Pricing, Even When Predictive, Requires Context
Many predictive analytics platforms are designed for price optimization, but in today’s world of deep discounts and markdowns, brands must prevent themselves from entering a race to the bottom.
Effective pricing requires studying both pricing trends and the consumer’s potential action. With predictive analytics, brands can monitor consumer’s buying habits and offer predictions on what actions they may take at certain price points, or in response to a particular set of bundled offerings or discounts.
Lakshman Lakshmanan, a Senior Manager in the Analytics practice of A.T. Kearney, noted that contextualization drives predictive pricing. During an online shopping trip for a new mobile phone, Lakshmanan compared prices between Amazon and another retailer. He noted that the competing retailer lowered prices of the particular phone in real time, and even prompted him to purchase the phone immediately.
“For me, Amazon offered a lower price point, but they also had a lot of ads layered on top of the lowered price,” said Lakshmanan in an interview with Retail TouchPoints. “This ability to analyze consumers as they navigate the site, respond in real time and use pricing as a tool to enhance the shopping experience will be important going forward.”
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