According to a Treasure Data and Forbes Insights study, 74% of consumers are at least somewhat likely to buy based on experience alone. It’s clear that consumers care about how their customer experience (CX) feels, not just what they buy or how much it costs. Redefining customer experience means moving from brand-driven touchpoints to customer-driven interactions that adapt in real time — a data problem before it is a design problem.
The more we know about the current needs and preferences of our customers, the easier it is to create relevant customer experiences. The challenge is providing positive and profitable CX as tools continue to evolve and take on more and more complexity with every new technology. And, of course, new developments like the depreciation of third-party cookies, add another hurdle as we attempt to get to know and serve our customers.
CX Defined
The definition of customer experience (CX) isn’t complicated—it is the interaction a person has with your business at every touch point, from marketing to purchasing to ongoing customer service.
While the definition is simple, managing CX is anything but. Evolving customer expectations continue to change marketing best practices. Each CX at every touch point is a pass/fail test. You pass if your messaging, promotions, products and services line up with the consumer’s current needs and preferences. You fail if they don’t. Because customer journeys are omnichannel and constantly evolving, the chances to fail increase right along with the rewards for success.
CX Redefined
The redefinition of CX is the shift in focus from brand-driven to customer-driven, adapting to your customers’ changing needs in real time. In order to gain and retain loyal customers, brands have to be able to gather and use customer data from all channels and make CX the heart of the business. Stephanie Thum, CX Consultant and Practitioner explains that:
“If you want a customer-centric company, then CX practices need to touch every corner of your business: Risk management, marketing, strategic planning, business process improvement, policy development, digital, etc.”
Changing your business to a customer-centric model also means redefining your customer experience management (CXM) strategies. The best CXM strategies are seamless, omnichannel, real-time, and data driven.
Relevant & Seamless: CX Expectations
Customers expect prompt, easy, and consistent service. They want interactions to be relevant and seamless no matter how they choose to contact the brand. If your website is clean and easy to navigate but your customer service is spotty and difficult to reach, people may take their business elsewhere. Customers are increasingly blending digital and in-store shopping and want it to be easy to jump from one to the other.
A seamless CX builds confidence and encourages additional customer engagement. To create and maintain seamless customer experiences, your business must collaborate and share data internally. Analysis of customer data can identify pain points and challenges that create friction for the customer.
Omnichannel: Everywhere, All the Time
Customers should be able to interact with your business through as many channels as possible. All businesses need to be reachable through mobile devices, desktops, email, chat, and more. All of this connectivity offers your customers easy access to purchasing and offers your business multiple ways to increase engagement and profitability.
For example, Muji, a global retailer, wanted to plan for growth beyond their existing 650+ store locations. They discovered that people browsing their website were looking for products to buy in-store. Unfortunately, Muji’s online and social campaigns weren’t reliably driving foot traffic to in-store locations.
To bridge this gap, Muji used a customer data platform (CDP) to integrate online browsing data with in-store purchases. The result was a mobile app with relevant and timely personal coupons and in-app push notifications. Using the mobile app in combination with highly targeted promotions led to a 100% increase in coupon redemptions across all store locations, higher volumes of in-store foot traffic, and a 46% increase in revenue over a two-year period.
Muji’s story highlights the true power of the right offer delivered at the right time. Consumers expect purchasing to be easy and nearly instantaneous, and businesses need to be agile and ready to meet customers where they are, when they want to buy. The only way to truly keep up with changing customer expectations is to have clear data profiles that can be updated in real-time.
A timely auto-generated coupon or push notification can increase sales. Current data about customers also avoids gaffs like offering a coupon for a product that the consumer just purchased.
Data Driven: What Do They Want?
CX data can also help analyze and improve your bottom line. Successful businesses are rolling out data-driven initiatives based on individual customer experiences. The paradigm shift from, “who wants my products?” to, “what products do you want?” can only be achieved through intense analysis of customer data.
Stephanie notes that, “You need both operational and experience data to power your business decisions. Operational data tells you what’s happening. Experience data can help you to understand why.”
Companies that provide excellent CX use insights gleaned from clean, comprehensive, near real-time data. A Customer Data Platform (CDP) can not only gather and unify this data, but it can also power analytics and insights that drive decision-making.
How a CDP Drives CX
To be relevant and profitable, businesses need to collect, unify, and analyze as much consumer data as possible. A CDP does the grunt work of stitching together different sources of data to create an actionable single source of truth. The right CDP gives you the tools to really know your customers as individuals and to use that data to create exceptional experiences.
CDPs store data about the entire customer journey and can automatically focus on the most profitable channels for any given customer. From preferences about communication to predictive modeling, CDPs keep up with marketplace and individual customer changes so brands can make the right choices at the right time.
Customers expect business to offer personally relevant CX at every touch point. To meet these demands, your business needs a single view of the customer that unites data from across the organization. CDPs create centralized, accurate, and relevant data streams that allow your business to redefine CX for your customers.
What Changes When AI Runs the Experience
The data could already update in real time once a CDP was in place — what stayed on a human clock was deciding what to do with it. A segment was rebuilt on Monday, the campaign shipped Thursday, and results were read the following month — by which point the customer’s situation had moved on.
