3 Digital Practices Brands Need to Master Before It's Too Late

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It's August 2013. Do you know where your markets are?

In terms of digital analytics, that is.

With content focus shifting rapidly to mobile (as if the web was going anywhere!), and multi-channel analytics all the rage, it's important to note that whatever the platform, three principles remain key to brand success.

The larger the brand, the more important these items become. And with added layers of measurement complexity, they become that much more difficult to achieve - as well as that much more essential to success.

Time to get the woodwinds playing with the strings; and the brass playing along, too. If you miss this opportunity to make a symphony, you'll have an awful time getting control of it later when it's even more complex. And by then the hall will be empty - your audience will have gone home.

Here are three important challenges that must be met by any brand hoping to get more value out of its digital properties.

1. Analytics governance. Far-flung content owners? One big, rather dated and rather expensive measurement solution that seemed to be the answer to everything back in 2007 (but that most business users don't like or don't use)? Lots of agencies each making the case they should measure their own success? Rogue sites with non-standard tools measuring in non-standard ways? And no way to roll up reporting because nobody seems to have any measurements in common anymore? It's a poorly tended garden indeed, but it's more common than you'd think among big brands.

There's a way to get this under control, but that's the keyword: control. Some call it "governance." Governance requires at least the following:

• Create a central digital measurement authority and run all analytics through this team without exception.
• Choose a single, not overly costly measurement platform (or suites for different channels) and enforce its use.
• Create a basket of basic measures that all properties must measure no matter what else they also measure (again, there may be one at least for desktop and one for mobile).
• Don't let agencies measure their own content; not only is it unmanageable for the brand, it's also a natural conflict of interest.
• Drive reporting responsibility to the markets and business owners. For instance, ask them to justify why they need a particular custom report (e.g., "What would you do different if you knew the numbers?").
• Update reporting often. Underutilized custom reports and long-forgotten profiles are the bane of good analysis. They are confusing resource hogs and should be deleted. A clean interface leads to better adoption by business users.

2. Data integrity. They don't trust the numbers. And they won't take action (see below) because they don't trust the numbers.

Adoption remains low.

Millions of dollars may be lost because no one's keeping track of the data till.

In order to establish data integrity, institute governance, then:

• Perform tag audits on everything right now (tags are the snippets of code that collect data); make sure they are connecting with the analysis engine!
• Establish baseline reporting and a set of standard tags to support it.
• Think seriously about tag management systems and how they can simplify tagging across the organization.
• Don't just accept numbers from external sources - use your own analytics to see if there's a match.
• Data-integrity laggards should be sharply questioned as to why they won't or can't measure accurately.
• Remember the audit? Perform this not once, but often, and have the results reported up to senior management.

3. Content actionability. Does a digital campaign make noise in cyberspace if no one is there to hear it?

The answer is "no." There's no value to content that doesn't drive conversion.

And that's why you measure. To optimize content. To get better conversion rates.

This suggests rather strongly that you may need to do something different once you see the data gathered by measuring user interaction with your content.

There are two ways "actionability" works. One is indirect via human intervention. The other is automatic via sophisticated content delivery strategies supported by algorithms and what's often called "real-time" data.

• Human intervention means never having to say "my creative team liked it" even though the data says you wasted your money. They may have liked it when they launched it, but if it doesn't bring dollars or meet an exposure goal (all measureable), then they should stop liking it and get to work fixing it. It can be very difficult to drive this message home to the teams you rely on to build excitement for your brand; but the best ones know which side of the bread has butter, and it's the side that also has the conversions. Who's paying the bills? You are. They work for you. Demand changes to content areas that don't perform.
• Automatic actionability is a more recent development but it can be very effective. Dozens of measurement platforms claim to be "real time," and to deliver what they call "predictive" analytics. An awful lot of that is bunk. But when the right algorithm is hooked up to the right data at the right time, then content can be served up based on criteria gathered during the measurement phase. When it's done right, this qualifies as both "real time" (very fast) and "predictive" (properly modeled based on data). This is what ad networks do all the time; and now this capability, via several competing multichannel analytics applications, is available to brands that want to leverage all the data they've gathered to achieve better-targeted messaging.

Whether by human hands or robot power, the feedback loop from data to content and back again is essential to digital marketing success - and now is the time to get a handle on it.

Managing the digital brand experience is only going to get more complex; and the cost of reining in the wild analytics horses is going to get higher, quickly.

Best get out the lariat.

Image on home page via Shutterstock.