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AI Website PersonalizationContent and offers for each visitorB2B PersonalizationEach company sees its own industryProduct RecommendationsWhat each shopper wants nextContent RecommendationsThe next article each reader wantsA/B TestingA winning version for each audienceDynamic Landing PagesPages that match the ad they clickedAI Search & Chat AgentAnswers from your own pagesBanners & Pop-UpsShown by behavior, source, locationAI Promotion ManagerAI picks each shopper’s best offerSocial ProofLive ratings, stock and recent buysReach them after they leave
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Behavioral TargetingAudiences that update themselvesAudience DiscoveryBuyers you didn’t know you hadWebsite AnalyticsSessions and revenue, per personWhat visitors tell you
Reviews & TestimonialsReviews from 17 sites, per visitorSurveys & NPSAsk a question; use every answerAI Chat AgentAnswers, then hands over to peopleMeeting SchedulerThe right visitors book a callAI tools and your stack
Personalization PlatformEvery tool on one visitor profileAI AgentDescribe a campaign; it drafts itIntegrationsHubSpot, Salesforce, Segment, GTMApp MarketplaceBuilt-in and reviewed partner appsAPIs, SDKs & AutomationREST API, server and mobile SDKsMCP ServerRun Personyze from your AI assistantAn AI shopping assistant on your page. Shoppers describe what they need in their own words — “something warm for walking to work in the snow” — and get picks from your own catalogue, weighed against everything they viewed and bought and ranked by your recommendation engine, each with the reason it fits.
Not sure where to start? See AI finder ideas for your site ↓

















A bar sits on the page, with a first line written for the shopper in front of it. They describe the need in their own words, and it answers with a short summary and up to four picks from your catalogue — each with the reason it fits — plus a few more worth a look.
For cold, wet days on the trail you want insulation that stays warm when damp and a shell that packs small. All three are under €250; the first is the lightest.

Warm to minus fifteen, and packs into its own hood.
Warm when dampPacks smallYour size in stock
One layer instead of two on a wet day.
WaterproofUnder €200Best seller
The mid layer for evenings in the hut.
LightGoes under a shellTrendingThe AI writes the summary and the reasons; the picture, price, stars and link on every card come straight from your catalogue. A sold-out item never appears as a pick.
Under the results, “Ask about your picks”: which one is warmer, does it come in navy — answered without starting over.
It answers, and writes every reason, in the visitor’s language — and searches your catalogue in the catalogue’s own.
Results stay for the whole visit: “See your picks” brings them back on the next page, in a whole page, a box or a side panel.
Private by design. What a shopper viewed and bought shapes the picks; it is never said back to them.
Free AI tool · Inspire me
Give Inspire me your address. It reads your pages the way a first-time visitor sees them and writes where a product finder, a chat or a question would help: on which page, for whom, and how to measure it.
Like an idea? Describe it to our AI personalization agent and it builds the campaign for you.
1What kind of ideas?
2Your website
Free · nothing to install · it reads your public pages
Reading yourstore.com
As a new visitor would see it · about 4 minutes

Waypoint & Co. Done
Only: Chat & surveys · your plan
2Ask what they need and narrow the catalog
Waypoint & Co. assistantWalking to work in the snow? These three keep you warm and dry.Ask about fit, repairs, delivery…Drawn on your own page — for a visitor on a phone who asked for something warm.
The question says what they need. Their history says what they like: every product they viewed, carted and bought. The finder weighs both, and your personalized recommendation engine ranks the fits by how likely this shopper is to buy each one — the same scoring behind your recommendations.
“Something warm for walking to work in the snow”
Shoppers see the picks and the reasons. What they viewed and bought shapes the order, and is never said back to them.
Only products that answer the need are in the running — not every item that happens to share a keyword.
What they viewed, carted and bought, on this visit and the ones before, moves the likely ones to the top.
The ranking comes from your personalized recommendation algorithm, so the finder and your recommendation widgets agree on what this shopper will want.
Under the picks you choose what comes next, so a question can end in a cart, a coupon or a booking — without the shopper leaving the page.
Straight from a pick, where your store’s add-to-cart is set up in product tracking.
Everything picked, side by side, with up to two buttons of your own — See the range, Book a fitting.
Up to three more items under the main picks, for the shopper who wants options.
Let it mention your offers, and the right coupon can appear with the picks.
Let it offer a meeting, and a calendar opens in the results for the shopper who wants a person.
Up to three of your other actions under the picks — reviews, a survey, social proof, recommendations, a form.
