Case Study: Location-Based Programmatic Advertising

Études de cas

L'affichage publicitaire programmatique basé sur la localisation - une introduction

Mobile ads can be targeted to users in highly specific physical areas, defined by geo-fences as small as 25 meters in radius. When a device sends an ad request, it includes GPS-based location data — often accurate within 10 meters.

Targetoo’s geo-targeting tool allows advertisers to upload and process thousands — even hundreds of thousands — of addresses (based on postal code and house number) in a single campaign. Geo-fence radius settings can be adjusted globally or individually across all locations.

Problèmes et défis

Despite its capabilities, location-based targeting presents challenges. For example, clients often ask to see a live ad on their own device by placing a geo-fence over their office location — yet the banner doesn’t always appear. This undermines confidence in the accuracy of location-based advertising.

Common reasons a banner may not appear include:

• Active ad blockers (often enabled unknowingly)

• App-level ad blocking preferences

• Mismatched or inaccurate device GPS data

Although browser-based location transfer is improving, GPS data transmitted via in-app ad requests remains the most reliable source for location accuracy.

Because of these factors, demonstrating location-based delivery in real time can be difficult. However, several techniques can increase the likelihood of showing an ad on a specific device — for example, targeting a known device ID.

Alternatively, performance data from real campaigns provides the clearest proof of how well location-based advertising works.

La campagne

A client — a recruitment agency for a healthcare provider — needed to hire 18 new employees urgently. We proposed a programmatic display campaign targeting locations relevant to healthcare workers: nursing homes, hospitals, and care facilities.

We acquired a list of 12,526 addresses matching those criteria and uploaded it into our geo-tool. Each address was assigned a 110-meter radius geo-fence.

• We ran two parallel campaigns:

• Location-targeted campaign (above those specific addresses)

• National campaign (same creatives, no geo-targeting)

Both campaigns ran for three weeks, serving a total of 1.43 million impressions. The campaign successfully generated enough applicants to fill all 18 vacancies.

Résultats

• La ligne principale (diffusant des publicités sur ces 12 526 adresses/localisations spécifiques) a réalisé un CTR de 0,72% sur la base des bannières standard de l'IAB. Un CTR de 1,56% a été obtenu avec le format Interscroller.

• Le taux d'atterrissage pour l'ensemble IAB était de 74%, tandis que le taux d'atterrissage pour l'ensemble Interscroller était de 56%.

Comme nous l'avons expliqué, nous avons lancé une campagne avec exactement les mêmes créations, mais sans ciblage de l'emplacement. Ces annonces ont été diffusées dans l'ensemble des Pays-Bas (là encore, pas de ciblage d'adresses spécifiques). Les résultats ont été les suivants :

Results – Location-Targeted Campaign

• CTR (IAB banners): 0.72%

• CTR (Interscroller): 1.56%

• Landing rate (IAB): 74%

• Landing rate (Interscroller): 56%

Results – Nationwide Campaign (no location targeting)

• CTR (IAB banners): 0.23%

• CTR (Interscroller): 0.82%

• Landing rate (IAB): 44%

• Landing rate (Interscroller): 36%

Performance Comparison

• CTR of IAB banners 3× higher with location targeting

• CTR of Interscroller 2× higher with location targeting

• Landing rate of IAB banners +85% higher

• Landing rate of Interscroller +65% higher

These results confirm that location-based delivery drives significantly stronger engagement. Ads served above relevant physical locations generated higher click-through and landing rates — proving that contextually targeted impressions reach more interested audiences and perform measurably better.

N'hésitez pas à nous contacter pour en savoir plus et/ou pour discuter des options de ciblage géographique qui pourraient vous aider à atteindre votre public de manière plus efficace et plus rentable.

DEPLOYING A WHITELIST ON OPENRTB

Running programmatic campaigns exclusively on premium whitelists can be extremely challenging — but when it works, performance can be exceptional, with CTRs exceeding 40%.

Some advertisers insist on running campaigns solely across approved premium publishers — and they’re right to do so. Reasons include brand safety, precise audience targeting, and skepticism about automated brand safety tools, which don’t always prevent placements on low-quality sites.

Experienced traders know that achieving significant campaign volume while maintaining a strict whitelist is rarely realistic.

To understand why, consider the breadth of today’s digital ecosystem: virtually every hobby, interest, or niche community has its own set of dedicated publishers. This opens fascinating possibilities — in theory, you could target only those sites and apps that align perfectly with your exact audience profile.

Exemples :

Targeting niche audiences by category is technically possible — for example:

• A horse feed supplier can advertise across equestrian publishers.

• A kite-surfing brand can target sites covering wind and surf conditions.

• A driving instructor can focus on publishers offering driving education content.

• A premium travel agency can run ads in top-tier travel and lifestyle publications.

Voici ce qui s'est passé :

We began bidding at a $21 dynamic CPM, steadily increasing to $44, $111, $241, and eventually $900 — still with no traction.

At $5,002, we finally secured limited impressions, averaging a CPM of $3,349. Despite the high bid, the campaign achieved exceptional engagement: a 45.6% CTR, peaking at 66.7% on certain days.

Qu'est-ce que tout cela nous apprend ?

These results highlight two truths about programmatic trading:

1. Competition for premium inventory is constant and intense.

2. At scale, campaigns inevitably rely on Run of Network (RON) placements for volume.

While exclusive whitelisting offers unmatched brand alignment, it also limits reach and dramatically increases costs. Striking the right balance between whitelist control and scalable reach remains key to efficient programmatic strategy.