Salesforce Einstein Prediction Builder Boosts Opportunity Win Rate for a Global Flooring Brand
The client is a global manufacturer of commercial flooring with an integrated collection of carpet tiles. They are also a market leader in sustainability with a fully integrated collection of resilient flooring. Their modular system helps customers create interior spaces while positively impacting the people who use them and our environment.
The client has operations in six continents and 40 global showrooms. Opportunity amounts change throughout the business lifecycle, so predicting the final amount becomes extremely important for forecasting. The Einstein Prediction Builder was implemented for powering workflows, focusing on important deals, and working smarter.
• Predicting the win rate (a basic measure of sales success). To enhance a team’s overall performance it’s natural for companies to set a benchmark against the average that will help them increase their chances to win an opportunity
• Analyzing bulk data in order to predict and increase opportunity win rate, especially in the manufacturing industry with a huge variety of products, styles, and various other aspects
• Understanding what companies should do to minimize the overall operation and manufacturing cost and how they can enhance the profitability of a deal
• Predicting the win rate in different scenarios such as sales user, commission, and product style & sales users
• Predicting scenarios by changing sales representative, commission rates, and product
Einstein Prediction Builder was implemented to enable the client to predict any field in the Salesforce environment with just a few clicks. It helped in streamlining the sales process, optimizing workflow, focus on key areas, and work smarter without any coding knowledge.
• The einstein prediction builder dashboard was set to analyze the opportunity win rate for the first-ever environmentally sustainable flooring brand
• With machine learning, patterns in the historical data were analyzed to apply to new data and make predictions
• Upon analyzing historical data & figures, opportunity win rate was predicted and results for questions as to how and what opportunities are worth leveraging, that helped to get a win in the past, and factors influencing the opportunity win rate were answered
• Based on this in-depth analysis, the system automatically suggested recommendations
• Answers to some crucial cases were implied, such as - how to minimize the operation cost, how to enhance the profitability of a deal, how to decrease the manufacturing cost.
With the Einstein Prediction Builder, Sales Managers/ Opportunity Owners get predictions for each opportunity they focus on or intend to focus on.
• With detailed analysis, the flooring brand managed to focus on the opportunities are worth following up, which in turn aided in designing growth-boosting business strategies
• Since the opportunity win rate was derived using the past data, the eCommerce company was able to surge their sales just by making changes in different factors - such as product style, sales user, etc
• Einstein prediction builder suggested impact on win rate in the following scenario changes:
o Win Rate by Sales User: Einstein predicted a Win Rate of 88.79% with a particular sales user
o Win Rate by Commission: Einstein predicted a Win Rate of 92.25% with zero commission
o Win Rate by Product Style & Sales User: Einstein predicted a 15.6% increase in opportunity by changing product style and the sales user