CASE STUDIES

Enhanced consumer shopping experience on portal and customised recommendations of products

SUMMARY

One of the clients had a requirement of an enhanced precision in the recommendations of the personalised product mix to the consumers on the ecommerce portal based on evolving consumer preferences and decrease in run time while processing high volume of data.

METHODOLOGY

• Thoroughly analysed the past behavioural patterns of the consumers from various website POS

• Ran various Machine Learning algorithms to derive the best recommendations

TAKE AWAYS

• Identified the clusters of the client base in terms of their demands of various product categories on the basis of their age, income, region and so on

• Integrated stakeholders by helping them with optimum problem solving solutions

END RESULTS

The solution resulted in the increase in customer engagement and sales by more than 50%