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TDT Analytics: Predictive Analytics for Optimal Pricing

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Michael G. Foliot, President & CEO, TDT AnalyticsMichael G. Foliot, President & CEO
“How do I optimize my product pricing such that I can increase revenue while retaining customers?”—A very crucial question that organizations are struggling to answer when it comes to revenue management. However, traditional methods of pricing carried out by the finance professionals are limited in scope. This is because they access excel spreadsheets with the list of customers, and divide them into various segments. Based on the organization’s targeted increase in revenue, the professionals raise the price within each segment by a certain percentage. However, when these pricing strategies are applied; the customers stop buying the organization’s products due to an increase in price. The revenues estimated in spreadsheets do not translate into reality. Also, spreadsheets fail to address the customer retention component. This is where TDT Analytics differentiates itself. The company develops a model based on predictive analytics that optimizes prices based on forecasted demand, price elasticity, and competitive rates to ensure customer retention as well as revenue increase.

The first step that TDT Analytics takes in the client onboarding process is to understand their revenue goal and business rules if any that apply on pricing. Then, the company works with the client to understand the segment of customers on which the price increase needs to be applied. Here, TDT Analytics identifies the upper level and lower level constraints of the products and services that the client offers, associated business rules, pricing to end customers, and then creates a predictive model customized to each client. The model uses a combination of descriptive, predictive, and prescriptive analytics. This model identifies the price elasticity of each customer that shows their sensitivity toward products and their pricing scheme.

Our primary focus is around the development and application of predictive and prescriptive models to assist clients with their key objectives, be it revenue management, customer retention, or upsell cross sell of products and services

The price elasticity enables TDT Analytics to estimate the optimal price increase for each customer segment without upsetting them. “Our primary focus is around the development and application of predictive and prescriptive models to assist clients with their key objectives, be it revenue management, customer retention, or any other area,” says Michael G. Foliot, President and CEO of TDT Analytics.

By creating a unique and customized model for each client, TDT Analytics ensures that all client requirements are met. "Instead of taking a cookie-cutter approach, we take a very consultative approach by understanding client business, imperatives and pain points. We then articulate a methodology that best works for them and brings the highest ROI,” mentions Foliot. To best illustrate the effectiveness of TDT Analytics, he mentions a customer success story of an integrated payment processing solution company in the U.S. who historically increased its product prices every six months. Every time the client increased its price, the customer attrition rate would go up leading to a loss of 12-15 percent of their client base. With TDT Analytics, the client was able to come up with a completely revised pricing strategy while minimizing the attrition rate to 2 percent only. “The way we applied the pricing strategies, certain end customers did not even realize the increase in price, but in totality, the client was able to increase its revenue.”

With such successful case studies, TDT Analytics will be involved in dynamic pricing strategies by exploring technologies such as AI, robotics, and NLP to learn price elasticity. For this, the company is backed by the support of a team of skilled data scientists and technologists. Operating in the U.S., Canada, and the UK, TDT Analytics will continue to power new customers along with their pricing strategies.