At A Glance
Brands can scale local marketing without losing brand consistency when they separate fixed brand elements from variable local decisions and automate only where the stakes are low. In this Ask the Expert conversation, Experian and Butler/Till discuss how brands can spot real local signals, decide what to automate, and keep people in the loop on decisions that carry brand risk.Key takeaways
- Manual oversight of local marketing tends to break down at around 100 store locations, according to Butler/Till, since decision latency makes it hard to keep pace with simultaneous market-level calls.
- Butler/Till recommends separating fixed brand elements, like voice and positioning, from variable ones, like media mix, audience targeting, and local partnerships, when scaling marketing across many store locations.
- When comparing a local campaign’s performance against a market baseline, a gap of 20% or more usually signals something real, while a gap of just a few percentage points is more often noise.
- Brands running local campaigns across thousands of store locations can automate budget allocation within clear guardrails, but should keep people in the loop on creative selection and other brand-risk decisions.
In our Ask the Expert series, we interview leaders from our partner organizations who are helping lead their brands to new heights in advertising. Today’s interview is with Ryan Lammela at Butler/Till.
When a national brand says it wants to market locally, what does that usually mean to them, and what does effective local marketing require? Where’s the biggest gap between the two?
Most national brands think “local” marketing means communicating the same message with different prices. They want consistency at scale, without surrendering national control. Effective local marketing requires something more demanding: adapting strategy, not just price, to each market’s competitive intensity, seasonal patterns, media preferences, and regulatory environment, while keeping brand integrity intact.
The biggest gap between national and local marketing is structural. Brands underestimate how different markets actually behave. A media mix that works in Seattle might fail in a small rural town in the Mid-Atlantic. Local audiences respond to different messaging angles. The friction comes from centralized decision-making trying to enforce one strategy across fundamentally different market dynamics.
What we’ve found is that successful brands need a framework that distinguishes fixed elements from variable ones. Brand voice and core positioning? Fixed. Media mix, audience targeting, local partnerships? Variable. Without that clarity, you get either chaotic fragmentation or missed local opportunity.
At what point does scale fundamentally change how you have to operate? What starts to break when you move from 50 or 100 locations to tens of thousands of campaigns?
In our experience, the breaking point tends to show up around 100 physical locations. Below that, marketers can still oversee most decisions. Beyond it, you hit the wall: you can’t have people make thousands of media decisions monthly and stay competitive on timing or cost.
Coordination breaks first. When you’re managing multiple channels across multiple markets, decision latency becomes critical; manual approval chains that worked at 50 locations can’t keep pace with thousands of simultaneous market-level decisions. Execution consistency degrades because there’s no visibility into what’s actually running everywhere.
Then measurement becomes a nightmare. You’re collecting data from dozens of sources: platform dashboards, local partners, point-of-sale systems. The noise drowns out signal. Without a consistent way to tie those sources back to the same person or household, you’re comparing apples to oranges across markets.
What’s a pattern that can come to light when you can compare results across thousands of campaigns, something you wouldn’t have trusted from a single market?
When you run 5,000 campaigns across 4,000 locations, patterns emerge that a single market would never reveal. A media mix that looked like a failure in one market? It works in similar demographic clusters. A creative asset that seemed like an outlier? It’s the winner among underserved audiences nationally.
You also spot seasonality patterns you’d miss regionally. When you compare July performance across 2,000 markets, you learn that summer media preferences shift in ways single-market data would dismiss as noise.
Local markets behave differently. How do you decide which local signals are worth acting on versus which are noise, and what data are you leaning on to tell the difference?
Telling a real local signal from noise starts with a baseline: establish expected performance benchmarks across similar market clusters, then look for deviations that are large relative to a market’s normal swing. A gap of 20% or more usually warrants investigation; something in the low single digits is more often noise.
Layer in market context: competitive intensity, demographics, media consumption patterns, seasonality. When a campaign spikes in one market, ask why. Is the market fundamentally different, or are we optimizing for the wrong thing?
Local signals worth acting on are consistent across similar market types, tied to something measurable (seasonal shift, competitive move, audience behavior change), and actionable without breaking brand consistency.
The data that matters most is comparative data, not absolute performance. When Phoenix outperforms Denver on a tactic, and both are similar sunbelt markets, that’s worth investigating.
