Big Data Analytics can be used in Retail Industry for customer profiling & segmentation and predict customer buying behavior

Study of a Leading Garments Retailer

Use of Advanced Retail Analytics for Customer profiling and segmentation based on Online and In-store customer data.

With the recent large scale popularity of online retail shopping in the UAE and GCC , most retailers are offering  online shopping channels to customers .One of our clients- a leading Fashion Retailer started its online channel recently. However without suitable Retail Analytics techniques .they were not able to accurately measure the impact of the new online channel on their overall marketing and sales performance and believed that online channel was cannibalizing their in-store sale.

The retailer was not able to understand their target customer profiles and how they were using the new online channel and its impact on their in-store visits.

Hence they could not plan synergized in marketing efforts which could deploy the online web shopping experience to  complement the in-store sales .

We compiled data from their online channel in terms of Clickstream data , Web Analytics, Product preferences and shopping basket analysis with their In Store Sales and inventory data  using Big Data Analytics techniques.

For customers who had registered online and were also registered in the In-Store mailing list , their profile and online and physical visit data was combined using advanced analytical techniques providing a complete 360 Degree View of Customers profile and behavior.

These different data sources and dimensions were combined to analyse online and physical visit patterns and shopping preferences across different customer profiles based on multiple dimensions like demographics, locations, branches visited etc.

These customer profiling and market segmentation analytics have helped the client to design and develop well-structured and targeted marketing campaigns like  customized emails and discount offers to encourage online as well as in-store visits . In addition the customer response on the marketing offers and campaigns is also being carefully monitored and tracked as client now appreciate the value of this data and how it can be used to make more robust and effective customer analytics models.

The results have been encouraging and have started to give the client better visibility on customers profile and preferences for online vs in store shopping . They are able to come up with more focused marketing campaigns for different customer segments based in their profiles and preferences and hence are able to reduce cost of poorly targeted promotions and campaigns. The market segmentation analytics are also being now used by the client for better targeting of their advertisements online and in Social media .

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