Can't personalize beyond basic email and SMS
Personalization apps you bolted on, and the ones that keep failing
ResearchBrandCloud does it natively instead, an all-in-one retention marketing platform for ecommerce brands where a forward-deployed marketer replaces the bolted-on stack.
The problem
Recommendations that ignore what someone just did
Product recommendation modules often run on fixed logic: bestsellers, or a static "you might also like" block that never updates. A shopper who just looked at one category keeps seeing suggestions from a completely different one, which reads as inattention rather than personalization.
What we hear from brands
product recommendations are static and not predictive, according to a handbag brand
a kitchen-appliance brand frustrated that a shopper who just viewed a juicer gets shown a blender next
static product carousels ignore customer segments, according to a sustainable underwear brand
The new way
Turn the same catalog into a different asset for every channel
ResearchBrandCloud converts a product feed into on-brand dynamic visuals, with tags, ratings, and current pricing, that render in real time for ads, email, and the website alike. When a price changes, the image updates everywhere it appears, without a design request.
Outcomes brands report
5.6x
growth in Memorial Day sales revenue
34x
Meta ads ROAS, up from 17x on the previous dynamic product ads
2.6x
growth in Meta ads ROAS versus the previous dynamic product ads
How it works
How the switch to ResearchBrandCloud actually works
You grant access
Give your ResearchBrandCloud forward-deployed marketer access to your current stack and approve the migration plan. That is the extent of the lift on your side.
Your old stack stays live
Nothing goes dark. Your existing tools keep running while your marketer rebuilds data, flows, and campaigns behind the scenes, including domain warm-up for deliverability.
You go live on your timeline
Growing brands are typically ready in two to four weeks. Complex, nine-figure setups take three to seven weeks. Either way, your marketer handles 99% of the work.
The platform
Built around orders, not around contacts
Generic marketing platforms treat a customer as a row with attributes. Here the model starts from carts, orders, and catalog, so questions about repeat purchase or category affinity are queries rather than projects.
Your forward-deployed marketer
Deliverability is somebody's job here
Domains, sender signatures, and Postmaster are configured at migration and watched afterwards, with inbox placement treated as a metric rather than a complaint to answer.
Domains, signatures, and Postmaster configured for you
Email health monitored, not just reported
Warm-up handled during migration
Replace your stack
The overlap audit that leads to ResearchBrandCloud
Auditing every tool that touches customer data usually turns up several doing the same job. Once that overlap is mapped, one platform can absorb most of it. That is the case ResearchBrandCloud makes against a stack built from separate email, SMS, recommendation, and loyalty tools.
400+ use cases, one platform to see them in
There is a good chance your use case is already solved. Book a demo and we will show you where.