The 4 Ps of Digital Analytics: Why They’re in Sequence

Written by Andrew Edwards. Posted in Digital Analytics

Sometimes it’s helpful to have simple reminders about what’s important in a complex process.

The “4 Ps” of digital analytics represent one such reminder.

It helps you understand both the key elements in a successful digital analytics effort as well as the relative importance (and sequence) of each item.

There’s a reason it’s a list and not an array. One comes first. One comes last.

  1. People
  2. Purpose
  3. Process
  4. Platform

That’s the sequence and the relative importance of these critical elements. Notice that “people” comes first, and “platform” comes last.

Many companies fail by focusing on “platform” while ignoring either some or all of the first three elements of success. They fall victim to sales pitches from platform vendors who want to tell them it’s their tool only that will solve the problem, no matter the environment.

Make no mistake: you absolutely need a platform. But you decide what that is after you’ve got the right people, have a purpose to your measurement, and a process wherein you’ll generate marketing success. Then, and only then, should you add the platform.

The best platforms will be able to adapt to your people, purpose, and process; the lesser ones will have restrictions and will need to attempt to impose process, purpose, and sometimes even people; these should be seen as weaknesses in the offering, rather than features.

The best tools are adaptable and powerful, and can be configured by people who have a purpose and process.

People: Who’s going to understand how to do all this? People are. Expertise is the first essential ingredient. Minus this, the rest is for naught.

Purpose: What do you want? You have to know what you want to know and what you would do about it if you knew it, before you decide what to measure and with what platform. Some folks call it KPIs, but that’s really just the half of it. The other half is the “doing something.” It’s equally important.

Process: How are you going to do this over and over? Think about something like this: define, measure, analyze, change, and measure again. It’s a virtuous cycle of improvement. Implemented properly it should look like an upward-charging spiral of better and better marketing.

Platform: Once you know the above, go out into the marketplace and find out which tool matches your requirements best. These days, especially in multi-channel or convergence analytics, there are probably a hundred vendors to look at. They range from all-encompassing suites that want you to marry them and deploy everywhere, all the time; to point-solutions that elegantly solve a single part of the problem (and then you can cobble it with other elegant point solutions).

The most important part is understanding the sequence. First, you need people who know what they are doing. Then, those folks should determine what you want to know, and what you will do about what you find out. After that, your smart people need to settle on a process, the broad outlines of which are easy to discern. Finally, they need to locate a tool or set of tools to accomplish their goals.

And your expert people then need to take responsibility for the entire effort looking much more like an upward-vaulting spiral than a lazy doodle.




5 Essential Practices of the Data-Driven Organization

Written by Andrew Edwards. Posted in Digital Analytics

Analytics may be multi-channel these days – mobile, digital, social, email, and yes, even “web analytics” as once it was known. Analytics also means audience measurement via surveys and panel-based analytics as part of a site-ranking methodology. Whatever its latest form, analytics only helps when integrated into the creative and decision-making processes of the organization.

Too often analytics itself works in a small building off on the edge of the corporate campus. Occasionally a paper airplane flies into the executive window with a message from the analytics team. And the executive, on his way to a meeting, steps on the folded paper. It sticks to his shoe and by nightfall the janitor has swept it into a dustbin. So ends the influence of analytics in the non-data-driven organization.

Try to imagine an organization that is designed around intelligence gained from the data it collects about its customer interactions. This organization will have at least these five characteristics:

Define what it wants to measure. Analytics deployment experts will work closely with marketers and business owners to understand the key business drivers for the organization. These drivers will be closely aligned with actual business success. For instance, branding will want close interaction. Services will want leads. Sites that rely on advertising will want volume plus careful segmentation. The analytics experts will turn these needs into reporting structures that can answer important questions – going well beyond the baseline reporting that comes before customization. As important as deciding what to measure is deciding what not to measure. The organization will avoid overcrowded report structures; will have realistic goals about what is measurable and why; and will make sure expensive tools are not overburdened with whimsical profiles that never get viewed.

Deploy analytics tools expertly. That clamor you hear is the sound of the poorly chosen agency or miseducated IT team grabbing their pitchforks and torches as they try to kill this initiative – they may believe their jobs depend on “controlling analytics.” But in the data-driven organization, they are quietly asked to go back to doing what they do best – create great content; make sure systems function. Perhaps the most common difference between the properly aligned team and the data-flunking team is the way expertise is deployed. The data-driven organization will not blame the tool. It will not permit content creators to claim they “also do measurement.” They will audit their tags for completeness and functionality. They will have a neutral third party – expert specialists in analytics – deploy the tool with clarity of purpose, and without bias to anything but the truth about content success, campaign success, and ROI. They’ll know that any other road leads to costly waste, bad politics, and ultimately, no insight.

Analyze results and make recommendations. At the successful organization, reports won’t gather dust. They will be shared with the right people in the organization – people who can make decisions and direct action based on the findings. The findings will be clarified by people who understand how the data was gathered, can vouch for its accuracy, and put the data into context. In the same meeting, an action plan will be devised. What content will live – or be retired? Which partners seem to drive the most successful visits? What campaigns pulled not just the most visitors, but the most desired actions? Resource reallocation may be in order. Cuts in a place least expected. Additional effort toward an area that measures well – perhaps one that had been undervalued. The ability to reprioritize and react to data is one of the most important characteristics of the data-driven organization.

