They’re the most sought-after candidate of the 21st century (according to the Harvard Business Review, at least).
The sales scientist.
No lab coats, no Bunsen burners, no graduated cylinders. These are scientists of statistics, trends, and possibilities, wrestling with a problem every data-rich company faces: what does that data mean?
Data scientists fit anywhere in an organization wherein there’s a lot of information and little expertise to interpret it. And in the data-driven and AI-enhanced world of sales enablement tools – sales teams are no exception.
More than 96% of sales leaders consider data critical for their organizations, according to a survey from Domo. Still, 65% say it’s too difficult to get meaningful insights from that data, and more than half feel overwhelmed by the sheer volume of the data they collect.
If you’ve noticed job postings popping up for dedicated sales scientists, this is why. And if you’re asking yourself what kind of value these scientists bring to the table beyond the AI-enabled tools that track and measure sales today, well, there’s more to the story than metrics:
Piecing together the puzzle
With new technology and widespread availability of data, it’s easy to track what’s happening in your sales process with cold, hard facts. But when those numbers live across many different tools and tech, who will put the pieces together? Sales scientists look not only at what’s happening across the board, but why it’s happening, too.
Understanding how data fits with your process
It’s not all about the facts. Context matters, too. As part of your sales team, a data scientist is an interdisciplinary connector who can pair the information gleaned from your reps and the tools they use with the nuances of your business and your sales process.
Picking the right problems
Knowing the inner workings of your sales organization means a sales scientist can not only identify where problems may occur (sometimes before they become problems in the first place), but pinpoint which ones will have the biggest impact, and which ones can wait.
Gaining a competitive edge
Data is commonplace in many organizations. Simply having the tools to collect and compile it isn’t enough anymore. The quality of the insights you gain is now a key differentiator that can set you apart.
But who are these scientists?
Scour the job postings for a sales scientist and you’ll see requirements like a background in science or mathematics, most commonly probability, statistics-based disciplines, and academic research. They probably have a bit of coding background and they know how to use visualization tools to make data come to life.
They build predictive models and work with formulas and equations like L x %LW x %LWC x %OW x %WR x Avg($Deal) to investigate things like how customers flow through your pipeline. (Yes, that’s a real equation used by sales scientists at Baseline to measure and evaluate key conversion points of the sales process – just one of many calculations they do every day.)
They find gaps and test hypotheses. And they make actionable recommendations based on the results to leaders and company stakeholders.
Adopting a scientific approach with your reps
Some sales scientist traits are useful for sales leaders, too. Maybe not the part about the math degree, but certainly the quant-based approach to understanding customers makes a difference.
In media sales, for example, “questions are getting more technical during pitches. It’s hard for traditional salespeople to answer them when on their feet,” writes Christopher Hansen, President of Netmining. When an algorithm is the only thing that sets you apart, “the tech world needs a data-versed seller who can get down in the weeds while making it all seem not so scary.”
And it’s especially true in a world where we partner with computer software to get our jobs done, and where face-to-face interactions are being replaced with digital ones. Now more than ever, sales leaders need to leverage technology in a way that works on a repeatable and testable basis.
That's why Kiite is built to strategically break down knowledge silos and scale subject matter expertise across the organization. The more people on your team that have access to the knowledge they need in an instant, the more seamless these digital interactions will go. When a sales representative needs an immediate answer from in-house counsel, Kiite is the application that makes that transaction happen.
So, does your team need a sales scientist? There’s no silver bullet to making sales successful. Sales scientists (and scientifically-driven salespeople) aren’t a magic cure-all. But given the power of statistics, probabilities, machine learning, and AI, it’s easy to see why there’s so much demand for people who can help sales reps and leaders make sense of the data overload… and answer their most nagging questions.