The same assistant also comes as a box you drop into a page. Point it at your product catalogue or your content catalogue and it does not stop at a paragraph: it answers in a sentence, then hands back the items themselves — ranked for the person searching by the same engine that orders your recommendations.
For rain and wind rather than cold, the waxed and shell layers do more than the wool does. All four are in stock in your size.
The same engine that orders your recommendations, ordering your search results. Keyword search returns the same four to everybody — this does not.
And it can be held to one part of the library. An ask box beside the pricing table can be told to answer from pricing only, and to say so rather than wander into the returns policy.
The wizard’s steps, then the designer with each of its settings open — real screens from the panel, one after another. Or watch both finders set up, start to finish.
The first step checks what it picks from: how many products, where they come from, and what every card needs — a picture, a price, whether it is in stock.
Viewed, added to cart, purchased — the events behind the rankings, and behind what it knows about each shopper.
You switch on what it may use: the page they are on, this visit, earlier visits, what they finished before.
Audience rules in plain words or built from conditions, with a forecast of who will match.
Dark, light or your colour, then every surface, corner, font and the way it arrives — previewed beside you.
A title, more titles taking turns, the invitation and examples to tap — or words written for each visitor.
Your catalogue, plus the recommendation algorithms it may lean on — trending, best sellers, new, similar, viewed together — and “Only recommend” rules.
The whole page, a box or a side panel; the question box, the waiting animation and the next-step buttons.
Whether it hands over to a person, extra instructions, what it must never say — and whether it may mention offers or a meeting.
Where on the page, when it opens, how often and where it may run — with a summary of what the visitor actually gets.
A shopper describes a need, and the assistant picks the products — each with a reason.
A reader asks a question, and the assistant picks what to read next.
Screens from a Personyze demo shop. The products and numbers are illustrative.
A finder is not always the best one. All three run in Personyze on the same catalogue — use each where it works.
| The way | The shopper | Best when |
|---|---|---|
| AI Product Finder | The shopperDescribes the need in their own words | Best whenThe range is wide and needs are specific: they know what it is for, not which item it is. |
| A quiz with pictures | The shopperTaps an answer, picture by picture | Best whenThere are a few clear paths — a size, a style, a use — and you want every answer kept for targeting. |
| Recommendations | The shopperAsks nothing; the page shows them | Best whenThey are browsing, not asking: what they viewed, what is trending and what goes together fills the page. |
AI product finder vs. product recommendation quiz — the longer answer →
Nothing reaches a shopper until the last one — and even then it can start in testing, visible from a staging address only.
A connected store, a feed, a file, SFTP — or Personyze reads the products off your site. With several feeds, choose the one it picks from. The content finder also reads your site’s own pages.
A title, the invitation and up to four examples to tap — or let it write the bar’s line for each visitor. Then one of twelve looks, your colour and your font.
“Only recommend” rules like your recommendation filters, the rankings it may lean on, a list of what it must never say, and whether it may mention offers or offer a meeting.
A bar at the foot of the page, a side spot or inside your page, and the campaign decides who sees it. Preview it as a real visitor, then start it in testing.
A bar on your store where a shopper describes what they need in their own words and gets a short list of products from your catalogue, each with the reason it fits. It is the conversation they would have with someone in the shop, answered from your own range.
Yes, in the sense shoppers mean: it helps them choose. It answers questions about the picks too — which one is warmer, which fits a small kitchen — and on a product page it can answer questions about that one product.
Search matches keywords and returns the same page of results to everybody. The finder reads the whole sentence — the trip, the budget, the person it is for — and answers with a short summary and a handful of picks, each with its reason. The same assistant also comes as an AI search box that answers in a sentence.
A quiz asks fixed questions with fixed answers, so it works when there are a few clear paths. The finder takes one free-text question, so it works when needs are too varied to script. Personyze runs both: a quiz is a survey with picture answers, and every answer can be kept for targeting.
From your product catalogue only. The AI writes the summary and the reasons; every card is drawn from a catalogue row, so a card cannot show an invented product, price or link, and a sold-out item never appears as a pick. You can limit what it may recommend with the same rules as your recommendation filters.
Yes. Their words decide what fits; their history decides the order. The finder weighs every product they viewed, carted and bought — on this visit and the ones before — and your personalized recommendation engine ranks the fits by how likely this shopper is to buy each one. What they viewed is never said back to them.
The product finder needs a product catalogue: a connected store, a feed, a file, SFTP, or Personyze reading the products off your site. The content finder picks from your articles and your site’s own pages.
