present the data as simply as you possibly can. And often, you don't need to go very far from the defaults in Excel – though you are welcome to use any software you want.

Lesson 3: Calibrate data altitude optimally.

Here's a more subtle error.

Ignore the ugly graph and the terribly formatted axis, time periods used, etc. All simple fixes.

Look at the text under the graph. Do you see the problem? Don't scroll any further. Look at it again, see the mistake made?

confused paid organic 1

It is not completely obvious, but the Analyst is expecting that in the very short time the leadership team has to look at this data, that they'll also be clever enough to do the math for each row, commit it to memory and then compare all four rows and figure out which video is performing better.

Terrible error in judgment. The altitude is all over the place!

You are the Analyst. You do the math. Then make the hard decisions and figure out how to present data as effectively as you possibly can.

In this case I had to decide what the key point was (this is the think part). I believe it was that using advertising to drive views of a video fueled organic views as well.

That gave me the anchor, paid views. Then it was simply a matter of figuring out the best way to present the data. I decided to use an index of 100. All that's left now is to do the math in Excel and paste it on to the dashboard…

confused paid organic fixed 2

The recipient can get to the insight really fast because there is less data (fewer words and clutter), it is well thought out, and we can move to asking hard questions about performance.

What the heck happened with Video B? And OMG what is up with Video D???

That is what you want, shift the discussion from the data to what happened and what to do now.

Bonus: As the smart Analyst that you are, at this point you'll realized Earned and Paid Views don't tell the full story. So you'll change the table to Total Views and % Earned. You would not have known that's what you needed if you'd stuck with your original textual version! The value of focus and think.

Lesson 4: Eliminate distractions, make data the hero!

Raise your hand if you've not created a slide like the one below for your presentation. Come on!

My hand is raised.

We have all done this.

And it is so silly.

We take the most interesting part, the data, and surround it with clutter that only makes it harder to understand what the point is. The data is the hero, what is the need to have the arrows and the box and the descriptions? Is there any need for the useless stock photos (and what is up with the magnifying glass to represent research, who does that?)? And why repeat "use online sources," is that not obvious in the awfully crafted title?

Look at the image for a moment. Don't scroll. Stop. Really. Don't scroll. How would you decrapify this slide?

Got an answer? Ok, now scroll.

research to purchase process 1

Share your decrapified version via comments below.

My process was to simplify the title to something more direct and easy to understand. Then use three different bars to represent each stage of the process, and to fill each up to represent the percentages. Finally, I'm slightly allergic to terms like awareness and consideration. They are too generic, they encompass too much. So I took the direct route, just wrote down what each bar actually represents.

research to purchase process fixed 1

You can use different colors, mix to suit your own taste. Red in my case is to make the online usage stand out on a very large screen.

I'd experimented with having a break in the gray x-axis (yes, I worry about those things!), it looked nicer. But visually it ended up representing a break, rather than the continuity that each stage represents. Hence the single line you see above.

If you spend sometime on the think , it is so much easier to decrapify the data presentation to focus on the most essential element and make data the hero (again, so that you can get off the data very quickly and have a discussion about what the business should do).

Lesson 5: Lines, bars, pies… stress… choose the best-fit.

If you are a student of the Market Motive web analytics master certification course, you'll note my love for segmented trends rather than snapshots in time when it comes to data presentation.

Trends are often better at delivering deeper insights. And because all data in aggregate is crap, segmented trends are even better!

But, as all smart analysts know, often is not always.

Here's a great example… The dashboard module shows how American's consume media, and how that behavior has changed over the last four years.

Please take a minute and reflect on the graph. Do you love it? Does it communicate the change optimally?

line graph us media consumption 1

You'll agree, the graph is nice and clean. It is easy to understand what is going on. Sure we can line up the numbers on the right correctly, but that is a minor point.

As a Digital Marketing Evangelist, you can imagine I love the data. : ) I was not sure that I love the line graph.

I felt it would take too long to understand just how much things had changed. People would spend too much time trying to understand the graph. And even then, at a deep gut level, not internalize it (even though to you perhaps it is utterly obvious).

My decision was to eliminate the trend. Except for TV, the trends adds almost no value (and even for TV just a little). This allowed me to switch the x-axis to each media channel, they were the heroes here. And finally, switch to a bar graph.

Here's the result….

bar graph us media consumption 1

I believe this version shows the change much more starkly and since you can look at one channel at a time, you can absorb the change much, much faster than with the line graph.

While with the line graph you could see people spent more time with digital than with TV in 2013. The big rise in digital consumption vs. 2010 is much more obvious now. And while TV is physically from Digital in the above picture, you can easily see that one is much higher than the other.

Remember, often is not always. Question how you've always done things. Even question your teacher who might love segmented trended graphs! : )

Understand who your audience is, think about the point you are trying to make with your analysis, and then use the best-fit data presentation method.

