You’re probably familiar with the phrase “garbage in, garbage out” (GIGO). In the software development world, GIGO means that no matter how meticulous a program’s logic is, if you enter in garbage data, you’re going to end up with garbage results.
It gets even worse if you’re the sales exec who’s responsible for developing an accurate sales forecast with bad data as your input. At that point, you’d have better luck consulting a crystal ball than relying upon your system’s output for any meaningful sales insights.
Garbage Data In –> Low Sales Out
It’s a given that list vendors can’t guarantee 100% accuracy. The best vendors strive to keep their lists updated, proactively searching for new data and revising their lists frequently. But just how much does this data quality affect your sales reps’ ability to do their jobs?
In one study that analyzed information from over 20,000 sales phone calls, two groups of in-house sales reps were given different lists to work from. One sales group’s list had a high data accuracy of 91%. The other group worked with a list that had data accuracy of only 67%.
Guess who won the contest? Not surprisingly, the sales reps who started out with the better input ended up with better results. The 91% accuracy group achieved a live conversation with a prospect after four touches on average. The group working with the inaccurate data list took an average of 10 touches to get a live conversation.
The sales reps working with the 91% accurate data continued to lead the sales race when it came to the lead to conversion rate. It took only five touches average for them to convert their lead to an opportunity, compared with the eight touches average for the 67% data accuracy group.
The takeaway is that sales teams working with quality data get to their target prospects quicker, which not only enables an efficient sales process but is crucial to ensuring the reps make the most of their time.
Tools that Take the Guesswork Out of Sales Forecasting
Poor quality data not only affects your sales reps’ ability to close sales, but it can wind its way through your sales processes, affecting your ability to make reliable forecasts. The good news is there are several technology strategies you can employ to improve the situation.
Implementing a sales acceleration tool will help your reps fix inaccurate data on-the-fly as they interact with customers. A CPQ solution (Configure-Price-Quote) that enables your reps to use web analytics and built-in tracking allow for instant customer engagement feedback to accompany proposals.
CPQ provides quality data and immediate insights, enabling your sales team to respond quickly to your prospect’s needs. This real-time, interactive collaboration between sales reps and customers is part of the next big evolution in sales.
Another important part of this evolution is the continued need to encourage sales reps to take ownership in fighting the “garbage in, garbage out” data problem.
Reps need to understand that each conversation with a prospect or customer is more than just another opportunity to confirm basic contact information. It’s also a critical opportunity to record in detail a wide range of valuable data—such as the prospect’s current needs, anticipated future needs and pain points.
Given a CPQ solution that enables reps to easily document, organize and share this data, each member of your sales team can become a powerful weapon in replacing bad data with good data—which, as we’ve seen, can be a very good thing for improving forecasts and increasing sales.
Put simply, to excel in a dynamic and evolving competitive environment, you need data in your sales forecast and you need data to realize or beat that forecast. Ask yourself: Is your operation data-optimized?
