I’ve seen adtech chase the same dream for a decade: the promise that one more data source, one more audience segment, will finally unlock perfect precision. As product leaders, we were all part of a race to integrate the next great audience feed, the next behavioral signal, the next predictive attribute. We believed that with enough volume, a perfect picture of the consumer would emerge.

But the opposite is happening.

More signals are adding more noise. The 15th signal telling you someone is a “car buyer” rarely changes an outcome, and the complexity tax we pay in time, cost, and confusion is killing our ability to move fast.

Faced with this reality, my team and I made a bold, transformative decision. Instead of adding a 16th data integration, we rebuilt our planning system from the ground up, focusing on the fusion of two core, orthogonal signal sets: online behavior and real-world mobility.

The signal bloat problem

Audience signals keep multiplying, but precision isn’t. I see three recurring system failures:

1. Redundant inputs: Each new data source largely overlaps with existing ones. Your 20th feed adds rounding-error reach once you de-duplicate, not incremental value.
2. Correlation isn’t insight: Correlated signals produce the illusion of precision. A “hyper-targeted” segment of ten million people isn’t precise; it’s mass marketing with a fancier label.
3. Channel mismatch: We’re investing heavily in channels like CTV and DOOH where targeting mechanics are fundamentally different. The unit of planning is no longer a “micro-audience everywhere,” but fit-for-channel reach and business context, market by market.

And a fuzzy question often invites detailed irrelevance. “Grow in Florida” isn’t a brief. This is:

“With Chick-fil-A gaining share across Miami-Dade, our Doral location is particularly soft on late-night visits. We need to elevate brand consideration among after-hours students and service workers within 15 minutes.”

Signals only matter if they sharpen that kind of decision. You don’t need a 16th data integration. You need a sharper question.

Start from the business. Audience is the answer, not the brief.

Advertisers don’t buy audiences; they buy business outcomes. The same brand needs a completely different strategy depending on the local context: competitive pressure, brand strength, and consumer habits.

This is why we architected our entire system around Business Context Planning.

The first question isn’t who, but where and why.

To do this, we had to move beyond our legacy as mobility experts.

The single biggest transformation my team shipped this year was building a system to unify that decade of ground-truth data with its digital counterpart. Adtech has always treated these as separate domains, reflecting how our industry was built, not how consumers actually live.

• Online signals (web traffic, engagement) are the best proxy for intent.
• Offline signals (store visits, mobility) are the ultimate ground truth of economic activity.

The breakthrough is not in analyzing them separately, but in fusing them into a single, cohesive view of a brand’s commercial reality. Instead of chasing endless attributes, we built a system that maps the entire customer journey using just four powerful, unified indicators:

1. Awareness (Online): A brand’s share of web traffic in a given city, measuring its digital-shelf presence.
2. Engagement (Online): The rate of meaningful on-site interactions, separating passive curiosity from active consideration.
3. Attractivity (Offline): A brand’s share of foot traffic to its physical locations—the real-world market share.
4. Preference (Offline): The visitor overlap with competitors, revealing where the battle for loyalty is being won or lost.

Mapping these four metrics moves us from abstract audience labels to a concrete, actionable diagnosis of the local business problem.

Omni Planner in practice: from diagnosis to action

This “less is more” philosophy is the engine behind our Omni Planner. It’s designed to turn this unified signal set into a plan you can launch, and launch fast.

Let’s make this real. Imagine an automotive brand launching a new EV in Chicago.

The old approach would be to buy a national audience of “EV Intenders” and target them across all channels. It’s a blunt instrument.

Our Omni Planner, powered by this fused On+Off data, does something radically different.

First, it analyzes the Chicago market through our four-metric lens:

• Insight 1 → High-Awareness / Low-Engagement Zone: In one cluster of northern neighborhoods, we see strong web traffic share but weak on-site interaction. Offline, the nearby dealership underperforms on foot traffic compared to a key competitor. The diagnosis: People know the brand, but they aren’t seriously considering it or visiting. The audience job is mid-funnel conversion.
• Insight 2 → Low-Awareness / Strong-Fit Zone: In another catchment to the west of the city center, awareness is low, but engagement rates are high among those who do visit the site. Offline, the local dealership converts well with loyal visitors and low switcher rates. The diagnosis: A strong product-market fit that lacks awareness. The audience job is upper-funnel demand creation.

