The Role of Proactive CX

Customer feedback occupies a paradoxical space in the world of business, wherein the infrastructure to collect it has been in use far longer than today’s best practices of how to most effectively utilize it. Even in the days of pen-and-paper forms, the dominant customer feedback collection strategy was to collect now and analyze later, leading to enormous quantities of responses that have only grown in the decades since. This strategy has been amplified exponentially by our modern customer journeys’ abundance of touchpoints, resulting in a new challenge for leadership: how to examine this mountain of data.

Not long ago, business leaders racked their brains to try to figure out how customers think and feel, confident that they would be able to tailor their products and services to customers’ needs if only they had access to their thoughts. Now, for better or for worse, it’s not hyperbole to claim many organizations do have direct access: data points across myriad experiences supported by detailed demographic, psychographic, and behavioral information. As technology enables accessible widespread data collection, market competition increasingly takes place along the lines of how this data is used to drive experiences. 

Where AI comes in

AI represents a path forward through the abundance of data. With the right approach, AI can both aid in illuminating the stories data can tell and the way these insights are applied to customer experiences. By intelligently digesting customer data, you will unlock the ability to deeply understand customer needs and proactively design experiences for them. 

Like any other tool, AI is only as valuable as its outcomes. What halts progress for many leaders is the notion that use of AI–due to its amorphous intelligence–is sufficient for it to provide value. Widespread use of AI for CX currently takes the form of self-service. Self-service, primarily in the form of chatbots and voice AI, add value by operating within existing principles: automation and expedition optimize processes by reducing the resources needed without diminishing experiences. Rather than focusing our efforts on never-ending optimization, the opportunistic value of AI in CX will be in the new experiences we create that anticipate customer needs. 

“Data is, by its very nature, historic. The best example is like driving a car looking through the rearview mirror. Our guests absolutely want speed, but what they really want is to understand what’s happening before it’s even happened.” -Rob Swain, COO of KFC

Understanding proactive CX

Proactive CX is the strategic usage of data to innovate experiences that anticipate customer needs and desires. This can look like outbound experiences that leverage personal and aggregate data to offer unexpected value. It may also take the shape of predictive experiences that prompt next steps in the journey using the data available. 

Outbound CX has been gaining traction and popularity as a way for brands to capitalize on the short distance between digital upselling and digital CX. Outbound CX isn’t inherently proactive–outbound experiences that don’t leverage specific and relevant data will ultimately result in more of the same results you’re currently seeing. And while there is merit in pursuing sales wrapped up in outbound customer experiences, a direct selling experience rarely offers the level of customer centricity that customers appreciate and seek out. 

Proactive CX has a role in every industry, although it may look different according to the level of familiarity customers have come to expect from brands. Most prudently, anticipatory experiences must be implemented with tact and sensitivity, otherwise there is risk that the personal nature can create a negative experience.

“The ‘blue dot consumer’ is the world. They stand perfectly still in the center of the frame at all times. They take a step left, they expect your brand to take a step with them. This changed everything,” Ken Hughes said in his Qualtrics X4 2025 keynote.  “It’s personal, you don’t go on Google Maps and follow someone else’s blue dot around. You’d end up at their destination, not yours. It’s all about personalization. It’s your journey.”

In healthcare, a predictive experience may look like a doctor’s office reaching out by sending an email to set up an annual appointment; it may add a personal flair to the experience by suggesting appointment times based on the patient’s past bookings. This level of personalization is appreciated: a reduction in patient effort is often met with gratitude. On the other hand, if the email also includes how long it will take the patient to drive from their home address to the doctor’s office, some patients may be put off by this added level of personalization. The value added by personalization cannot be outweighed by the potential negative effects of customer concern that their data is unsafe or being used in nefarious, or even just superfluous, manners. 

Integrating data at every level of decision making

When it comes to the amount of customer data that never makes its way through the organization to product, marketing, and customer success teams, many leaders may as well be sitting on a gold mine. Data siloing, outdated systems, and bureaucracy prevent organizations from truly being guided by the enormous volume of data they are collecting. 

Promoting the value and utility of aggregate customer data is a cause that will likely need to be championed by CX leaders, but will require multidisciplinary coordination and strategy. The “siloing problem” goes beyond data, and CX leaders often find themselves frustrated at not being a part of high-level strategy conversations. Contact center leaders are invaluable because their analysis can and should be used to identify targets for improvement across all areas the entire customer journey. As customers’ expectations heighten to match the capabilities they know are available, brands that previously held a competitive advantage in their product quality and simple, convenient delivery will be undercut by a new competitive edge: highly personalized, proactive CX.

Enjoyed this article? Find more insights on the practical application of AI for CX in the Agentic + Generative AI issue of the CCW Digital Magazine. 

Image by Sagar Soneji on Pexels.