Allwyn
AI-driven omnichannel programmatic buying with retail data activation
Allwyn, operator of the UK National Lottery, ran an omnichannel campaign on The Trade Desk Kokai by activating Tesco retail data and reports a 43% higher ROAS, a 30% lower CPA, and a 64% shorter time to conversion versus standard prospecting.
Key points
- AI-driven omnichannel programmatic buying (CTV, audio, video, display).
- The Trade Desk Kokai platform, with Tesco retail data activation.
- ROAS +43%, CPA -30%, time to conversion -64% versus prospecting.
- Evidence level B, living status confirmed.
Objective
Converge an omnichannel plan (CTV, audio, video, display) onto a single performance view and shorten the path to conversion for the Lotto and EuroMillions products.
The deployment
Allwyn, operator of the National Lottery in the United Kingdom, built a full-funnel omnichannel campaign on Kokai, The Trade Desk's AI-driven media-buying platform, with the agency Hearts & Science. The setup combines CTV, digital audio, online video, and display, and activates Tesco's retail data to target audiences rather than prospect cold. Kokai's AI arbitrates cross-channel allocation and cross-channel frequency control. Against a standard prospecting strategy, the audiences powered by Tesco data delivered a 43 percent higher ROAS and a 30 percent lower cost per acquisition. Using three channels rather than one cut time to conversion by 64 percent, and cross-channel frequency control returned 8 percent of budget. This is a case of optimization and automation of programmatic media buying, not creative generation.
Results Proof B
Quantified The Trade Desk platform case study naming Allwyn, the agency Hearts & Science, and the data partner Tesco; an interested official source, hence B. Kokai's average performance is corroborated by a second The Trade Desk publication.
How it works
Documented architectureThe stack in detail
- plateforme The Trade Desk Kokai AI-driven DSP: cross-channel allocation, bids, and cross-channel frequency control across CTV, audio, OLV, and display.
- outil Data retail Tesco Audiences derived from Tesco purchase data, activated in Kokai to target rather than prospect cold.
- integrateur Hearts & Science Media agency that steers the full-funnel omnichannel strategy on Kokai.
- outil Mesure de conversion cross-canal Unified view of ROAS, CPA, and time to conversion in Kokai, which feeds cross-channel reallocation.
How it runs, concretely
For ops teams-
1Audience activation media team / agency
Tesco retail data is activated in Kokai to target audiences rather than prospect cold.
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2Omnichannel plan agency (Hearts & Science)
CTV, digital audio, OLV, and display are orchestrated in a single full-funnel campaign.
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3AI optimization AI (The Trade Desk Kokai)
Kokai arbitrates cross-channel allocation, bids, and cross-channel frequency control.
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4Unified measurement Allwyn media team
The team reads ROAS, CPA, and time to conversion on a single view and adjusts the mix.
Attributed conversion and membership in the retail data audiences (Tesco). Without activated retail data or cross-channel measurement, the AI loses the lever that sets this plan apart from ordinary prospecting.
How your customers perceive this type of use
Sourced studiesLe pricing algorithmique est le terrain le plus inflammable : 68% des consommateurs disent se sentir leses quand les marques utilisent le pricing dynamique et 80% jugent plus dignes de confiance les marques aux prix constants (Gartner, 2024). L'equite percue varie selon le secteur : le pricing dynamique n'est juge juste que par 33% a 40% des repondants selon qu'il s'agit de concerts ou de cinemas (YouGov, 17 marches). Le prix personnalise par les donnees individuelles est le plus rejete : 47% des Americains s'y opposent fermement (Consumer Reports, 2024).
Acceptance conditions
- La constance des prix comme signal de confiance : 80% jugent plus fiables les marques aux prix stables (Gartner 2024)
- Le secteur conditionne l'equite percue : le pricing dynamique est mieux tolere pour les cinemas (40% le jugent juste) que pour les concerts (33%) (YouGov 2024)
Red lines
- Le pricing dynamique percu comme abus : 68% se sentent leses (Gartner 2024)
- Le prix individualise a partir des donnees personnelles : 47% d'opposition ferme (Consumer Reports 2024)
- Les frais caches et hausses imprevues, vecus par 79% des consommateurs sur un an et associes a la perte de confiance (Gartner 2024)
Sources: Gartner 2024 · YouGov 2024 · Consumer Reports 2024
How to replicate
Inference, not sourcedData prerequisites
- usable retail data audiences
- cross-channel conversion measurement
Org prerequisites
- omnichannel media budget
- an agency or team able to operate a DSP
- a retail data sharing agreement
Possible stack
- The Trade Desk Kokai
- retail data partnership (e.g. Tesco / dunnhumby)
The plan, step by step
- Step 1Frame the retail data sharing agreement (scope, consent, compliance) with the partner.Deliverable: Retail audiences activatable in the DSP
- Step 2Build the omnichannel plan (CTV, audio, OLV, display) and validate cross-channel conversion measurement.Deliverable: Campaign plan + validated conversion tracking
- Step 3Launch the campaign under AI optimization, with cross-channel frequency control enabled.Deliverable: Active campaign with automatic cross-channel allocation
- Step 4Compare retail audiences and standard prospecting on ROAS, CPA, and time to conversion, then reallocate.Deliverable: Quantified comparative review and reallocated budget
First step: Activate a retail data audience in a DSP and compare its ROAS and CPA with standard prospecting on the same channels.
The same pattern, proven in other industries
adidas
AI-driven audience prospecting and bidding (ARO) across the full funnel
Nivea
genAI testing and optimization of creative elements + automated localization at scale
Best Choice Products
real-time AI optimization of bids, budget, and placement on retail media
Sources
- S1 Allwyn hits the jackpot - reducing time to conversion by 64% with Kokai Interested party archive pending
- S2 Kokai's AI fuels measurable business outcomes Interested party archive pending
An error, newer info, a source?
This page lives on its accuracy. If a figure has moved, if the deployment has changed, or if you have a higher-quality source, tell us. Every sourced correction is verified before publication.