As many sports fans know, the book (and later, movie) “Moneyball” tells the story of the Oakland Athletics’ 2002 season - specifically, how the team’s General Manager Billy Beane, saddled with the lowest salary constraint in the Major League Baseball (MLB), took the Oakland A’s to the playoffs by defying baseball’s conventional wisdom and relying on analytics.
While other teams were spending big money on players who could wrack up home runs, Beane and his team found through detailed statistical analysis that the key to winning games wasn’t having a lineup stacked with heavy hitters; it was being able to get players on base.
How can sales teams use a similar approach to bring home those big wins? TTEC’s Kacey Hartung, director of marketing analytics, and Eli Igoy, director of insights and analytics, recently spoke with Customer Strategist Journal Editor-in-Chief Elizabeth Glagowski about the key role analytics should play.
Dig into the details
It can be tempting to look at the big picture - sales that were closed, versus sales that weren’t - and try to draw conclusions from there. But delving deeper into data provides valuable insights, helps flags problems, and make solutions more apparent. Even some of the smallest points of data can have a big impact on a sales team’s success.
“We as sales professionals like to look at the highlight reel. We like to applaud and give kudos to those people that are knocking it out of the park; they’re getting the sales, they’re closing the deals,” says Hartung. “But the details behind [the sales] are really where the nuggets are.”
Analytics offer real-time insights that bigger-picture thinking simply can’t. Data can identify what really made a sale happen, what made a salesperson successful in that particular instance. What is the time of day? The day of the week? The channel used to reach the consumer? Analytics provide numerous data points that, together, give a more complete picture of the sales process.
“We can take those pieces of data and see what is attributing to their successes or failures,” says Hartung. Data gleaned from the successes can help improve failure points elsewhere.
Start at the top
With so much data out there, and so many analytics available, it can be difficult to know where to begin. It’s best to start at the outset of the process - the top of the sales funnel - says Igoy.
Start by looking at the volume and quality of sales leads since, as Igoy puts it, “You’ll never make a sale if there are no customers.”
He adds, “At the very top of the funnel, you need to make sure everything is alright there. If it’s not, you need to figure that out, and that’s where the analysis comes in.”
Examine all the data points that go into the sales funnel and see if any roadblocks emerge that prevent things from moving through that funnel. It’s important to travel down the funnel, stage by stage - like a player rounding each base on the way to home plate - guided by analytics along the way.
Next, identify any leads that are likely to translate into opportunity. For leads that won’t lead to opportunity, analyse data to see why they aren’t bringing opportunities and determine what can be done to mitigate that.
Progress down the funnel, attaching metrics to each state, and identify failure points where the sales team is having trouble along the way. Analytics shouldn’t just be used at the beginning of the process, but rather throughout it, Igoy says.
“That is a very robust way of generating home run after home run after home run,” he says.