With that volume of decisions, where do you let the system decide and where do you still want a person in the loop?
Automate based on decision complexity and consequence, not based on volume.
Budget allocation across channels within a market? The system could handle it. The variables are clear, the data is clean, and wrong decisions are recoverable. We set guardrails—don’t shift more than 15% week-to-week, don’t kill a performing channel below threshold—and let optimization work.
Creative selection or messaging? That stays with people. Those decisions carry cultural and brand risk that algorithms can’t weigh. Same with market-level strategic pivots or major partnerships.
Audience targeting is trickier. There’s a lot of data, patterns aren’t always obvious, and bad targeting ripples through the program. We build algorithmic recommendations, but a strategist validates them against market context. The algorithm says shift audience targeting toward women 35 to 44. The person asks why and either confirms the insight or catches something the algorithm missed.
We also keep humans in the loop for anything that breaks the established playbook. When a market starts behaving unexpectedly, we escalate.
The rule: automate routine, standardized decisions with clear success metrics. Keep people in the loop on decisions that shape strategy or carry brand risk.
What have you learned running local programs at this scale that a brand with 50 or 100 locations could apply on Monday?
Brands running campaigns for 50 or 100 locations should start by building their decision framework before they build their system. Know which decisions are local and which are national before you automate them. We’ve seen brands implement tools that actually slow them down because they skipped this step.
Establish market benchmarks now instead of waiting until you’re at scale. Group your locations by similarity and start comparing performance across similar markets. You’ll spot inefficiency fast and understand what good performance looks like in different market types.
Treat automation as a channel tool, not a thinking replacement. Ask yourself what decisions are slowing you down. What insights are you missing because you don’t have bandwidth? Start there, not with the fanciest tech.
Invest in measurement rigor. When you’re coordinating across multiple locations, measurement becomes competitive advantage. Know which metrics matter locally and which are noise. Build data infrastructure to compare performance across markets without creating reporting chaos.
And here’s what matters most: successful local marketing at scale gives local teams better information and faster decision velocity while maintaining brand guardrails. That balance—autonomy with consistency—is where real leverage lives.
Thanks for the interview. Do you have any recommendations for our readers if they want to learn more?
If your brand is managing multiple locations and feeling friction, the question isn’t “should we automate?” It’s “which decisions are slowing us down, and why?” Start there. Talk to teams running campaigns in the field. They’ll tell you where the friction actually is. Then build systems to solve that friction, not to solve a problem you think you have.
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About our expert
Ryan Lammela
VP of Channel Activation, Butler/Till
Ryan Lammela is VP of Channel Activation at Butler/Till, an independent media agency. He leads media execution strategy for brands managing distributed marketing across hundreds or thousands of locations, translating integrated strategy into measurable market impact at scale.
FAQs
Butler/Till defines effective local marketing as adapting strategy, not just pricing, to local market conditions like competitive intensity, seasonality, and media preferences, while keeping core brand voice and positioning fixed. Most brands think local marketing means the same message at different prices, which misses the structural differences between markets.
Manual oversight tends to break down around 100 locations, according to Butler/Till. Below that threshold, people can still review most decisions directly; beyond it, decision latency and inconsistent visibility start to undermine execution.
A performance gap of 20% or more against a market baseline usually signals something real, while a gap of just a few percentage points is more often noise. Butler/Till recommends grouping similar markets, setting expected performance benchmarks, and investigating deviations tied to a measurable cause like seasonality or a competitor’s move.
Budget allocation within clear guardrails is well-suited to automation, since the variables are clean and mistakes are recoverable. Creative selection, messaging, and market-level strategic decisions should stay with people, since they carry brand and cultural risk that algorithms aren’t built to weigh.
Experian’s identity resolution and measurement capabilities help brands tie data from disparate local sources, like platform dashboards, local partners and point-of-sale systems, back to the same person or household. That consistent view is what allows comparative analysis across markets to actually hold up, rather than comparing apples to oranges.