These are two completely different business problems within the same city, invisible to any plan based on a single audience segment. Once the fused on- and offline signals surface these contrasting realities, the omnichannel plan naturally diverges.

• In the high-awareness but low-engagement zone, broad awareness tactics like CTV would be wasteful. Instead, we’d focus investment where intent can be converted, deploying high-impact DOOH near competitor clusters and running hyper-local digital campaigns to devices seen in those areas, driving to richer online experiences and stronger engagement.
• Meanwhile, in the low-awareness but high-fit zone, the challenge flips. This is where we need to build the brand. Here we’d activate CTV across the most relevant ZIPs to grow reach, using local unique-reach optimization to fill the top of the funnel and bring more qualified audiences into the discovery phase.

This is what it means to make audience a response to brand context. The where (the specific local business challenge) determines the who (the right audience) and the how (the right omnichannel levers).

Clarity over complexity

Unifying these two fundamental datasets has allowed us to deliver something I believe the industry desperately needs: relevance to the brand context. relevance.

A compact, explainable signal set, rooted in business reality, beats a sprawling catalog of lookalikes every time. You can build a plan in hours, not weeks. You can explain it to a CMO in a single chart. And most importantly, you can launch it, measure the impact on both online and offline behaviors, and learn.

This is the Plan ▸ Activate ▸ Learn loop our platform is built to accelerate. It’s not about finding more data. It’s about having the right data, fused into a single source of truth, to give you direction.

Less noise. More signal. Better outcomes.

We’ve built our teams into highly specialized, channel-specific experts. We have a CTV team focused on reach, a DOOH team focused on high impact locations, and a performance team (Display, Social) focused on conversion.

MMMs provide the national blueprint. But driving growth across a country means translating that strategy with actionable Media Receptivity signals.

The Humble Zip Code

70% of consumers expect a seamless experience across channels. 72% use their smartphones in-store to check reviews or offers. And 69% still shop primarily in physical stores.

Locala’s Retail Insights Barometer 2025 reveals major shifts: shopping is now fully omnichannel. Consumers move between digital and physical touchpoints without noticing the boundaries. For marketers, that means the old way of planning, by channel, by broad audience, by national activation, is no longer enough.

Consumers don’t buy on average. They buy in specific cities, catchment areas, and moments. The challenge for brands is adapting strategy to this hybrid, mobile, and local reality.

How planning has shifted

Three major shifts are reshaping media strategy:

• Signals surpass IDs. Privacy ended the dream of perfect targeting. What scales today are business signals:  who captures attention online, who drives visits offline, and how those patterns shift.
• Channels converged; measurement didn’t. Mobile, CTV, DOOH, and social all deliver value in isolation, but measurement remains fragmented. Marketers need a connected view linking early intent with real outcomes.
• Local dynamics drive national results. Even in the same region, a brand may face very different objectives: consolidate in one area, conquest in another, and defend elsewhere. One-size-fits-all planning is costly.

The new priorities for advertisers

To keep pace, marketers must focus on four priorities:

• Speed to signal: catch intent early, interest, engagement, traffic, and respond quickly.
• Outcome clarity: link upper-funnel attention to store visits and brand preference, not just clicks.
• Orchestration, not fragmentation: use each channel for its role in the local context.
• Repeatable playbooks: scale strategies without losing relevance.

Our answer: Omni Planner

This is why Locala created Omni Planner, a new layer inside Locala Planning. It unifies online signals with offline outcomes on the same canvas, at the city and zone level, and turns them into actionable strategies.

Four key indicators mirror the consumer journey:

• Awareness (online traffic share)
• Engagement (website engagement)
• Attractivity (store traffic share)
• Preference (store switcher rate)

Online without offline is incomplete. Offline without online lacks context. Together, they shape smarter, outcome-driven plans.

Why this changes the game

Locala Planning brings a unified workflow where online intent and offline impact meet locally. Budgets follow contextual opportunities, not just CPMs. Strategies become both scalable and locally nuanced.

The future of media is not about chasing the cheapest impression. It’s about aligning with how people actually shop: omnichannel, mobile, and local. The brands that adapt will be the ones that thrive.