Lesson 6: Consolidate data, be as honest as you can be.

This example comes from a presentation. The data was spread over two slides. Notice how nicely it is presented.

The first slide showed the desktop and laptop performance for search traffic for puppies (real data below, just not that category!)…

searches for puppies desktop

It is easy to see how puppies are doing in context of the average number of searches for land animals and sea animals. Put another way, company performance compared to two benchmarks.

The second slide illustrated the mobile search performance for puppies, and compared it to the same categories…

searches for puppies mobile

Both sets of data presented simply. You cannot misunderstand it.

So, what is the problem. Look at the graph above carefully. Then scroll up a little more, look at the first one. Now scroll back down.

See the problem?

One obvious problem is, why spread the data on to two different slides? Most people are terrible at keeping track of things as they jump slides/pages.

The second problem is more subtle.

The graphs make it seem like there are two similar sized problems to deal with for us as PuppiesRUs Inc. But that is not really true. Look at the y-axis.

Perhaps, for a good reason, we want the company to believe that they are similar sized problems because our company sucks at mobile and we want to light a sense of urgency under our collective butts.

I believe as an Analyst we should be as honest as possible in these cases. (I'm NOT implying that there was a deliberate attempt to not be honest above.) We should show the data in as honest a way as possible, we should be as objective as possible.

I simply took the data in the two graphs and put it on to one graph, same bar graph, and fixed the title to make the presentation simpler (I hate long complicated titles).

In an attempt to pay an homage to the importance of mobile, changed the color to red…

searches for puppies fixed

To our leadership team, the recipient of our presentation, it is really clear how we are performing overall and in mobile.

It is also clear that desktop plus tablet, blue, is the most important area of focus. We have to keep the pedal to the metal when it comes to that. But that mobile is also an important area deserving some dedicated focus.

There is no chance that they will inadvertently think the size of both the opportunities is the same.

An effective presentation of data by 1. consolidating it and 2. having it play off the same y-axis.

Lesson 7: Ditch the text, visualize the story.

Often we hear that data is overwhelming or that graphs are evil or that tables suck or… well, I'm sure you've heard it all.

Our response to that is to try and "simplify the story" by eliminating all that and just writing the insights in text with a big summary number.

That strategy does work some times. More often than not you end up with something super-ugly and value-deficient like this…

search data puke 1

Imagine yourself to be sitting in the audience and trying to internalize everything that's going on here! I'm sure someone is going to walk you through it. But still. Do you think there is any chance you can grasp the multiple agendas at play above?

I seriously doubt it. Scroll back up. Look at it!

Even if you only have two minutes, all I had in this case, it is pretty easy to fix the above textual representation and make it much easier to understand what is going on.

First, get your custom font. Ok, kidding.

First, think of what the key point is and replace the long red-book ended title with it. In this case: Search Opportunity.

Then draw a bar in PowerPoint, eyeball the size (no, really, don't even go in Excel to create the graph, no one is going to notice!), and fill in the sub-components.

For data you can't find an obvious home for, use call-outs.

Two minutes later…

search simple data presentation 1

So much easier to see that story is about how many people search for our company topics and that weight management and monitors are the most interesting. In this case we have the data that can fill out rest of the bar, but we want the leadership team/audience to focus on just two and those are the ones you see above.

It is less obvious how to illustrate the mobile growth. Two more bars? Perhaps a heat-map showing high and low? Nah! Just add two call-outs and you are done!

When the data's end state is a PowerPoint/Keynote presentation, use the fade transition (all other transitions are evil) and bring one piece of data at a time up on the screen. It will look beautiful and the audience with stay with you as you narrate other insights you know that are not represented on the slide. [A style of presentation you should use every time you present anything.]

Here's another example of eliminating text, reducing complexity, focusing the the key point and visualizing data simply to get off the data quickly and discuss actions.

Pause. Look at the example below. What is done right or done erroneously? If you had to improve on the power of communication for this example, what would you do?

Pause. Really think about it. Got it? Now scroll.

media targeting efficiency

The first simple mistake you likely won't make as an analyst is to use two different things to represent the same number. For example, either stick to the dollars or use the percentage. This might not seem like a big deal in isolation, but every little bit like this takes a tiny bit of your credibility away and it causes the audience to have to shift their minds a little. Over a number of these types of mistakes in your dashboard or your presentation take away 0.25% here and 0.5% there and 1% somewhere else. Taken together, you lose 30%. Why dig that hole for yourself to have to climb out of?

The second simple mistake, obvious in hindsight I'm sure, is that there is simply too much text. Why not simplify the data presentation to make it boom (!) impactful right away?

I did like the map, but it was intrusive. So my first act was to take the map, fade it out (use a white transparency, 13%). It is there, but it is not in the way.

