The Salesperson That Never Sleeps: How an AI Shopping Assistant Recovered $410K
in Would-Be-Lost Sales
eBizTrait built a custom AI shopping assistant trained on a retailer’s own catalog and policies – answering pre-purchase questions instantly and recovering carts that would otherwise have been abandoned.
Results At A Glance
-
+19%
Conversion Lift
AI-assisted sessions
-
$410K
Recovered Revenue
annualized, cart-rescue
-
24/7
Coverage
zero added headcount
-
71%
Query Resolution
without human handoff
The Challenge
TrailForge Outfitters sold technical outdoor gear – tents, backpacking systems, layering setups – where customers routinely had specific, catalog-dependent questions before buying: “will this tent fit two sleeping pads and a dog?” “is this jacket warm enough for a Colorado winter or do I need the heavier one?” Questions generic FAQ pages couldn’t answer.
Their support team could answer these questions well, but only during business hours, and pre-purchase questions submitted via contact form had an average response time of 14 hours – by which point a meaningful share of customers had simply bought from a competitor or abandoned the purchase entirely out of uncertainty.
They’d tested a generic rule-based chatbot previously and pulled it within a month – it could only follow scripted decision trees and frustrated customers with questions even slightly outside its narrow flows, actively damaging trust rather than building it.
Our Approach
We built a custom AI shopping assistant grounded specifically in TrailForge’s actual catalog, sizing charts, technical specifications, and policies – not a generic chatbot layered on top with limited knowledge, but a system with genuine, accurate product-level understanding.
The assistant was designed around a strict accuracy-first principle: it would only answer from verified product data and clearly say when it didn’t know something and needed to hand off to a human, rather than a generic AI risk of confidently inventing an answer about technical gear where being wrong (a tent’s real waterproof rating, for instance) has real consequences.
We integrated the assistant directly into the shopping experience – available on product pages, in the cart, and proactively triggered when exit-intent signals suggested a customer had an unanswered question rather than simply abandoning silently.
What We Built
- Custom AI shopping assistant grounded in TrailForge’s full product catalog, technical specs, sizing data, and policies via a retrieval-augmented architecture
- Product-page and cart-embedded chat widget with context-awareness of exactly which product the customer is currently viewing
- Strict groundedness controls preventing the assistant from answering outside verified product/policy data, with clear human handoff when uncertain
- Proactive exit-intent triggering: the assistant offers help when behavioural signals suggest hesitation rather than waiting to be summoned
- Comparison assistance: customers can ask the AI to compare two products directly (“what’s the difference between the Ridge 2P and Summit 2P tents”) with accurate, spec-sourced answers
- Order-status and post-purchase query handling integrated with Shopify order data for logged-in customers
- Human handoff integration to the existing support team’s helpdesk for the ~29% of queries requiring a person
- Continuous accuracy monitoring: flagged conversations reviewed weekly to catch and correct any drift in product knowledge as the catalog changes
Results – Before & After
| Metric | Before | After |
|---|---|---|
| Pre-Purchase Question Response Time | 14 hours (contact form) | Under 5 seconds |
| Conversion Rate (AI-assisted sessions) | 2.4% (baseline) | 2.86% |
| Cart Abandonment (exit-intent recovered) | No recovery mechanism | 19% recovery rate |
| Query Resolution Without Human Handoff | N/A | 71% |
| Support Ticket Volume (pre-purchase queries) | Baseline | -38% |
| Annualized Recovered Revenue | – | $410,000 |
“The old chatbot made people angrier than no chatbot at all. This one actually knows our gear – it’ll tell a customer honestly if a jacket isn’t warm enough for what they’re describing, which sounds like a strange thing to praise a sales tool for, but that honesty is exactly why people trust it enough to buy. It’s like having our best gear specialist available at 2am.”
– Head of Customer Experience, TrailForge Outfitters
Key Takeaway
The failure mode of most ecommerce chatbots isn’t unavailability – it’s inaccuracy and rigidity, which erodes trust faster than having no assistant at all. An AI shopping assistant genuinely grounded in accurate, current catalog data – with strict honesty about the limits of its own knowledge – resolves the specific pre-purchase uncertainty that silently drives abandonment, at a scale and speed no human support team can match around the clock.
Ready to achieve similar results?
