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Better decisions with real-time marketing intelligence

Overview

Automated the reporting system to generate consolidated, real-time interactive dashboards on customer orders, product performances and customer preferences across geographies enabling marketing teams to chart effective strategies for growth.


    Challenges

    TI cycle introduces new products every quarter and to do that it needs some insights related to distributors analysis, order analysis, finding potential market, customer preferences, market trend analysis, etc. but the major challenge here was the delayed decision making of the marketing team because of the existing solution which was time consuming as it required more of manual effort.

    The reports were generated and presented to users in a tabular format. The users, as a result, were unable to effectively read and derive inferences from it. They found it difficult to correlate inferences made from individual excel reports and had trouble understanding the data because there were no visual reports which could provide better insights on Order Analysis, Customer Detail analysis, New Product Analysis, Customer preference analysis, DSO trend analysis, Geographic analysis. With increasing data volume, the manual effort and man-hours required to develop and validate reports was increasing at a very fast pace and significantly increasing costs of the company.


    Solution Overview

    The goal was to reduce the manual effort and increase efficiency in generating reports by automating the system, getting visual and simplified reports for better insights for faster decision making on new product, logistics, customer preference, etc., and reducing the costs associated because of increased manpower.

    The business required an automated robust solution that could solve their problem because of the limitations of their existing solutions.

    As previously associated with Murugappa group, GainInsights, with its expertise in Qlik Sense, recommended the implementation plan for TI cycles.

    Firstly, all the data was extracted from more than 20 tables that were in the Oracle database and using that, a data model was built which could provide marketing intelligence such as customer preferences, order analysis, new product analysis, potential areas for new product, customer analysis, distributors analysis, etc.

    Data security was provided to every level of management. As the reports were available to the salespersons, marketing team and head office team of different hierarchy levels, the application was equipped with various features such as authentication, authorization, and data governance to maintain the integrity of data. Dashboards were created so that users could conduct in-depth analysis such as order analysis, customer detail analysis, new product analysis, AICMA Analysis, and DSO trend analysis. Users were empowered to perform Market Penetration Analytics powered by household, population and market index data which could also refresh everyday data and give insights when these parameters are compared against the sales. Qlik Mashup, a feature in Qlik Sense was added to incorporate various KPIs and give the overview value to the management.


    Value Delivered

    Improved strategies for their market approach based on the analysis that they now get from different dashboards by using it anywhere and at any point of time.
    The fact tables have been transformed in sequence of business logic on Qlik ETL layer. This extraction and transformation operation takes only 11 minutes with Qlik
    Reduced manual effort because of implementation of automated Qlik sense and getting real-time faster reports thus reducing the manpower and costs associated with it.
    Increase in claims in the AICMA (All India Cycle Manufacturers Association) share trend because of AICMA analysis dashboard which provides stand alone reports to the management at the Head Office.
    Data security for every level of management with necessary restrictions in it for monitoring sales performance, customer analysis, customer preference, distributor analysis, etc.

Highlights


  • OEM Manufacturing, Cycles

  • Data modeling, ETL development

  • QlikSense, Postgres DB, MySQL DB

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