The premise of online advertising is not just that people see ads like they do in print, but that the effectiveness of the ad is supposed to be directly measurable. Based on measurement using web analytics, the enterprise can model customer behavior and plan future campaigns – at least that is how it’s been sold to us all. But what happens when the measurement process is so truncated as to become almost a parody of measurement? Who wins the race when we just stop at the beginning like a balky thoroughbred refusing to get out of the gate?

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Many marketers have said they have difficulty getting buy-in from management for digital analytics; and especially analytics reports. And while the marketer may understand the value of these reports, the reports don’t do that much for the organization if no one else gets interested or involved.

The problem may not be the reports themselves, but they way the report data is being presented.

Here are three ways to make people in the organization aware of the impact of the data provided by digital analytics for a single marketing channel (the same principles will apply for multi-channel reporting but the presentation and cross-referencing will be more complex):

1 – Start with Basic Principles

Often reports alone lack context. The marketer, especially when communicating with senior management, should provide a “basis for caring” about what is being shown. For instance, part of the presentation deck should include some basic facts about the process of optimization and how data about usage patterns helps drive content; and how content and campaign adjustment will drive revenue, save money and improve ROI.

2 – Tell a Story

Showing reports unfiltered by editorial can be stultifying. Most senior managers have little time and no taste for looking at tables of data. It’s up to the marketer to pull the relevant data, simplify it, and tell why it matters. Link your data to real problems being confronted by the organization and show how creating improvements based on the data can help. In short, tell a story with data and your ideas, rather than just sending reports and hoping for the best.

3 – Follow Up with a Process

It’s not over when your presentation is done. It’s important to lay the groundwork for a process that will result in content optimization. It means letting the right people know that the only way they will get any value out of the exercise is to make changes based on what’s been shown to work well and what’s been shown to work not-so-well. Remember that you are not trying to prove the value of analytics. Instead, you are using analytics to prove (or disprove) the value of content. It will be important for everyone to remember the old maxim that says “You can’t manage what you don’t measure”.

By deploying the above three techniques, the marketer should be able to gain much more buy-in from a variety of constituents: from senior management, from other marketers, and from content creators/providers. Everyone has a stake in understanding the success of their digital properties. Part of the marketers’ job is to make sure everyone understands what content/campaigns are getting the desired results, and which are not. And if you can get enough of your team on board to actually react to/make changes based on analytics, you can go back and show improvements in the performance of your content; which in turn should drive additional buy-in!

One of the most challenging parts of digital measurement is getting the data collected properly. You will want both accuracy and relevance in your page tagging in order to accomplish this.

No matter what vendor application you’re using to collect clickstream data, you will first need to define your reporting priorities (which means you’ll need to define what you want to know about your visitors’ behavior). For the sake of this post, let us assume you’ve gone through that exercise already and know what you want to report on.

Most web analytics applications today require page tagging to collect data. Tags are snippets of javascript that generally go in the header of your html and are comprised of a combination of a supplied formatting (specific to the tracking tool) plus a location in the script to place variables that are unique to your site and sometimes to the campaign, page or activity you are tracking. For some sites that need only basic, generic reporting, the placement of a single line of code with your domain as the variable will be sufficient–but most serious marketers need to go beyond this.

It’s key to success that a tagging expert create these tags, especially when you need to go beyond the generic tracking built into the vendor’s application.

Deployment of tags then moves to either a tag management tool or to your developers who will put the tags into the html in the appropriate locations. In order for this process to go smoothly, some tagging expertise is necessary, as developers typically do not concentrate on this as part of their skill-set. If you have a tag management solution, you’ll be going through a somewhat different process (we don’t have space to detail it here) but the tags still need to be carefully constructed by an expert.

Testing for data collection throughput and accuracy takes place after tag deployment and, usually in a test environment, some data is coming through (its not a good idea to launch before tagging QA). This is accomplished by checking each and every tag to make sure that when the relevant action takes place, it is picked up by the tag and delivered to the analysis engine. A good way to set up a QA report is to use a spreadsheet showing the tag name, its function, the expected result and the actual result. Unexpected or null results will then have to go back to the developers for adjustment–usually your tagging expert will know what was done incorrectly and can make sure it gets fixed.

Once a rigorous QA plan is completed and the tags are collecting data as they should be, it’s finally okay to launch and begin to collect actual user data. At this point you should expect to see live data flowing into your reports as expected.

Many marketers struggle with mapping Data to KPIs.

In other words, they want to review the reports that come in and see whether they achieved their goals. And in most cases, the data just sits there unyielding. It doesn’t tell the marketer what the marketer needs to know. It doesn’t say “here is your KPI and here is how well you did”.

Data doesn’t know what you want to know.

But that doesn’t mean you can’t get answers to your business questions.

You’ll need to put the data in context. Creating context is one of those cognitive abilities only humans have (so far). It’s a trait not unlike intuition, and relies on the combining of lots of experiential information, plus empirical data, plus what still passes for “gut” in parlance, even though we can be pretty sure even this murky sense of “what’s right” will one day be quantified by neuroscience.

“Key Performance Indicator” is a term that goes halfway towards a data definition of “why you have a web site”. Data itself has no idea, nor will it ever, why you built your site–no matter how large nor how small it is.

Think of KPI as metadata about your site. It needs to be layered on top of the reports.

Here is an example of how this mapping of KPI metadata might work. As you may begin to notice, the KPI for even a large, complex site may be rather simple, and that much of the content on the site is supportive in nature (in digital analytics, that would be called “engagement content” because it is supposed to help drive customers to perform the most important KPI, or the “conversion” event).

Let’s say your site wants to disseminate content about different topics your company has deemed important–or that your company wants to develop certain ideas based on some content popularity metrics.

Much of the work lies in reducing the ratio of signal to noise in your data. In other words, for this exercise, you will want to focus on certain reports while ignoring everything else (analytics tools are very good at giving you much more data than you need and burying what you want).

For the sake of this exercise, let’s say the concepts you are market-testing reside in a pdf or other downloadable format.

What you will want to look at is the following:

• reports that indicate which campaigns drove the most traffic to your “pdf section” (for instance)–possibly a landing page

• reports that indicate which campaigns drove traffic that moved beyond the landing page and got to the download page

• reports that tell you how many times a particular asset got downloaded, and which ones were the most popular

So out of thousands of possible reports, we have isolated just a few.

And they will not necessarily be sitting in a single dashboard. You may have to go find them.

Then, in order to describe them to others as KPIs, you’ll have to extract the data from them and create a story to tell.

That story (supported by charts or visuals) might read something like this:

• Our most popular pdf was “Comparing Icebergs to Big Data”.

• The campaign most successful at driving traffic to this pdf was called “Don’t Get Sunk in Oceans of Data”.

• We should devote more resources to our consulting offering about the dangers of mishandling Big Data.

• We should come up with another campaign that calls to mind disaster on the high seas.

Of course I have oversimplified. But decoupling what you want to know from actual reports; and finding reports that answer your business questions is an exercise that, at least until robots replace nearly all of us, can only be made by a human observer exercising some fairly straightforward powers of observation and deduction.