Yes. The AI Content Finder is the same assistant pointed at your content: a reader asks a question and gets the articles that answer it, each with its reason.
It answers, and writes the reason on every card, in the visitor’s language, and searches your catalogue in the catalogue’s own. Its built-in buttons and messages come in eleven languages, and your own wording can be translated per language.
Yes. A finder is an action in a campaign, so the targeting you already use applies — audience, page, country, device. Its words can change per audience, and its first line can be written for each visitor from what you know about them.
The campaign report counts shows, clicks and goals, and its Conversations tab shows reach, conversations and what it could not answer. Every question shoppers asked is kept and searchable, so you can read what they wanted in their own words.
“Warm for the snow”Insulated Parka — stops the wind
“Easy espresso at home”Compact Espresso — easy to clean
“My first 10K”Trail Runner — cushioned and light
“A gift for a new cyclist”Bike Light Set — seen on dark evenings
“Camping with two kids”Dome Tent — up in five minutes
“Carry-on for a week”Cabin Case — fits the overhead bin
“Warm for the snow”Insulated Parka — stops the wind
“Easy espresso at home”Compact Espresso — easy to clean
“My first 10K”Trail Runner — cushioned and light
“A gift for a new cyclist”Bike Light Set — seen on dark evenings
“Camping with two kids”Dome Tent — up in five minutes
“Carry-on for a week”Cabin Case — fits the overhead bin
“A gift for a new cyclist”Bike Light Set — seen on dark evenings
“Camping with two kids”Dome Tent — up in five minutes
“Carry-on for a week”Cabin Case — fits the overhead bin
“Boots that grip on ice”Winter Boots — lined, with grip
“Layers that don’t itch”Merino Crew — soft, warm when damp
“Hiking in the heat”Insulated Bottle — cold all day
“A gift for a new cyclist”Bike Light Set — seen on dark evenings
“Camping with two kids”Dome Tent — up in five minutes
“Carry-on for a week”Cabin Case — fits the overhead bin
“Boots that grip on ice”Winter Boots — lined, with grip
“Layers that don’t itch”Merino Crew — soft, warm when damp
“Hiking in the heat”Insulated Bottle — cold all day
“Boots that grip on ice”Winter Boots — lined, with grip
“Layers that don’t itch”Merino Crew — soft, warm when damp
“Hiking in the heat”Insulated Bottle — cold all day
“A coat for travel”Merino Travel Coat — packs flat
“Cold feet at my desk”Merino Socks — warm, not sweaty
“Something under $30”Ribbed Beanie — $28, in rust
“Boots that grip on ice”Winter Boots — lined, with grip
“Layers that don’t itch”Merino Crew — soft, warm when damp
“Hiking in the heat”Insulated Bottle — cold all day
“A coat for travel”Merino Travel Coat — packs flat
“Cold feet at my desk”Merino Socks — warm, not sweaty
“Something under $30”Ribbed Beanie — $28, in rust
“A coat for travel”Merino Travel Coat — packs flat
“Cold feet at my desk”Merino Socks — warm, not sweaty
“Something under $30”Ribbed Beanie — $28, in rust
“Commuting by bike”Saddle Bag — keys, phone, a spare tube
“Gloves I can text in”Knit Gloves — touch-screen tips
“A present for my mum”Wool Scarf — soft, in oatmeal
“A coat for travel”Merino Travel Coat — packs flat
“Cold feet at my desk”Merino Socks — warm, not sweaty
“Something under $30”Ribbed Beanie — $28, in rust
“Commuting by bike”Saddle Bag — keys, phone, a spare tube
“Gloves I can text in”Knit Gloves — touch-screen tips
“A present for my mum”Wool Scarf — soft, in oatmeal
“Commuting by bike”Saddle Bag — keys, phone, a spare tube
“Gloves I can text in”Knit Gloves — touch-screen tips
“A present for my mum”Wool Scarf — soft, in oatmeal
“Warm for the snow”Insulated Parka — stops the wind
“Easy espresso at home”Compact Espresso — easy to clean
“My first 10K”Trail Runner — cushioned and light
“Commuting by bike”Saddle Bag — keys, phone, a spare tube
“Gloves I can text in”Knit Gloves — touch-screen tips
“A present for my mum”Wool Scarf — soft, in oatmeal
“Warm for the snow”Insulated Parka — stops the wind
“Easy espresso at home”Compact Espresso — easy to clean
“My first 10K”Trail Runner — cushioned and lightBring your catalogue, pick a look and write the first line — and shoppers get a shortlist with reasons instead of a page of keyword matches.