PPC
Eurochange: Increase Store Footfall Driven By Google Ads And Identify a True Return On Ad Spend
THE RESULTS
158% | increase in revenue YOY from PPC activity |
128% | increase in revenue YOY from SEO activity |
Eurochange is one of the UK's biggest foreign exchange and currency exchange specialists. They provide a range of financial services and products, both online and in more than 240 branches all over England, Scotland, Wales and Northern Ireland.
When eurochange brought us on board as their digital marketing partner, they wanted to use paid media advertising to drive more users to physical stores. Users are roughly twice as likely to visit a shop if they’ve seen a geo-located ad, so there was huge potential to use Google Ads to create a trackable, repeatable ad strategy.
Can the data be trusted?
Because of their industry, eurochange work to tight margins and take the accuracy of reported data very seriously. They raised concerns over how accurate Google’s reporting of ad efficiency really was. How does Google know when someone has seen an ad and visited a shop?
As with all its reporting, Google uses aggregated, anonymised data to build an accurate picture of ad performance.
So, Google takes two disparate data sets - users who have viewed an ad and users who have visited a store - and uses the combined data to extrapolate the success of the ads. It will never be a 100% accurate metric - users must have their location tracking services turned on to register a store visit, for example - but given enough data, it’s an acceptable metric.
The current landscape
Before implementing our ad campaign, we needed to understand how eurochange’s stores performed organically. This meant measuring walk-in custom.
The clicker test
First, we measured how often customers completed a transaction after walking into a store off the street. This was done over a range of stores, and over 30 days, so we got a good pool of data to work with. The concept was simple - eurochange employees used a clicker device to count how many people visited the store each day, and how many transactions happened.
Once we excluded click & collect transactions from the data, we had a base conversion rate for walk-in customers.
Analysis of store transaction data
Next, we analysed in-store transaction data to get an average transaction value. We also worked out the average margin for in-store transactions, to make it more relevant to eurochange. This helped us tailor our optimisation plans to their requirements.
Multiplying the average margin value with the in-store conversion rate gave us an estimate of the profit of a PPC-driven store visit.
Collaboration with eurochange data warehouse team
We worked with eurochange’s data warehouse team to check our data was accurate. They supplied us with daily GCLID (Google Click ID) uploads to filter out any conversions attributed to home delivery or click & collect. This meant we could attribute the other conversions to our in-store ad campaign.
This gave us accurate conversion rate data without duplication (where a click & collect conversion was incorrectly attributed to a walk-in ad).
Results
Once our initial work was complete, we ran and tested an ad campaign for six months. Store visits driven by PPC grew by a massive 218% over the following quarter, from an average of 3,138 visits to 10,003 visits.
Then, we switched to a profit-on-ad-spend (POAS) model. This improved sales performance across the board:
- Revenue +8%
- Transactions +74%
- ROI +33%
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Our Work
We’ve worked with a variety of companies to produce outstanding results. From internationally recognised brands to small family-owned businesses, we’ve gotten to know our clients inside out to produce perfect projects and create captivating campaigns that truly express their message and values.