Create changes based on data. The developers may say they’ve got the best new wireframes this side of paradise, but somehow the numbers indicate rethinking the existence of that entire module. The content provider may insist on real estate where its click-throughs don’t pay the rent. The data-driven organization knows how to say “no” to the ineffective; and to insist on creative, content, and campaign changes based on what came out of the analytics. Was that partnership successful? Yes? Why? The data will reveal why – and the next partnership had better incorporate some of the characteristics of the winner. The organization won’t have time for slight tweaks to a tanking campaign – it will demand wholesale change if it’s needed. It will stand by the numbers, and insist its agencies and other content managers stand with them.

Measure again – and again. Done with that measurement exercise? Here’s the next. Analytics is a cycle of definition, measurement, planning, informed improvement, remeasurement, definition, measurement…forever. The organization knows that optimization is never one-and-done. It should not be enslaved solely to IT or developer “release cycles.” It should not come into the picture too late to have an impact. It should be as close to real time as possible without anyone twisting an ankle by being in too much of a hurry. Here is where you ask: how’d it go with those changes? Helpful? Better? Even a little better? OK, let’s make it better still. Incrementally, perhaps…but always on the road to Betterville. The data-driven organization lives in a cycle of measurement and improvement.

Do you recognize your organization in the above? If so, you’re in a great place. But chances are you’ll notice where your team is off in some other direction – they’re not on the proven path to improvement. And with soaring emphasis on digital enterprise, how long can you afford to be part of that team? Making the necessary changes may not be easy. Failing to take advantage of data is worse.

If your company is going to thrive in the digital marketplace, it will be as a data-driven organization.



4 Ways Digital Analytics Is Changing Forever

Written by Andrew Edwards. Posted in Digital Analytics

If you plan on getting your digital analytics done the way you’ve done it in the past, you may want to scrap those plans and start fresh.

Because in 2013, an entirely new approach to digital marketing and analytics is taking hold. Some have called it multi-channel analytics; some have called it business intelligence for marketers; some have called it (somewhat one-dimensionally) big data. I have called it convergence analytics.

Whatever you or your advisors want to call it, the facts about these important changes remain the same, and here are the four most important:

1. Everybody is measuring everything. And putting the reports in a dashboard. By everything, I mean everything. Begin with the desktop (this now means ” web”); add “mobile” (which means several things not very well-defined); add what is euphemistically referred to as “unstructured data” or social media; then add census or other data; CRM (like Salesforce); CDNs; predictive models; ad network data; geographic data; add in revenue data; add any data from any tool that has an API or SDK (and that includes about everyone). And you begin to get a sense of what “everything” is.

From the vendor side, the level of activity is nothing short of spectacular. To say that every company that ever measured a digital property now says they can connect to any data and visualize it for you might be an overstatement, but not by much.

From the marketer side, it’s going to suggest a need for re-architecting your entire approach to data. And possibly an entire new round of tool selections and skill enhancements.

2. Digital is getting married to television. We thought we were done with TV, right? Wrong.

All television is now digital (pretty much by government mandate). Which means TV really is just another IP address-driven content container.

Here’s why it’s important: people still love television. It’s engaging and compelling in ways that websites and apps never will be. It’s the movies. Except on a big flat screen (or a small flat screen) in your own home or office. And we haven’t yet figured out how much it will distort or even destroy the rest of the digital content universe. No matter what, we will have to figure out how to market there (again). Because it will be more like YouTube or perhaps Netflix than like “primetime.” And we will have to measure usership in more sophisticated ways than ever before.

3. Privacy may be dead, but nobody likes surveillance. I’m a digital analyst. So I’m not going to climb on a holy soapbox and complain about how corporations are tracking your every move online. They are. But then again, they’re not charging you any money for most of the stuff you use online. That’s the price users pay for “free stuff.” They pay with information about the way they interact with the content.

While Europe has gone buggy about privacy, in the U.S., only a few people really care about it. And even fewer ever do anything about it (like, for instance, reject or delete cookies at intervals).

But now that we’re starting to see so-called “surveillance scandals” at the government level, especially as regards the news media and beyond, the subject of privacy may well come into focus for the American consumer. The government can get records of almost anything it wants (and the recent advances in digital tracking make this a more important factor than ever). Most people try not to think about this. And they shouldn’t, as long as the government respects the individual’s right to due process. But we are one or two scandals away from folks deciding they don’t want to be tracked anymore because they’ve become paranoid of the Feds.

We don’t want that. So we should try to make sure the government understands that there is a huge difference between the shopkeeper knowing what frock you looked at while you were in the store, versus Big Brother knowing where you were the night of September 17.

4. Marketers are losing control of the data. To be fair, the concepts of “marketing” and “data,” while not quite an oxymoronic pairing, have never been a comfortable fit. Marketers aren’t typically wired for data. Measurement has landed on them and they have embraced it; and some of the most agile and forward-thinking have made big wins with data-driven decision-making.

But that was when we were talking about web analytics and a dash of campaign attribution. Now we are talking about an enormous new push by vendors and senior management to squeeze the marketer on measurement of ROI. Vendors have created powerful new technologies that need selling. Management has gotten the sense they can somehow know successful marketing through measurement; and thereby save tons of money. Both vendors and management are more or less correct. And marketers, caught in between, will again be forced to adapt to rapidly advancing technology.

It’s an open question whether they will, as a group, be able to do it. Or whether the entire task of digital measurement, having grown far more complex than it was even a couple of years ago, gets yanked from marketing and put back in the hands of data people who don’t report to marketers.

Marketers will need to get out in front and lead on this – or they will find themselves roasting in a rather hot sweatbox, penned in by data scientists using sophisticated tools that until recently were far too difficult to build and too expensive to buy except for the very largest and most data-intensive organizations.

Digital analytics is changing forever. Some might say it’s about time.


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