This is the fourth part in our series on general-purpose BI versus purpose-built BI for sales.
Let's start with a softball: Do you agree that really knowing your deals helps you call your number accurately and make your number consistently?
If not, I'll save you time: skip this post.
But if you agree, you're probably considering tools to help you know what's really going on in your pipeline. Maybe you even went to Dreamforce to check out options. If you did, you saw 10, maybe 20 companies screaming"Predictive Analytics for Sales" on their swag, business cards, or cheap pens. How do you choose?
To cut through the noise, look for the three fundamental capabilities: COLLECT the right info, ANALYZE the data, and make it easy to ACT.
1. Collect High-Quality Data
Almost any tool that you'll consider starts with CRM data. But all of us in sales know that CRM data is notoriously incomplete and inaccurate. Your reps want to be selling, not updating the CRM—and most of the time that's probably fine with you. It's OK, because the real source of truth is your reps' email and calendar. When a tool automatically gathers data from email and calendar, you know exactly how engaged customers are because you know who is in meetings and who replies to emails. And you eliminate manual data entry. Your reps sell, the right system records, and you get instant visibility.
2. Analyze Data
Instant visibility into deal progress and customer engagement is already valuable to have. But insight based on analyzing thousands of your deals is another leap ahead. Advanced data science improves exec and manager intuition. It answers questions like: Which deals are on track and which are at risk? Why? What next action can get us a win this quarter? Once you've experienced data science boosting your deal awareness, giving it up would feel like selling without a phone.
3. Take Action
Insight is a waste unless you take action. BI that's truly designed for sales drives action and makes it fast and easy to take the next step. Adjust the forecast, coach your managers and reps to save a key deal, allocate resources where they'll make a difference, and automatically send alerts to reps on what to do next. The path from insight to action should be a tap, not a pain.
Purpose-built BI for sales means collecting all of the data that matters, analyzing it for meaning and insight, and taking action to call the number or make the number. Any BI for sales tool worth your time should excel at all three. If it doesn't, keep looking.
"Analyze" By Any Other Name: How to Know Machine Learning When You See It
Everyone's talking about machine learning. Is it marketing hype? Only when companies fake it. Machine learning helps your team compete by getting smarter over time. Machine learning learns what actions—at what pace, in what order—lead to wins.
Some products take shortcuts. For example, an app might calculate a forecast by assigning a probability to each deal stage and then simply multiplying the active deals by that probability. (Does this sound like one of your spreadsheets? Didn't it always seem kind of wrong?) A weighted average is a formula. It's a guess. It's not machine learning evaluating the details of individual deals.
Machine Learning Example
Let's consider a super simple example of machine learning—evaluating the strength of a deal in Commit. The deal is two months into a POC (proof of concept) and you need it to make the quarter.
Here's the problem: two years of data on similar deals show that a POC should take ~41 days and—more important—POCs taking 60+ days are less likely to ever close. In this one-factor example, a machine learning system alerts you and your rep that the POC is dragging. So when it's time to forecast, you'll know why that deal in Commit is actually "at risk." And you'll know this early enough to take action, doubling down to bring it in or pushing it out and focusing elsewhere.
Needless to say, most signals aren't so obvious. As a taste, we've found that if a deal size shrinks—but by less than 10%—or if your customer starts looking at competitors, these are signs that you can have more confidence in the win.
This kind of learning is a long way from static weighted averages, right?
It won't surprise you that I believe that Clari towers above everyone else at helping you Collect the right information without manual data entry, Analyze it for brilliant new insight, and take immediate Action. But what you believe is all that matters. Request a demo to let us prove it.
Up next: How to narrow the field to solutions that easily collect all of the data that matters, automatically analyze that data to deliver insight about forecast and more effective selling, and help you act decisively with the right insights at the right time.