3 Reasons Data Pollution Is On the Rise and What You Can Do About It

I want to talk about an issue that’s become increasingly prevalent in the last few years; one that is often an afterthought, only realized once it’s too late: data pollution.

We often talk about needing clean data, which may be an even more pervasive buzzword than big data (although not as sexy). Clean data is something we focus on during audit and implementation work, yet often forget until it’s too late.

Working as a digital agency analyst the past few years, I’ve had the privilege to work with dozens of clients ranging from huge global corporations to family businesses with a handful of employees. While there are certainly a multitude of differences, the one common trait I see time and time again is polluted data.

Here are three reasons I believe data pollution is on the rise, and some ideas on where to start to keep your data clean:

1. Innovation

The digital analytics space is evolving rapidly. New tracking and targeting functionality is constantly being added to analytics tools. The methods by which we track things like campaign performance and user engagement are frequently changed, as well. For most organizations, this innovation is hard to keep up with.

Starting Solution: Documentation

I know, I know. I used a dirty word. Documentation is boring, uneventful, and there are dozens of other things you would rather be doing. But keeping good documentation on the tracking methods you have deployed will help you out when someone in your organization needs to know how something is tracked, or why something was deployed a certain way. And with the number of tags being placed on sites on the rise, losing track of what tags go where and what each one is actually tracking is an increasing problem.

For help selling this in your organization, try to avoid the term ‘documentation.’ Instead, I like to use the term ‘analytics standards/guidelines.’ People are used to working within brand standards/guidelines. Getting members of your team to think of it this way is usually a little easier than a broad term like documentation.

Include in your analytics standards things like what the tags are, what the tags do, when they should fire, when they shouldn’t fire, how they should be deployed, etc. If you’re really serious about keeping your data clean, reach out to a data/analytics consulting firm that has experience in this, or build an internal team whose job is to constantly monitor your organization’s data creation and usage. It will be an investment, but well worth it in the long term.

2. Easy Access to Tagging

Tag management systems are becoming widely adopted and with many of the barriers to entry being removed, such as cost and ease of use, the adoption of this technology is likely to continue. Don’t get me wrong, I think this is a great thing; however, we still need to be cognizant of what exactly our organizations are doing within these tools. Similar to the emergence and adoption of content management systems, tag management systems are tools that are tremendously valuable, but also need to be governed by the right people.

Starting Solution: Tool Governance

Make sure that someone is accountable for maintaining these systems and continuing the act of documentation/analytics standards, and staff it appropriately. A great resource would be someone that understands the business needs for various tags and tracking snippets, but also has enough technical knowledge to think through how the deployment of various tags may affect your site. Other helpful resources include analytics consulting forms that have experience with your chosen tool, and can help train internal members on its proper usage.

3. We’re In High Demand

Analytics practitioners, that is. As I mentioned previously, the digital analytics space is constantly evolving, meaning the needs of practitioners in the space are constantly changing as well. Good analysts and implementation specialists who stay on top of these changes and continue to solve business problems using current analytics technologies can really write their own ticket on where they want to continue their career. This means as the industry continues to grow, turnover and churn in analytics departments likely will, as well.

Starting Solution: Training, Challenging Work, and Documentation

A common trait I see among good analytics practitioners is curiosity. We want to know why things behave a certain way and how they interact with other things or systems. We are also used to learning, constantly. When boredom or complacency begins to set in, those emails from recruiters get much more interesting.

However, even with great training and work that excites the mind, most analysts aren’t going to stay with one organization for their entire career. Be ready for that transition with proper documentation and constantly updated analytics guidelines. This way, when one of your key members does leave, you’re not left wondering how or why things are tracked the way they are.

These measures definitely won’t solve all of your problems, but are a good place to start buttoning things up.

Now, what are your thoughts? I’d love to hear your feedback.