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Smarter Commerce in Action: Petrol drives retail success with suggest-sell insights
Pratin Ashtekar 2700046SAG firstname.lastname@example.org | | Tags:  ibm carol_marting zenterprise im bao system_z_software z/os db2 | 1,617 Visits
By Carol Marting,
Client References Manager - System z software .
How many times have you returned home from a trip to the store, only to realize you’d forgotten to pick up the one thing you went in for in the first place? It happens to all of us – but the rise of Big Data analytics means this kind of scenario could soon be a thing of the past.
Petrol d.d., the principal supplier of energy products to the Slovenian market, operates a thriving retail business with thousands of loyalty members. With its transactional databases of members’ purchasing histories growing by the day, the company saw an opportunity to enhance the retail experience for these loyal customers.
Working together with IBM, Petrol deployed IBM SPSS Modeler software with IBM DB2 Analytics Accelerator for z/OS on its high-performance IBM zEnterprise 196 server platform. Using lightning-speed DB2 queries, the company now harnesses SPSS predictive analytics insights to generate personalized sales suggestions based on customers’ purchasing histories, which are delivered directly to the point-of-sale interface. In the blink of an eye, Petrol’s sales clerks can see a loyalty customer’s recent purchases, and suggest related products that they may not have considered – or frequent purchases they might otherwise have forgotten.
To learn more about how a smarter approach to suggest-selling is helping Petrol to drive increased sales in its retail business, check out the IBM case study now: http://www-01.ibm.com/software/success/cssdb.nsf/CS/KPES-99PQGU?OpenDocument&Site=default&cty=en_us