Weak or manual product recommendations
14 recommendation engines, one catalog, zero guesswork
From bestsellers to personalized post-purchase picks, ecommerce brands run all 14 on KitGrowth, a marketing personalization platform with a dedicated forward-deployed marketer, to match products to real customer behavior.
The problem
When recommendations actively work against your average order value
Some recommendation setups surface whatever is cheapest or easiest to match, quietly dragging down AOV instead of lifting it. Others require so much manual customization that teams end up doing the engine's job for it, defeating the point of automation.
What we hear from brands
an ecommerce brand with a companion mobile app sees product recommendations surfacing very low-priced items, dragging down AOV
an industrial-supplies company wants recommendations based on industry affinities and cart context, but existing solutions require heavy customization
a home goods and drinkware brand says current upsells require significant manual editing and don't effectively cross-sell between categories
The new way
When browsing isn't enough, ask the customer directly
Product-picking quizzes cure decision fatigue by asking a few short questions and surfacing matching products immediately, while capturing preferences that sharpen targeting across every channel. Pair that with value-packed bundles built from products that actually go together, and discovery stops depending on the customer getting lucky.
Outcomes brands report
27%
reduction in marketing stack costs
7.4%
of total revenue generated through a personalized cross-sell flow
+26%
total sales after consolidating the marketing stack
How it works
Migration at any scale, same method
Map what exists
Every flow, segment, and integration currently running is inventoried before a single one is rebuilt.
Rebuild in parallel
Your marketer has moved brands of every size and runs the new setup next to the old one until it matches.
Go live in weeks
Two to four weeks is typical, three to seven for nine-figure complexity, with no gap in sending.
The platform
Speed is a feature of the data model
Personalization only works if it answers before the page does. The platform handles 2M requests per minute with responses under 300 milliseconds, which is what lets a widget react inside the visit rather than after it.
Including
Your forward-deployed marketer
Lessons from hundreds of brands, applied to yours
Your marketer has run this migration and these flows for ecommerce brands before, so the first version of a program starts from what already works elsewhere rather than from a blank canvas.
Patterns taken from hundreds of implementations
Ecommerce-specific expertise, not general martech
Faster results because the first draft is not guesswork
Replace your stack
Agency plus point tools, priced honestly
The common setup is several subscriptions and a retainer for the people who operate them. Here the operating is included, which changes what the comparison is actually between.
Replaces
Klaviyo
Attentive
Rebuy
Nosto
Yotpo
The next step is smaller than a migration
Look at the platform, ask what your first month would look like, and decide after that.