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It’s been over a year since Google announced they’d be deprecating the third-party cookie and in that time there’s been a major focus on two types of cookieless identity solutions. Identity vendors and marketers are strategizing which of these two future solutions best fits their needs so they can achieve privacy-safe scale once third-party cookies are no longer available for use on Chrome. Let’s break down these solutions and the considerations marketers need to take into account when deciding what partners to move forward with in the future of identity resolution. Authenticated Traffic Solutions Authenticated traffic solutions (ATS) are a type of digital identification that asks the end-user to identify themselves via personal information, most commonly email address. Often, you’ll see self-authentication at the point of entry to a website that asks you to create an account or login immediately to access the content you are seeking. E-commerce sites use authentication to keep track of consumer purchases and inform advertising decisions for that customer; and publishers use it to tailor featured content, or, more importantly for this discussion, leverage it within the ad ecosystem for targeting. While authentication can provide very valuable user data for audience segmenting and targeting, it can be limited in scale for a single publisher to leverage and monetize on their own. That’s why some identity vendors have worked to integrate themselves within as many publisher authentication modules as possible, so that they can create an aggregate of scale for the ad ecosystem to tap into. But, even this isn’t going to deliver the reach marketers truly thirst for. Alternatively, Facebook has the scale for authenticated traffic, but they keep their data inside a walled garden, so the utility of those authenticated users is only valuable within the Facebook ecosystem. So how can authenticated traffic solutions increase scale to broaden the scope of identifiers they can collect and leverage? Hint: a few of the biggest players have already figured it out. It’s the single sign-on. Google is probably the largest purveyor of a single-sign on solution that can directly impact advertising capabilities. Can you think of a site you visit that doesn’t offer a sign-in with your existing Google account? It’s a short list. Google has integrated themselves into so many applications and publishers that “Login with Gmail” is just second nature (you pictured the Gmail logo when you read that, didn’t you?). Now, if you’re about to purchase something you found off an Instagram ad, or perhaps a retailer you buy from regularly, you’ve probably noticed options to proceed with your checkout via “Amazon pay” or “Apple pay”. These are also single-sign ons. You’re authenticating yourself through Amazon or Apple to that retailer in exchange for A- the safety and security that Amazon or Apple provide for your financial information and B- skipping the annoying process of manually entering personal information over and over again at point of sale. It’s starting to sound like there’s a lot of authenticated data out there isn’t it? Well, that’s true, but again, Amazon and Apple are walled gardens. Amazon is working diligently to build out their own ecosystem to leverage their content and retail channel data for a holistic offering. And Apple keeps user data very close to the chest, constantly limiting its utility for themselves and advertisers. So what is identity resolution doing about it? The Trade Desk announced their solution; Unified ID 2.0, which promises to leverage email authenticated identity for a truly scaled solution for publishers via Javascript through Prebid. By handing over UID2.0 to an independent unbiased organization like Prebid, The Trade Desk is creating instant scale and trust in their solution. Unauthenticated Traffic Solutions Unlike ATS, unauthenticated traffic solutions do not rely on a log-in to identify a user, but they also don’t rely on third-party cookies. Instead, unauthenticated solutions (UATS) leverage their existing streams of real-time data through Javascript on publisher sites or an SDK (software development kit used by apps). The type of information UATS solutions can collect via Javascript or SDK vary, but it can include IP address, user agent and device level info. But being able to read this information at the point of entry to a website does not make a quality identifier. The best unauthenticated solutions will have the ability to set or ingest this information into a unique ID through an infrastructure with incredibly fast speed that can process trillions of anonymous data signals across multiple channels and devices. And even more so, be able to interpret those signals into a profile using machine learning– all at the moment a user enters a domain. It sounds complicated because it is, but it also has a lot of potential. The identity space cannot rest solely on authenticated traffic solutions, because, as you can see, it could limit ownership and operability to just a few power players/walled gardens. This doesn’t help the larger ecosystem monetize and personalize ad inventory. The right unauthenticated solution, however, can unify cross-device individuals and households at scale, because they’re integrated on the broadest number of publishers/SDKs across platforms, have the best algorithms to build confident connections between identifiers, and are universally transactable across the most common sell and demand side platforms. Think of it as the perfect partner- speaking a common language that everyone in the ecosystem understands and acts on. Today more than twenty cookieless identifiers are available in market for the ad ecosystem, and Google hasn’t even announced a date of deprecation. It’s important to be on the lookout for differentiators like scale and precision. Most importantly, choosing a truly cross-device partner will be key, especially as more digital devices and IDs grow in adoption, like CTV has this past year. 