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The Decision Factor offers insightful comments and observations on analytics—from views on new technology approaches and market dynamics to the latest industry trends driving demand for faster, smarter information analysis. This blog contains personal views, thoughts, and opinions from SAP employees, mentors, and friends working in the area of analytics. It’s not endorsed by SAP nor does it constitute an official communication of SAP.

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Cross-Channel Customer Intelligence Makes Big Data Actionable

Man paying with credit card at grocery storeWhat if you knew exactly who your customers were, what products they wanted, and when they were most likely to purchase them? It would have a huge impact on your marketing and sales strategy and execution!

We now have an unbelievable amount of data on every customer. Each of these data sets opens up a new window on a customer and reveals insights before, during, and after the purchase cycle. But most companies lack the right data, unified platform, or mathematical expertise to accurately predict customer behavior from all this data.

Fundamental new tools and techniques have recently emerged that enable the effective analysis of customer data—making your big data actionable.

Tracking Behavior on Multiple, Disparate Levels Poses Problems

Consumers increasingly exhibit a buying behavior that crosses multiple channels before a purchase is made. While this creates opportunities for marketers, it also makes it difficult to identify which efforts are truly effective.

From a system perspective, analytics for these channels remain quite separate from each other:

  • The web team collects metrics like page views, unique visitors, average time per page, bounce rates, etc.
  • The marketing and sales analysts analyze point of sale data from actual stores or an e-commerce site.
  • The IT department collects usage statistics for the mobile app.
  • For retailers, store operations measure traffic, movement throughout the store, sales, and conversion.
  • A customer relationship management system of a company contains the interaction history in channels like direct mail and email campaigns.

Essentially, different metrics in different systems are viewed by different people within the enterprise. And all the while, they’re viewing the same set of customers.

The Omni-Channel Strategy Solution

Enterprises need to have both a single view of customers and the ability to analyze behavior (intent, tendencies, actions, and transaction) across channels. An omni-channel strategy meets those needs.

An omni-channel strategy views the customer as a single human being who understands and interacts with products through all of these different channels together. Once an enterprise gets a handle on the cross-channel customer intelligence, questions about customers’ holistic shopping behavior begin to answer themselves.

Here are just a few examples of questions your company can have answered:

  • What’s the probability that this specific customer will switch to a competitor in the next week, six months, year?
  • What campaign frequency is an optimal cadence to engage without annoying customers?
  • How can I, with a single click, look at behavior patterns of all customer responses to a specific offer? How can I filter by any parameter of interest and develop an automated plan for each customer?
  • How frequently does the same customer look at products in the store and then purchase through another channel?
  • Does my online store actually serve as the starting point, enabling customers to winnow down their choices before they purchase in the store?
  • Direct mail
    • Which customers should I target to maximize return on investment? Why am I sending him catalogs in the mail when he has never redeemed any coupon?
    • Is this customer price conscious? Is a loyalty recognition message more appropriate than a coupon?
  • Business to business
    • Does this prospect need further nurturing via email or an approach from a direct sale manager?
    • Did this prospect decide to opt out of further emails on this topic?
    • Who else has interacted with this prospect from my company in the past and what has been the response and outcomes?
  • Mobile app
    • How does mobile app use affect a customer’s behavior in other channels?
    • How much do customers use the mobile app while they are actually in the store? Are shopper behavior patterns different when a mobile app is in use?
    • Are mobile purchases net-new or cannibalized from the older channels? Does mobile app usage actually increase use of these other channels?
  • Email
    • Which specific product offers should I include for each user to maximize conversion?
    • Which users should be withheld from a campaign to reduce email unsubscribes?

With an omni-channel strategy solution, your enterprise can have answers to all these questions and more. With the right tools and techniques, your big data can be analyzed for big results. 

I’d like to hear about your experiences with the usage of cross-channel customer interaction data. How much implementation have you seen in actual practice? What are the challenges you’ve come across in making it happen?