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Enterprises: Fix These 3 Analytics Challenges Now

Written by Andrew Edwards. Posted in Analytics

advanced-analytics-185x114We’ve all been at this analytics thing for a while now, and with all the advances in big data and algorithms and data visualization it’s sometimes too easy to lose sight of some of the bedrock disciplines that got us here.

Big companies are different from smaller ones and the stakes are higher where mistakes are made. Getting these three basics in good working order at the enterprise level makes positive change much more likely than not.

1. Governance

Who’s in charge here?

Many large organizations have content owners across the country or across the globe, and they are often in different stages of analytics maturity. Each team seems to think they have found a solution that works (more or less), but when it comes time to compare a Golden Delicious to a Granny Smith, often enough it turns out your team in Kalamazoo is using a pomegranate. You need to standardize on a platform and make it your benchmark. Each platform measures things in different ways and there is no reliable way to compare (for instance) what a “visit” is in one platform versus another. Most of the time, they won’t match.

The enterprise may also engage a fair number of content-creators, ranging from full-service agencies to bloggers to pure-play development shops. Too many of them also claim they can do the measurement as well as the creation. Avoid this trap by centralizing measurement inside one team that’s responsible for standards, governance, and measurement itself. It may require bringing in a digital analytics consulting team that can laser-focus on these issues. The alternative is a world of rogue sites, unhelpful self-measurement, and no way to roll up results beyond the market level.

2. Data Integrity

The notion of data collection is often remote and mysterious to marketers and decision-makers. They have little knowledge of the details and less control of it. Safety seems to require skepticism about accuracy – and this leads rapidly to nothing at all. Because if you cannot trust the integrity of the data, you won’t be taking any action based on it.

Taming this problem requires standardization (as noted above), but also trust in your analytics team.

Trust is a nice word, but how about verification?

A tag audit is a great place to start. Find someone neutral on content and measurement and have them look at whether the data is being collected properly. Too often, the answers will be less comforting than you’d hoped, but knowing is the first step toward fixing. Are tags firing more than once on a page? Are certain things not tagged at all? Are parameters set correctly so that the data maps to actual reports? Audit today.

3. Content Actionability

The main reason you measure user activity is to find out whether your content is working. This implies that if it turns out the content is weak, it will need to be changed. And how will that happen? Do you have a plan, a process, a regime that addresses this key element to success? Or do you end up making recommendations that never see the light of day? Are politics getting in the way? Is someone’s favorite campaign or favorite agency looking not-so-good after measurement? It’s tough, but this kind of thinking needs to be defeated before you can win at optimization.

Actionability requires human intervention. It requires putting aside personal preference and prejudice and looking at the data. Your mindset needs to be grounded in success metrics rather than aesthetics or alliances. If you want more customer activity and a healthier bottom line, ditch the so-called loyalty to any particular campaign or site design and look at its performance. The race goes to the swiftest car, not the prettiest and certainly not anyone’s subjective “favorite.”

Simply put, you need to have a plan to govern your data collection, then verify its accuracy, then be confident enough to make changes based on what you find out. If you are thinking this sounds pretty hard, you won’t be the first.

But making a success of it brings success to the business. Take immediate steps to fix these problems and you will be glad you did.




5 Weird Tricks for Keeping Analytics Projects on Track

Written by Andrew Edwards. Posted in Analytics

analytics-shutterstock-139983946-185x114Analytics is complicated and, because it is designed to provide facts, is not often as welcome in a marketing discussion as other disciplines. Analytics sits between marketing and technology in a place where neither party feels altogether comfortable; and too often the analytics consultant finds herself taking arrows from both sides.

Here are some suggestions for the analyst in order to make sure your analytics customers remain happy, whether internal or external.

1. Establish Legitimacy (Confidence)

Do you know what you are talking about? Make sure your customer knows it. Often the more insecure a stakeholder is, the more skeptical they are of you. When you meet these kind of folks for the first time, have handy a brief “elevator pitch” that lists your qualifications and experience in a friendly way. Then, avoid jargon and instead, talk in a way that some folks call “storytelling” but which I call “narrative.” This requires you know the data and where it points. In this scenario, you are the scout-leader heading the group on a hike to the facts.

2. Overcommunicate

Don’t make yourself a burden by going over the top, but when you wonder “should I check in,” it often means your subconscious has already answered that question and is trying to get your attention. Making sure your stakeholders are nearly as well-informed is key to keeping them happy. Communicate more judiciously than you would with a colleague. Your customer is more averse to surprises, and that’s mainly because they often have their own reports to do, and when you surprise them, then they have to surprise their boss. And their boss really does not like surprises. Keep from surprising your stakeholder, even when you think the news is good.

