• APPROACH

    The solution had four aspects:

    • Bringing data from diverse ERP and CRM systems like SAP and Salesforce
    • Process, standardize and dedupe the data
    • Whitespace identification
    • Present the output in an interactive Graph Network

    Tredence’s AI/ML based augmented data quality engine Sancus was used to dedupe customer records and a whitespace identification solution was built on top of it to help identify up sell and cross sell opportunities. The solution:

    • Cleaned, standardized and deduped customer data coming from different Salesforce systems using proprietary AI/ML algorithms
    • Cleaned the product data, and used ML algorithms to create product hierarchies
    • Used an advanced recommendation solution to identify whitespaces to boost up sell & cross sell opportunities. This helped the sales team to target the right customer with the appropriate product
    • Created a graph network-based visualization that was integrated with Tableau Dashboards so that the sales team could easily interpret the suggestions

    KEY BENEFITS

    • Entire solution was hosted on AWS ensuring alignment with client’s cloud strategy
    • The clean, deduped and standardized Product data helped in improving the accuracy of the recommendation engine
    • Deduped customer and product data helped in restructuring of accounts, thus bringing in operation efficiencies

    RESULTS

    Sancus powered whitespace identification system helped in improving the customer satisfaction ratings and lead to 11% increase in year over year sales

     

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