The Marketing Ecosystem in Flux: From Linear Paths to Fluid States
Marketing plans once treated attention like a tidy relay race baton but today it slips between screens, formats, and intents so quickly that stages blur into seconds and outcomes hinge on whether a brand recognizes the moment before it disappears into the next swipe. That reality has put pressure on the century-old funnel, which mapped a steady march from awareness to consideration to purchase. The latest cross-market evidence shows that the map no longer fits the territory.
Rather than asking consumers to climb stages, commerce now meets them in shifting states—watching, browsing, buying—that cycle multiple times within an hour. Exposure on connected TV can spark search on a phone and trigger a purchase inside a social app before attribution systems can blink. This report examines how that shift reframes planning, creative, and measurement, and why a state-based model better reflects the signals marketers can actually see and act on.
Industry Scope: Segments, Screens, and Stakeholders
The analysis spans household-level behaviors across millions of homes and two large surveys of consumers and marketers in mature advertising markets. It focuses on the interplay among connected TV, mobile, social platforms, and AI interfaces that increasingly mediate discovery and purchase. Retailers, direct-to-consumer brands, app publishers, and media owners are the primary stakeholders, with agencies and ad tech vendors as operational enablers.
Segments behave differently by age and context. Under 24, viewing tilts toward paid streaming, YouTube, and social; older audiences maintain heavier linear TV habits. Yet device mixing collapses these differences, because simultaneous usage—particularly TV plus phone—becomes a common denominator that unites disparate cohorts in shared real-time behaviors.
Technology Stack Shifts: Identity, Clean Rooms, and Agentic Advertising
Three stack changes underpin the state shift. First, identity resolution is fragmenting as cookies deprecate and platform identifiers tighten, forcing reliance on modeled reach and privacy-safe joins. Second, data clean rooms move from experiment to infrastructure, enabling cross-party collaboration without raw data sharing. Third, agentic advertising emerges, where bidding, pacing, and creative selection adapt autonomously to short-lived signals.
Collectively, these shifts move activation from static audience segments toward context-aware decisioning. The systems that thrive are those that interpret state from sparse, fast signals—co-viewing probabilities, session recency, device pairings—and that can coordinate creative and frequency across walled and open ecosystems.
Why the Funnel Persists—and Why It’s Breaking
The funnel persists because it simplifies budgets, ownership, and scorekeeping. It assigns channels to roles, teams to stages, and metrics to dashboards, producing order in a messy world. However, the same rigidity now breaks performance. When passive “watching” frequently jumps straight to buying, classifying TV as awareness-only leaves money on the table and misprices valuable moments.
Moreover, sequential logic ignores how quickly intent cools. With most viewers second-screening and many abandoning mid-journey without prompts, delayed retargeting and siloed channel strategies arrive too late. The funnel’s backbone—time—no longer stretches long enough to hold it together.
What’s Driving the Shift to State-Based Marketing?
Rapid Behaviors and New Interfaces Reshape Demand
Short-cycle behaviors are the catalyst. Consumers report switching digital activities at least once per hour at striking rates, and many describe purchase paths as random. This is not aimlessness; it is responsiveness—reacting to content, context, and convenience in minutes. A product seen on TV becomes a mobile search; a creator review becomes a one-click buy in the same app.
New interfaces tighten the loop further. Within social platforms, discovery, validation, and checkout live side by side. AI assistants compress research by summarizing reviews and suggesting options, often shepherding buyers directly to shoppable links. Demand is not built step by step; it is sparked, shaped, and closed inside a handful of interactions.
By the Numbers: Cross-Screen Activity, Social Commerce, and AI Adoption
The measurement backbone confirms the pattern. In any given 30-minute window, large shares of the audience are simultaneously watching, browsing, and buying, with significant proportions flipping states before the half hour ends. Within an hour, most remain in watching, but a notable slice toggles to buying or back to browsing, underscoring constant churn.
Second-screening is the rule, not the exception: more than nine in ten viewers use a second device while watching TV, with CTV plus mobile as the dominant pairing. Among younger consumers, social apps now house the full journey, and a majority have completed in-app purchases. AI shopping assistance has moved into the mainstream, with usage highest in younger cohorts and additional growth expected in the near term.
Friction Points and Failure Modes in a State-Shifting Market
Attribution in a Multi-Screen Minute: The Visibility Gap
Attribution cracks under multi-screen simultaneity. A CTV impression may initiate curiosity, mobile search may nurture intent, and a social checkout may capture the sale—each platform logging a partial truth. Single-channel views either inflate last touch or diminish earlier influence, especially when walled environments do not expose granular paths.
