The Evolution of Local Marketing in the Age of AI

For several years, Waze Ads has held a unique position in drive-to-store strategies, enabling brands to reach drivers in the middle of their trips—at a time that often coincides with the intention to make a purchase or visit a store.

At Ekstend, we’ve long leveraged this tool to help chain retailers address their local foot traffic challenges. While the platform has evolved, one conviction remains: mobility data remains one of the most powerful signals for linking intent to an in-store visit.

The goal here is not to revisit a product evolution, but rather a core business conviction: to understand what Waze Ads offered advertisers, why this type of signal addressed a real need, and how this logic of local intent remains central to today’s performance strategies.

To explore this topic, we brought together two complementary perspectives: that of Pierre Kalil, Director of Waze Local for France and Belgium, who discusses the fundamentals of local marketing, and that of Julie Taktak, a Google Ads & Performance Max expert, who analyzes the evolution of local campaigns in an ecosystem now driven by AI.

Waze Ads: Reaching Drivers at the Right Time

Waze Ads initially addressed a need that traditional digital channels struggled to meet: reaching drivers on the go, at a moment close to a purchasing decision. As Pierre explains:

“Waze Ads filled a gap in the digital landscape: reaching drivers while they’re on the go. It’s an in-vehicle medium that targets a captive audience at the exact moment they’re traveling—often on their way to a retail location.”

This positioning quickly resonated with advertisers whose goal was to drive traffic to physical stores. The sectors most affected shared a common trait: a dense physical network and a strong focus on local presence.
He explains:

“B2C retailers whose goal was to drive visits that would result in a transaction at the point of sale. Specifically, this included the restaurant and retail sectors first and foremost, but also the entire automotive ecosystem in the broadest sense: dealerships, gas stations, and parking lots.”

The strength of the platform lay primarily in the quality of the signal. Waze Ads didn’t rely solely on geographic data, but on a specific moment in a user’s life: a trip, proximity to a retail location, a time slot, and a potential intent. According to him:

“Waze’s strength lay in the combination of three factors. First, the time spent on the app—which was both substantial and of high quality. Second, proximity: nearly 80% of trips took place within 30 kilometers of home, meaning they were everyday commutes in areas where users actually make purchases. Finally, the temporal context, with specific time slots that reveal intent.”

It is this combination that has made Waze Ads a unique tool in local marketing strategies. It allowed digital best practices to be applied to a physical moment: the commute, just before a visit or a purchase decision.

But its value did not lie in a standalone campaign. For Pierre Kalil, Waze Ads needed to be integrated into a broader drive-to-store strategy:

“Waze Ads brought the full power of digital advertising to a context that digital hadn’t yet been able to address. It offered precise targeting, a variety of creative formats, and concrete measurement of in-store traffic—all applied to a unique moment: the drive itself. The key point is that Waze wasn’t meant to operate in a silo.”

A lesson that still holds true: the timing of mobility remains strategic

Even though the tools have evolved, the core principle remains relevant: the moment leading up to a purchase decision continues to hold significant value. He summarizes this challenge as follows:

“Capturing the driver’s attention in the minutes leading up to a purchase decision is a rare opportunity. This pivotal moment, just before arriving at the point of sale, retains its full value regardless of the tools used.”

For network brands, this conviction comes with a requirement: effectively coordinating national and local efforts. One of the most common mistakes is a lack of synchronization between the central campaign and multi-local activations. He points out:

“When national and local efforts aren’t coordinated, we lose consistency and effectiveness.”

Local performance therefore depends not only on the marketing lever used, but also on the ability to align a consistent brand message with relevant on-the-ground activation. In this context, local marketing continues to play a key role in the customer journey.

According to Pierre: “This is the final point of contact before the in-store visit and transaction, and as such, it deserves to be handled with the utmost care.”

Performance Max: A New Way to Leverage Local Signals

The fundamentals remain the same, but the advertising ecosystem has changed. Local campaigns are now integrated into broader strategies, where artificial intelligence plays a central role in analyzing signals and allocating budgets.

For Julie Taktak, the major shift lies in the transition from a “network-based” buying approach to a “goal-based” one: “The major shift in recent years has been the move away from buying a ‘network’ toward buying a ‘goal’ (drive-to-store).”

In this context, Performance Max plays a central role in drive-to-store strategies. Advertisers no longer simply seek to choose an ad placement; they provide the algorithm with a goal, signals, and content to identify the users most likely to visit a store. She explains:

“Performance Max has become the operational backbone of drive-to-store. Its role is to find the user most likely to visit a store or take a local action—such as clicking on directions, making a call, or taking action on Google My Business—regardless of where they are within the Google ecosystem.”

Artificial intelligence thus makes it possible to cross-reference multiple signals: immediate context, search intent, distance from the point of sale, and mobility status. What’s changing isn’t the value of the local signal, but the way it’s used.

Julie Taktak puts it in practical terms:

“AI cross-references millions of data points in real time. In very practical terms, it analyzes:
The immediate context: Is the user in a car (Waze), walking with their phone (Maps), or on their couch (YouTube)?
The intent: Have they recently searched for a specific product on Google Search?
The distance: Are they within a relevant catchment area or on a route that passes by the store?”

The Right Ingredients for a Successful Restaurant

With Performance Max, human control doesn’t disappear—it just shifts. The focus is less on micromanaging each bid and more on providing the algorithm with a solid foundation: reliable local listings, product feeds, creative assets, and conversion data.

Julie Taktak sums up this change:

“Today, we feed the system our ‘ingredients’ (location, budgets, creative assets, product feeds) and set a bidding goal (target CPA or ROAS). Control has shifted from micromanaging bids to managing assets and audience signals.”

In reality, the quality of the local foundation remains crucial. An incomplete Google Business Profile, outdated hours of operation, a lack of video creatives, or overly segmented accounts can limit performance.

To measure the actual impact of a local campaign, Julie Taktak recommends tracking metrics directly related to intent to visit:

“The number of in-store visits: The key metric if the account is eligible for visit tracking.
The in-store visit rate
Cost per in-store visit (CPV)
Direct local actions: Clicks on directions and phone calls.”

These KPIs allow us to move beyond a purely digital view of performance and refocus on the original business objective: driving qualified traffic to the point of sale.

AI does not replace local relevance

The evolution of local marketing is therefore not limited to a question of tools. It is based on a shared conviction: signals are powerful when used effectively, but they are not enough on their own.

For retailers, the challenge now is to build a system capable of feeding AI while maintaining genuine local relevance. This is precisely where Ekstend supports chain brands: transforming local signals into concrete, measurable, and useful actions to drive foot traffic to stores.

Julie Taktak concludes with some practical advice:

“Give the algorithm the tools it needs to achieve its goals by localizing your creative assets. It’s a classic mistake: people use the same polished national corporate video for drive-to-store campaigns. PMax needs raw material to drive conversions. Provide it with short videos shot in your actual stores, copy that speaks to the local catchment area, and visuals featuring your real local teams.”

Even in the age of automation, the advertising message remains fundamental. Because while the tools evolve, the challenge remains the same: connecting the right person, at the right time, to the right point of sale.