- Tension: Brands collect unprecedented volumes of behavioral data yet still treat loyalty as a transactional punch card.
- Noise: The industry obsesses over IoT’s data volume while ignoring the structural inability to act on what devices reveal.
- Direct Message: Data without operational integration produces surveillance, and customers can tell the difference between tracking and caring.
To learn more about the DM News editorial approach, explore The Direct Message methodology.
Across retail, hospitality, automotive, and consumer electronics, a conspicuous pattern has taken shape: brands are enrolling customers in loyalty programs at record pace while simultaneously losing the ability to make those programs feel meaningful.
Connected devices, smart appliances, wearable sensors, and in-store beacons now generate behavioral signals at a granularity that would have seemed fantastical a decade ago. A refrigerator can report consumption habits. A fitness tracker can surface health routines. A connected car can map daily commutes down to the minute.
The irony is difficult to miss. The same era that handed marketers an almost omniscient data supply also exposed how shallow most loyalty architectures remain. Points, tiers, and generic discount emails persist as the dominant engagement mechanism, even as the data flowing in from the Internet of Things paints a portrait of each customer rich enough to warrant something far more personalized.
The gap between what brands know and what they do with that knowledge has become the defining failure of modern loyalty strategy.
The widening canyon between data capture and customer care
The tension at the center of this problem runs deeper than a technology shortfall. Loyalty programs were originally designed around a simple premise: reward repeat purchases to encourage more of them. That logic made sense when data was scarce and customer touchpoints were limited to the point of sale.
But IoT has fundamentally altered the information landscape. Devices embedded in products, homes, and public spaces now transmit continuous behavioral data, often without the customer consciously providing it. The result is that brands possess an extraordinarily detailed view of how products are used, when they fail, what adjacent needs arise, and how daily routines shift over seasons.
Yet most loyalty infrastructure was built for a different era. The databases, segmentation models, and communication triggers that power these programs were engineered to respond to transactions, not to ambient behavioral signals.
A white paper published by SAS examines how IoT provides marketers with significantly more data about consumer behavior but stresses that realizing value from that data requires event-based and real-time marketing capabilities. Without those capabilities, the data accumulates in warehouses, technically accessible but operationally inert. The paper underscores a challenge that many marketing organizations still have not resolved: collecting signals and acting on them are fundamentally different competencies.
The disconnect creates a peculiar customer experience. A consumer who owns a smart thermostat, for example, might generate thousands of data points about heating preferences, occupancy patterns, and energy consumption. The manufacturer’s loyalty program, meanwhile, sends a quarterly email offering 10% off a second thermostat. The data says the customer needs a filter replacement, or that their energy usage spiked in a way that suggests a maintenance issue. The loyalty program says, “Buy more.” The canyon between what the data reveals and what the program delivers erodes trust incrementally. Customers sense, even if they cannot articulate it precisely, that the brand knows more than it lets on and chooses to use that knowledge for upselling rather than genuine support.
The industry conversation that keeps missing the point
Much of the discourse around loyalty and IoT focuses on the wrong problem. Conference panels and trade publications frequently frame the challenge as one of data volume: too much information, too many streams, too complex to integrate. This framing flatters technology vendors selling integration platforms but obscures the more uncomfortable truth, which is that the structural incentives within most organizations actively prevent loyalty programs from becoming useful.
Consider the manufacturer-retailer relationship. Manufacturers want to understand how end customers use their products; retailers guard customer purchase data as competitive advantage. The customer, caught between these two entities, experiences the friction firsthand: contacting a retailer about a warranty that the manufacturer controls, receiving conflicting messages from both, and finding that the loyalty program administered by one party has no awareness of interactions with the other.
Zsuzsa Kecsmar, Chief Strategy Officer of Antavo AI Loyalty Cloud, captures the paradox concisely: “Loyalty programs are everywhere, but loyalty isn’t.” The observation points to a saturation problem that compounds the data problem. When every brand operates a loyalty program, the programs themselves become noise. Customers enroll, collect points passively, and rarely feel that the program recognizes them as individuals. The addition of IoT data was supposed to solve this by enabling hyper-personalization. Instead, it has largely added complexity without adding meaning, because the organizational structures, data-sharing agreements, and real-time decision engines required to translate device signals into genuinely helpful loyalty interactions remain underdeveloped at most companies.
The trend cycle amplifies the confusion. Each year brings a new buzzword layered onto loyalty strategy: gamification, blockchain-based rewards, AI-driven personalization, and now IoT-enriched engagement. Each promises transformation. Each, in practice, tends to be bolted onto existing program architectures that were designed for a simpler time. The fundamental question of what a customer actually needs from a brand after purchase gets buried under layers of technological enthusiasm.
Where the real shift begins
The brands that will earn genuine loyalty are those that use device-level data to anticipate customer needs and resolve friction before the customer even recognizes the problem, turning passive data collection into active care.
The insight here challenges a widespread assumption. Most organizations treat IoT data as a marketing asset: something to be mined for targeting opportunities, campaign triggers, and segmentation refinements. The reframe positions that same data as a service asset. The distinction matters because it changes what success looks like. In a marketing frame, success means higher open rates, better conversion, and increased program engagement metrics. In a service frame, success means fewer support tickets, longer product lifespans, and the kind of quiet satisfaction that turns an owner into an advocate without ever requiring a points balance.
From ambient surveillance to ambient service
Translating this insight into operational reality requires changes at several levels, and none of them are primarily technological. The first is organizational. As long as loyalty programs sit within marketing departments whose performance metrics revolve around campaign ROI and customer acquisition cost, IoT data will be treated as another input for promotional messaging. Moving loyalty into a cross-functional position, one that bridges marketing, product, customer service, and supply chain, allows device data to flow toward whoever can act on it most effectively.
The second change involves data governance between commercial partners. The CMO Council research referenced earlier describes the need for a “single pane of glass” between manufacturers and retailers: a shared data environment that allows both parties to see relevant customer interactions without either surrendering full control of their proprietary information. This kind of architecture remains rare, in part because the business models of retailers and manufacturers create competing incentives.
The third change is philosophical. Loyalty programs were born from a scarcity mindset: brands assumed customers needed to be incentivized to return. IoT data reveals that many customers already want to stay; they leave because post-purchase experiences are frustrating, impersonal, or invisible. A connected dishwasher that detects a failing pump and triggers a proactive service appointment through the loyalty app does more for retention than a thousand points ever could. That scenario is technically feasible today. The barrier is rarely the sensor or the software. The barrier is that most loyalty program owners have no line of communication to the product engineering team, no access to device telemetry, and no mandate to solve service problems.
The question facing every brand that operates both a loyalty program and a connected product portfolio is straightforward: does the data flowing from those devices serve the customer’s experience, or does it serve the brand’s next campaign? The answer, visible in the structure of most programs currently in market, leans heavily toward the latter. Shifting that balance represents the most significant loyalty opportunity of the current decade, and it requires no new sensors, no additional data, and no technological breakthrough. It requires the willingness to treat what devices already know as a responsibility rather than an asset.