Then I did not like the numbers, they don't add any value. Just throw in two simple bars (standard shape in PowerPoint, no Excel necessary), and add a touch of color to show targeting efficiency of TV and Radio. Finally add the bridging text and use the brace (use the little yellow handle to drag the brace so it is aligned) to show how well or badly each media channel is doing.

Red is bad, blue is good….

media targeting efficiency fixed

Scroll back up. Then back down. Then up. Then down. (Think of the Old Spice ad! :)

The presentation is simpler. Even without reading anything you can get a sense for what is good and bad. The questions will come fast and loose: Why do we do TV? And if there is 75% leakage, is it still worth it? What is the optimal media-mix for our efforts?

We believe that summarizing our findings in text is the solution. We believe tables and graphs add complexity. We could not be further from the truth.

Closing Thoughts.

It's not the ink, it's the think.

It takes a tiny amount of time to really look at the data you are presenting, really think about what you are trying to say and identify the singular point. Once you know that, it is only a couple of minutes of work to decrapify the report/dashboard/slide/spreadsheet and ensure we are presenting data as simply as possible using the most optimal visual.

You worked so hard to collect the data. Then invested all that time and energy in reporting it. Finally, really dug deep, did the analysis. Don't stop there. Spend time optimizing the end product. Your goal: Get of the data as fast as you can, switch to the discussion of actions.

Victory, I promise, will be yours!

As always, it is your turn now.

Which one of the eight examples above is your favorite? And the least? Would you have taken a radically different approach on any one of them? Care to share your version? What are your go to filters for taking something complicated and making it simple? What is your favorite annoying data presentation method? Is there a visualization strategy that consistently helps you switch the discussion from talking about the data to talking about what to do with the insights?

Please share your insights, recommendations, critique, alternatives and complaints via comments.

Thank you.

7 Data Presentation Tips: Think, Focus, Simplify, Calibrate, Visualize++ is a post from: Occam's Razor by Avinash Kaushik

February 25th 2014 Search Engine Marketing

SEO 101: Beyond the Basics

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SEO BasicsA phenomenal amount of material has been written about Search Engine Optimization (SEO) over the past decade (plus).

Although much of the material is still applicable, the amount of out-dated SEO tactics that are still being touted as best-practice is growing.

The other day, I read SEO 101: Beyond the Basics, a 31-page complimentary white paper / ebook that outlines current best practices that companies of all sizes can use to increase site visibility, increase traffic, and most importantly, improve conversion rates.

In this very well-written ebook, you will learn:

  • How search engines make money (and why it matters)
  • Why you need to know your audience and what they want
  • All about keyword usage
  • Best practices for writing post content on your blog
  • How to optimize posts, pages and your entire site
  • and more…

I appreciate that this book emphasizes the techniques and tips that I teach at Rosalind Gardner’s Academy for blogging affiliates. :-)

If you are not already a member of our Academy, pick up SEO 101: Beyond the Basics for free now. You will have to either supply your info or login through LinkedIn to access it, but it’s worth it.

Get the facts about what works now, so that you too can increase traffic to your website / blog.

Comments, questions or suggestions? Please leave a comment below!

Cheers,

sig-ros

Empowering Analysis Ninjas? 12 Signs To Identify A Data Driven Culture

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focusedEvery indicator we have is that companies are investing more in every facet of analytics. Tools. People. Consulting. Processes.

Yet, it is unclear if that increase in investment is being followed by a commensurate increase in value delivered to the organization's bottom-line.

A part of reason for this mis-match in value delivered is that there is a natural evolution that needs to occur. There is an analytics ladder of awesomeness each company needs to climb, and it just takes time. But a larger part of the reason is that companies don't quite make the right choices in what behavior to incentivize, they make mistakes when creating the organization structure, and in the expectations that are set for what success looks like.

First… it is important to realize that big data's big imperative is driving big action.

Second… well there is no second, it is all about the big action and getting a big impact on your bottom-line from your big investment in analytics processes, consulting, people and tools.

So in this post, let's look at twelve signs you can use as signals to identify if your organization is set up for magnificent success. Each sign is essentially an action you can take, expectation you can set up. It is specific, it is, this will not surprise you, impactful.

#12: Almost all reporting is off custom reports.
#11: Close to zero aggregated analysis exists, everything's segmented.
#10: The KPIs in your DMMM reflect your company size/evolutionary stage.
#9: Your qualitative analysis practice rocks like crazy!
#8: Your Team's DC, DR, DA effort allocation is 15%-20%-65%.
#7: 25% of all analytical effort is dedicated to data visualization/enhancing data's communicative power.
#6: All automated reports are turned off on a random day/week/month each quarter to assess use/value.
#5: 80% of your external consulting spend is focused super-hard analysis problems.
#4: The Analytics/Marketing skills in your Analysis Ninjas is 70/30.
#3. Your organization structure for magic with numbers is: Centralized Decentralization.
#2. The organization functions off a clearly defined Digital Marketing & Measurement Model.
#1. You know what your Return on Analytics is!