 

I’ve shipped more insight decks than I can count. Some were genuinely sharp: clean maps, tidy funnels, a couple of “aha” overlaps between market intelligence and audience patterns. People nodded. Screenshots got copied into eleven other documents. Then… nothing changed. Budgets didn’t move. No new tactic went live. I don’t regret the craft, but I do regret the outcome: pretty narratives with no operational spine.

If that sounds familiar, you’re not alone. In the real world of the AAA trinity (advertiser, agency, adtech), it’s the simple, practical stuff that kills momentum.

• You go hunting for the one audience the deck depends on (say, “switchers near priority stores from the last 90 days”) and discover it’s named differently or doesn’t exist across partners: a third-party segment in one DSP, a 6,000 users lookalike somewhere else, a taxonomy that maps poorly, and often.. x3 the CPM.
• Then the geo-targeting: the plan says “12-minute drivetime around these places”, but your platform only supports postcodes, so someone spends a day hand-building circles on a map, cleaning duplicates, reformatting place lists, and re-uploading after a reject.
• Meanwhile you’ve promised to adapt locally (let’s say, by city), but you don’t actually have fresh insights on your own brand per market, so “localization” becomes guesswork and templates.

By the time audiences, geos, and “we’ll tailor per sub-goal” are reconciled, the campaign has likely ended. At Locala, we’ve had the time (and scars) to study why this happens and, with that maturity, we rebuilt our approach so the work doesn’t stall between “insight” and “go live.” The short version: we stopped optimizing for great slides and started engineering for time-to-flight.

What “insight decks” get wrong (and why most plans stall)

Over the years, I’ve seen three very common planning traps across digital advertising, not Locala-specific, just industry-standard habits that quietly kill momentum:

1) Treating audiences as the brief. Plans that start and end with “Who’s our audience?” ignore the real brief: the business job by market. The job changes block by block, defend leadership here, grow there, conquest across that corridor. If the question changes by place, your audiences, budgets, messages, and surfaces must change too. Audience is the answer, not the brief.

2) Splitting one insight per slide instead of building a unified view. A chart of traffic share vs competitors. A map of cross-visitation. A table of affinity scores by categories. Useful on their own; misleading in sequence. Strategy needs everything in one frame at once: brand + competitor, macro + granular, audiences + channels, so you can resolve conflict and trade-offs before you touch a budget.

3) Stopping at “interesting,” which is hard (or impossible) to activate. “Interesting” doesn’t move a pixel. Only mandates do: where to lead/defend/grow/conquest, how to weight budget by tier, which channels unlock the job, which audience to talk to, geo-targeting to deploy, which creative to rotate. If a finding doesn’t collapse into a rule I can push to activation easily, it’s more of a nice slide than a useful strategy.

Locala’s evolution: from “interpret these” to “switch this on”

I’ll be direct about us. For years, audiences sat on one side and market insights sat on the other. Even with our great and innovative planning approach, we still asked teams to bridge the last mile: interpret, rebuild, and re-enter it all in activation tools.

Two things happened at once that changed our posture (and mine). We onboarded our online dataset, finally letting us see digital signals next to real-world ones and I moved from Insights Manager to Product Marketing. Perfect timing. I could take the learnings from insight-only workflows and turn them into product requirements: one place for truth, fewer handoffs, and a plan that doesn’t stall between “interesting” and “live.” That’s the moment we decided to stop shipping decks and start shipping decisions you can switch on.

The product principles that birthed Omni Planner

When Baptiste Bernard and I started sketching the earliest concepts, I asked one annoying question on repeat: “How do we translate so many signals into something anyone can grasp, and that actually guides the next step?” (we’re talking billions of signals here). The answer couldn’t be “another dashboard.” It was leading us to a different way to build our solutions:

• Activation-first. Begin at the end. What media decision should this view produce, and how do we push it live in a single motion?
• Automate the bridge. Shrink the gap from planning to activation, no downloads, no manual rebuilds across platforms.
• One home for truth. Regroup all brand insights and audience intelligence so all the learnings we need are centralized, and tactics are applied in one place.

We also had to unlearn an old reflex: adding features to show more insights. In adtech, that’s friction. The new rule we hold ourselves to is simple to say and hard to build: if the tool can read a signal, it proposes the next step and makes it easily pushable.

