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SPECIFICTION
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SocialHub.AI Recommendation Engine

socialhub.ai

WebAPI
Visit socialhub.ai
Spec score 7.0 #19 of 23 in Email Personalization Software

What it is

SocialHub.AI Recommendation Engine personalizes retail product picks from order history, product affinities, and product pairings. One engine can supply campaign emails, websites or online stores, and API calls for apps or other channels. The email Recommendations block calculates selections at send time, uses live catalog names, images, prices, and links, and excludes products already purchased by that member. Members without purchase history see no email block rather than invented suggestions; new or anonymous visitors can receive trending and popular items. Product-pair patterns are rebuilt nightly from order data, with cross-sell suggestions requiring multiple shared buyers and orders. Unsupported suggestions are omitted. The built-in engine is the default, though an external recommender can replace it. Browser setup uses a public key, allowed domains, and a script snippet. Pricing is available on request; integrations include Shopify, Amazon, Salesforce, and others.

Spec sheet

Purpose
The Recommendation Engine personalizes product picks for members using order history and product pairings.Read 8 Oct 2026 · socialhub.ai
Audience
The company describes its platform as an Agentic Retention Loop for enterprise retail.Read 8 Oct 2026 · socialhub.ai
Security
The trust page states AES-256 encryption at rest, TLS 1.3 in transit, customer-managed keys, and per-tenant database schemas.Read 8 Oct 2026 · socialhub.ai
Support
The company page invites inquiries about products, pricing, and implementation by email at [email protected].Read 8 Oct 2026 · socialhub.ai
Headquarters
The company page lists its address as 314, 8015 SE 28th St, Mercer Island, WA 98040.Read 8 Oct 2026 · socialhub.ai
Bought-together cross-sell
The engine mines cross-sell rules nightly from order data and scores product pairs to account for popularity.Read 8 Oct 2026 · socialhub.ai
Catalog data
Recommendations are drawn from the live product catalog and include current product prices and links.Read 8 Oct 2026 · socialhub.ai
Catalog grounding
Recommendations use live catalog names, images, prices, and product links.Read 8 Oct 2026 · socialhub.ai
Certifications and privacy
The trust page lists SOC 2 Type II and ISO 27001 certifications and describes support for GDPR and CCPA obligations.Read 8 Oct 2026 · socialhub.ai
Cross-channel access
The same recommendations are available through the API and to AI assistants as well as in email.Read 8 Oct 2026 · socialhub.ai
Email engine details
The email recommendation block fills at send time for each recipient, and excludes products the member already bought.Read 8 Oct 2026 · socialhub.ai
Email recommendations
Its Recommendations block fills each recipient’s email with picks computed at send time.Read 8 Oct 2026 · socialhub.ai
Encryption and residency
The trust page states AES-256 encryption at rest, TLS 1.3 in transit, customer-managed keys, and data-region options in the US, EU, and Asia-Pacific.Read 8 Oct 2026 · socialhub.ai
Evidence threshold
Cross-sell suggestions require multiple shared buyers and orders, and the suggestion card is omitted when the data does not support a recommendation.Read 8 Oct 2026 · socialhub.ai
External recommender option
The built-in engine is the default, but the email recommendation page says customers can use an external recommender instead.Read 8 Oct 2026 · socialhub.ai
Integration examples
The integrations page names Shopify, Amazon, TikTok Shop, SAP S/4HANA, Dynamics 365, Manhattan Active Omni, IBM Sterling, Salesforce, Segment, Adobe Experience Platform, HubSpot, Braze, Klaviyo, and Iterable.Read 8 Oct 2026 · socialhub.ai
Intended customers
SocialHub.AI describes its platform as serving enterprise retailers and says it serves 50 enterprise brands across 12 countries.Read 8 Oct 2026 · socialhub.ai
Nightly refresh
Product pair patterns are rebuilt nightly from the latest orders.Read 8 Oct 2026 · socialhub.ai
No setup for email block
The maker says adding the Recommendations block requires no data feed connection or recommendation rules.Read 8 Oct 2026 · socialhub.ai
No-history behavior
If a member has no purchase history, the email block does not display rather than showing fabricated suggestions.Read 8 Oct 2026 · socialhub.ai
Optional external recommender
An external recommendation engine can be used instead of the built-in engine, which the maker describes as the zero-configuration default.Read 8 Oct 2026 · socialhub.ai
Personalization
Known members receive recommendations based on their product and category affinity; new or anonymous visitors get trending and popular items.Read 8 Oct 2026 · socialhub.ai
Purchase exclusions
Products a member has already bought are excluded from their recommendations.Read 8 Oct 2026 · socialhub.ai
Recommendation surfaces
One recommendation engine serves personalized picks in campaign emails, on a website or online store, and through an API for apps or other channels.Read 8 Oct 2026 · socialhub.ai
Security certifications
The trust page lists SOC 2 Type II and ISO 27001 certifications and states GDPR and CCPA compliance.Read 8 Oct 2026 · socialhub.ai
Support contact
The company page lists [email protected] and +1 (425) 922-5280.Read 8 Oct 2026 · socialhub.ai
Web setup
Browser setup uses a public key, an allowed-domain list, and a small script snippet; the same key can be used to call the API.Read 8 Oct 2026 · socialhub.ai
Website and app use
The platform page says recommendations can appear on a website or online store and can be called from an app through the API.Read 8 Oct 2026 · socialhub.ai

Strong points and limits

Strong points

  • Recommendations use live catalog data
  • Email picks calculate at send time
  • Bought products are excluded
  • Unsupported cross-sells are omitted
  • API and website delivery are available

Limits

  • Pricing is available only on request
  • Pair patterns refresh nightly
  • No-history members get no email block
  • Browser setup requires domain and script configuration

Who it suits

It is aimed at enterprise retailers seeking personalized recommendations across email, web, stores, APIs, and apps. The maker describes the wider platform as serving enterprise retail.

Verdict

The engine offers one recommendation service across email, web, stores, and APIs, with catalog-grounded content and purchase exclusions. Retailers should account for nightly pairing updates, evidence thresholds, and the need to configure browser access.

Where Specifiction places it

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