Before we go too deep, let's get a couple of definitions right first.

Reporting Squirrels vs. Analysis Ninjas.

No company hires anyone called a Reporting Squirrel. Everyone hires what they believe are Analysis Ninjas. Leaving people skills and capabilities aside, it is the work the employee does that makes them a Squirrel or a Ninja.

Reporting Squirrels spend 75% or more of their time in data production activities. The primary manifestation of this is in creation of reports for their direct leader, or team or division or bunch of people. In service of report creation the job includes: Pulling data, writing queries, fulfilling ad-hoc requests, scheduling data outputs (reports, dashboards), liaising with script implementers / IT teams to collect more data, etc.

Analysis Ninjas spend 75% or more of their time in analysis that delivers actionable insights. The primary manifestation of this is expressed in English (or native country language). An example is: "We should add these 80 keywords to our PPC portfolio with a max bid of $14." Another example is: "I recommend a shift of $150k from our Display budget to our Affiliate budget to increase profitability of our purple pants." In service of analysis the job includes: Pulling data, segmentation, slicing and dicing, drilling-up, drilling-down, drilling-around, modeling, creating unique datasets, answering business questions, writing requirements for data sources and structures for Reporting Squirrels to work with IT teams to create, etc.

Again, remember no company actually hires anyone called a Reporting Squirrel. Most companies hire a Web Analyst, Sr. Digital Analyst, Web Analysis Guru, Digital Marketing Analyst, so on and so forth. (Remember none of these jobs will do any data collection/IT work, even in medium-sized companies.) But if their primary output is just data, and not actions to take expressed in English or verbally in weekly senior staff meeting, then they are simply Reporting Squirrels.

It is important to understand this difference. If you remain delusional about this difference, your Return on Analytics (ROA) will remain negative.

reporting squirrels analysis ninjas

It is also important to understand that many medium and all large-sized companies feel need Reporting Squirrels. Primarily because they believe that the mere act of data regurgitation makes the organization smarter. (They ignore the obvious flaw that people upon whom this data is regurgitated often do not posses skills to understand the data, ability or access to ask clarifying questions of the data or key context to transform the regurgitated data into insights.) To convince them otherwise is a lost cause, they just feel they need Squirrels, they will hire Squirrels, you can make good money being one, neither I nor anyone else will ever advice against taking this job.

But, it is important for you to understand the difference for the impact it will have on your career. I recommend a honest self-assessment (after all you don't have to tell anyone the results). It is important that your company understands that there are two different roles. If the company has the revenues or size, it is important to hire for both roles to ensure the ROA will be positive.

Reporting Squirrel work has a minor incremental impact on a company's bottom-line, and rarely justifies the investment in analytics tools, people, consulting and processes. An Analysis Ninjas' work does. So let's look at the twelve signs that your company has an environment with incentives to move Reporting Squirrels work to become Analysis Ninja work and set up a structure where Analysis Ninjas thrive.

#12: Almost all reporting is off custom reports.

This one is so simple, and a great first step to incentivize Ninja behavior: Stop accepting any standard report from any tool.

All standard reports are simply the vendor engineer's attempt to showcase the data in the tool. They are generic mash-ups that tailor to almost no one's needs, and more often than not contain awful things like nine not-really-thought out metrics for one dimension in a report.

This means they don't apply to you, despite valiant attempts by your Squirrel to add Secondary Dimension or a in-line filter.

Force your analytics team to create custom reports. Rather than using standard reports to deliver they they think you need, they'll be forced to pause and ask you: "And what business question are you trying to answer?"

Kisses. Hugs. Angels singing!

Creating custom reports is hard work. You need to take the business question, distill it down the the core four or five metrics needed, identify relevant dimensions, add the filters to narrow and focus the scope of the data provided and include contextual drill-downs to aid decision making. (There in a nutshell are the four requirements of a complete custom report.)

search marketing data analysis vp digital

In the process you've created an incentive for the Squirrel to talk to the business folks, understand the actual business needs, upon creation of the report really look to see if it answers the question, what the answer is and if it really matters to the company (Ninja-work!).

Mandating only custom reports will not by itself lead to nirvana (see the 11 additional signs below), but it is a great first step. It incentives asking of questions, it reduces cookie-cutter implementations that so many Squirrels or external consultants will foist on you, and it increases the quality of what you get: An almost insight.

That is worth fighting for.

Bonus: Download: Three awesome analytics custom reports. Collection of end-to-end Paid Search analysis reports.

#11: Close to zero aggregated analysis exists, everything's segmented.

All data in aggregate is crap.

Total revenue. Number of Monthly Visits. Average Time on Spent. Site Conversion Rate. Downloads. App Installs.

There is an initial OMG that is how much we are selling to those many people! OMG! OMG! But since those numbers have no context or drill-downs, people get over it very quickly and set your automated data output to auto-delete.

