Hot Lead Prediction Analytics Use Case - Smarten

To conserve resources and optimize investment, a business must determine which potential opportunities are most likely to result in conversions and evolve into successful deals and determine which opportunities are at risk. This Hot Lead predictive analytics use case describes the value of predictive analytics to prioritize high-value leads and capitalize on an opportunity to convert a lead into a relationship by identifying key patterns that contribute to successful deal closures. Use these tools to identify the leads that are most likely to result in conversion and provide the most benefit to the enterprise. This technique can be used in many industries, including Financial Services, B2C and B2B. For more info https://www.smarten.com/augmented-analytics-learn-explore/use-cases.html

1. Hot Lead Prediction Predictive Analytics Use Case

2. Hot Lead Sample Application Description In order to conserve resources and optimize investment, a business must determine which potential opportunities are most likely to result in conversions and evolve into successful deals and determine which opportunities are at risk. By analyzing factors such as Opportunity Amount, Region, Client Size (by Revenue and Employee Count), Competitor Type, and Deal Size Category, Hot Lead predictive analytics helps sales teams prioritize high-potential leads and enables businesses to forecast the likelihood of capitalizing on an opportunity to convert a lead into a relationship by identifying key patterns that contribute to successful deal closures.

3. Hot Lead Sample Application Target Opportunity Result (Loss/Win)

4. Hot Lead Sample Application Influencing Factors Most Impacting Factors: Opportunity_Amount_USD : Represents the monetary value of the opportunity, directly affecting the likelihood of closing and conversion . Total_Days_Identified_Through_Closing : Represents the time period from identifying the opportunity to closing and conversion, and indicates lead engagement and urgency . Other Contributing Factors: Region, Route_To_Market , Client_Size_By_Revenue , Client_Size_By_Employee_Count , Competitor_Type , Deal_Size_Category

5. Hot Lead Sample Application Algorithm(s) The Classification analytical process is used to classify numeric and/or categorical data into two or more groups based on predefined categories. Higher classification accuracy (>=70%) means the results are reliable and accurate. Lower classification accuracy (<70%) means the model needs to be rebuilt using different input parameters.

6. Hot Lead Sample Application Model Visualization

7. Hot Lead Sample Application Model Visualization

8. Hot Lead Sample Application Model Visualization

9. Hot Lead Sample Application Model Visualization

10. Hot Lead Sample Application Interpretation

11. Hot Lead Sample Application Interpretation

12. Hot Lead Sample Application Model Summary

13. Hot Lead Sample Application Result Likelihood/probability of a given opportunity result. Flag containing opportunity result with ‘Loss’ and ’Won’ values.

14. Hot Lead Sample Application Single Apply To predict the lead based upon the selected parameter values, APPLY functionality is used.

15. Hot Lead Sample Application Mass Apply Predict lead for multiple records and compare actual result with the predicted ones.

16. Hot Lead Sample Application Mass Apply Model Validation Summary

17. Hot Lead Sample Application Key Influencer’s Analysis

18. Hot Lead Sample Application Simulation

19. Hot Lead Prediction Predictive Analytics Use Case For more information, contact us today. www.Smarten.com [email protected] Smarten – Hot Lead Prediction Use Case - 2025