Do you approach data analytics with the same enthusiasm as a big pile of leafy vegetables? You know you need to consume more of it, but, man, that steak, fries, or big piece of chocolate cake just seem so much more appealing.
Recently I asked Forrester webinar listeners (mostly marketing folks) to rate how they approached data analytics. It's a small sample, I know, but bear with me for a second.
Of the 16 people responding to the poll, six said that they were somewhat effective, and nine said that they were not effective or didn't use data analytics at all (the figure here shows the actual results). Taken together, that's more than 90%.
I found this fascinating because, just about a year ago, I teamed up with ITSMA and VisionEdge Marketing to explore the state of marketing’s performance management. While quizzing participants about reporting and dashboards, we slipped in a question or two about data analytic effectiveness, and the distribution of responses in 2013 are similar to this poll: Only 10% of those surveyed gave themselves a “thumbs up” for data analytic proficiency. What’s going on here? Do marketers really approach data with the same gusto as a large plate of kale?
Embracing big data is a topic I have written about recently (subscription required) and will talk about more at Forrester’s Forum For Marketing Leaders, happening May 13th and 14th in London. I’m taking the trip across the pond to help B2B marketers face their big data destiny and see analytics, not as a data quality and technology problem, but as the way to transition their teams from list managers and campaigners to custodians of customer insight.
Like a new diet or exercise regime, starting is often the hardest part. But now is the time for B2B marketers to put data to work. To make the task more manageable, dig into your existing data and follow these three key practices:
- Analyze your “best” customers. Talk with sales and product teams to uncover what distinguishes your most valuable accounts. Who was involved in the decision-making process, how did their influence change at various stages in the journey, what information did they rely on, and where did they go to get it? Validate the answers you come up with against existing customer data to uncover nonobvious insights and clues that may not show up in the first round of discussion. (It also helps you test whether your teams rely on facts or assumptions when assessing what makes customers valuable.)
- Apply insights to accelerate sales. Use what you learn to identify strong complementary offers and to arm sales with information that grabs buyer attention. Analytics can help marketers understand which individuals matter in the accounts that fit the pattern of their better customers, what content to deliver to engage them with the information they want and need, and how to apply this insight to creating a more informed marketing mix.
- Use data analytics to predict where to go next. Understanding how buyers buy helps marketers figure out how and where to intercept decision-makers as they explore solutions — especially when they are early in the problem definition and solution exploration phases. Use analytics to help sift through undifferentiated top-of-the-funnel activity to spot and cultivate new leads as well as look for new business opportunities (perhaps in an unexplored industry?) to pursue.
So, c’mon folks. Take a big bite of your data analytic spinach. You’ll find out that it not only is good for you but also will make you feel better about your marketing.