Foundations of Data-driven Selling: Collect

What’s Data? What can it do for Sales? I believe that data has the potential to transform a sales organization. Traditionally, sales teams have relied heavily on intuition, instincts, experience, and trust. This approach has its advantages but also its limitations — and I think we can agree that it is not the future. In this three-part blog series, I will talk about how you can create a data-driven sales organization by collecting the right data, performing the right analysis and executing the right actions.

Let’s start with data collection:

You’ve heard it a million times: garbage in, garbage out. To make the right selling decisions, you need high quality data from the field. But data collection is tedious, so the quality of your data suffers. With poor data quality, tracking a pipeline can be like driving across the Golden Gate Bridge on a foggy morning — its all guesswork. One week the pipeline is strong, the next week panic has set in as it looks like you might miss the number, followed the next week by claims, “It’s OK, we’re good.” — a total guessing game that is super stressful. Despite systems like CRM and spreadsheets, you’re still driving through the fog.

Sales remains a black box.

And human nature doesn't help. Ever known a salesperson who doesn’t “manage” their pipeline? They don’t report on some potential opportunities, underreport on others, and — on occasion — are overly optimistic as they try to manage how their leaders perceive their pipelines. This complicates the job of today's sales leader. How do they manage this lack of visibility (i.e. lack of data)? They're forced to add layers of managerial oversight, daily reporting, frequent account and pipeline reviews — micromanaging the whole process.

As a sales manager, you need to know what’s happening in your top "make or break" deals. Yes, the CRM should have that info, but we all know that it's an out-of-date record of what reps remember — or have time — to enter. And, the painful push to get reps to update the CRM leaves reps less time to sell. Our CEO’s most recent post on why analyzing CRM isn’t enough outlines the challenges from a sales manager's perspective. 

Fortunately, there's a solution that delivers what execs and managers need — full visibility into both rep and customer activity — by collecting data from mail and calendar systems, with zero burden on the sales teams.

Combining rep and customer activity data with CRM data, delivers a staggeringly accurate real-time picture of deal status. And even more incredible is what happens when you use machine learning (aka predictive analytics) to translate that data into which deals will close and which are at risk and need management attention.   

All this adds up to new pipeline insights and more accurate forecasts. In my next post, I’ll talk about exactly what you can analyze when you switch to "treasure in, treasure out."

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