You're showing everyone the same products.
Intempt Recommend builds a personalized product feed for every visitor using real behavioral history, purchase patterns, and catalog signals.
“We were losing visitors before they signed up. Intempt's personalized experiences changed that - we started meeting people where they were instead of guessing. Once they're in, Intempt's automated email takes over and keeps the relationship moving. Acquisition and retention finally feel like one connected motion instead of two separate problems.”
Jim Stromberg
CEO, StockInvest
Every visitor sees what they'll actually buy.
One behavioral model. Every placement. Every channel.
Recommendations trained on behavior.
- Product view, cart, and purchase event mappingEvery interaction feeds the model. Views, adds-to-cart, purchases, and browse sessions all shape what each customer sees next.
- Real-time behavioral model updatesThe recommendation updates as behavior changes mid-session. Not once a day. Not on a batch schedule.
- Catalog ingestion via Shopify sync or APIConnect your product catalog in minutes. Changes propagate automatically without manual updates.
Homepage Best Sellers
48 items
PDP Similar Items
124 items
Category Trending
36 items
New Arrivals Feed
20 items
Feed preview
LiveMerino Crewneck
Canvas Tote Bag
Slim Chino
Linen Shirt
Feed name
Sorting strategy
Time range
Performance (30d)
Match the recommendation to the moment.
- Most Popular, Recently Viewed, Purchased Together, User AffinityDifferent placements need different logic. Intempt supports multiple strategies per placement.
- Image Similarity for visual-first catalogsSurface products that look similar to what a visitor browsed, even if the behavioral signal is thin.
- A/B test strategies per placement before going liveCompare 'Purchased Together' vs 'User Affinity' with real traffic before committing to a strategy.
Blu · insight12 products synced · 4 active in feeds
2 draft items excluded from live feeds. Catalog last synced 2 min ago.
| Product | Price | Status | Updated | |
|---|---|---|---|---|
 | $99 | Draft | Oct 24, 2023 | |
 | $185 | Active | Nov 02, 2023 | |
 | $245 | Active | Dec 01, 2023 | |
 | $320 | Active | Jan 10, 2024 |
Serve recommendations wherever it matters.
- JavaScript embed for on-site recommendation widgetsDrop a widget into any page in minutes. Homepage, PDP, cart, post-purchase, no engineering required.
- Personalized recommendation blocks inside Journey emailsThe same behavioral model that powers on-site recommendations powers your email content blocks.
- REST API for custom implementationsBuild your own recommendation surface with the Intempt API. Full control over presentation, same personalization engine underneath.
Blu · insightHomepage feed drives 34% of total recommendation revenue
PDP similar items feed CTR is declining. Try switching to collaborative filtering for this placement.
| Product | Price | CTR | Revenue | |
|---|---|---|---|---|
| $99 | 4.2% | $2.1k | |
| $185 | 6.8% | $4.9k | |
| $245 | 5.1% | $3.7k | |
| $320 | 3.9% | $5.8k |
Use cases built for the metrics that matter.
Three outcomes teams measure from day one.
Connect every trusted source.
Plug into the tools your team already runs on.
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Your customer data stays yours, and stays secure.
FAQ
Frequently asked questions
With sufficient catalog events, views, adds-to-cart, purchases, most customers see meaningful personalization within 1 to 2 weeks.
Yes. Feed strategies can be segmented by LTV tier, purchase history, or any Intempt segment.
Yes. The recommendation engine works for any catalog with a product ID: software plans, digital content, courses, and more.
Yes. Business rules let you exclude out-of-stock items, low-margin SKUs, or any product by ID or category.
Your catalog working smarter, starting this week.
Connect your catalog, drop a widget, and start serving personalized recommendations in minutes. No engineering required.