The Gig Economy Group, Inc. announced its partnership with Kineviz, the maker of GraphXR, a visual analytics platform that delivers unprecedented speed, power, and fluidity to anyone working with connected, high-dimensional big data — providing a line of sight to millions of sales interactions in real-time.
“In-person selling is no longer available to those who are focused on keeping sales going during these tough times. This requires sales and businesses to pivot and adapt to new “work-from-home” techniques,” says Dave Toole, CEO of The Gig Economy Group. “Moving from ad hoc coordination to repeatable processes is critical.”
Remote selling is new to big as well as small businesses, including contractors like real estate agents, life insurance people, distributors, sellers, etc. Getting up to speed and getting to best-in-class performance will determine who wins in this new economy.
A case in point: One of The Gig Economy Group’s customers found that as a direct result of implementing the GEG app, the first dollar sold in the first 30 days went from 5% of new remote workers to 22%. They also found a remarkable decrease in churn.
Advancing the skills and results of remote workers will be vital as companies adjust to the new challenges and realities of a business environment dramatically changed by COVID-19.
Data from the GEG app is stored in a Neo4j database and visualized in Kineviz’s GraphXR. The graph data model provides insights from the GEG app. It shows how a new seller (dot in the middle) using the GEG Platform has been effectively onboarded and provided best-in-class training, coaching, and mentoring to always have 10 fresh contacts that they are continually communicating with (teal dots). The platform delivers best practices messaging, content, and approaches unique to each contact. This personalized content is delivered by the app at the right time and guides the seller to impart the most salient information to move their prospects/customers down the funnel to close (orange dots)—bringing the remote worker to best in class performance in real-time.