Next Best Action in Real Time: The True Test of Big Data
In business, every moment is a moment of truth. Every moment can spell the difference between keeping a customer or losing them to a rival that makes them a better offer or delivers a superior experience. And no two moments are ever the same. If you don't seize that tiny window of opportunity, you've lost it, and possibly the customer, forever.
Next best action rides on a never-ending flow of such moments. One of the most enlightening windows into quality of experience is customers' real-time behavior within and across your diverse channels. How often do they visit your portal and what do they do in the flow of a typical session? Do they click quickly through to their desired result? Do they often abandon the portal in frustration? Do they immediately share their gripes with friends, family, and the world at large, telling everybody how shoddy your online presence is, how unprofessional your call center agents are, how subpar your products are, and how tone-deaf your company as a whole is? Do they jump to the competitor's portal on a moment's whim without giving you advance notice?
To avoid being blindsided, your business needs a 360-degree view of the world through the customer's eyes that is updated moment-to-moment. That calls for big data of the most demanding sort. Ideally, you'll need to roll up a unified view that combines everything you already know about the customer with everything new that you can glean from their real-time online behavior, plus everything that you can predict about their likely behavior under various future scenarios.
Scale is everything. In a global economy, you need an extremely scalable data analytics infrastructure to fine-tune your real-time, proactive, contextual customer engagements across multiple channels. The true test of your big data infrastructure is whether it encompasses the following core components at the heart of real-time next best action:
- Deep past: How deeply can you look into the customer's history when identifying how best to serve them? You need the full historical customer record, including all purchases, transactions, interactions, and the like. In other words, you need the centerpiece of all next best action: a customer data warehouse (DW), such as one built on IBM Smart Analytics System (ISAS) or IBM Netezza. If much of your historical data is in unstructured and semi-structured formats, you may need to extend and supplement you customer DW with a Hadoop platform, such as IBM InfoSphere BigInsights.
- Deep present: How deeply can you drill into the moment that the customer is currently experiencing? You need to correlate the full historical customer record with real-time feeds of customer clickstreams, interactions, geospatial coordinates, social posts, and other behavioral data that changes moment to moment. For this, you may need to call on IBM InfoSphere Streams and other low-latency big data platforms.
- Deep future: How far into the customer's likely future does your predictive crystal ball let you gaze, and how confident are you that you can nudge that future in a positive direction with actions you take right now? You need to continuously generate next best actions by aggregating past and present data; mining it for patterns relevant to customer propensities; and using it trigger embedded predictive models that can drive loyalty, upsell, experience, and the like. Ideally, you need to leverage big data technologies, such as IBM InfoSphere BigInsights and InfoSphere Streams, that can execute these compute-intensive operations and drive embedded recommendations leveraging decision automation platforms such as IBM SPSS Decision Management.
We're in a frictionless experience economy. Customers won't wait for you to upload the nightly batch of fresh intelligence in order to recalculate your next offer to them. If you don't satisfy them right now with a nuanced response that reflects your deep knowledge of their world, you're history. To them, at least.
For More Information:
- IBM's big data platform
- The big data conversation
- Follow IBM big data on Twitter
- on the IBM Netezza data warehouse appliance