Shoppster Case study
Shoppster Finds Hidden Revenue in Dormant User Pool
Full-funnel approach delivers growth without sacrificing profitability

higher ROAS
higher AOV
higher engagement*
About the client
Part of United Group, Shoppster is a regional ecommerce shopping platform operating in Serbia and Slovenia.
Since launching in 2020, Shoppster has built an innovative platform focused on comprehensive product coverage spanning consumer electronics, home and garden goods and sporting equipment. They've positioned themselves as a growth partner for smaller local sellers, offering greater visibility, marketing support, and access to broader audiences without the complexity of independent storefronts.
What they say about us
"In collaboration with RTB House we achieved outstanding results in both new customer acquisition and retargeting campaigns. Our unique approach based on Deep Learning models demonstrated that a full-funnel programmatic setup can be extremely effective when it comes to long-term scaling of revenue and profitability in the digital performance ecosystem."
Igor Možek
Head of Performance, Shoppster
DESCRIPTION
The challenge
After running successful campaigns with RTB House for over five years, the company wanted to activate a fresh customer base through a full-funnel approach. All without a significant deterioration of ROAS. Shoppster understood that sustainable growth meant focusing on long-term customer value rather than short-term conversion spikes. As with many brands, their retargeting pool, while effective, is finite.
Attracting quality new visitors who complete their first transaction and become loyal customers, while simultaneously convincing dormant users to come back and spend more per order became our challenge to solve. It required a shift in strategy—moving beyond retargeting into full-funnel territory without compromising the profitability metrics that defined Shoppster’s success.
Story
The solution
Drawing on years of retargeting collaboration, we saw potential in dormant visitors who had demonstrated purchase intent but fell outside traditional targeting windows. We secured a dedicated test budget to prove this hypothesis, carefully designing a multi-segment strategy that covered the full customer journey without cannibalizing existing performance. We refined segment boundaries based on engagement patterns, using RTB House Deep Learning capabilities to deliver personalized creative and messaging to each user group based on their journey stage. This data-driven approach enabled us to overdeliver campaign goals and maximize incremental value for Shoppster.
Success
The result
We achieved an average increase of 30% in ROAS, 22% lift in average order value, and 160% improvement in the engagement rate. Beyond these metrics, Shoppster's perception of what was possible shifted.
Impressed with the results, the client immediately extended the full-funnel campaign setup beyond the trial period. We maintained steady performance during promotional periods, expanded Shoppster’s addressable audience, and supported other marketing channels in driving new visitors and sales.
The impact extended into future quarterly planning. Shoppster increased allocated budgets and opened conversations about deeper collaboration. By targeting overlooked dormant users alongside acquisition, we demonstrated that expansion doesn't require sacrificing efficiency—it requires some fresh thinking about where opportunities exist.
*click-through-rate
Shoppster CASE STUDIES
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