The result is Omni Planner: our On & Off unified view and location-based advertising expertise expressed in a single feature. It puts market context and audience logic on the same rail, and it’s opinionated about what to do next using machine learning. That’s not only a nicer UX, it’s us reinventing the space so strategy and activation finally live together.

The Omni Planner shift

1) Unified + Granular Benchmarks Everything sits together: brand + competitor in the same view, from global context down to local markets. You see the whole picture at once, no slide-by-slide archaeology, so trade-offs are resolved before a single euro or dollar moves.

2) Insights → Activation (built-in) When Omni Planner reads a signal, it interprets the business context meaning and translates it into the next step automatically. That means:

• Allocate where needed with explainable weights tied to business reality.
• Propose the right, business-driven audience mix (e.g., loyalists to sustain, lapsed to re-engage, competitive switchers to win back) derived from local context, not a generic 25–54yo.
• Auto-build geo-targeting from real movement (trade areas, competitors POI..) instead of arbitrary circles or postcode hacks.
• Output everything in a pushable format (audiences, shapes, pacing, mixes) that DSPs can ingest, to cut “time-to-flight” from weeks to hours.

Because brand insights and audience insights live together, the path from “we’re underperforming here” to “we’re live with a better plan” is just one step.

TL;DR

What changes for our advertisers, concretely starting now:

• Time-to-flight → Hours, not weeks. Brief in, decisions out, campaigns live, without rebuilding yourself in five tools.
• Ease-to-flight → One motion. Omnichannel signals in one place, translated to tiering, budgets, audiences, geo-areas, and channel stacks you can push.
• Decision coverage → Most of your spend governed by explicit rules. Fewer “custom one-offs,” more repeatable success.

What we do differently:

• We don’t sell generic audiences divorced from the job.
• We don’t accept arbitrary circles that ignore real mobility.
• We don’t pretend a single national plan is “local” because the slide title says so.
• We don’t call a chart “strategy” unless it resolves into a rule with a path to activation.

Why this matters now: IDs fragment, lookalikes converge, platforms abstract what used to be visible. The answer shouldn’t be “collect more signals.”, but to express a sharper point of view per market, and wire that POV into the tools that spend your money.

With Omni Planner, brand + competitor, global + hyperlocal, unified + smart live in one place, and the tool translates signals into next steps you can push. That’s what we’re building at Locala. If you’re stuck in the “insights that don’t move” loop, send us a brief. I’ll bring a plan that flips the default from tell me more to turn it on.

For years, audience targeting has shaped how we plan media.

Marketers build segments, define profiles, and apply them across territories. It’s logical. It’s scalable.

But in a fragmented, post-ID world, that logic is starting to fall short.

Because what’s really behind those audience segments?

Too often, they’re pre-packaged, created by platforms or third-party providers, with little transparency into how they’re built or how recent the data is. You’re told you’re reaching “shoppers,” “intenders,” or “loyalists”, but you rarely know whether those behaviors are still relevant.

Even with custom audiences, we often rely on socio-demo proxies or outdated behavioral signals.

And with the disappearance of personal identifiers, many marketers are turning to contextual or cohort-based targeting, but with the same logic underneath: → Build a segment. Run it everywhere

Same audience. Same message. Every area.

It feels efficient. But it misses the point.

Because while your audience may be the same on paper, your brand challenges aren’t.

It’s not just who you reach → it’s where and why.

The real issue isn’t just who we target, it’s what we’re targeting for.

Audience segments are just a media response to a business objective. And those objectives can vary dramatically, even for the same brand, in the same country.

• Want to grow your customer base? You’ll look to reach new or underexposed segments.
• Looking to build loyalty? You’ll re-engage existing customers, with tailored creative.
• Facing aggressive competition? You’ll focus on brand switchers or competitor loyalists.

These scenarios require different strategies. Yet, many brands still deliver the same campaign everywhere.

One brand. Multiple local contexts. Different dynamics.

Local dynamics vary, and so do consumers. What works in Lyon may fail in Marseille. What performs in Brussels might flop in Antwerp. Milano and Roma don’t follow the same path to purchase.

Each local context has its own:

• Brand presence
• Shopper journey
• Competitive landscape
• Level of media saturation

So why apply a single targeting logic across all of them?

The Business Context Planning imperative

At Locala, we believe the next big shift in media isn’t just about better audiences, it’s about smarter planning. That’s the idea behind Business Context Planning.

