Personalize
Dynamic content, recommendations and search personalisation for digital experiences.
Product directory
Digital personalisation
Tools adapting digital content, recommendations and layouts to customer context.
1 product
Supplier A–Z · Public-source research · Select up to three to compare
Coverage is being expanded. A listing is not an endorsement. Product capabilities reflect the cited public sources.
Before you shortlist
How to evaluate digital personalisation
Specify the placements you want to change: game rows, banners, search or messages may require different interfaces. Compare eligibility rules, recommendation inputs, controls and fallbacks against the same placement.
A recommendation engine should be evaluated with both technical and operational criteria. Check integration effort, measurement, exclusions and the ability to review or override rules. Keep content relevance and incremental effect separate, and confirm which surfaces are in the proposed package.
What to compare
01
Product role
What job does this product perform, and which adjacent jobs need another product?
02
Delivery and integration
How is it connected, what data or interfaces are required, and who owns implementation?
03
Pricing and packaging
Which recurring, usage, setup and add-on charges are included in the proposal?
04
Scope and coverage
Which markets, inputs, content or use cases are actually in the proposed scope?
05
Surfaces
Which website, app or messaging placements are covered?
06
Rules
Which eligibility, promotion and suppression controls can be applied?
07
Latency
What serving and fallback commitments apply?
Buyer questions, answered
Is personalisation limited to marketing messages?
No. This category also covers eligible website and app experiences such as content rows, layouts and search.
Does a recommendation model determine what content is legally or operationally eligible?
Do not assume that. Eligibility and suppression rules need explicit implementation.
How should the effect be measured?
Agree the placement, audience, control design and success criteria before interpreting changes as incremental impact.