The Big Missing Piece of Sales Analytics

March 02, 2016 | Joe Gustafson
The Big Missing Piece of Sales Analytics

You’ve read the statistics around reps not hitting their quotas. You’ve also likely seen firsthand the inefficiencies in determining the tactics that produce wins. Why the high degree of difficulty and failure? Because sales analytics has a black hole. And as B2B sales continue to become more data-driven, filling that hole could yield significant improvements in sales productivity.

That missing piece is conversation data, the information that defines the very heart of a sales transaction. Let’s think about it as one of three major areas of sales data-tracking:

The first is the marketing profile. Companies track this today with fairly sophisticated levels of marketing analytics – in fact, it’s where most analytics advances have been made. Another is the overall sales transaction data. At its most basic, this consists of reps importing data into their CRM to track the activity of a transaction, so we have that information at hand.

What Did You Talk About?

But what’s going on during the actual selling interaction? That’s the missing element. We don’t know what’s transpiring between seller and buyer, the conversations inspiring a purchase. If sales teams could track and analyze that data, they could greatly improve their ability to say, “If we do this, at this time, we have a better chance of closing the deal.”

This is the leap from descriptive analytics to predictive analysis. And that’s where sales organizations get a firmer grasp of outcomes.

The shift to more data-driven selling is a trend others have recognized, as well. Salesforce, for example, is making a clear investment in predictive analysis and machine learning, recently acquiring startup PredictionIO, which follows their acquisitions of intelligence software companies RelateIQ and Tempo AI.

Where’s This All Heading?

There is some incredible potential in the predictive analysis of sales conversations, especially as machine learning technology continues to evolve and analyze things like voice inflection from recorded phone calls.

We already know the “who” – that’s the marketing profile. We already know the “what,” in terms of what interests a prospect. What we’re missing – and what must become an essential aspect of the selling cycle – is the “how”: How is the sales interaction developing? What are reps saying, sharing, and doing? What are their presenting styles?

When you have this information, you have an enormous leg up on being able to predict what works. But let’s not overlook an important item: Any technology or new learning system is only as valuable as its data. Once you amass the data, and have efficient ways to import into your system, two things must happen: 1) The data must inform your sales process quickly, and 2) You must do smart things with it.

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