The media planner’s role is no longer to chase IDs, but to orchestrate campaigns based on market-specific business signals.

That means understanding, for every geography:

• Your brand’s performance vs competitors
• Who you’re reaching, and who you’re not
• Where growth, loyalty, or conquest opportunities lie
• How to act on those signals across channels

Because media planning shouldn’t stop at insight, it should tell you what to do next.

Other platforms optimize audiences. We optimize brand outcomes.

From insight to action: Omni Planner

To make this vision real, we built Omni Planner: the first tool to operationalize business context planning at scale.

It doesn’t just show you where you’re strong or weak. It translates signals into actionable, local media strategies, by bridging online and offline signals for your brand and its competitors.

• In Chicago, you’re a category leader but engagement is soft → we deploy a consolidation strategy with high-frequency, upper-funnel formats.
• In Detroit, your competitor is gaining ground → we run a conquest strategy with broader reach and price-focused creative on mobile and Meta.
• In Cleveland, online traffic is high but footfall is low → we activate a drive-to-store mix using DOOH and geo-mobile.

Omni Planner helps marketers zoom in on the brand’s local context, assess audience relevance, and deploy tailored, scalable campaigns without media waste.

Rethinking campaign logic

In a world without IDs, your targeting logic becomes your strategic edge. You can’t afford to treat every audience the same, and every territory as equal.

At Locala, we help brands switch from generic targeting to context-driven media strategies, built on real signals, adapted to real-world dynamics.

If you’re done running the same campaign everywhere,

If you’re ready for your media to reflect your brand’s ambition in every local context,

If you want to know where and how to grow, not just who to reach…

Let’s explore how Business Context Planning could improve your brand performance.

 

The Rise of Attention Metrics 

When leveraging ad tech solutions and planning 2024 media strategies, staying ahead means constantly reevaluating the metrics that gauge campaign success. Traditional metrics like viewability and time in view, previously considered benchmarks, are now being supplemented with more comprehensive measures to truly grasp user engagement.

Enter Attention metrics. These metrics go beyond simply noting if an ad was viewed; they provide insights into the depth and quality of user interaction with the ad. This shift is not just theoretical but is being embraced by industry leaders. The Interactive Advertising Bureau (IAB) has acknowledged Attention metrics as a critical evolution in ad measurement. Several key factors are propelling this shift:

• Linking Campaigns to Business Outcomes: Attention metrics show a stronger correlation with business outcomes than other measurements, with evidence of a significant impact on brand lift, consideration, and sales uplift.
• Unlocking Creative Potential: Recognizing that 70% of advertising success is due to the creative, attention metrics are gaining interest for evaluating creative effectiveness.
• Optimizing for Channels: Attention measurement helps gauge the effectiveness of various channels, like CTV, where high viewer engagement is noted.
• Reducing Waste: Advertisers can reduce budgets wasted on ad creative and placements that do not secure sufficient attention. In an environment where budgets are tight, any saving is welcomed.

Locala’s Integration with DoubleVerify  

Locala’s integration with DoubleVerify places it at the vanguard of attention-based advertising. By combining advanced Attention metrics with Locala’s unique offerings like Dynamic Commerce Areas and precise audience segments, advertisers can significantly enhance their campaign performance and media quality. 

At DoubleVerify (DV), pioneers in this field, Attention measurement is a sophisticated process. DV has determined that the most effective method to assess attention involves evaluating various detailed data points at the individual impression level, which can be compiled into practical metrics. DV Authentic Attention®, a privacy-conscious and MRC-accredited attention measurement solution that operates independently of cookies, examines more than 50 data points related to a digital ad’s exposure and the user’s interaction with the ad and their device, doing so in real-time.

• In terms of exposure, DV evaluates the complete presentation of an ad, measuring its strength and visibility using metrics such as the time the ad is viewable, its proportion of the screen, the quality of the video presentation, and its audibility, among others.
• Regarding engagement, DV analyzes essential actions initiated by the user during the display of the ad creative. This includes interactions such as user taps, changes in the screen’s orientation, video playback, and adjustments in audio settings.

These metrics of Exposure and Engagement collectively contribute to the DV Attention Index, a comprehensive indicator of attention that offers vital insights into the effectiveness of a campaign.