Segmentation is the process of identifying important clusters inside your data.

For example, which countries contributed to total revenue. Or, which pool of customers is most profitable. Or, which campaigns cause the type of repeat visits that deliver 250% higher average order value? Or, which products are loss-leaders for people from Saskatchewan compared to Manitoba?

Once a custom report is created, asking for segmentation incentivizes the asking of the next layer of questions that will almost directly lead to an insight that will lead to a action by the business. So insist that no piece of data (report, dashboard, sexy table) will ever be presented without relevant segmentation.

cohort feb cpc 1

When you review the portfolio of segments being used by your Squirrels, ensure that they have Acquisition, Behavior AND Outcome segments.

Additionally a sign of mastery of segmentation analysis (only likely if you have Analysis Ninjas, hence a good test) is if you see User, Sequence and Cohort segments/analysis, along with the normal Session and Hit level segments/analysis.

Bonus: Download three awesome advanced segments. Marry custom reports to advanced segmentation for deeper insights!

#10: The KPIs in your DMMM reflect your company size/evolutionary stage.

(More on the Digital Marketing & Measurement Model, DMMM, in #2 below.)

Because we have access to so much data in Google Analytics, WebTrends, Adobe Analytics et. al. the instinctive response of the Squirrels is to go grab the most obvious metrics and start partying. Visits! Time on Site! Pageviews! Hurray! Hurray!

While these metrics sound good, and yes they do get a bunch of press coverage (they have good PR Agents), they are rarely deeply relevant and even more rarely yield valuable insights into business performance.

Pick hard metrics to designate as your key performance indicators. Ensure that they reflect the size of your organization, and its current evolutionary stage. This will set significantly higher expectations for your analytics team to understanding business needs, work harder on the KPIs to find insights, and to deliver a more relevant higher quality outcome (in custom reports with advanced segments applied).

A very good incentive.

Here's an example of KPIs that set a higher standard to meet for small, medium and large businesses, and measure end-to-end success…

best metrics small medium large business 1

You don't see Business Profitability up there, it is only for the Super Analysis Ninjas. If you measure true business profitability, you'll unleash so much Analysis Ninja power it will blow your mind.

Hence the importance of picking the right KPIs. They incentivize optimal Ninja behavior vs. useless data regurgitation.

Bonus: Kill Useless Web Metrics: Apply The "Three Layers Of So What" Test. Four Useless KPI Measurement Techniques.

#9: Your qualitative analysis practice rocks like crazy!

One sure sign of asking for more, forcing more Analysis Ninja type efforts is to have a robust qualitative analysis practice in your company. They force the Reporting Squirrels to move beyond their obsession with Site Catalyst and web analytics data. But the most important impact is that they will get access to a why source of data in addition to their what source of data.

(My second blog post covered what and why! Overview & Importance of Qualitative Metrics.)

Three primary types of qualitative analysis that should be a part of your raised expectation set are: Heuristic evaluations. Usability testing (lab based or online). Surveys.

Heuristic evaluations, as you'll read in the post, are simple and easy to do, all you need are resources you already have. Your goal should be at least 4 evaluation sessions a month.

Usability is now so affordable with so many good online options. Your goal should be at least 5 tests per month.

qualroo

And finally by surveys I don't mean the 40 question puke of a survey that you are torturing your website visitors with right now! The world's greatest survey only needs you to ask three questions. Just three to get 85% of the actionable value you'll ever get from any survey (no matter how long you make it!). Your goal should be to have a task completion survey live on your site at all times.

What plus Why will create a powerful combination allowing your team to act like real Ninjas and arrive at actionable insights that can be presented in English and in lay terms. And guess what, that drives an impact on your bottom-line!

Bonus: In addition to qualitative analysis, Super Analysis Ninjas also engage in incredible competitive intelligence analysis. Do yours?

#8: Your Team's DC, DR, DA effort allocation is 15%-20%-65%.

Now that we have focused on the types of actual work that our analytics resources are engaged in, it is time to shift to the core of what we started with when we discussed the difference between a organization that has Reporting Squirrel work vs. one that has Analysis Ninja work.

I've split that into three pieces (simply to acknowledge the effort of our IT brethren): Data Capture, Data Reporting and Data Analysis.

Each quarter, if your practice is new, else every six months, audit the time spent by your analytical resources (in-house or consultants). Here is what the allocation looks like for organizations that are empowering Analysis Ninjas…

data capture data reporting data analysis

What does your effort distribution look like?

If you would like to evolve to the above distribution, and you will have to if you want positive ROA, here's a post with more details and helpful guidance: DC-DR-DA: A Simple Framework For Smarter Decisions.

#7: 25% of all analytical effort is dedicated to data visualization/enhancing data's communicative power.

Now that you understand the overall distribution of effort, I want to place a fine point on one facet of work that is truly Analysis Ninja work: Data Visualization.

