Matas lifts ad revenue by 57% with data-driven insights
By implementing an advanced attribution model, Matas can now directly link campaign interactions to in-store purchases, understanding the true value of its marketing efforts for better allocation of resources and optimised strategies.
incremental increase in online revenue driven by Google Ads*
incremental increase in in-store revenue driven by Google Ads*
increased Return On Ad Spend (ROAS)
*We split-tested campaigns to gain full insights into incremental revenue, ensuring that these results reflect true incremental growth rather than merely re-attributed revenue.
How can we measure the true value of our marketing efforts if we don’t know the customer’s journey from the first click to the purchase in–store?
This question marked the beginning of an extensive digital collaboration between Matas and IMPACT Commerce.
The goal was to break down the data silos between online and offline channels to gain a deeper, data-driven insight into customers’ purchasing behavior and journeys.
Together, we developed and implemented an advanced, data-driven attribution model that tracks the customer journey from online interaction to purchase in physical stores.
This has given Matas a significantly deeper understanding of the customer journey, crucial for optimising marketing budgets and activities, ensuring targeted advertising, and improving the customer experience across touchpoints.
KEY FEATURES OF THE ATTRIBUTION MODEL
When consent is given, the model collects and combines data from web behaviour, Meta campaigns, Google ads, app engagement, and email interactions with in-store and online transactions.
By linking these data to a user ID, Matas now has an overview of the timeline for the entire customer journey and associated interactions. For example, tracking customers’ journeys from a click on a Google ad to a purchase in-store.
Assigning sales value to each interaction helps understand the impact of ads on final purchases, allowing for a direct link between campaign interactions and in-store sales.
Google then automatically receives feedback on attributed in-store sales (referred to as an omni-pixel), resulting in more precise bidding than ever before. This has, for example, enhanced the data quality of Matas’ Google-ads by 69%, enabling the performance marketing team to adjust and optimise the marketing activities for peak efficiency.
INSIGHTS FOR STRATEGIC DECISION MAKING
The model revealed that 25% of the revenue in physical stores came from online activities. Additionally, it showed that digital channels generate 40% more revenue in physical stores compared to online sales. These insights have empowered Matas to better allocate resources and optimise channel mix, budgets, and campaigns based on a holistic understanding of customer behaviour across online and offline purchases.
And the results speak for themselves. The model has contributed to an impressive lift in ad revenue by 57% online and by 21% in the physical stores. All of this has been achieved with a relatively moderate increase in advertising costs, which has increased the Return on Ad Spend (ROAS) by around 10%.
LIFT YOUR MARKETING EFFORTS WITH DATA-DRIVEN INSIGHTS
Reach out to Thomas. He’ll help you get started.