The visibility gap widens as AI mediation grows. When an assistant drives recommendation and link-out behavior within its own interface, standard tags and identity graphs rarely capture the chain, pushing marketers to modeled lift and experiment-driven inference rather than deterministic joins.
Retargeting Under Time Pressure: Speed, Frequency, and Fatigue
The abandonment rate reframes retargeting as a race. Most shoppers who pause mid-journey rely on prompts to return, but attention decays quickly. Retargeting must trigger fast—often within minutes—to convert residual curiosity before it cools, and it must cross devices to reach the screen where the user currently is.
Frequency control is equally tight. Overexposure breeds fatigue when cycles are short, yet underexposure loses the fleeting window. Batch audience refreshes and siloed setups can neither move fast enough nor calibrate intensity, explaining why many marketers report inconsistent retargeting outcomes.
Data Fragmentation and Identity Deprecation: Practical Workarounds
Data fragmentation is structural. Cookies fade, device IDs fluctuate, and cross-app journeys hide inside platforms. Workarounds rely on probabilistic links, publisher and retailer clean rooms, and modeled reach and frequency that treat precision as a spectrum instead of a switch. Identity becomes an ensemble, not a single key.
Operationally, this means shifting resources into privacy-safe collaboration and experimentation. Geo splits, time-based tests, and incrementality frameworks supply truth in the absence of perfect joins. While they trade granularity for validity, they align better with real consumer behavior than brittle last-click chains.
Creative and CX Mismatch: Turning Passive Watching into Purchase
Creative strategies lag behind states. Many campaigns treat passive viewing as awareness-only, missing the documented jump from watching to buying. Designing TV and video for immediate action—QR codes with real utility, clear incentives, and synchronized mobile handoffs—unlocks that path.
Customer experience either completes the arc or breaks it. Slow sites and complex checkout flows cause high drop-off, which shortens the retargeting window and reduces total conversion opportunities. Investment in performance UX—load speed, one-tap pay, cart persistence—becomes a media multiplier rather than a separate line item.
Rules, Walled Gardens, and the Measurement Reform Agenda
Privacy and Identity: GDPR, CCPA/CPRA, and Emerging Consent Standards
Privacy laws remain the boundary conditions for state-based marketing. Explicit consent, purpose limitation, and data minimization govern collection and activation, while regional rules vary in strictness and enforcement. This pushes value creation toward techniques that respect user choice and emphasize outcome-based modeling over persistent tracking.
Consent frameworks also evolve in practice. Richer consent experiences, adjustable preferences, and clean auditing trails foster trust. Marketers that align signals and use within compliant scopes can still orchestrate states, but must do so with guardrails designed for user control, not simply for legal coverage.
Platform Policies and Walled Gardens: Limits on Data Portability
Platform policies restrict portability, shaping how far data can travel. Social and retail environments increasingly favor on-platform measurement and conversion, limiting off-platform stitching. As a result, insights and optimization must operate within each garden’s constraints while reserving neutral ground for cross-channel truth tests.
Strategically, this duality encourages modular planning: optimize inside platforms using their best signals while running independent lift studies across regions or time to unify the bigger picture. The aim is harmony, not hegemony—accepting partial paths while resolving impact at the outcome level.
Cross-Media Standards: IAB Incrementality, CIMM, and Clean Room Protocols
Industry standards gather momentum around incrementality and interoperability. Guidance on experiment design, audience splits, and readouts offers a common language for proving lift across TV, digital, and social. Meanwhile, clean room protocols standardize joins and queries so partners can learn together without sharing raw PII.
These frameworks do not solve identity outright, but they reduce confusion and disputes. When brands and publishers test consistently, attribution fights give way to evidence. That clarity unlocks budget movement from awareness silos into state-responsive investments tied to verifiable outcomes.
Security and Governance: Safe Collaboration Without Leaking PII
Security sets the floor for collaboration. Role-based access, limited query templates, differential privacy, and audit logging ensure that joint analysis does not create leakage risk. Governance councils and clear data-disposal rules reinforce trust, which is essential when multiple parties contribute signals to detect and act on states.
The payoff is cumulative. As governance matures, more partners participate, more signals enter the system, and the fidelity of state detection improves. That, in turn, sharpens activation and measurement, creating a virtuous cycle bounded by strict privacy norms.
Where the Curve Bends Next: Scenarios for the Post-Funnel Era
State Detection at Scale: Sensors, Signals, and Real-Time Models
The next bend features state detection that runs continuously. Lightweight signals—content genre, screen pairings, dwell patterns, session recency—feed real-time models that estimate whether someone is likely watching, browsing, or buying now. The emphasis shifts from who the person is to what the moment allows.
