- Posted by Tim Manning
- On October 8, 2014
Why are big data analytics relevant for OmniChannel retail? McKinsey suggests that “a retailer using big data to its fullest can increase its operating margins by more than 60 percent.” See our thought leadership paper on the subject.
Big Data Analytics and Retail Pricing Strategy
Today, OmniChannel shoppers use blogs, review websites, comparison shopping engines and then shop in-store, at kiosks, on your website; and use multiple devices including computers, tablets and smart phones. This interaction of devices and channels has expanded the data and the corresponding data management challenge and yet holds the key to retail pricing strategy plus creating a seamless shopping experience. Big data is only part of the solution. A complete solution is required analyze, interpret data and generate actionable intelligence for merchants so retailers can compete effectively.
Using Big Data Analytics for Competitive Advantage
What are the applications of big data analytics in OmniChannel retail that make sense?
OmniChannel Shopping Analytics. Online shopping behavior can be correlated with in-store shopping behavior and online conversions, in near real-time, to reveal opportunities to drive sales.
OmniChannel Competitive Surveillance. Competitive prices from websites and in-store can be processed more dynamically and compared with internal pricing rules so merchants can be alerted when their prices deviate from strategy.
OmniChannel Product-Line Rules. Product line relationships (e.g. private label) can be monitored so shoppers are presented with legitimate price trade-off relationships which reinforce a retailer’s strategy and price image.
OmniChannel Pricing. Demand models made richer with data from 1) shopping behavior, 2) competitive prices points, and 3) shopper segmentation can be leveraged to administer lifecycle pricing (regular pricing, promotions and markdowns) with more precision and consistency.
Clear Demand sees a practical vision for OmniChannel retail pricing technology which uses big data and evolved science engines to support a close alignment between customer demand and pricing strategy.