Next-Gen Retargeting
Personalized retargeting chosen by deep learning, including products the user has not viewed; setup and creative sit with the RTB House team.
ExploreAcquisition is RTB House's solution for getting a first sale from users who have never ordered. Dynamic product ads are shown across several touchpoints, aiming to bring the person to the site over a journey of a few impressions. For us, the real question is whether the new customer in the report is really new and whether they buy a second time.
We use Acquisition to bring users who have never bought from your brand (new-to-file) to the site over a few touchpoints on news and content sites and win their first order. The aim is to add an open web source to new customer campaigns on Meta and Google, and to set acquisition cost based on these customers' return and repeat purchase behavior.
Funnel stages it serves
RTB House defines this solution as getting the first conversion from someone not yet in your customer file (new-to-file). Simple on paper, it is the most debated point in practice. Does someone who visited your site before but never bought count as new? What about someone who bought in a store but has no online order? We settle this definition in writing with the RTB House team before the campaign opens, because the acquisition cost you see in reports depends entirely on it.
To apply the definition, we add new vs. existing customer status to the purchase event in the tag and, where possible, remove existing buyers from the campaign with a KVKK-compliant (Türkiye's personal data protection law) hashed email list. If the list cannot be shared, we at least separate users with a recent order from tag data and state this limitation clearly in reports.
Few people buy from an unfamiliar brand at the first ad, especially for mid and upper-priced products. So Acquisition reaches the user several times, at different moments and on different pages, while a deep learning model tries to predict who will complete the journey. For this setup to work well, we check the following:
Most brands already have Meta Advantage+ and Google Performance Max for finding new customers. We see Acquisition as a complementary channel next to them: an audience reached with product-led ads on news and content sites, outside social and search. If a Criteo Commerce Audiences new customer campaign runs in the same period, we do not open both at once; the two DSPs compete for the same user and it becomes impossible to tell which one brought the new customer.
RTB House provides insights showing the most valuable new customers and the best-performing publishers and creatives. We combine these with order data: we track the first order value, return rate and second order within 60-90 days for customers coming from Acquisition as a cohort. We run this analysis in BigQuery by customer ID and set the campaign's acquisition cost target based on this repeat purchase data, not on the first order's profit.
We recommend it
We don't recommend it
Metrics we track
What you need to get started
Official sources
To learn more about Acquisition or other RTB House ad formats, contact The Brand Move RTB House team today.
Personalized retargeting chosen by deep learning, including products the user has not viewed; setup and creative sit with the RTB House team.
ExploreAn RTB House solution that optimizes for tag-verified site visits, not clicks; we check visit quality in GA4.
ExploreRTB House video and display ads with product overlays that build awareness and consideration among new, in-market audiences.
ExploreRelated pages
It is RTB House's solution for winning a first order from people who are not yet your customers. It shows dynamic product ads over several touchpoints on the open web and uses deep learning to predict who will complete the journey.
First orders show up within a few weeks, but the real value appears in repeat purchases. We use the first month for learning and validating the definition, and make budget decisions only after at least two to three months of cohort data.
We see that gap when we match order data by customer ID. If the share is high, we update the exclusion list, fix the new customer status in the purchase event and re-report the past period with the corrected definition. Budget decisions are always based on the corrected figure.
The RTB House report can include post-view conversions. We show post-click and post-view new customers on separate lines and try to validate the weight of the post-view share with a control group test. We also fix the length of the view window in writing during setup.
Not at the same time for the same goal. Two DSPs would bid for the same users and it would be impossible to tell which one brought the new customer. We run one, or split them clearly by market or period.
In a free call we review your audience, inventory needs and measurement setup, then tell you in writing which platform makes sense to start with.