You bought AI for discovery. Why isn't it paying?
44% of retailers invest in AI. Only 9% see measurable revenue from it. The difference is intent: bad signals in, bad results out. Most shops never learn what their shoppers actually mean — and without that, no tool can prove impact. The gap runs across discovery: search, suggestions, ranking, recommendations. Your highest-intent surface stays your least optimized.
Detect. Act. Excel.
One agent covers the whole product-discovery journey — for shoppers and AI assistants alike. It runs continuously on the stack you already have, and every decision stays yours to override.
Find customer journeys with untapped conversion potential.
Standard analytics count sessions and stop there. searchHub uses causal analytics: it follows the full product-discovery journey and ranks every journey by its potential for greater conversions, so you know what to optimize first.
Fix product discovery at the moment of intent.
Shoppers reveal intent one query at a time, and every touchpoint guesses alone. searchHub shapes intent as they type and rewrites each user query to its proven master query.
Turn one-off wins into compounding gains.
Rank by what shoppers buy, not by catalog text. Add neural intelligence only where it provides value, then test two answers at identical intent and keep the winner. Every outcome flows back into your discovery-intent data, so nothing resets and the whole system keeps getting sharper.
Where searchHub optimizes across the discovery journey.
The Detect, Act, Excel journey, shown as the six concrete touchpoints inside it.
Guessy autocomplete becomes intent as-you-type, statistically ranked. Discovery is guided from the first keystroke.
Zero results and wrong matches — 10 to 15% of searches — collapse into one clean intent before your stack retrieves. Thousands of spellings become one.
Route intent-matching search traffic straight to the landing and listing pages you already curate, instead of a one-size results page.
Most engines rank by how closely catalog text matches the words typed. searchHub ranks by what converts: among equally relevant results, the ones shoppers actually put in the basket.
Session analytics miss the full journey users and agents take on your site. See where discovery succeeds or fails, and correct where it counts.
Wasted intent becomes a signal every system learns from — signals, feeds and an API in one tool. Own your discovery-intent data; feed the rest of your stack and your AI.
Rank by what shoppers buy, not by what your catalog says.
Clean intent reaches your stack before it ranks. NeuralInfusion then re-weights the result set on what actually converts, so the right product surfaces higher. It is not a replacement ranker.
Not one test. A loop that never stops improving.
Because searchHub shapes the input before the engine ranks, every answer to a shopper intent can be challenged on live traffic — pass by pass by your team, or handed to autoLoop and run unattended. Winners ship, learnings feed the next round, and the gains compound.
Challenge what the same search returns by electing a different intent.
Send that search to a curated, merchandised page instead of a result list.
Blend neural-matched products into the set where they lift conversion. Beta.
Every improvement pays off by itself. Together, they learn from your own traffic — so results get better without you guessing what to fix next.
"Even a good onsite search benefits from searchHub. Our A/B tests showed an increase in both conversion rate and average order value."
Your shop's richest first-party signal is the discovery trail. Own it.
Session analytics credit the last click. searchHub follows every shopper's and every agent's full trail — query, suggestion, impression, redirect, click, basket, purchase — and consolidates it by intent. That is causal analytics, and it is exactly the first-party data AI-driven discovery runs on.
Hand an agent your full assortment and it still ranks by what performs on its platform — not the products you want to position. searchHub structures your intent and product data so agents surface your choices for the right intent.
AI-referred retail traffic grew 393% year over year and converts 42% better than other channels. (Adobe, 2026)
- — Not a shopping agent. We do not buy for the shopper.
- — Not a replatform. Your engine and catalog stay where they are.
- — It is the layer that makes both readable, today.
Keep your stack. Improve what it delivers.
searchHub runs in front of Algolia, FactFinder, Bloomreach, Coveo, Elasticsearch and more. Live in weeks, not a months-long migration.
Same traffic. Same engine. More revenue.
One agent. Distributed value.
A vendor that accelerates your roadmap instead of blocking it: engine-agnostic, no replatform, agentic-ready, and controlled by your team. Neural only where it pays for itself — and your first-party discovery-intent data stays yours.
A growth lever you can pull without headcount: live in weeks, fully deployed within 30 days, scaling across languages and tenants. Search and product discovery are your highest-intent real estate. Don't leave them unoptimized.
The next source of revenue is already in the house: board-ready return on the discovery stack you already paid for. No replatform. Deployed by peers.
The agent groups every spelling and variant of a search into one intent, then routes that traffic to the pages you curate. Redirects, keyword landing pages, category pages: you decide where shoppers land, the agent gets them there. You manage a tool instead of a pile of rules.
One source of truth for what shoppers are looking for. The tool shows exactly what changed and why, and you stay in control — without touching your existing discovery technology.
Every step of the journey — from people and from agents — collected as your own first-party data, available as signals, feeds or API. The data foundation for product discovery that web analytics never provided.
What is your search quietly costing you?
See where shoppers feel misunderstood, fix it at the source, and prove the lift. On the stack you already run.