Let met hasten to add I don't mean making things pretty or creating a data-pukey infographic. I really mean effort that enhances data's power to communicate effectively.

Reporting Squirrels so rarely have an incentive to focus on this, their time is taken up in shoveling the data. This is Analysis Ninja effort. Hence it is critical. After all, what's the point of all that data if it can't speak?

25% of all analytical effort should be dedicated to this quest. It is simply that important.

At the simplest level this is taking what we do every day and making it significantly easier to understand…

simplifying data presentation

Learn more, and how to, here: Excellent Analytics Tip #21: Convert Complex Data Into Simple Logical Stories.

Or it is leveraging a tag cloud or using conditional formatting or weighted sorts or many of the other simple techniques to allow data to speak for itself.

A more complex example might be to use Streamgraphs to visualize trends, patterns (say seasonality) for a chosen metric and dimension…

streamgraph

And perhaps an even more wonderful example might be to use Sunbursts to present a radically different way to understand content consumption patterns of users that lead to a desirable outcome for your business…

sunburst

Dedicated data visualization efforts will transform the efficiency with with your organization identifies insights (go Ninjas!) and the speed with which these insights can be communicated (this time without English!) to drive big, impactful action.

Hence my recommendation that 25% of all analytical efforts be dedicated to this magnificently valuable venture. You'll separate the Squirrels from the Ninjas pretty quickly, and create the right incentives.

Bonus: Win Big With Analytics: Eliminate Data & Eschew Fake Proxies.

#6: All automated reports are turned off on a random day/week/month each quarter to assess use/value.

Over the years I've developed an allergy to data automation efforts. They are almost completely useless.

The primary reason for this is that automation is based on the assumption that every single day/week/month the question we want answered with data is exactly the same. While that was true through early 1900s, it is no longer true. The world changes too much every day.

Automation also contains the assumption that the person being regurgitated will look at this finite set of auto thingy and will get all their questions answered. This will only happen if nothing changes in the auto regurgitated thingy. If something changes, the first question will be why and then its useless because they have to call someone, open a ticket, get access, wait seven days.

data reporting automation

In a small number of cases automation is ok. The CxO is expected to take zero action. They have their five KPIs, they just want to know how things are going and then take the next sip of their expresso. If they see something interesting, they still won't have any responsibility to do anything, they'll just shoot an email off to someone else (or raise a withering eye in a meeting!). For all such use cases…. Fine, automate their dashboard. There might be a couple other scenarios, but not that many.

In summary: Report production can be automated, analysis can be to a small tiny extent, but identification of insights to action can't be automated. Yet.

Now the reality is that people will want automation. It just seems so good on paper and in our hearts. If you can't avoid it, make sure your analytics practice has this process: Turn off a random number of automated reports/dashboards/widgets/data blah at least once a quarter. See what happens.

If you are kicking at a Ninja level, you'll have this practice for daily reports, weekly reports and monthly reports. The practice will lead to automated culling of automated stuff that no one misses, or does not drive action.

For your Analysis Ninjas, elements of their job will be automated. Certain data pulls, certain initial data mashing, etc. But the actual job of finding insights can't be automated and never will. If they say it is automated, you have a Squirrel faking it as a Ninja.

#5: 80% of your external consulting spend is focused super-hard analysis problems.

Consultants are a key part of what will get you to glory faster, and more number of times.

As a young company (Stage 1) you might use them to massively accelerate implementation and deployment. (More on each stage, what you should own vs. what the consultant should do here: Web Analysis: In-house or Out-sourced or Something Else?)

consultant 2dclient 2dstages

The problem is that due to our under-powered expectations or consultant's lack of skills, that is all we expect of them after the initial implementation plus deployment engagement of three months.

We might add automation of reports (eeek!) to their work load, and data starts getting regurgitated. Because all that automation just shares data, your employees will simply ask for more data (only insights in English drive action). So that leads to more regurgitation.

A real sign that you are empowering a Ninja culture is that you'll be in Stage 4 in 12 months or less (assuming you start from scratch in month one). Your consultants are handling challenges that you have no capacity to deal with (media-mix modeling, complex non-line behavior analysis, controlled experimentation, customer lifetime value optimization etc.). They will be adding real and material value by closing your sophistication gaps, by helping you innovate on the bleeding edge.

If you hire consultants, and they are not in Stage 4 (or 80% of their efforts powering advanced DA) then you have Reporting Squirrel consultants faking it as Analysis Ninjas. That is ok. Recognize that. Pay them accordingly, and accept your company's lack of improvement.

#4: The Analytics/Marketing skills in your Analysis Ninjas is 70/30.

The type of people you hire is critical in creating a Ninja culture. (Yes, yes, yes, tools are important and vendors are amazing, and all that stuff. Remember the 10/90 rule for magnificent analytics success.)

