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Here’s how to use Decision Management to improve cross-channel experience

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Retailing today had an interesting article – “Best Buy, Sears, Target tops in cross-channel performance” – about the importance and challenges of becoming a cross-channel retailer. I was struck by the potential of Decision Management Systems to improve cross-channel experiences in a couple of key areas:

  • 60% had inconsistency across in-store and online promotions;
    Obviously inconsistency is a real problem – potential customers can feel cheated and there’s nothing like learning that someone else got a bigger offer to make the offer you got look worse. A centralized Decision Management Systems for handling promotions and making sure that everyone gets the promotions to which they are entitled can not only help with this it can also eliminate accidental inconsistency caused by staff who make mistakes. Check out this case study from IBM where a retailer builds a system to calculate prices based on all the eligible offers (whether online or offline, loyalty or basket-based) and pushed this into the Point of Sale terminals to make sure it was 100% consistent. With a single promotion decision management system you should be able to guarantee 100% consistency.
  • Only 52% use collaborative filtering, which provides tailored recommendations to customers;
    In fact recommendation engines don’t need to use collaborative filtering at all but are simple to build as Decision Management Systems as I discussed previously. You can use data mining to find the right cross-sell and up-sell recommendations, predict a prospective customer’s propensity to buy with predictive analytic models and encode your own expertise on what works for people using business rules. And all this can be fed into a recommendation decision management system that works across channels, can be used to push advice to staff on the floor or to a customer’s iPhone. With a Decision Management System you can start simple, with a few rules perhaps, and improve over time by analyzing what works, adding more rules from more experts and mining increasing amounts of data. A modest immediate return that grows over time.
  • A majority of retailers — 64% — fail to provide estimated shipping charges, increasing chances of cart abandonment.
    Failing to provide estimated shipping charges is just silly. This is not even a very complex Decision Management System. Just a reasonable number of fairly stable rules. And using a rules-based Decision Management System for this would let you vary the calculation whenever the rates changed, easily offer promotional rates and even manage a program like Amazon Prime without having to change your website.

Don’t get caught out as you strive to become a multi-channel retailer. Take control of decisions now with Decision Management Systems, business rules and predictive analytics.

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