Companies that use Ptengine

Source: Analysis of tech stacks from 112 companies that use Ptengine

I noticed that Ptengine users are predominantly e-commerce companies operating in Asian markets, particularly those selling through multiple channels and dealing with cross-border commerce. The presence of QuickCEP, a Chinese customer engagement platform, appearing over 10,000 times more frequently is a dead giveaway. These aren't just any online retailers. They're sophisticated operations juggling marketplace selling, direct-to-consumer strategies, and international expansion simultaneously.

The pairing of Attribuly and Awin tells me these companies are obsessed with attribution and performance marketing. Attribuly helps Shopify merchants track customer journeys across touchpoints, while Awin is a major affiliate network. Combined with Ptengine's heatmaps and session recordings, they're building a complete picture of how customers find them, what marketing channels actually work, and where people drop off. Forter's appearance makes sense too. When you're processing payments across borders and scaling quickly, fraud becomes a real concern. These companies are protecting their growth, not just chasing it.

My analysis shows these are marketing-led operations in rapid growth phases. They're past the startup stage where founders handle everything manually, but they haven't reached enterprise scale with dedicated analytics teams. The Walmart Brand Shop correlation suggests many are marketplace sellers who've graduated to operating their own storefronts and now need proper analytics infrastructure. They're data-hungry but probably don't have massive budgets for enterprise tools, which is exactly where Ptengine fits.

Source: Analysis of Linkedin bios of 112 companies that use Ptengine

I noticed Ptengine attracts predominantly direct-to-consumer brands selling physical products online. These companies manufacture and sell everything from consumer electronics (solar generators, pool cleaners, e-bikes) to fashion and home goods (furniture, athletic wear, travel accessories) to specialty items (fishing gear, portable music instruments, water filtration systems). The common thread is they're product companies with significant e-commerce operations, needing to optimize their digital storefronts and understand customer behavior across their websites.

These are predominantly growth-stage companies. The employee counts cluster in the 50-500 range, with several showing signs of recent scale (multiple international offices, millions of customers served, extensive retail partnerships). Some have raised Series A or B funding, but many appear bootstrapped and profitable. They're past the scrappy startup phase but not yet enterprise giants. They have enough traction to invest in optimization tools but still need to prove unit economics and customer acquisition efficiency.