Do You Know What Your Data is Trying to Tell You?

“Facts are stubborn things — but statistics are pliable” – Mark Twain

Every day a new data set—new studies with statistics about America’s consumption habits, our prescription pill intake, the amount of garbage we produce. Each of these studies includes useful facts, but it’s what you do with them that matters. Useful facts, wrongly interpreted, become at best a misstep and at worst a manipulation. Data is useful, reliable, and actionable only when analyzed in the context of a particular situation or business challenge.

Marketers are often tasked with analytics and reporting tasks despite not being trained in data analysis. It’s easy to think that because we have access to endless streams of data (social media comments, Google Analytics, survey results, etc), we should all be data experts. That would be great, but it’s not that simple. Information ≠ Insight.

Common Pitfalls of DIY Data Interpretation

Here are some of the most common mistakes we’ve seen companies make with DIY data analysis.

Focusing on the Wrong Data

It’s easy to get overwhelmed with the sheer volume of information we have at our fingertips these days. Clickthrough rates, abandoned shopping carts, page views, focus group interviews—the list goes on.

We always start with a precise objective for what we’re trying to learn through research. This focus allows us to ignore data we don’t need and hone in on what’s truly important. Sure, the number of likes you get on your Instagram feed is a fun statistic to look at, but will it really help you meet your quarterly sales goals? Maybe, if it fits within your defined research objective.

Every good market research project begins with a clear objective. Without one, you’ll easily drown in data overload, which isn’t going to help you arrive at any meaningful insights.

Failing to Read Between the Lines

Numbers on a page or comments from consumers can only say so much. In our experience, it’s not what they say, it’s what they don’t say. If the data tells you that one Facebook ad is performing 20% better than another, does that mean that consumers prefer one design over the other? Or, perhaps it’s the headline that hooks your readers. Often, we can pinpoint the what behind the numbers, but the why can be harder to analyze.

When people leave comments on social media or write reviews of your products, are you skilled enough to read between the lines and pick out the recurring themes? What do all those interviews from your focus group really mean? If you are able to translate qualitative feedback into actionable items for your next round of marketing or product development–that’s great! Otherwise, you may need the help of professional data analysts.

Looking at the Data Without Context

For data to yield truly valuable insights, you have to consider the context of your competition and current market conditions. For example, the COVID-19 outbreak has forced market researchers to reevaluate previous existing data in the context of widespread stay-at-home orders in the U.S. and globally.

What were consumer habits like prior to the outbreak, and how have consumers responded since? Most companies have experienced the need to alter their marketing message in light of the “new normal” in which we now live.

You should also consider how your brand’s performance compares to top competitors. Will you position yourself as better or different than your competitors, or ignore them completely? Will your marketing strategy change if theirs does?

Data analysis, when done effectively, looks more like an art than a science. A qualified research partner can help you read between the lines, ask the right questions, and understand how your brand fits into the bigger picture.