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Are Your Sales Insights Descriptive or Prescriptive?

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RX Blog

The sales acceleration technology market – which encompasses tools dedicated to sales intelligence, data visualization, predictive analytics and more, yet excludes CRMs – is expected to break $30 billion in North America alone by 2017. Keep in mind this is separate from the $36 billion projected by the global CRM market.

With so much money being spent to enhance sales performance and productivity, it’s hard to believe that 65% of sales leaders still say it’s too difficult to get meaningful insights from their data. So what constitutes meaningful sales insights, and what does it take to uncover the type of information that helps sales leaders make smarter, more strategic decisions?

Descriptive Insights

While many sales platforms promise deep insight into sales performance, the reality is that most are actually providing reports that simply describe a company’s sales results. If you want answers to basic questions such as, “what were my total sales last quarter?” or, “how are my reps performing according to plan?” these reports can give you a simple yes or no answer. Unfortunately, there’s not much “insight” to be gleaned from these types of surface-level observations.

Prescriptive Insights

In contrast, next-generation sales platforms not only enable businesses to understand their results, but they also provide in-depth sales insights that prescribe the actions a company can take to achieve a desired outcome. With these types of sales science solutions, you can get answers to complex queries such as, “if I were to move prospects from the Qualified to Proposal stage 3X faster, how much more revenue could I generate quarter over quarter?” Or, “by how many minutes per sales rep do I need to increase my time to first action to meet my forecast?” Answers to questions like these can fundamentally improve the way you do business.

How It’s Done

Chicago-based publisher Guerrero Howe was on a mission to scientifically measure the value of its referrals to determine how its sales reps could most effectively spend their time. “We knew we wanted to show reps a path to working smarter, and that the key was in our data,” said Kyle Evangelista, VP of Sales at Guerrero Howe.

After capturing more than 41 million data points through its all-in-one sales platform, Guerrero Howe turned to the first sales science solution to isolate and codify the key factors, or dimensions, impacting its sales performance. Measuring dimensions like prospect industry and sales rep using a consistent sales formula uncovered actionable, prescriptive sales insights.

Apollo View

The publisher quickly identified profiles of prospects who were providing high quantities of referrals; however, these referred deals represented only a small percentage of total revenue. While these referrals generated significant revenue per deal, the deals were not being closed. After analyzing this information by the dimension of sales rep, Guerrero Howe discovered that the reason for this was rep-related, with some reps closing these specific deals at a much higher rate than others.

“The sales insights we’ve gained allow us to help reps focus their time and efforts toward the most effective channels, as well as pinpoint opportunities to coach reps in areas where they might need additional training and resources,” says Kyle. With a clear understanding of the types of prospects that generate the best referrals, Kyle’s team now knows exactly what to do to more quickly qualify high value prospects. “Rather than focusing on leads that have a low chance of success, our reps can now hone in on the most successful advertisers and grow our relationships with those partners,” says Kyle.

You Can Do It Too

Want to follow in Guerrero Howe’s footsteps and start uncovering prescriptive sales insights? Enroll in our Sales Science Academy to learn how you can start scientifically measuring, analyzing and improving your sales performance.

The post Are Your Sales Insights Descriptive or Prescriptive? appeared first on Base CRM Blog .


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