Data is Great, But the Value is in the Insights

Retailers use purchase data to estimate a pregnant woman’s due date and target relevant advertising accordingly. According to McKinsey & Company, Google used insights from big data to modify the font color in its ads, boosting click-throughs and increasing revenue by $200 million. B2B marketers identify spending (and gap) patterns by county to boost statewide demand generation.

We all have aggressive business goals to reach, and limited resources. That’s why it’s vital that any conversation around marketing analytics focus on the insights that we glean, not just the data that we analyze. We know that data – big or otherwise – can produce insights that drive business growth. Tools and technology are important, but even more so are leadership commitment, talent and strategic focus. The “why” we do this is because of the business insights.

All the great technology and analytic models in the world will not grow the business if we are measuring things that don’t matter or are not actionable.

It’s sort of shocking to see how often that point is missed in all the activity and investment in marketing analytics. I’ve had several opportunities in the past month to discuss how “big data” is being tapped to improve market share and drive growth. The strategies and practical applications of the analytics insights that are working best are those that focus on clearly defined business objectives, rather than on the size or scale of data.

Here are a few of the ways marketing analytics is being used in a “big data” world:

  1. A multi-property publisher told me that from a planning standpoint, he’s not interested in what will change in the next five years. “Show me what will stay the same, and I can build an analytics strategy around that.”
  2. A B2B marketer in the insurance business defined sales markets with tight granularity. Each “micromarket” was a 25-mile radius around a sales rep. This gave the marketing team the chance to use limited resources more effectively to pursue the best opportunities with the most qualified and likely-to-close prospects.
  3. A digital media company boosted ad sales by identifying opportunities outside of existing customers. While current buyers are important and must be nurtured, the analytics focused on identifying profiles of companies that would benefit from actual subscriber/reader activity and interests. That laser focus on matching ad buyers with readers resulted in a reduced sales-to-close cycle and the increased competition for reader attention generated a greater share of wallet from significant segments of advertisers. 
  4. An enterprise software company focused on variances across sales territories to prioritize around pockets of potential growth. Using market data and sales feedback, they were able to identify geographic areas that had the most growth potential. While no territory was neglected, focus on those areas that had bigger opportunity resulted in a more than 30 percent increase in sales productivity and conversion of marketing qualified leads (MQL) to close.

There are three big lessons for marketers to take away from these examples. First, what you decide not to do is just as important as what you do. The discipline of focusing on the right business drivers is a very difficult thing to achieve and get right. It usually takes deliberate collaboration between the analytics, operations, privacy/governance and marketing strategy teams.

Second, getting insights to the front line is essential to success. Having data-driven intelligence back at headquarters is great, but if you have sales, community and marketing people interacting with customers and prospects, you have to get those insights out to the people who can use and test them. These kinds of insights should be predictive and forward-thinking, not just reports on what has happened already.

Finally, all of your insights must be customer-centric; what will work for customers and prospects, not what will promote the team’s favorite product attributes.

What are you doing to ensure marketing analytics insights are applied to the business? Please share in the comments section below.

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