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.
Challenges
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 a 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
Solution
Einstein Prediction Builder was implemented to enable the client to predict any field in 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.
Benefits
With the Einstein Prediction Builder, Sales Managers/Opportunity Owners get predictions for each opportunity they focus 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:
Win Rate by Sales User: Einstein predicted a Win Rate of 88.79% with a particular sales user
Win Rate by Commission: Einstein predicted a Win Rate of 92.25% with zero commission
Win Rate by Product Style & Sales User: Einstein predicted 15.6% increase in opportunity by changing product style and the sales user
CRMIT have been good partners to us on our journey to next CRM. To me coming here to see the team that supports us and seeing how much passionate an interface they have here? I really appreciate your team for it and would look forward to working with CRMIT again.
VP & GLOBAL CIO
Customer Success Stories
From an idea to an unforgettable and measurable customer experience
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1, true, US, https://www.wp.crmit.com/wp-content/uploads/2023/11/naveen-vemulapati-1.png, Naveen Vemulapati, Senior Vice President – US Operations & Global Analytics
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