Klearly Visualizes Your Sales and Marketing Teams’ Contributions to the Company’s Revenue

After more than 20 years leading marketing and sales teams at companies of all types and sizes, Alex Krawchick realized a secret: many of those teams didn’t actually know how they were generating revenue.

“I have seen dozens of CMOs come and go because they cannot prove their teams’ contributions to revenue,” Krawchick tells Hypepotamus, pointing out that companies still see marketing as pure loss while perceiving sales as purely profit.

“They don’t actually have the insights to be able to sit at the executive table and say how they’re contributing to revenue, and most importantly, how they can help the company grow.” 

The frustration at this lack of insight led Krawchick to pursue a master’s degree in predictive analytics. He felt he needed to know exactly why certain sales and marketing activities were likelier to win over customers than others.

Krawchick says, “I couldn’t look at myself in the mirror in terms of being intellectually honest and saying ‘why are we crushing it?’ What’s happening? And that’s why I went back to school.” 

After working for so many “data-rich, information-poor” companies over the course of his career, he wanted to figure out how to harness that data to help sales and marketing teams know, for sure, how they’re contributing. 

Alex Krawchick of Klearly

He founded Durham-based startup Klearly to leverage machine learning and historical data to pinpoint what marketing strategies have the greatest impact on revenue.

Klearly combats what Krawchick calls “spray and pray,” a practice popular in sales and marketing typified by using certain tools without being sure they will result in revenue.

Krawchick says that his teams had used a variety of sales and marketing tools including email, sales calls, trade shows, white papers, blog posts, and more, without a strategy behind which one was most effective.

The platform examines all historical customer interaction data influenced by sales and marketing activities, identifies patterns, and makes recommendations for next steps based on patterns. 

For example, Klearly can use years of data to tell that marketing team that publishing a certain white paper or blog post may give them a 30 percent chance to close a sale, then recommend the use of another activity, like producing a webinar, that may increase that probability.

“This is data that we can exploit to help companies become more sophisticated,” Krawchick says. 

Klearly’s product will complete a beta phase within the next three months to be available to the public due to outsized customer demand. “We need to get this into the customers’ hands and get feedback as quickly as possible,” Krawchick says. 

Klearly also plans to use a recent $1.3 million investment led by IDEA Fund Partners to increase headcount by 200 percent and finalize a new headquarters in North Carolina.