My Analytics Are Better Than Yours: A Dashboard Confessional

As a Sales Engineer at ClearSlide, one of my main jobs is to assist people in integrating their CRM systems with our tool. One of the main advantages of using ClearSlide is that you get this awesome unique dataset that can be put into lots of cool visualizations and give you better insights about your sales process… but over the course of speaking to hundreds of Salesforce administrators and sales operations professionals, I slowly came to a startling realization: Although almost everyone who has implemented Salesforce has awesome, actionable data filling up this great relational database, very few of them are accessing it, processing it, or using it in effective ways. This realization was the beginning of a several-month journey, wherein I would delve into the depths of Salesforce apex and formulas to figure out how to get the most out of the CRM.

The first thing that I learned is that it’s surprisingly difficult for a layperson to get the data out the way that they want. Over time, however, I figured out how to leverage custom fields, triggers, and formulas to attain the full power of the reporting and dashboarding capabilities within Salesforce. Salesforce actually has a pretty limited default data set. There are TONS of fields, but the ones that you really want won’t be there. The platform is customizable and they expect you to build customizations in order to get the insights you’re looking for.

Here’s an example: I spoke with some sales leaders internally and at other companies to see what sort of data they were missing. One thing that I heard was that they wanted to know how much pipeline they were building and how quickly they were progressing through the stages in a deal. I checked out what sort of reporting I could do within Salesforce to assist with this, and I found out that activities actually don’t store the opportunity stage at the time the activity took place. This means that you can’t really get this information! That’s where the trigger comes in. We just build a simple trigger which fires whenever you insert a task, and it grabs the opportunity stage and sticks it in a custom field. Now we have a few really cool things we can do: We can report on activities with opportunities and see how opportunities are moving through the stages, or we can report on activities by rep and see who is building their pipeline and who is not. This gives us insight into how deals are moving along, and it also tells us which members of our team are building for next quarter and which ones might be planning to leave.
One of the things that our founders realized when looking through ClearSlide data is a strong correlation between engagement and deal closure. This is contrary to how most sales teams are goaled, which is usually on the basis of activity levels: more emails sent, more outbound dials, higher attainment. In reality, those metrics have almost no correlation with won opportunities. I wanted to capture time spent on the phone with the rep, and I wanted to be able to separate it out by opportunity. Again, this second piece of information wasn’t quite reportable using the default Salesforce configuration, but by rolling call duration up from the activities to the opportunity level, I was able to stack rank all opportunities in the pipeline by engagement time. This ended up telling a really interesting story: Your typical company had 20 deals in their pipeline at 75% to close with vastly different engagement stats. One has 600 minutes of engagement, nearly 6 hours spent talking back and forth with your rep. Another has 25 minutes of engagement. Which one is really going to close this quarter? Same story at less than 25%, but here’s what’s concerning: Why have you spent 200 minutes talking to a deal at 20% to close? Is your forecast wrong, or are your reps just wasting their time?

These are just a few ways to dice up the data that is being synced into your Salesforce environment. The possibilities are almost limitless with some clever implementation of triggers and formulas. Everyone is going to need something different; what I really wanted to do with this project was get people thinking about interesting things they could do with the data they have. So, are my analytics better than yours? What are you going to do about it?
Written By: Gabe Abinante, Sales & Support Engineer