AI changes the clock speed rather than the goal. The underlying cycle is the Customer Intelligence Loop: collect, unify, understand, decide, engage, with engagement outcomes feeding back into collection. AI agents can run that loop continuously — reading a profile and choosing an action in minutes rather than in weekly campaign cycles, while the models behind that choice keep retraining on their own, slower cadence — while people set the strategy, own the brand’s voice, and decide which moments are off-limits to automation. That division is the point: agentic customer experience is harnessed by human creativity and strategic judgment, not a substitute for it.
The practical consequence is that the data foundation, not the channel tooling, becomes the binding constraint on CX. An agent that decides in seconds is worth little against a profile that updates overnight, and an agent that cannot write its outcome back into the profile learns nothing from the interaction it just had. This is the most common shape CX failures now take.
Common Mistakes When Redefining CX with AI
The sections above describe what a redefined CX program looks like when it works. The failure patterns below turn up most often in organizations that already have the data and the tools — they are ownership and measurement failures more than technical ones.
Treating CX as a redesign project rather than an operating model. A website refresh, a new chat widget, or a loyalty relaunch gets funded as “the CX initiative,” and each team optimizes the touchpoint it owns. The handoffs between them — where a customer explains the same problem to a third agent, or is marketed a product that support already flagged as out of stock — belong to nobody. That is where the experience actually breaks. Fix: give one person ownership of the cross-channel profile and report at the journey level, so handoff failures land on a named dashboard instead of between two of them.
Letting AI write the message but never read the outcome. Generative tools produce subject lines, product copy, and chat replies at a volume no team can match, and most of that output is judged once, by the person who approved it, and never again. When responses do not flow back to the profile that triggered the message, the system produces faster without getting better. Fix: require every AI-generated interaction to write its outcome — open, reply, resolution, return — back to the same profile the next AI decisioning step reads.
Treating consent as a downstream filter. Preference and consent state usually sits in the tool that collected it — the cookie banner, the email platform, the service desk — while decisions are made against the unified profile. Suppression then arrives one sync late, which is how an unsubscribed customer receives one more campaign and a deletion request produces a message nobody can account for. Fix: hold consent as profile attributes — per channel, per purpose — enforced at the decision point, rather than as a filter each channel applies before send.
Scoring CX on survey averages alone. NPS and CSAT are cheap to run and slow to move, respondents self-select, and the customers who leave quietly are the ones who never answer. Stephanie Thum’s distinction applies directly here: experience data explains why something happened, but operational data is what tells you it is happening now. Fix: pair every survey metric with a behavioral counterpart measured on the same profile — repeat purchase rate, time to resolution, second-contact rate — and investigate wherever the two diverge.
Automating the moments that need a person. Scale is not the constraint in a billing dispute, a complaint, or a bereavement call; judgment and tone are. Routing those into the same automated flow that answers order-status questions saves minutes and costs the relationship, and the cases most likely to escalate are the ones automation handles worst. Fix: define the handoff categories before launch and track the human-handoff rate as a designed CX metric, not as an automation defect.
Buying an experience layer before the data layer can feed it. New engagement, personalization, and service tools each arrive with a profile store of their own, and a tool that assembles its own view of the customer adds a fragment rather than removing one. The integration project that follows exists only to reconcile the copy the purchase created. Fix: before signing, confirm the tool reads the unified profile and writes events back to it in real time — check whether the CDP can feed the tool a live profile, not just accept a one-way connection from it.
Measuring the experience only up to the sale. Marketing touchpoints get instrumented in detail while returns, service contacts, and renewals are logged in systems nobody joins back to the profile. Churn then surfaces in a quarterly report with no attributable cause, and the post-purchase experience that produced it stays invisible. Fix: bring at least one post-purchase touchpoint per journey into the same event schema as marketing data, starting with the one customers contact most.
FAQ
What is customer experience (CX) and why does it matter?
Customer experience (CX) is the total perception a customer forms across every interaction with your brand — from browsing your website to post-purchase support. CX matters because it directly drives loyalty, retention, and revenue. Companies that deliver superior CX outperform competitors and build stronger long-term customer relationships.
How does data improve customer experience?
Data enables businesses to understand individual customer preferences, predict behavior, and deliver personalized interactions at the right time. By combining operational data (what is happening) with experience data (why it is happening), companies can identify friction points, optimize journeys, and create relevant offers that increase satisfaction and conversions.
What role does a CDP play in customer experience management?
A customer data platform (CDP) unifies data from all customer touchpoints into a single, actionable profile. This gives marketing, sales, and support teams a consistent view of each customer, enabling real-time personalization, predictive modeling, and omnichannel orchestration that would be impossible with siloed data systems.
Related Articles
- How to Deliver Real-Time Personalized Experiences With a CDP — The activation side of CX, step by step
- Customer Experience Management: Omnichannel Guide — Managing CX consistently across channels
- How to Use a CDP for Customer Journey Orchestration — Sequencing interactions once the data is unified
- How AI Is Redefining the CDP — The platform shift behind agent-run customer experience