Experian QAS’ recent study “Data Quality and the Customer Experience” is a telling story for today’s data-driven marketers. To start off, here are a number of interesting insights culled from the study:
- Less than 1% of organizations surveyed lack a data strategy.
- 66% of respondents use a manual process like Excel to manage data and perform light analysis on that data.
- 1/3 of respondents don’t know how much of their data is inaccurate.
- 94% of respondents realize that some of their data is inaccurate due to incomplete, outdated, or duplicate data.
- 65% of the time, respondents blame these inaccuracies on human error.
So, what kind of picture does that paint of today’s “data-driven” marketer? To me, it looks like organizations overwhelmingly acknowledge that data is critical to their success. A similarly overwhelming number of organizations understand that they, in fact, do have a data quality issue. Yet, for whatever reason, these organizations haven’t invested in the tools needed to rectify that issue.
My suspicion is that marketers haven’t decided to adopt an automated tool for addressing these data issues for a few key reasons:
- The economy may be slowly righting itself, but it’s not anywhere close to full strength. That means budgets are still agonizingly hard-won battles fought in boardrooms across the land.
- This whole idea of big data, as well as its touted benefits, is still rather new and unproven. If the status quo has worked all these years, why not wait until the picture is less murky before making a big investment.
- The sheer number of tools available, and their panoply of features, has heads spinning. While there’s surely a goal or an ideal outcome of their data strategy, marketers may not know which tool will get them to that point.
So, what’s the answer? Marketers would benefit from first identifying the problems in their current processes, and then identify a tool that solves those problems.
If the issue is duplicate data, look for a tool that can de-duplicate databases and then merge that data into a new, unified database. If inaccurate records are plaguing the organization, it makes sense to look for a tool that includes hygiene and validation capabilities. Better yet, find a solution that can collect data right from your lead capture forms, validating and autocorrecting it as it is imported.
If you don’t understand enough about your current customers and inbound leads, look for a platform that provides appending services and enriches your contact database. Take the same approach if your database analytics are lacking. The key is identifying priorities and seeking out a tool that aligns with those priorities.
The trick, though, is not settling for a tool that bottoms out with capabilities that can only solve your current problems. You want a tool that’s going to allow you to continue to grow as a data-driven organization. Think about how you see your marketing evolving over the next one to two years, and move towards a tool that aligns with that vision. Once you can nail down these two areas of your data strategy, choosing the right tool should be much easier.