Digital advertising is a sophisticated game. This is especially in regions where data infrastructure hasn’t quite caught up with demand. 

In emerging markets, this challenge is complex because open source data is sparse, public records can be inconsistent, and manual geo-tagging simply doesn’t scale. 

Launching campaigns into emerging markets is no easy task. However, with location intelligence, the hurdle is smaller. 

Growing pains and open-source data

To illustrate how location intelligence can help those in the digital marketing space break into emerging sectors, we’ll refer to a real-life use case from an Echo client. 

The AdTech company in question was a mid-sized programmatic platform operating in Mexico, the Philippines, and Morocco. With successful growth in these regions, they were ready to scale. They had a platform that promised brands smarter location-based ad delivery across mobile and DOOH (Digital Out-of-Home). However, the location signals that powered their ad logic were only as good as the underlying POI data it was built on. 

Unfortunately, in these markets, the data was unreliable at best. 

To start, the open-source POI datasets were outdated, inconsistently riddled with missing attributes like no brand name, wrong categories, and incorrect coordinates. Their internal team was busy spending far too many hours manually cleaning and validating the data for every new market expansion. This was exhausting and tedious work. On top of all that, they couldn’t offer category-specific filtering (e.g., a drive-through fast food place vs. a sit-down restaurant. That was a major deal breaker for large clients like food delivery apps. 

The platform was smart, but it wasn’t at the potential it could be with the inputs they were relying on. 

The shift in location data quality

With data quality issues staring them in the face, the company sought to help out with its growth bottleneck issue. They needed improved coverage and granularity in priority countries. This included: country-specific POI datasets validated for accuracy and updated frequently; custom category mapping enabling filtering by venue type and commercial relevance; and scalable delivery formats they could plug directly into their existing systems. 

Our team worked with them to deliver high-quality, enriched POI data across all three regions, tailored to the campaign planning needs of their clients. Parallel to this, we provided flexible data licensing. This aligned with their rollout plans, supporting pilot runs and quick scaling when results came in positively. 

Doubling campaign launch speed

Now working with accurate POI data, the platform launched campaigns twice as fast in new markets. This eliminated the need for manual cleaning and verification of every data point. The ops team could shift its focus to producing improvements and customer success. 

With our POI data as an underlying layer to the platform, they could build smarter geofencing logic based on venue types, not just coordinates. On top of that, they won new Requests for Proposal from varying quick-service restaurants and telecommunication companies who wanted location insights.

As a result, they expanded into 3 new cities without adding headcount.

The accuracy and freshness of data brought greater confidence and trust for major clients who were entering these markets, which were difficult to gauge due to a lack of data visibility. 

The AdTech lesson for emerging market expansion 

Emerging markets have massive opportunities, but they come with nuance. You can’t come into them like a bull in a China shop, hoping you’ll see fruitful ROIs from campaigns. Every new region is different because local behavior, infrastructure, and context matter. An existing targeting model might work in one region but perform poorly in another. 

Generic POI data and open-source material can be very effective in markets like the U.S. and Germany. However, in emerging regions, data gaps are a frequent business blocker. For ad targeting to be precise, it requires precise input. Scalable programmatic growth needs scalable location intelligence. 

Three lessons for AdTech expansion

1. If you’re scaling globally, don’t assume all markets are equally mapped: Data gaps are blockers when they’re invisible. You won’t know what’s missing until your campaign fails.
   
   
2. Don’t waste your engineering resources on cleaning data: Let your team focus on the product, not on patching up flawed infrastructure.
   
   
3. Think of location intelligence as a feature, not a dataset: Your clients don’t care what database you use. They care that your platform delivers results. Clean, context-rich data makes that happen.
   

Want to explore smarter decision-making for AdTech?

Echo Analytics provides global POI and mobility datasets that plug directly into programmatic platforms, CTV systems, and footfall analysis tools. With us, you go from “where?” to “what works” faster. Discover how Echo Analytics has helped AdTech companies on an arrange of different use cases by checking out our latest eBook.