Here's a typical job description for a Sr. Web Analyst: "You have experience working with advanced web analytic methodologies, rich data techniques, experimentation, A/B & Multivariate testing. You have a passion for data and information that allows for laser focused strategies and decisions to be made. SQL and web analytics is your wheel house."

And that is important, it will form the bedrock of their skills. (Please, please, please do not ask for 15 years of "advanced web analytics experience," it does not exist and you are mistaking white hair for wisdom.)

70 30 people

But also look for 30% of their skills to be in immediately adjacent areas. For most digital analysts, that is marketing (online and offline), persuasion, communication and customer service. If you are unique to a certain niche, look for the 30% to be in areas immediately adjacent to that core niche. In your job description ask for it, in the interview ensure they have them (along with testing for critical thinking).

Focusing on just numbers skills overlooks the importance of other things that are key when it comes to just looking at data or making magical sense of it all. For the latter you need a much deeper understanding of business strategy, marketing objectives, customer experience and competitive realities. That's where the 30% skills play such a key role.

You will need people who can understand the See-Think-Do framework, or have the knowledge to create a new business framework for you because they are so good at business and analytical thinking! You will need people who can not only understand data, but data myths that get marketing people fired .

You hire narrowly, you'll end up with a Reporting Squirrel even if you call her/him the Director of Web Intelligence Services.

Are you hiring current/future Analysis Ninjas, or one-trick ponies?

Bonus: More on one-trick ponies and the 70/30 rule.

#3. Your organization structure for magic with numbers is: Centralized Decentralization.

Do you have an organization structure that will incentivize Analysis Ninja behavior, and where Analysis Ninjas will thrive?

centralized decentralized distributed 1

Some organizations have a centralized org structure for their analytics practice. This is ok for small companies, it falls apart pretty quickly for larger companies (or worse, evolves into an order taking bureaucratic IT organization).

Others have a completely decentralized structure work at some level. But with everyone doing their own thing it ends up being a structure were there are no efficiencies of scale, little incentive to innovate, and almost no optimizing for the global maxima.

In Chapter 14 of Web Analytics 2.0 I describe my favorite org structure: centralized decentralization. There is a lean (# of people) and agile central tem that is responsible for all the pro's you see mentioned above and also satellite lean team (of one or a very small number of people) in the BU's / divisions, that are responsible for the pro's you see mentioned above for decentralized teams.

Any company hoping to empower Analysis Ninjas will have a model very close to centralized decentralization.

Bonus: Who Should Own Digital Analytics? A Framework For Critical Thinking.

#2. The organization functions off a clearly defined Digital Marketing & Measurement Model.

You can do every single one of the above ten things and still fail.

Sad, isn't it? So much work, and still fail? Yes.

The single biggest reason for failures of your big/small/tiny/giant data effort is simple: A lack of any connection between the data effort and business priorities.

Your Squirrels or Ninjas spend valiant efforts, find amazing data, incredible insights, and yet if they are not aligned with business priorities nothing will get actioned. Causing incredible waste (and frustrated Squirrels!).

Yet, most senior leaders don't know how to answer the question, what should our analytics efforts focus on? Or what questions we can answer with data? The latter especially results in a massive laundry list of stuff for the Squirrel/Ninja to do, and still no tie to the business.

I'd developed the Digital Marketing and Measurement Model as a simple five step process that each organization can go through on a quarterly basis. At the end of the process, in which Sr. Leaders, Marketers and Analysts provide input, you end up with extreme clarity on what's important to the business, what data and analysis to focus the analytical efforts on. No running around. No making stuff up. Extreme focus and tie to business.

You can create a DMMM for a non-ecommerce (with goals and goal value!) content-only site like the one you are on now…

dmmm occams razor 1

And you can definitely create one for your for-profit or ecommerce digital efforts…

digital marketing measurement model step five

A clearly defined and well understood digital marketing and measurement model is absolutely critical in creating a culture that empowers Analysis Ninjas. It brings a sharp focus to their work, it ensures their insights will be actioned, and that in turn brings joy to everyone's lives. As a bonus, it forces the company leadership to really, really, think about what they are solving for with digital – such a big gigantic bonus!

Bonus: Five-Step Process for Creating your Digital Marketing and Measurement Model.

#1. You know what your Return on Analytics is!

The surest sign that you've created an organization that is truly rocking analysis, and empowering Analysis Ninjas, is that on a quarterly basis you compute your Return on Analytics (ROA).

Everyone in the organization gets measured and every dollar spent is evaluated in terms of the resulting addition to the bottom-line (or cost savings delivered), why not analytics?

Here's the formula…

return on analytics spend formula details 1

If you have Reporting Squirrels in your company, this is an impossible task (and they'll tell you that). If you have Analysis Ninjas in your company, this is not hard at all (and they'll tell you that as well!).

Beyond that delightfully satisfying test, measuring ROA ensures that your senior management team is aware of the value your big data efforts are adding to the company. That in turn results in their full support and incremental investment in analytics efforts, which in turn fuels a virtuous cycle that leaves the employees happy, the senior leadership delighted and the company richer.

