Finding and using the right statistics in marketing

By Laura Lambeth   |   August 4, 2017

As marketers, we are always searching for the latest statistics on various issues. For us, it usually centers around the technology world. Data security, BYOD challenges, the prevalence of cloud application usage, and the list goes on.

As an agency team, we had the pleasure of helping prepare the 2017 IBM X-Force Threat Intelligence Index for publication to a global audience. It was a thrilling experience, as the data that’s compiled each year has been gleaned from world–renowned researchers. And it’s full of statistics based on respondent answers from around the world, data that IBM itself has collected from clients, and global security events.

The great thing about this report is that it meets all the standards that we as marketers should always be looking for when mining for statistics. More on this in a bit.

Why you need them

Statistics can make your points more credible. In marketing, the ultimate goal is usually to sell. Sometimes it’s just to increase visibility or reinforce your brand, but usually it’s to convince people in buying positions that they should purchase your product or service—that they need it. But it’s easy to overlook that this need has to be proven. Especially for a savvy, skeptical audience, “because I said so” just isn’t good enough.

Statistics help to prove to a decision-maker that the claims you are making—”people who go into public establishments expect to have WiFi accessibility”—are real, because there is verifiable evidence of the statement as fact. Far more credible, powerful, and concrete to say “83% of consumers are more likely to visit an establishment where WiFi is publicly available.”

How to find them and what to look for

A simple online search might reveal hundreds or possibly thousands of sources for relevant-sounding data. But ask yourself, who did the gathering? In our case, valid sources include proven and trusted organizations that have been publishing studies for decades, like the Ponemon Institute, and industry analysts such as IDC, Gartner and Forrester. (And, of course, IBM research.)

What to look for in a study:

  • A large respondent pool
  • A clearly outlined methodology
  • Transparency about respondents’ roles in their organizations (establishing their qualifications to answer the questions)
  • Consistently repeated or updated studies (which helps to compare year-over-year data, track percentage increases or decreases, and define patterns of change that bring new light to trends)
  • Respondents that align as peer groups to your target audiences (which underscores the credibility of your data). People are naturally more inclined to put stock into responses from someone who faces similar challenges and requirements within their organization.

What to avoid

Old statistics. It’s disappointing when we find a statistic that underscores the exact point we are trying to make—only to find that it comes from research reported five years ago. Generally speaking, if the data is more than a year old, it’s considered outdated. Definitely stay away if the data is more than two years old. Why? Because things change. Chances are, the data is no longer valid. This is nowhere more true than in the technology world; even if the old data is still accurate, its context has probably shifted.

Studies conducted by small or obscure organizations. Again, proven and trusted organizations are key for credibility. Small organizations may be trustworthy and accurate, but may inspire justified skepticism.

Small (or undisclosed!) sample sizes. Anyone can commission a study or conduct one on their own. But when drawing conclusions, it’s important to know that enough responses were obtained to make a valid case. The study may have been opened to 1000 global respondents, but if only 75 of them answered the questions, the data is simply not as strong. Sometimes the best numbers are small, though—responsible sources are upfront about absolute numbers as well as relative ones.

Go forth and prove your point

Finding good, solid, recent data to lend credibility to a point can be time-consuming. To save research time down the road, start making a list of the sources you consider credible, and proactively gather data as it is released. Updates to previous studies are especially valuable, to help you put numbers in context. Know ahead of time if you will need to ask permission to cite the data in your marketing content, as is sometimes the case. Finding good data takes effort, but in marketing, it’s usually worth it.


About the author

Laura Lambeth, Technology Writer at DeLaune & Associates, has been writing for B2B clients for nearly 20 years. She gets giddy when she finds good data.

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