Data Integrity: Actionable Analytics Fundamentals

Across all analytical marketing specializations, data integrity is guarded and protected like money in a vault. A major advantage of web analytics over traditional market research methods is the ability to collect and analyze alldata, not just sample data. But what happens when web analytics fails to collect all data?

The Asterisk: An ambiguous enemy

During the X Change show this past August, I had the chance to talk to many analytics pros who work in the trenches every day. One story in particular caught my attention.

This analyst was a very successful consultant for a major web analytics vendor for several years. He recently landed a new position working for a rapidly growing SaaS company. One of the first times he sat through a presentation from his team to the executives, he noticed asterisks on several slides. After the presentation, he asked the team about the asterisks, and they told him that some of the data contained anomalies, and the asterisks were placed in the presentation to caveat some of the hypothesis.  I can imagine how disappointing it was for this analyst to see asterisks up on the projection screen, watering down the data.

Welcome to the Real World

I think we’ve all experienced this sort of disappointment. It’s like learning that Santa Claus isn’t real; it’s innocence lost; the kind stuff that makes nice people become bitter, cynical, and jaded. It’s having your data underminedwith an asterisk because somebody else messed up!

The good news is with some process improvement, gaps in data can be prevented, and every analyst can be confident about the recommendations they present. But how?

The problem is that web analytics aren’t front and center in requirements or processes in many companies.  All too often, the analyst is left out of the conversation. When that happens, who is looking out for the data? It isn’t the content team, it’s not the director of marketing, and it definitely isn’t IT. How can an organization make data-driven decisions without knowing all the data is collected correctly?

The fact is, when the right JS isn’t on the most important pages, your organization will never get the data it needs just to stay in the game. A recent Forrester study even indicated that 45% of analytics customers worry about accurate collection of data.

How do you know when you’re missing data? Sometimes, you will see skewed or missing data in your analytics suite. But I’ve found that too often, some data isn’t being collected, and it’s nearly impossible to tell it isn’t being collected! It’s the classic case of the unknown unknown. Even if data is flowing, it is useless if the JS isn’t configured correctly (custom variables not populating, for example). The result: an asterisk on your PowerPoint slide and ammo for management to shoot your hypothesis down.

Bottom line: tracking down individual data collection problems, each on individual pages, without any real enterprise-level tools, in an environment where you don’t know what you don’t know, is like trying to find a needle in a haystack, on the hot side of Mars with an FAO Schwartz telescope. Absurd!

Improving data through planning and process

The adoption of some simple practices can go a long way toward improving your data. The assistance of a few purpose-built tools can actually provethat the data collected is complete; ergo valid and actionable. Personally, I’m a fan of this three-pronged approach: Development QA, Quarterly Audits, and Continuous Monitoring. Here’s how it works:

Development QA

1. After pages are built in dev, use a tool to audit the analytics implementation on each page.
2. After the pages move to staging servers, all pages should get a complete “pre-flight test”. The auditing tool should be run in live mode, allowing server calls to be made. The success of these server calls should be checked in the analytics solution.
3. Audit new pages after they are pushed out to production to ensure the implementation is still intact and ready for prime time.

Quarterly Auditing

Every page over the entire site should be audited quarterly to confirm analytics are working correctly, to identify any problems, and to show complete implementation for reporting purposes. Specific items to watch for are:

1. All pages are tagged
2. Pixels are loading
3. Custom variables are populating with correct data

Continuous Monitoring

Landing pages, checkout process, unsubscribe forms, and other mission-critical pages or multi-step processes should be continuously monitored to ensure the pixels always fire. This prevents long periods of data loss.

Truly, this is why I co-founded ObservePoint: to give you the tools you need to increase data integrity, get traction in your organization, and relieve the frustrations inherent in the craft.

Outcomes

With some forethought and the right tools, you can make huge strides toward ousting the asterisk. Processes, such as I’ve discussed here, can remove much of the ambiguity and doubt in analytics data. By confiscatingthe weapons that management uses against analytics recommendations, you can help your organization make use of the insights you find. You’ll valuate Web Analytics to management, and gain funding for new initiatives.

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