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Information Management in Retail: Magic for the customer found in federated data management

iStock_customer_offer_XSmall.jpgBy incorporating diverse data sources in a federated, agile hub model, retailers are developing a predictive, adaptive 360-degree view of the customer. We’re concluding a conversation with Mario Vollbracht, global director of Consumer Industries and Retail Information Management and Analytics, HP Enterprise Services about the exciting potential that modern information management and analytics presents for the retail industry. HP’s Industry Edge digital magazine this month examines the information challenges facing the retail industry.

 

KHoward: We have looked at the market-driven need for a more flexible hub approach to information management for retailers. Can you explain a little more in-depth how this approach might work?

 

MVollbracht: Sure. As we’ve said, large and complex data sets are now available from point of sale (POS), social media, call center voice records, and video feeds. Retailers need a more flexible approach to information management. This new approach incorporates the transactional databases that they already have in a federated fashion into a hub with unstructured data sources that have been harmonized and assimilated to gain maximum insight and value from that information.

 

Within this information and analytics hub, we see three major tiers:

 

1. Data

2. Intelligence

3. Delivery

 

IM&A_retail_hub.jpg

 

The hub’s data tier combines a traditional enterprise data warehouse and a specialized enterprise consumer warehouse, both of which are very familiar to retailers, with the unstructured data sources that we get from social media and consumer sentiment research, customer service interactions, shopping patterns, and traditional and digital marketing channels.

 

Because unstructured data is not easily analyzed and assimilated to structured data by a computer in raw form, the data tier must be capable of handling business rules and responses, analytics, offer management, and real-time events. This harmonizes and assimilates the unstructured data so that it can be analyzed for insight and value.

 

At the center of the data tier sits the hub’s Master Data Management function. This is where all of the data from across the various sources is managed and aligned to enable a 360-degree view of the customer’s shopping experience. As consumers become more and more omni-channel, the hub approach enables retailers to create, capture, manage, store, and deliver content and documents across the enterprise. Content management in the retail setting addresses all types of structured and unstructured information for products, consumers, employees, and suppliers.

 

The intelligence tier is where the “thinking” gets done. This tier serves to classify, segment, analyze, and report insights from the wide range of data sources. Here, there are some really sophisticated analytics packages that use advanced algorithms to develop rich, predictive models of what is likely to motivate a customer to make a purchase.

 

Retailers can use these capabilities to automatically recommend and personalize appropriate offers to the customer. These might include new product samples, skipping a holiday credit card payment, rate adjustments, or customer win-back offers.

 

These actionable insights from the decision engine then get applied to the various business functions of the retail enterprise. This includes, obviously, customizing offers for the customer, as well as improving service opportunities, gaining insights for marketing promotions, as well as better insights into how customers use the various channels to interact and engage with your business.

 

Finally, in the delivery tier, we see the magic come to life. The right kind of offer is made to the customer at just the right moment. Or we win back a customer that we very nearly lost. Lessons learned are shared across various parts of the enterprise, including marketing, sales, supply chain and customer service. All of this is delivered in the right form at the right time thanks to the federated and flexible approach that has been built into the hub.

 

KH: It seems that there are a lot of opportunities for retailers in analytics. Where do you think the greatest opportunities are?

 

MV: Linking the different channels and understanding how this omni- consumer is moving through my channels, and picking this consumer’s conversation up from where they left off. If I do some product research online, and I then go into the store, wouldn’t it be nice if the retailer could understand the research that I already did and dispatch a sales associate or present a tailored interactive display or send a message through my phone that says, “OK, I know exactly where you are and here is some additional information.” That would be a fairly easy win. We just need to bring it all together. The hub approach makes that possible.

 

Associate mobility is low-hanging fruit. So often, the customer has more information than the associate. That makes for a frustrating shopping experience for you as the customer when you walk in and the associate tells you something you know isn’t right, because you’ve done the research. And you know it better.

 

So the associates need to be armed with that information to help the customer. And you need to pull in the information about the customer – are they an early adopter or a late majority customer? The level of information needs to be tailored for the type of customer.

 

These are the types of projects that provide a tangible ROI for retailers.

 

The whole sector of information management and analytics is an area of tremendous innovation for retail. There are organizations we are working with, setting up mesh networks in stores. Talk about contextual. We know exactly where the shopper is in a store. We can even do some analysis about who that customer is. By applying social, cultural and physical intelligence, we can analyze what kind of customer they are. This is an exciting time for the retail industry and the possibilities are just becoming visible.

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