Incorporating these sophisticated Attention metrics, Locala enhances its strategic offerings. Advertisers can now enjoy the benefits of campaigns that are not just targeted, but finely tuned to capture and hold consumer attention, leading to improved brand outcomes and ROAS. These metrics also aid in making informed decisions about channel mix, placement, creative, and format types, tailoring each aspect of the campaign for optimal engagement and visibility.

Conclusion

Attention metrics are more than a buzzword; they are essential tools for understanding and optimizing ad campaigns. Locala’s integration with DoubleVerify’s solutions exemplifies industry best practices, where quality of engagement trumps quantity. 

For media strategists and advertisers, these developments offer an exciting opportunity to refine their strategies for maximum impact. We encourage readers to explore further, using Locala’s case studies to see how these innovations can be applied to their advertising strategies.

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 “As an Insights & Analytics Lead at Locala, I’ve had the privilege of witnessing firsthand most of recent transformative shifts in the adtech landscape. One area that has seen significant evolution is Digital Out of Home (DOOH) advertising. Until recently, DOOH buying was largely influenced by the environment of the screens (whether they were located in malls, train stations, or other high-traffic areas..) and probable affinity to certain audiences based on traffic patterns at specific times of the day. While effective, this approach often missed the intricate nuances of local brand preferences”.

 

The Landscape of DOOH Buying

DOOH advertising has experienced rapid growth. According to Statista, the global digital out-of-home (DOOH) advertising revenue is projected to grow by over 10 percent in 2023, reaching almost €16.48 billion. This significant increase in investment highlights the importance and potential of DOOH in the modern advertising mix. However, with increased investment comes the need for more sophisticated strategies.

The traditional approach, while effective in its own right, often missed the mark when it came to understanding and leveraging local brand affinities. Every region, city, and even neighborhood can have distinct brand preferences and shopping patterns, influenced by a myriad of factors from cultural nuances to economic conditions.

The Shift Towards Local Brand Affinity

Locala is proud to introduce a new planning capability that allows DOOH screen selection based on screen affinity with a chosen brand, a feature we call Dynamic Commerce Area (DCA). DCA is a revolutionary approach to DOOH advertising. It enables brands to select DOOH screens based on their affinity with specific brands, ensuring that the advertising message resonates with the local audience.

With DCA, brands can redefine the way they approach DOOH advertising. By focusing on local brand affinity, our partners can now craft more strategic and impactful campaigns, with data at its core. This approach not only ensures that the advertising message is relevant to the local audience but also maximizes the return on investment for advertisers.

Here’s why this approach is transformative:

• Performance-Driven Campaigns: By understanding where brand affinity is strongest, advertisers can ensure their messages resonate deeply with local audiences, leading to higher engagement and ROI. 
• Strategic Expansion: For brands that are already dominant in specific regions, targeting areas with lower brand affinity can be a strategic move to capture new market segments. 
• Competitive Conquesting: Knowledge of areas with high affinity to competitors provides an opportunity to deploy targeted campaigns aimed at swaying audiences and increasing market share.

Benefits for Advertisers

• Smarter, Data-Driven Investments: With insights from our Retail Analytics platform, advertisers can make informed decisions based on consumer shopping behaviors, both nationally and locally. This ensures that investments are not just vast but also strategic.

• Enhanced Ad Targeting: By understanding where brand affinity is strongest and combining it with foot traffic data and local demographics, campaigns can be crafted that deeply resonate with local audiences. 
• Optimized Inventory Selection: Our insights consider traffic patterns leading to specific stores, ensuring that the selected inventory is not only relevant but also timely. 
• Seamless Activation: Our solutions facilitate the seamless activation of DOOH campaigns fueled by mobility patterns, going beyond traditional geotargeting with custom media strategies tailored for each location.

The Bigger Picture

The trends in DOOH are clear: there’s a move towards more personalized, data-driven strategies and overall measurement. Media decisions fueled by local insights, and granular attribution capabilities are just a few of the innovations we’re seeing creating. In conclusion, as we’ll continue to invest and innovate in DOOH, it’s imperative to keep data at the center of our strategies.
DOOH planning isn’t just about reaching more people; it’s about reaching the right consumer with messaging that truly resonates. The future of DOOH lies in harnessing the power of local insights, and with Locala, that future is now.