Stable device identification powers personalization, A/B testing, and cart recovery for anonymous traffic. 90-97% of e-commerce visitors never log in — TRACIO turns them into a personalized audience.
90-97% of e-commerce traffic is anonymous — never logging in, never identifying themselves. Every unrecognized returning visitor is a broken personalization loop.
Dynamic Yield Anonymous Visitor Research, 2024
Between 90% and 97% of e-commerce visitors never log in. They browse, abandon carts, and disappear — only to return days later as 'new' visitors. Cookie-based tracking forgets them every time browser data is cleared. The result: every personalization signal you collected is wasted.
Recognized returning visitors convert meaningfully higher than anonymous ones — industry benchmarks put the lift in the 1.3-1.8× range. The gap is driven entirely by the personalization signal you can build over time — preferences, cart history, browse patterns, A/B test assignments. Cookie loss erases all of it.
Persistent device identification rebuilds the link. When you can recognize a returning visitor without requiring a login — across cookie clears, incognito mode, and browser switches — anonymous traffic becomes addressable. Personalization works for the 97% who never log in.
TRACIO links every visit to a stable device identity, powering personalization without login.
Every visitor receives a persistent device identifier that survives cookie clears, incognito mode, and browser switches. The same device is the same visitor — always.
Browse history, cart events, search queries, and A/B test assignments are linked to the device profile. Personalization signal accumulates over time, even without login.
Returning visitors are recognized in under 50ms. Personalized content, recommendations, and offers are served from the first page view.
Recognized visitors see relevant products, recover abandoned carts, and stay in consistent A/B test cohorts. 15-30% conversion lift on returning anonymous traffic.
Each gap exists because cookie-based identification fails the moment a user clears state. Hardware-level identification bridges them.
Browser cookies are routinely cleared by privacy tools, ITP, and manual user actions. Every clear erases the personalization signal you collected. Device identity is independent of cookies.
Users switch between Chrome on desktop, Safari on iPhone, and Firefox at work. Cookie-based tracking treats them as three separate visitors. Cross-browser linking unifies them.
When cookies are lost, returning users get re-randomized into A/B tests, contaminating your results. Stable device identity preserves test assignments across sessions.
Cart recovery emails require login or cookie persistence. Device-based recognition lets you trigger personalized cart reminders for anonymous users on their next visit.
Results based on industry benchmarks and published research.
conversion lift on returning anonymous visitors
McKinsey Personalization Research, 2024
increase in recommendation CTR
Dynamic Yield Benchmarks, 2024
revenue lift from targeted personalization
McKinsey Personalization Research, 2024
A/B test assignment across sessions
Fingerprint Device Intelligence Report, 2026
Results vary by industry, traffic mix, and personalization strategy. Figures represent ranges observed across published research and case studies.
Recognize the same visitor across sessions, browsers, and privacy modes. Hardware-anchored identity stays stable where cookies break — 99.5% accuracy.
Build and update anonymous reader profiles automatically. Browse history, cart events, and A/B test assignments persist across sessions.
Sub-50ms visitor recognition for personalization, recommendations, and dynamic content. Fast enough for first-paint personalization.
Unify visits across Chrome, Firefox, Safari, and Edge on the same device. End the fragmentation that breaks personalization signals.
Track personalization lift by visitor segment, content category, and A/B test cohort. Quantify the revenue impact of recognition.
Lock visitors into consistent A/B test variants across sessions. Eliminate the cookie-loss contamination that pollutes test results.
A few lines of code, one API response with everything you need.
import Tracio from '@tracio/client'// Initialize on every page loadconst tracio = await Tracio.load({ apiKey: "tk_live_..." })// Get persistent visitor identityconst { deviceId, isReturning } = await tracio.identify()// Fetch personalized contentconst profile = await fetch(`/api/profile/${deviceId}`)const recommendations = await fetch( `/api/recommendations/${deviceId}`)Start with a free plan. Deploy in minutes. See results from day one.