We detected 66 customers using Maestra, 9 companies that churned or ended their trial, and 5 customers with estimated renewals in the next 3 months. The most common industry is Retail (32%) and the most common company size is 51-200 employees (30%). Our methodology involves detecting JavaScript snippets or configurations on customer websites.
About Maestra
Maestra provides an all-in-one personalization platform for direct-to-consumer brands that combines real-time customer data, omnichannel messaging including email and SMS, site and product personalization, price personalization through loyalty and discounts, and analytics to help drive conversions through tailored customer experiences.
🔧 What other technologies do Maestra customers also use?
Source: Analysis of tech stacks from 66 companies that use Maestra
Commonly Paired Technologies
i
Shows how much more likely Maestra customers are to use each tool compared to the general population. For example, 287x means customers are 287 times more likely to use that tool.
I noticed that Maestra users are clearly e-commerce brands operating at a sophisticated level, specifically on Shopify Plus. The overwhelming presence of Shopify Plus tells me these aren't small online shops testing the waters. They're established brands doing serious revenue, likely $1M+ annually, who need enterprise-level commerce capabilities. The combination of tools points to companies focused on customer retention, repeat purchases, and maximizing lifetime value rather than just acquiring new customers.
The pairing of Loop Returns and Rise.ai is particularly revealing. Loop Returns handles product returns while Rise.ai manages gift cards and store credit. Together, they show me these companies are turning a negative experience (returns) into retention opportunities by offering store credit instead of refunds. Add in Attentive for SMS marketing, and you see a coordinated strategy to keep customers engaged and buying repeatedly. Triple Whale's presence suggests these brands are data-obsessed, constantly tracking their metrics and attribution across channels to optimize what's working.
My analysis shows these are marketing-led operations in growth or scale-up stages. They've moved beyond basic acquisition tactics and are now optimizing the entire customer journey. The stack reveals companies that understand their unit economics well enough to invest in retention infrastructure. They're likely spending significantly on paid acquisition through Customers.ai and other channels, which makes the retention tools even more critical for maintaining healthy margins.
👥 What types of companies is most likely to use Maestra?
Source: Analysis of Linkedin bios of 66 companies that use Maestra
Company Characteristics
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Shows how much more likely Maestra customers are to have each trait compared to all companies. For example, 2.0x means customers are twice as likely to have that characteristic.
Trait
Likelihood
Country: US
4.1x
I noticed that Maestra's customers are predominantly consumer-facing retail and e-commerce companies selling physical products. These aren't software companies or B2B services. They're businesses that ship tangible goods directly to customers: athletic wear and swimwear (JOLYN, Svaha USA, Coolibar), home goods and furniture (Dorai Home, I Love Linen, Furniture Fair), specialty food products (Bokksu, Hawaii Coffee Company), jewelry and accessories (jewellerybox, Loveweld), and sporting equipment (Selkirk Sport, Magnum Bikes). Many operate primarily online with their own branded products.
Most appear to be in the growth or scaling phase. Employee counts cluster heavily in the 11-50 and 51-200 ranges. Several mention rapid expansion (SEARADAR "expanded more than fivefold in the last two years"), international distribution networks, and moving beyond initial product lines. A few have raised Series A or seed funding, but most show organic growth characteristics. They're past the scrappy startup phase but not yet massive enterprises.
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