What's not to love?

Bonus: Download the Return on Analytics Calculation Model.

That's it. Twelve signs that your company has created the optimal incentives, structure and expectations where Analysis Ninjas will thrive, or evolve to if you only have Reporting Squirrels today.

Truly Data-Driven Analysis Ninja-Empowering Achievement Guide.

Go ahead and do a diagnostic of how many of these signs exist in your company. Here's how to grade yourself…

If signs 9, 10, 11, 12 exists, you have the core foundations required. Level bronze achieved.

In addition to that, if signs 5, 6, 9, 8 exist, you are the envy of your peer group. Level silver achieved.

In addition to that, if signs 2, 3, 4 exist, your financial performance is constantly discussed on CNBC! Level gold achieved.

In addition to that, if sign 1 exists, you are so successful and dominant as a company you are about to be sued by the government because they are confident you are doing something illegal (except you are not). Level platinum achieved.

What if you have random signs form various levels? 3, 7, 11? You likely run a Reporting Squirrel farm. The clusters, as identified above, are the key in achieving each level successfully and scalably.

I wish you all the very best.

As always, it is your turn now.

Are you in an Analysis Ninja or Reporting Squirrel work role? Do you agree with the 12 signs outlined above? Is there a sign you've found to be a key indicator that's not mentioned above? Which of the 12 signs has proven to be most difficult for your company, current or past? Do you have a tip, or five, to share with others of things you've done to get to level platinum? What is the single biggest barrier Analysis Ninjas face? If you could only pick three signs for your company/country, which ones would they be?

Please share your critique, insights, stories, examples and helpful guidance via comments below.

Thank you.

Empowering Analysis Ninjas? 12 Signs To Identify A Data Driven Culture is a post from: Occam's Razor by Avinash Kaushik

January 7th 2014 Search Engine Marketing

Rap Genius Searches for New Traffic Tactic After Google Slap

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It’s a good thing Rap Genius has an app coming out next week, because it just lost more than half its typical mobile Web traffic thanks to Google

Rapper Nas in a Fila headband

Rap Genius has been in battle mode for the past couple days. Google penalized the site —where people go for musical lyrics and other media—over apparent violations of its search engine code of conduct, involving link kickbacks.

Rap Genius revealed its own search scandal by publicly soliciting bloggers to post links to the site in exchange for tweets. It’s not arms for drugs, but Google takes any system gaming seriously.

Today, if a person Google searched for “Rap genius,” its website was nowhere to be found—the equivalent of online annihilation. Rap Genius, which has raised $15 million from venture capital heavyweights like Andreessen Horowitz and counts about 40 million unique visitors a month—saw its traffic drop about 64 percent today following Google’s downgrade, according to Quantcast data.

Most of that traffic comes from the mobile Web, which makes the company’s app next week an even more important launch. It was unclear how long Google would suppress the company’s results, but JCPenney was once penalized in search rankings for 90 days.

“The app will make us less dependent on Google,” co-founder Mohbod Moghadam said. “Everyone is screaming for an app.”

One of the major features of the app, built for the iPhone, is a song detector that calls up lyrics to whatever is being played through speakers—using Shazam-like technology.

With more than half of Rap Genius users visiting on mobile, the founders hope that the app will be the gateway to the site instead of Google. It’s part of a broader strategy that only has been made more urgent by the Google punishment.

Moghadam said that Rap Genius has more than 1 million registered users, but that’s only a small fraction of total visits. The company hopes to convert those lurkers—just passing through—into sign-ups.

Rap Genius is known for more than posting hip-hop lyrics, and the site has expanded into categories like rock music, art, news, fashion and poetry. It allows users to add publicly edited and ranked annotations within the content. For instance, famous singers could explain their lyrics by posting notes within each line.

Moghadam revealed some of the more advanced visions he has for the app, including allowing famous people to upload video clip annotations—about 10-seconds long—directly from mobile devices.

He said he also is petitioning brands to create verified accounts. The platform is moving beyond text into images that might be suitable for fashion content.

Rap Genius already is exploring the concept of sponsored or promoted annotations. The clothing maker Fila, for instance, posted a photo within a post about Nas lyrics in which the rapper mentions the brand. Moghadam said he is going after other brands like Karl Lagerfeld and Hublot.

They are also working on annotation platforms that are powered by Rap Genius but exported to other publishing sites.

Moghadam said he wouldn’t comment any further on the search engine troubles. However, Danny Sullivan of Search Engine Land, a site dedicated to the industry, said he was unsure Rap Genius even broke the rules.

Google would likely restore the rank shortly, he said.

“Google can’t do more than wrist-slap them for that,” Sullivan said in an email. “People searching for ‘Rap Genius’ expect—and should get—the actual site coming up first.”