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TurkNet Multiple Location Targeting
TurkNet is one of Turkey’s leading internet service providers in the telecommunication sector, making all sales and promotions through call centers and digital channels. It provides its customers with a “freedom internet experience” with unlimited, non-committal and high-speed internet advantages.
TurkNet segments its users as “adsl, vdsl, fibre and gigafiber” according to the speed in their infrastructure and targets users with high-speed infrastructure (100 Mbps and above) to keep customer satisfaction high.
In other words, we can define TurkNet’s target audience as users living in regions with Fiber infrastructure living in Turkey. At this stage, the biggest problem faced by TurkNet is that the Fiber regions are too small and numerous to be targeted (with 4K neighbourhood data). For this reason, campaigns were targeted as “All Turkey” in their campaigns. The fact that the ads received impressions all over Turkey caused conversions from 16-50 Mbps regions, which were undesirable. It also increased our costs.
By promoting the fiber product, which provides faster internet service than Turkey’s average, we aimed to reach users in locations that can benefit from this product.
Our Objectives & KPIs
The people we need to reach in the campaigns are the people in locations with fiber internet service and internet infrastructure, whose sales we want to increase. We planned to act with the right location targeting in order to reach the right people in search campaigns. In this way, it aimed to spend the budget on users who will convert and to increase the campaigns’ conversion rate. We expected an average monthly improvement of 2 times in performance metrics, the details are as follows;
- Increasing the Conversion Rate
- Increasing the transaction x2
- Keeping ROAS at the same level
we aimed to reach users in locations that can benefit from this product.
Challenges:
- Thousands of Location Data
We requested infrastructure data from our customer with a breakdown of provinces, districts and neighbourhoods. Location data with approximately 49K neighbourhoods came from the customer. From these locations, 4325 locations with fiber infrastructure (with speed above 100) were separated. Because 4325 locations were too many to target, we prioritized neighbourhoods based on possible conversion rates. - Import Format Docs
Google ads do not allow bulk uploading of this volume of data. Since the format in Google maps is not standard, we have observed in our research that there is no tool that we can bulk upload. As a result of dozens of unsuccessful attempts, we have brought our data into a format that we can use in Google campaigns and update when needed, using Google excel macros. - Campaign Limitations – Radius Limit
Unlike our plan, Fiber 100 locations would be targeted under a single campaign, but we ran into google limitations. We had to categorize neighbourhoods according to provinces, as radius targeting (close location targeting) does not allow targeting more than 500 in a campaign. At this stage, 2300 neighbourhood locations were activated by dividing them into 5 campaigns according to the provinces.
The Approach:
We received 49K location data from customers with fiber internet infrastructure.
We grouped these data on the basis of province/district and made them targetable. Then we created a Google Ads and Google Sheet link and automatically added locations within a 2-mile radius of the campaigns. Since there are too many locations, we grouped the campaigns on the basis of provinces and divided them into 5.
By rearranging the keywords and ad texts of the campaigns, we increased the ad rank rate to a higher level and targeted users in the right location.
Hard work always pays
Results:
We have reached users who can receive this service by launching the search campaigns we use to reach users who search for the words “fiber internet” only to users who have access to fiber internet infrastructure. Thus, although we narrowed down the locations, we increased the number of our subscribers by 10 times.
The user is increased by
3.3x
The conversion rate increased by
2.7x
The ROAS increased by
4x
The number of transactions has increased by
10x
