To ‘Always Be Closing,’ Always Be Listening

Use your app to connect with customer intentions

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As consumers, we take it for granted that the apps we count on will act intelligently on our behalf when we generate signals of intent.

Target’s app lets me know if an item on my list is in-stock, in-store. My Peloton connects to my heart rate monitor when I select a workout. Waze proactively warns me about traffic disruptions.

We should expect organizations we count on—including our own—to do the same.

For any digital business, customers and employees are continuously generating digital signals indicating what they are trying to get done (and whether it’s going well or not). Suppliers and public or for-profit data providers offer constantly expanding indicators of what might make their success more or less likely.

There’s no disputing that the volume and potential value of data from business transactions, communication channels, IOT devices, vehicles, or equipment, and information feeds (news, weather, market data, etc.) are already orders of magnitude greater than they were in the past and growing gangbusters. (According to forecasts by IDC, three times more data will be created in the next five years than the previous five.)

The technical pattern for building apps that exploit the opportunities this presents are well-documented: reactive programming, or, in a nutshell, making observing and reacting to asynchronous events “the backbone of your application.

Gartner calls this type of design paradigm “event-driven architecture” (EDA). “EDA is at the very heart of real-time-sensitive digital business. Organizations capture real-world business events in digital form as they happen, by “listening” to event sources like Internet of Things (IoT) devices, mobile applications, ecosystems, and social and business networks.[1]

It only takes a moment of reflection for consumers to grasp how organizations can distinguish themselves by acting intelligently on our behalf when we generate signals of intent.

Imagine you’re a retailer and I, the customer, have just placed a curbside pickup order for a grill. You likely have a recommendation engine that surfaces some “you might also like” options to add to my cart.

If you’re doing it right, those recommendations are based on my profile and purchase history.

But let’s add in listening intelligently to other signals with my expression of intent in mind.

To illustrate, forecasts say we’re about to experience unusually cold weather here in Seattle. If you know my location, you know that’s potentially going to throw a wrench in my plans. If you’re checking your inventory and supply chain, you might see that outdoor heaters are in short supply. (Extra bonus points for tapping data sources about COVID rules and the prevalence of outdoor dining to model demand.)

A nudge in real-time that gets me to assess whether I’m prepared for the cold (and to snap up a couple heaters right then if I conclude I’m not) would be delightful. (Or I should say, “would have been.” This anecdote has a basis in reality: we now have the number of  heaters we need to scoff to take low temperatures in stride, but not without some a bit of a mad scramble.)

Our favorite apps already deliver an experience that makes us feel as if they are looking out for us and keen to help. Looking ahead, that will be true for our favorite businesses as well.

My employer DataStax is helping organizations create value from streaming data. To learn more, see here.

Learn how to control escalating data costs and maintain peak performance here

[1] Gartner, “Maturity Model for Event Driven Architecture,” by Yefim Natis, Massimo Pezzini, Keith Guttridge, W. Roy Schulte, Refreshed 30 November 2020, Published 28 June 2019

Copyright © 2021 IDG Communications, Inc.