In the world of entrepreneurship, there are three key challenges that can impede the path to sustainable success. These three problems can limit the profitability of companies of any size at any given time:
- Are you running ads, but are they under-converting or reaching the wrong target group? Marketing problem!
- Are you reaching many interested customers from the right target group, but closing few or no deals? Sales problem!
- Customers are not satisfied with the delivery and are demanding a revision or even want their money back? Fulfillment problem!
There are numerous solutions for all three problems that can get the business back on track. In this Insight, we present a data-based approach that solved a persistent sales problem for one of our clients.
We carefully analyzed sales data for patterns and interaction effects using classification algorithms from the field of machine learning and XAI (Explainable Artificial Intelligence) methods. This made it possible to identify key indicators such as sweet spots of response time windows that were highly likely to lead to successful deals.
This data-based approach makes it possible to sound out the decisive steps in the sales process in order to ultimately gain control over new customer acquisition and have more planning security. The results of this machine learning application were impressive. The closing rate increased by 15% a few days after implementation, so that a direct correlation with the now more effective sales team could be established.
This use case shows how machine learning not only explains patterns, but also delivers concrete, measurable recommendations in sales – a key to sustainable success and fewer sleepless nights.
Author
Dr. Kay Stankov
Head Of Data Science & AI, Ainovate GmbH