Customers want their experiences to flow smoothly all the way downstream to happy outcomes. And you want that too, of course, as long as their personal outcomes sync up with your business’ outcomes: retention, sales, profits and so on.
Customer experience professionals are everywhere these days, or they will be soon. Every one them is at least roughly familiar with something called “big data,” though they may be fuzzy on the details of what that means or what its relevance might be to experience management. Nevertheless, there’s a growing awareness of big-data platforms, tools and best practices for delivering consistently satisfactory experiences.
The more fluid and frictionless the experience, the happier it is, as a general rule. We all want to build seamless satisfaction into our core business models, and it’s hard not to wonder how we can somehow weave it into the warp and woof of our IT infrastructure. But is customer experience something you can actually engineer? If you can, how can you produce it consistently across all of your business processes and channels? Can you automate it through next best action technology, or, at the very least, automatically generate real-time guidance for human interactions throughout your channels? And can you tune and refine a fluid, frictionless experience as if it were a calibration setting on a well-oiled machine?
Phrased in that way, it all sounds a bit absurd, far-fetched and impersonal. For sure, if you ignore customer experience and pursue next best action purely from a transaction-processing “decision automation” point of view, you run the risk of alienating customers who see you as just a heartless, profit-maximizing machine. But if you keep the focus on experience optimization while using next best action to automate and guide B2C interactions, you can have the best of both worlds. You can improve customer satisfaction without ignoring the bottom line.
How do you achieve this balancing act? Next best action initiatives help many companies to shape customer experience through inline guidance of business-to-consumer (B2C) interactions, offers and communications. Usually, this demands a layered approach architecture that involves big data, predictive analytics, business rules management systems, decision automation and stream computing at the very least. To ensure tight focus on experience management, you should also add tools for sentiment analysis, behavioral analysis, conversation management, knowledge management, social networking and other infrastructure that provide insights into what’s in your customers’ hearts and uppermost on their minds. Of course, IBM provides best-of-breed products in all of these next-best-action component categories, as well as experience-focused solutions from our recent acquisition of Tealeaf Technology.
That’s all cool and sophisticated, but it can be anything but fluid in terms of its impact on customer experience. As you integrate new investments into your next best action platform, you run the risk of introducing clunky handoffs into the customer experience, both across channels and even across moments in the same customer session. Human beings experience this all as a clutter of incongruous messages, prompts, questions and other interactions initiated by your people and systems, with no logical connective thread or relevance to their intentions or desires. Alternately, it may be perceived as heavy-handed targeting and scripting of interactions. But too much scripting becomes obvious, cliched and creepy to customers, as if the people in your channels are public speakers reading from teleprompters.
The core problem is that, as the complexity of your next best action infrastructure grows, you may have difficulty juggling the zillion “decision logic” artifacts – propensity models, business rules, process orchestrations, relationship graphs, customer-journey maps, etc. – that drive it all. Related to that is the problem of coordinating the work of data scientists and other next-best-action development teams, who develop and maintain this logic. Another big issue is that trying to automate, script or guide every moment from prewritten analytics and rules eliminates the crucial role of human situational judgment in experience management.
Even with next-best-action scripting as the core guidance approach, the appearance of “natural” flow of human conversation must be encouraged where it makes sense, even when it’s obvious to the customer that the (usually) stranger they’re speaking with must be following some predefined sequence of conversation points. Optimizing the rolling experience requires some dynamic blend of automated guidance and ad-hoc conversational give-and-take.
To humanize the customer experience throughout your channels, you should drive adaptive natural-language-processing technology, such as Watson, into your next best action platform. This will enable more nuanced response-scripting that reflects what’s happening in real time, especially if combined with real-time processing of clickstream, geospatial, analog-audio and other streams.
Also, you must give your human touchpoints – agents, sales people, etc. – more powerful real-time decision support tools so that they can use their judgment to dynamically fit their response to the immediate situation. This will enable them to occasionally go “off-script” from whatever auto-generated guidance the next best action infrastructure has produced.
And you must allow your human touchpoints to converse with customers through any and all social channels that add value. Ongoing cross-channel conversations should roll with the frictionless fluidity of modern experience.
Photo by Bobak Ha'Eri | Wikimedia Commons