The average sales team member is phenomenal at closing deals with one specific demographic, sometimes two. But most of the time, there are several other demographic groups that this sales representative does not close regularly. By using our Think Lead Optimizer (TLO), Think Unlimited has the ability to score & categorize not only your leads, but also your sales team.
Custom-Built Internal Benchmarks
Contrary to the standard model of comparing internal data to industry benchmarks, TLO takes the last 12 months of your company’s sales data to learn about the habits of individuals on your sales team & previous customers’ purchasing patterns. After enriching the historical set of your company’s lead data, Think Unlimited sets your previous year’s sales as your internal baseline and creates a custom-built algorithm. Once the algorithm is built and tested, our team outputs your custom lead scoring model through the TLO platform. The platform continues to learn through artificial intelligence and self-trains to provide you with real-time data, which includes projected project cost.
Typical industry benchmarks assign a numerical or alphabetical value to a lead which correlates to a specific range of revenue. For example, if Mark comes through the pipeline as a “3”, he could have a project cost ranging from $2,000 – $3,500. Additionally, industry benchmarks are typically founded on local data analysis, but does not consider that some customers may be worth $3,000 to one company and $5,000 to another. These numbers also do not reflect how or why people buy. TLO compares incoming leads to your company’s benchmark data, based on your unique internal trends and project costs, and creates projections accordingly. With our system, Mark will qualify as a $3,459 lead and suggests the best potential sales representative to close Mark.
Assigning the Best Sales Representative
Traditional CRMs and lead qualifying softwares assign your next available sales rep in the order the lead is received. The Think Lead Optimizer uses deep AI learning to qualify the lead, and lists the most qualified sales associates with the highest probability of closure in descending order.
In the initial enrichment process, previous leads are qualified, as are close rates and project costs by each sales team member. Our algorithm finds the patterns of each sales rep and compares them to the incoming leads to determine which match has the most potential.
For example, take two sales reps: Frank, a married, 50-year-old man who’s been in the industry for 25 years, and Chris, a 30-year-old single man who’s been in the industry for 5 years. On paper, they may have similar close rates but Frank’s average sale is $5,798 and Chris’ is $3,607.
Traditional models would lead a company to assign Frank due to his higher value sales, or assign to the next available representative. By using TLO, your sales team members will be analyzed by deep ai learning for demographic & economic indicators, past close rates, & average project costs. The algorithm will maximize your sales by suggesting that, based on both the lead & sales rep indicators, Chris is best suited as the sales rep to close Mark for this particular project request.
The learning process of our system is ongoing to continue to optimize your sales by analyzing the close rates of your sales team and their assigned leads. If your company’s sales team begins to implement new changes or if your company adds a new lead source, you can rest assured that the Think Lead Optimizer will learn and adjust to match the sales rep with the highest probability to close with each individual lead.
If you want to learn more about our Think Lead Optimizer, reach out to us today for a free demo.