CASE STUDY 1
Comsense helps the largest retail group of New Zealand to adopt dynamic pricing, thus improving the revenue via net new customer acquisition by 7% within 3 months and lifting sales by 6%
The client was keen on leveraging its gold mine of data of suppliers, store locations, website ,social media, customer purchasing and lifestyle behavior to drive better business outcomes. There was no tracking mechanism on what was currently selling or what would sell in future.The client was struggling to uncover what customers would like/buy next and how to turn one-time shoppers into brand loyalist.
The Comsense Mar-tech team created a data lake to consolidate all the customer data from various sources like portal data, in-store Point of Sales data, CRM transactional data, website and app login behavioral data,marketing campaign data which includes email open, click through rate and coupon codes redemption data. Then customer profiles/persona based on advanced segmentation were created integrating the transactional,demographic and behavioral data. Applications such as basket analysis,data-driven tree analysis, retail promotions tool, CLTV modeling were used by data scientists that enabled:
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