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boohooMAN Loomi Shopping and Messaging Agents

The conversational agent returned 13x ROI, and an AI-timed birthday SMS flow returned 25x.

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An always-on stylist agent on boohooman.com, and lifecycle decisions that pick who gets an SMS and when.

What the agent does

Acts as an always-on stylist that recommends from the live catalog, and decides for each customer whether and when an SMS goes out.

Contributed by
Bloomreach (Loomi Conversational Agent and lifecycle messaging)
Industry
Retail, Apparel & Footwear
Audience
B2C
Category
Search & DiscoveryMarketing & Personalization
01
The problem

Why this exists

The boohoo group runs a portfolio of ecommerce fashion brands, including boohoo, PrettyLittleThing, Debenhams, and boohooMAN. Shoppers on a large fast-fashion catalog rarely search by product name. They know the look or the occasion, and keyword search and static filters leave them to do the work.

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Messaging had the same limit. boohooMAN's earlier SMS tool sent unsegmented, non-personalized offers on big shopping days, mostly to inactive customers, and never returned better than 2x. Rules could not decide per customer who should hear from the brand, when, or whether at all.

02
Outcomes

What changes when this is in place

  • The Loomi Conversational Agent delivered 13x ROI by acting as an always-on, personalized digital stylist for every site visitor.
  • A birthday SMS flow aimed at customers not opted in to email returned 25x ROI.
  • SMS overall returned 5x ROI, and Black Friday returned 7x after messaging, personalization, and segmentation were tightened. These figures are for customers in the United Kingdom.
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  • Bloomreach credits the SMS results to AI-optimized timing and segmentation rather than manual rules.
03
How it works

Architecture

On site, the Loomi Conversational Agent interprets each shopper's natural-language request, searches the live catalog, and recommends products without human intervention. In a single conversation it works across Bloomreach's search API, the customer data engine for profile and behavior, and the recommendations API, so every answer stays grounded in products boohooMAN can sell.

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In messaging, Loomi works from the same customer data engine, which activates new behavioral data within seconds of ingestion. It decides per customer whether a send is likely to add value, which segment they belong in, and when to send, and SMS now runs as part of boohooMAN's omnichannel program rather than as a one-off channel.

Deterministic rules handle consent and frequency capping, machine learning handles prediction such as send time, and generative AI handles natural-language understanding. Bloomreach builds its agents on all three so each decision type uses the method that is reliable for it.

A shopper on boohooman.com talks to the Loomi Conversational Agent, an always-on digital stylist that interprets the request, searches the live catalog, and recommends. It works with the Bloomreach search API over the live product catalog and the Bloomreach recommendations API. The Bloomreach customer data engine, which activates profile and behavioral signals within seconds of ingestion, feeds both the conversational agent and the Loomi lifecycle decisions. Those decisions, constrained by a rules layer for consent and frequency capping, choose per customer whether to send, the segment and the timing, and produce personalized SMS such as the birthday flow, Black Friday, and lifecycle campaigns.

A shopper on boohooman.com talks to the Loomi Conversational Agent, an always-on digital stylist that interprets the request, searches the live catalog, and recommends. It works with the Bloomreach search API over the live product catalog and the Bloomreach recommendations API. The Bloomreach customer data engine, which activates profile and behavioral signals within seconds of ingestion, feeds both the conversational agent and the Loomi lifecycle decisions. Those decisions, constrained by a rules layer for consent and frequency capping, choose per customer whether to send, the segment and the timing, and produce personalized SMS such as the birthday flow, Black Friday, and lifecycle campaigns.
Open standards used
REST APIs
Tech stack
Bloomreach Loomi Conversational AgentBloomreach Loomi AIBloomreach customer data engineBloomreach search and recommendations APIsBloomreach Engagement SMS
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Resources

Published case study
Next step

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Bloomreach is behind this solution. Ask about guiding shoppers and timing messages without manual rules, and the MACH Alliance will put you in touch with the person who can answer.

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Everyone credited on this solution

  • BloomreachLoomi Conversational Agent and lifecycle messaging

Every organization named here has a page listing the rest of its work on the Hub.

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Verification

Published case study

The detail on this page is drawn from a case study published by the contributor or the MACH Alliance. Any figures on this page are the ones that case study states.

Where this came from

Published from the winner's case study and the 2026 MACH Impact Awards announcement. Solution detail is drawn from Bloomreach's 2026 MACH Impact Awards entry, its Loomi shopping agent product page and its boohooMAN case study.

Status: Live in productionAdded Sep 29, 2026A listing is an editorial decision, not a MACH Alliance certification.
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