Weak or manual product recommendations
15% more site conversion when recommendations actually understand your catalog
That's the lift Enlightened Equipment saw after moving product recommendations onto Maestra Platform, the marketing personalization platform that includes a dedicated forward-deployed marketer on every account.
Brands running on Maestra
The problem
Merchandising by hand doesn't scale past a handful of SKUs
Someone on the team is still hand-selecting which products show up in each recommendation slot, one placement at a time. It works for a small catalog, but every new SKU adds more manual work, and most of the catalog never gets a proper recommendation at all.
What we hear from brands
a leather handbag brand's small ecommerce team manually manages merchandising and A/B tests, limiting scale
an automotive parts retailer describes manual, time-consuming setup of upsells and bundles as SKU count expands
a men's grooming brand cites underperforming product pages and lean team bandwidth for testing and optimization
The new way
Matching that understands color, size, and material, not just category
Instead of grouping products by broad category, Maestra reads full product attributes so a red bikini top surfaces its matching bottom in the same size, material, and cut. Out-of-stock sizes are filtered out automatically, so customers never hit a dead end.
Outcomes brands report
+45.3%
more items per order among shoppers who engaged with recommendations
From the Blue Q case studyCustomer proof
Blue Q grew AOV 28.7% without touching its discounts
Blue Q needed to grow basket size without leaning on heavy discounts, so it migrated to Maestra for product recommendations, bundles, and a minicart slider of impulse-buy items. Shoppers who engaged with the recommendations bought more per order, and the lift held up without any deeper markdowns.
“Maestra has played a very significant part in raising our items per order and average order value. The result is real, and it’s not coming from deeper discounts.”
+28.7%
higher AOV
+45.3%
more items per order
How it works
The migration plan, in three plain steps
Grant access
Your forward-deployed marketer needs visibility into your current setup to plan the move. That access is the starting point.
Review the plan, then step back
Once you approve the roadmap, your dedicated forward-deployed marketer handles data migration, integrations, and flow rebuilding, covering the vast majority of the work.
Launch with deliverability already warmed
Domain warm-up happens before go-live, so your first sends on Maestra do not start from a deliverability deficit.
The platform
One system for the whole customer journey
From the first site visit to the tenth purchase, Maestra runs on a commerce-specific data model that keeps CDP, journeys, loyalty, and messaging in sync. The platform is built to process 2M RPM at under 300 milliseconds, so that sync holds up under real traffic.
Your forward-deployed marketer
A marketer who works inside your account, not around it
Migration, strategy, flow building, and A/B testing are handled directly by your forward-deployed marketer, reachable through a shared Slack channel, as part of every Maestra subscription with no separate line item.
Done-for-you migration, strategy, and flows
Shared Slack channel included
Included with every subscription, no extra fee
Replace your stack
Retire the point solutions, keep the results
Most ecommerce stacks run separate tools for email, SMS, recommendations, and loyalty, each with its own login and its own slice of customer data. Maestra replaces that sprawl with one platform, and customers consistently find that each tool they consolidate works better once it is unified.
Replaces
Klaviyo
Attentive
Nosto
Rebuy
Yotpo
Explore Maestra before you commit to anything
Walk through the platform, ask questions, and see how the modules connect. No pressure, just a clear look.