Latency becomes a key performance metric. Models must refresh fast enough to catch transitions and to coordinate sequential messages across screens. Wins accrue to systems that balance accuracy with speed and that can trigger cross-device handoffs without violating privacy constraints.
CTV–Mobile Orchestration: From Priming to Instant Conversion
CTV and mobile form the core duet. Creative is composed for call-and-response: the TV spot primes interest with utility-rich cues, and the mobile unit arrives minutes or seconds later with shoppable formats, deep links, or app banners. The sequence compresses discovery and conversion into a single, orchestrated arc.
Success depends on synchronized pacing and frequency. Too early, and the mobile follow-up feels irrelevant; too late, and curiosity fades. That timing is discoverable through experiment-driven windows, then enforced through bidding and suppression that adapt as co-viewing intensity and session recency change.
Social and AI Commerce: Closed-Loop Journeys and New Attribution
Social platforms cement their role as closed-loop commerce engines. Creator content, social proof, and native checkout condense the journey, especially for younger audiences. Attribution inside these gardens becomes more experiment-led, focusing on lift and matched-market designs rather than tag-based reconstruction.
AI commerce introduces a new loop of its own. Assistants turn vague intent into a shortlist, cross-check reviews, and navigate to purchase with minimal friction. Measurement leans on modeled influence and controlled exposures, since many AI surfaces remain opaque to conventional tagging.
Market Disruptors: Agentic OS, Retail Media Convergence, and Global Expansion
Agentic advertising systems disrupt workflows by letting software negotiate supply, craft creative variants, and pace budgets based on moment-to-moment signals. Marketers set constraints and goals; agents handle the rest, particularly where windows of opportunity are short and fragmented.
Retail media converges with upper-funnel channels, extending shopper data and closed-loop reporting into TV and video. Global expansion widens signal diversity as new markets and languages enter state models. The common thread is automation aimed at fluid states, not at static stages.
Strategic Takeaways and Actionable Next Steps
Key Findings in Plain Terms
Consumer journeys no longer line up as steps; they jump between watching, browsing, and buying within the span of a show or a commute. Second-screening is near universal, with TV and phone operating as a pair. Social apps and AI tools now host full journeys, often invisible to tag-based attribution.
Marketers feel the gap. Confidence in measurement is low, retargeting results swing with timing and frequency, and checkout friction kills momentum. The most reliable way forward is to match planning and measurement to states, then verify impact through incrementality rather than path reconstruction.
A State-Based Operating Model: Five Structural Moves
First, treat passive viewing as commercially potent. Build TV and video creative for instant action and measure outcomes, not just reach. Second, elevate social to full-journey status, pairing credibility and native checkout with external priming exposures. Third, track audiences across shifting screens using privacy-safe signals that infer state, not merely static segments.
Fourth, design for the CTV-plus-mobile sequence with synchronized creative and dynamic pacing that respects brief attention windows. Fifth, replace generic attribution with state-aware measurement that blends experiments, modeled paths, sales lift, and customer lifetime value to guide budget decisions.
Investment Priorities and KPIs for the Next 12–24 Months
Investment should tilt toward three layers: signal plumbing, real-time decisioning, and frictionless experience. On signals, prioritize clean room access, retailer and publisher data partnerships, and lightweight telemetry that correlates with state. On decisioning, fund agentic or rules-based systems that trigger cross-screen sequences with minimal latency.
For experience, focus on speed, checkout simplicity, and deep links that jump straight to cart. KPIs should evolve from impressions and last clicks to a mix of incremental lift, state-to-outcome conversion rates, cross-screen handoff success, retargeting recapture within defined windows, and downstream value indicators like repeat rate and LTV.
Risks, Caveats, and How to Pilot Without Overreach
Risks include overfitting to noisy signals, misreading state, and pushing frequency beyond comfort in short cycles. Identity deprecation and walled garden opacity also limit line-of-sight, and a single observation window can skew patterns if seasonality intrudes. These constraints argue for humility in modeling and rigor in testing.
A prudent pilot followed a crawl-walk-run path. Teams began with one or two high-intent sequences—such as CTV-to-mobile for priority products—layered in fast-refresh retargeting, and measured lift with clean control groups. Only after validating timing and frequency did budgets expand to additional states, devices, and markets. In doing so, state-based orchestration proved more reliable than stage-based planning because it met consumers where they were, when they were, and it translated fleeting attention into measurable growth.