3. Test Before Launch

Have you heard of the “small technical glitch” that “caused a big problem”? It happens a lot more than you’d expect. Almost always, this is because no one has set up a proper testing environment; and tested whether the program creates unexpected changes in data collection or reporting. A test environment is a great way of avoiding surprises (see above). In many cases, it can spell the difference between a good analytics program and loss of confidence.

4. Pay Attention to Narrative

People are storytellers. Data doesn’t tell a story, but it does provide you with reports so that you can tell a story. Perhaps one day there will be a truly engaging storytelling robot but today, it is still the job of the human being to look at seemingly unconnected threads of information, see patterns, understand nuance and relative importance, and to create a story out of raw numbers. You’ll likely need data from different sources to create a fully dimensional picture for yourself, which then you will use to create the narrative that comprises the insight needed to make changes based on data. Without the narrative, it’s just machines talking to other machines.

5. Don’t Defend Technology at the Expense of Business Needs

Technology is not business, it is a subset and a provider to business. So when a non-technical person says why not, the technologist is ill-advised to simply say “we can’t do that,” assuming the non-techie will accept that “the technology just cannot do that.” First, you may not be right. Very often, there is a solution out there, and maybe you need to find it. Second, many businesspeople see a technology lack as your lack, because without technology, you would not be there at all. It’s OK to say the technology cannot do it if the technology cannot do it, but you will need to communicate that as a business concept. For instance, “there is no data source” is not nearly as effective as “we need someone to give us access to the data sources, do you know who that might be?” All of your reasons for doing things (or not doing things) must serve a business purpose, or you need to supply a plausible business reason why you can’t do it.

With these five weird tricks you should be able to lose weight, get cheap car insurance, and even keep your analytics customers happy!


Yes It’s True: Television Rules the Ad Waves

Written by Andrew Edwards. Posted in Television

televisionAccording to recent Nielsen numbers on the topic of Internet ad-spend versus TV ad-spend, the Internet is like a small bird picking mites off the back of an elephant. I will admit these numbers are nine months old, but I do believe they still pertain, even as mobile ad-spend has pushed Internet spend higher in the last couple of years.

Nielsen gives less than 6 percent to “on line” while “television” (which includes cable) gets close to 60 percent of total global ad spend (including all advertising everywhere). If you think broadcast is still relevant, it might interest you to know that the Internet has already surpassed it. And while TV has grown much slower than the Internet, the Internet is still very small.

While Nielsen does not publish dollar amounts, ZenithOptimedia says the global total ad-spend surpassed half a trillion dollars in 2013. So both the little bird and the big elephant are billion-dollar babies. Zenith also gives the Internet a whopping 21 percent of spend, still dwarfed by TV. This may be because Nielsen gives no credit to search-engine ads, only display ads. Which is only a little bit silly, because last I read, Google has more ad-spend than all of print media in the U.S.

The elephant and the little bird are both “in the room,” if you will.

What’s the Hold-Up?

Why is TV still dominant? I read somewhere we had stopped watching TV; so I must have missed something.

In light of all the above, why is Internet the darling and TV too often portrayed as somehow the inevitable loser in this race?

If you want to hear answers from the tech community, it’s a mere statistical anomaly that the Internet has not yet completed its domination; and that advertisers just need to get with it. If you want to hear answers from advertisers, especially those that control the massive TV ad budgets, they may tell you it’s because when they go to buy ad space on the Internet, they don’t know what in the heck they are buying.

TV ad spend is pretty much ruled by Nielsen and that is because it always has been that way, and it is an article of faith that Nielsen knows best.

However silly that might be, the fact there is a single source of well-defined audience measurement for TV makes all the difference.

Digital analytics, which is supposed to be much more accurate than the extrapolated data from Nielsen, cannot begin to compete; not least because it is like a mirror shattered into a million pieces — each shard with its own reflection — while Nielsen is just a single mirror where you can see stuff.

So, is it really about slavish fealty to Nielsen? Or is there some other reason why Internet advertising continues to lag despite robust year-over-year growth?

Maybe It’s the Content

Is it possible the answer is that no one can stand Internet ads? And that they often refuse to click on them? I have one friend who says that whatever brand shows up in his free mail account is the brand he will not buy. He never said that about the ads that interrupted the ballgame.

I think there are natural limits to every market, and that Internet advertising may soon find that limit. It isn’t because people don’t love the Internet. It’s because when they watch TV, some commercials actually get their attention and make them laugh or listen. I have some doubt as to whether anyone anywhere has ever said to themselves, “Now that’s a cool Internet ad.”

I don’t have the answer — and I don’t click on ads either. But I do like that ad on TV with the hamsters driving a little Korean car.


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