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Use intelligent, predictive data to take omnichannel commerce to the next level

Real-time consumer relevance makes product recommendations more personal, accurate, and saleable—but you need to start with the right data.

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“Ultimately, the question that needs to be answered for real-time consumer relevance is: ‘What data does the in-store associate, call center employee, merchandizer, and e-commerce manager need to quickly tailor information for the customer?’”

—Benjamin Rund, senior director of product marketing, PIM and Procurement, at Informatica

Amazon has brought tremendous innovation to online sales with its product recommendations. Their dynamic recommendations are not entirely reliable at this point, however. Imagine being able to accurately recommend products or send coupons via text message while customers are shopping. These feats of live interaction with customers are within reach with real-time consumer relevance.

“Making the intelligent and automatic connections between existing and predicative information will be the foundation of true personalization and relevance to customers,” says Benjamin Rund, senior director of product marketing, PIM and Procurement, at Informatica.

Capture and define

Real-time consumer relevance begins with the data steward. Begin by working with product managers and merchandizers to understand the types of corporate, product, channel, and customer data you'll need to capture. Then define business rules and processes:

  1. Which channels are we using for selling and marketing our products?
  2. Who requests, consumes, provides, and reviews customer and product data throughout the company?
  3. Which business units create sales and marketing assets?
  4. Is our customer data, including customer profiles and segmentation information, current?
  5. How should we govern product and customer data that originates inside the company—and how do we currently apply these rules to our partners, including manufacturers?

“Ultimately, the question that needs to be answered for real-time consumer relevance is: ‘What data does the in-store associate, call center employee, merchandizer, and e-commerce manager need to quickly tailor information for the customer?’” says Rund.

Fine line between relevancy and privacy

Real-time consumer relevance is the natural next step for PIM and MDM systems. Together, these technologies can map the relationships between the different types of data you want to master, including product, customer, and transaction data. Used properly, they can feed the recommendation engine and provide the contextual insights necessary for real-time relevance.

Although current tools are already powerful, technologies on the horizon will force companies to navigate even more delicately the fine line between unwanted surveillance and value-added recommendations. Some retailers are looking for new types of real-time data, such as pulse or eye tracking, to record about shoppers as they browse.

“What are we legally allowed to capture? And what is deemed acceptable by customers? These are new topics popping up, and the answer is different in different countries,” says Rund, noting that smart organizations will find ways to build trust rather than erode it.

He says that for real-time consumer relevance to be most successful, your customers need to be willingly engaged in the process, which will only happen if they feel the price they pay in personal information is worth the convenience.

 

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