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Analytics key to omni-channel

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Retail is in crisis, but omni-channel shopping offers a remedy. The key, writes PRAKASH MOHAPATRA of IBM, can be found in analytics.

The recent IBM Global Consumer Study reveals that in a single year Internet commerce jumped nearly 100 percent, with 27 percent of retail purchases made online in 2013 versus 14 percent in 2012. From the explosion of mobile technologies to the spread of social networks, retailers must navigate the speedy, endless and evolving trail of communications. With the disruptive nature of the Cloud and a new generation of advanced big data and analytics, retailers can now leap-frog competitors by delivering new benefits to customers.

Today customers expect retailers to understand them and their lifestyles, whether in-store or online, and to serve them with the right product at the right price, any place and anywhere.

With a wealth of information at their fingertips, consumers are now better able to compare products, services and prices—even as they shop in physical stores. Retailers need ways to collect, manage and analyze a tremendous volume, variety, velocity and veracity of data. Harnessing big data can help retailers generate valuable insights for personalizing marketing, improving campaigns, optimizing assortment and merchandising decisions, and taking advantage of huge omni-channel business opportunities.

How can retailers use analytics to capture these omni-channel opportunities?

1) Insight-driven in-store order fulfillment: Retailers can use big data and analytics to analyze customer data and optimize order fulfillment for store locations. This analysis includes POS systems, online transactions, social media, loyalty programs and call center records. These insights deepen their understanding of customer path-to-purchase preferences to determine how much should they should stock in-store for faster delivery whether the customer purchased in-store, online or through a call center.

2) Insight-driven in-store shopping experience: Many retailers are scared at the thought of shoppers comparing prices with competitors while physically in their store. But this could actually benefit many brands that have a physical location. Analyzing combined data from in-store and online customer behaviorcan help retailers personalize promotions and offers across customer touch points and channels of interaction. The customer also benefits as they get a unified experience through omni-channel commerce.

3) Insight-driven personal e-commerce shopping: Customers expect retailers to understand their preferences and deliver personalized merchandise that fulfills their needs. Clothing retailer The North Face is piloting a digital “expert personal shopper” fueled by the IBM Watson platform that does just that. The expert personal shopper application acts like an online engine which makes personalized recommendations for customers based on their online queries.

4) Insight-driven retail merchandising: Better knowledge of competitive pricing, demand trends and customer buying preferences can drive sales and promotions that prevent lost business. Analytics can help predict optimal product pricing based on price and demand elasticity, and selecting and localizing the right merchandise for each channel based on a customer’s path-to-purchase behavior, locations and buying preferences.

Retail is in crisis. But it’s a crisis that can stimulate transformational change. Retailers who understand their customers, leverage data and insights to evolve the customer experience, and focus on their differentiators and assets, have the opportunity to thrive.

* Prakash Mohapatra is IBM Global Retail Industry Marketing Manager, Big Data & Analytics. This article first appeared in the newsletter of the IBM Amplify e-commerce conference held in San Diego, California, from 11 to 13 May 2015.

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