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The Switchboard module will increase the utility and value of the cookieless ID space in conjunction with other addressable IDs, by providing a layer of connectivity that will be natively missing with the deprecation of third-party cookies. Identity solutions at launch: Switchboard for graph customers For existing Tapad customers who leverage the Switchboard module in The Tapad Graph, it will provide a seamless way to facilitate interoperability while resolving identity back to a Household or Individual. By providing this translation layer, Tapad will take on the responsibility of encryption and decryption protocols where applicable, which will deliver added functionality to our customers. Tapad + Experian partners at launch: Use cases Resolve existing first-party data with new cookieless solutions through The Tapad Graph to minimize data loss Frequency cap at the Individual and Household level via Cookieless and traditional ID Reach consumers at scale across all touchpoints and IDs Build a more inclusive and holistic view of the consumer journey Run accurate and scalable measurement before and after the formal deprecation of third-party cookies in Chrome Map online data into offline activities Hear why industry leaders are adapting with Tapad + Experian As advertisers continue to contemplate the future of identity, Amobee is proud to partner with Tapad, a part of Experian, on this next-generation solution to provide a comprehensive view of consumers. With the imminent loss of cookies, advertisers must think creatively in order to respectfully engage consumers in a privacy-compliant way and Switchboard can play an important role in addressing their respective identity needs. — Bryan Everett | Senior Vice President of Global Business Development | Amobee Connecting offline and online shopper activity in a privacy-compliant way is fundamental to marketing effectiveness and determining return on ad-spend. That’s why we’re excited to be a launch partner for Tapad + Experian’s Switchboard offering; it provides a unified solution for supporting the variety of proprietary and anonymous user ID standards required by advertising demand-side platforms today. — Brian Dunphy | SVP Digital Business and Strategic Partnerships | Catalina As the industry evolves, Tapad + Experian’s Switchboard presents a privacy-safe solution that allows for the continued activation of data and an alternative to advertising within walled garden environments. We look forward to collaborating with Tapad and the industry as we collectively transition to support cookieless identity. — Don Lee |SVP of Global Platform Partnerships | Eyeota We are excited to participate in this proactive solution to the sunset of third-party cookies. Switchboard’s agnostic interoperability, with BritePool and other ID providers, will create high-value for marketers as they transition to the era of cookieless web advertising. — David J. Moore | CEO | BritePool Interoperability is paramount for brand marketers, agencies, publishers and platforms if we want to support an open and free Internet and break free of the stranglehold of walled gardens. Lotame Panorama ID’s participation in Switchboard reflects our steadfast commitment to collaborating across and within the industry and providing value to all of its players. — Pierre Diennet | Global Partnerships | Lotame At this pivotal moment in the industry, we are excited to be partnering with Tapad, a part of Experian on their cookieless initiative and making Retargetly IDx available into the Switchboard solution, providing global brands, platforms and publishers with a compliant, cookieless ID solution for the Latin American market; enabling them to target, reach and measure users at scale through the region. — Daniel Czaplinski | CEO and Co-Founder | Retargetly With Audigent’s Halo ID, we’re architecting a cookieless future where clients and partners have confidence in the actionability and interoperability of exclusive 1st party audiences, originated from some of the world’s leading publishers and creators. We see collaboration as being critical to a collective understanding of identity and Tapad, a part of Experian as a trusted partner with solutions such as Switchboard to support continuity for marketers’ addressability. — Drew Stein | CEO and Founder | Audigent Facilitating access and usage of 1st party identifiers is crucial to help marketers prepare for the cookieless future. Thanks to Switchboard, ID5’s cookie-less IDs will be available to a wider audience of brands and agencies and enable them to run effective, data-driven campaigns beyond the third-party cookie. — Mathieu Roche | CEO and Co-Founder | ID5 Addressing the current identity challenge requires transparency and collaboration. We are pleased to align ShareThis data with Tapad + Experian’s growing ecosystem. ShareThis data helps marketers evolve beyond the cookie to complete the picture. Tapad + Experian’s Switchboard offering will support ShareThis’s deep connections to clients and technology platforms, preserving and growing the accessibility of our data. — Michael Gorman | SVP Product and Business Development | ShareThis Get in touch