Over the years I’ve become obsessed with understanding prospects and customers really deeply.  There are bigger sins, I suppose.  “Understanding your audience” is critical to driving effective marketing and sales but is a vague topic.  What does it really mean, exactly?

Last week I gave two speeches on that topic in talk called “Building a Data-Driven Marketing and Sales Machine,” an area of focus for Boundless Markets.  I cited a Bain study which found that companies who excel in their use of analytics are twice as likely to financially outperform their competitors—and 5X likely to make effective decisions.   I also mentioned 1) fourteen different kinds of analytics, 2) some insights that can be gained from each one and 3) how we helped one of our clients achieve double digit revenue growth in two months by leveraging such data.

Here are the fourteen different types of data and a taste of some insights they can provide:

  1. Web analytics. What are your prospects searching for and how does that vary based on audience segment?   What content makes them come back again and again to your web site and convert?  Which pages of your site are most likely to attract visitors…and which pages turn them away?
  2. Third party data. What do your prospects and customers read, what do they purchase and from whom do the buy?
  3. Intent data. Which prospects are in the market to buy right now?  And what content are they reading?
  4. Predictive analytics. What messages and content are likely to move the customer further down the purchase cycle and how does that vary by customer segment?
  5. Multivariate and A/B testing data. What messages, design and offers resonate most and drive results?
  6. Social media analytics. What your customers and prospects are they saying about your company, brands and products?  What are their concerns, likes and dislikes?  Who are the top influencers shaping opinions in your market?
  7. Attitudinal/survey data. How do customers feel about your products?  How likely are they to consider or purchase and which levers can better motivate them?
  8. Best customer modeling. Which prospects have similar characteristics as your best customers?
  9. IP resolution data. What companies visited your web site today and earlier this week?  And where are the people in those companies located?   How does this stack up against your target accounts and VIP customers?
  10. Call tracking data. What times of the day and the week should you staff up your sales reps? What companies called your company in the off hours but did not leave a message?
  11. Semantic phone call analytics. Which sales calls with prospects were missed opportunities that could have resulted in a sale?
  12. Call center analytics. What is the optimal number of times a sales rep should try calling a prospect before moving on to another one? How many calls are not enough – and how many are too much?
  13. CRM analytics. Where exactly in the sales process are you losing prospects?  How much revenue is in the pipeline now?  Which sales reps are most successful at converting prospects into sales?
  14. Conversations with customers. Pretty much anything else…and a darn good starting point.

All of the above can be known if you have the right tools, resources and processes — what I call “data discipline.”  We’re pleased to offer a FREE data assessment tool that can help you understand the “data discipline” of your marketing.  This helpful tool is something you can use yourself or share with others in your company.  And yes, there is a grade at the end.

Check it out.  It’s on us.