One of the top grossers for retail is the flick covering Next best action (NBA) thrillers. And it has all the elements of thrill, action and decisions. Imagine a customer buying a product and witnessing a component getting damaged within a week. And the immediate action on the part of the customer to mail the customer service regarding this ordeal triggers the next best action. With the retailer replacing the product, free of cost, within a short span of time, what the ‘next best action’ has set in train are events leading to a loyal customer and increased customer lifetime value.

Every retail scenario, with the customer at the core of business, demands the best action that can tilt the scale in favor of the retailer, in terms of sales, marketing effectiveness and customer loyalty. For those micro moments demanding best actions, retailers turn to the next best action powered by analytics-driven decision engines.

Decisions and Next best action hurdles

Let’s take a marketer and the decision making scenarios and moments into consideration. The marketer has to find answers to critical queries to take the next best action and right decisions.

  • What product to recommend for customers?
  • Which channel to use for customer engagement?
  • What offers to provide for a specific customer segment?
  • Which customer is going to buy this product?

In all of these scenarios, it is the next best action supported by decision engine that facilitates right decisions to be made at the right time. As decision makers across organizations chance upon various scenarios calling for next best action, robust decision engines built out of predictive modelling, forecasting, adaptive learning, business rules, real-time event processing, behaviour modelling and recommendation engine strengthen decision making capabilities and allows next best actions to be rolled out across business scenarios.

The action plan for next best action boils down to prioritizing next best actions – is it targeted marketing, campaign optimization or churn prevention – or other business areas demanding next best actions across business operations.

Next best action scenarios

What sets the NBA into action?

It starts with an activity occurring and setting NBA into motion. Going from the activity means understanding the context to make the decision in rolling out the next best action. On hearing the voice of a customer on social media, a retailer wants to leverage the situation – customer’s voice and opinion has lent more credence to the brand and service. For the retailer, this customer activity has sparked off the need to come up with the best next best action. Realizing how the customer is doing well in terms of strengthening brand awareness, the retailer comes up with a special offer for the customer. The next best action is then rolled out to enhance customer loyalty and customer lifetime value.

Whether it is marketing, sales, customer experience, or supply chain, there are activities happening evoking next best action. From sending a customized offer and using the right channel to roll out a campaign for a specific customer group to enabling proactive measures to engage customers likely to return items, best action is triggered across operations. And next best action in relevance to customer-centric strategies is all about augmenting customer retention, upsell and customer satisfaction.

Data to Analytics to Next best action

Making next best actions work involves seamless journey from Data to analytics to Next best action. For instance, a retailer brings together transaction data, customer data, and social media data together to make predictions augmenting next best actions. In short, decisions at the point of action are enabled through predictive engines and recommendation engines- as in the case of recommending the best product for a customer based on behavior, preference and needs. In addition, maximizing value depends on how two significant parameters are embraced as part of next best action strategy.

  • What’s the context – It could be a banking customer exploring to avail the best home loan. That set’s up the context for a bank to roll out the next best action in terms of recommendations made to arrest the customer attention. For a retailer, the context of a customer calling the customer support in relation to a damaged product delivered and the anxiety to find a solution to the problem at hand puts the next best action in motion.
  • What’s at-the-moment action – At a retail store, a customer who is finding his way in the store receives a special discount for a product on his mobile. The retail store makes good use of in-store and online data to get a customer 360-dgree view and takes appropriate actions at-the-moment when it matters to improve customer experience and sales.

Based on NBA prioritization, Saksoft helps build robust decision engines out of big data technologies, real-time event processing, behaviour models, recommendation engine and predictive modelling, and model store encompassing segmentation, customer 360-degree, churn prevention, upsell as well as cross-sell and targeted marketing. We guide retailers to use varied data streams including Interaction data, call centre, web, SMS, transactional data, social, chat and CRM data to take next best actions across customer service, customer experience and other scenarios across operations.