Weak or manual product recommendations
Stop stitching a recommendation app onto five other tools
Maestra Platform replaces the bolted-on widgets with one marketing personalization platform and a dedicated forward-deployed marketer, so ecommerce brands run recommendations, email, and SMS from the same data.
27%
reduction in marketing stack costs
Brands running on Maestra
The problem
A big catalog is supposed to be an advantage, not a maze
When a store carries thousands of SKUs across categories, customers can end up clicking three or four levels deep just to find something relevant. Recommendation engines built for smaller catalogs choke on that complexity and default to showing whatever is most popular, not what fits.
What we hear from brands
a craft-supplies retailer says customers must go three or four levels deep to find products across a vast catalog
an art-supplies retailer reports poor product recommendations due to a huge SKU catalogue
an apparel brand with a large catalog has underperforming recommendation engines and inadequate personalization for mixed subscriber and one-time customers
The new way
One set of recommendations, synced everywhere a customer shops
The same product logic that powers your website also fills recommendation blocks in email, SMS, messengers, and even in-store POS. A customer who browses a product on-site sees a relevant follow-up in their next email, not a generic bestseller list pulled from a different system.
Customer proof
JOLYN's 4,000 SKUs finally get matched down to the exact cut
JOLYN's previous recommendation system ignored product detail entirely, showing the same popular suit to every customer regardless of size availability or color. After switching to Maestra, browsing a red bikini top surfaces the matching bottom in the same size, material, and cut.
7%
sales influenced by product recommendations
“Our previous recommendation system only looked at items generally, not specific product details, so if someone bought a red bikini top, they might get shown a totally unrelated bottom, or one that was out of stock in their size. Everyone got the same popular suit, no matter what they’d actually looked at. With 4,000 SKUs, this clearly wasn’t working. Now with Maestra, if you browse a red bikini top, you see the matching bottom, in your size, with the same material and cut. That attention to detail matters. It’s made shopping so much easier, helped people build full sets easily, and we’ve seen a clear improvement in conversion. Total game-changer.”
How it works
What onboarding with Maestra looks like, step by step
Answer a few questions
One customer's CRM lead described it this way: provide access, answer a few questions, help with domain warming. Everything else was handled for her.
Your forward-deployed marketer does the heavy lifting
Data transfer, integration setup, and rebuilding flows and campaigns fall on your dedicated forward-deployed marketer, who covers 99% of the work.
Go live on a realistic clock
Expect two to four weeks for a growing brand, three to seven weeks for a nine-figure business with a complex setup.
The platform
Built for commerce, not retrofitted for it
Maestra's data model was designed around products, orders, and customer status from the start, which is why it supports enterprise-grade scale without the usual integration tax. The platform holds up at 2M RPM with sub-300ms processing, so personalization does not lag behind the customer.
Your forward-deployed marketer
Why response time is the metric that matters most
A 72-hour reply is standard at most platforms. Maestra's forward-deployed marketers respond in 5 minutes, because each one manages under 15 accounts instead of the 60-plus norm, so your question is never sitting in a queue behind fifty others.
5-minute response time versus 72 hours industry-wide
Fewer than 15 accounts per marketer
Shared Slack channel included
Replace your stack
Consolidation without the compromises
Swapping five tools for one platform usually means giving something up. With Maestra, brands report the opposite: recommendations, loyalty, and messaging all improve once they share the same real-time data instead of syncing through exports and integrations.
Replaces
Nosto
Rebuy
Yotpo
Attentive
See what Maestra looks like on your data
Bring your current stack and your goals. We will show you where Maestra fits and what changes first.