Slazenger
orchestration of personalized journeys (cart recovery + price drop)
Slazenger achieved a 49x ROI in eight weeks and +700% customer acquisition by orchestrating on Insider One AI personalized journeys for cart recovery (40% of potential revenue recovered) and price-drop alerts.
Key points
- AI-driven personalized journeys for cart recovery and price-drop alerts.
- Insider stack with Architect and Insider One AI (segmentation, timing, channels).
- 49x ROI in 8 weeks, +700% acquisition, 40% of cart revenue recovered.
- Evidence level B, mixed signals status (region and date not disclosed).
Objective
Convert hesitant visitors on a sportswear e-commerce site by recovering abandoned carts and re-engaging on price drops, without breaking the margin.
The deployment
Slazenger built personalized journeys on Insider, driven by Insider One AI. For cart abandonment, Architect and the Smart Journey Creator determine the best channels, delays, and send times, with reminders by email, web push, and SMS and a promo code by SMS. For price drops, a notification goes out by email and web push within 24 hours as soon as a product that was viewed, wishlisted, or abandoned drops by at least 10%. The campaigns cover nearly thirty customer segments.
Results Proof B
Quantified Insider case study, echoed on a second official Insider page. No independent press source, region not disclosed, hence B.
How it works
Inferred typical approachThe internal detail is not public. Here is a proven approach that leads to the same result, to adapt to your stack.
The stack in detail
- plateforme Insider omnichannel engagement platform: unified customer base, journeys, and email, web push, and SMS campaigns
- outil Insider Architect cross-channel journey orchestrator: choice of channels, delays, and send times
- outil Insider One AI (Smart Journey Creator, Smart Segment Creator) generative and predictive AI layer: building journeys and segments (nearly thirty segments at Slazenger)
How it runs, concretely
For ops teams-
1Unification and segmentation AI (Insider One AI) / e-commerce team
The unified customer base and the Smart Segment Creator split the audience into nearly thirty segments.
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2Journey building AI / e-commerce team
Architect and the Smart Journey Creator set the optimal channels, delays, and send times.
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3Cart trigger AI (automatic trigger)
Email, web push, and SMS reminders with a promo code by SMS on abandoned carts.
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4Price-drop trigger AI (automatic trigger)
Email and web push notification within 24 hours when a tracked product drops by at least 10%.
Onsite behavior (views, wishlist, carts) and product price. Without reliable per-user tracking of price and cart, the triggering of price-drop notifications and cart reminders no longer works.
How your customers perceive this type of use
Sourced studiesLe paradoxe est documente des deux cotes : 71% des consommateurs attendent des interactions personnalisees et 76% sont frustres quand elles manquent (McKinsey, 2021), mais 75% declarent ne pas acheter aupres d'organisations auxquelles ils ne confient pas leurs donnees (Cisco, 2024). La « creepy line » est localisee : messages recus quelques secondes apres une recherche et suivi de localisation sont les pratiques qui mettent le plus mal a l'aise (Periscope by McKinsey, 2019).
Acceptance conditions
- La confiance dans le traitement des donnees precede l'achat : 75% ne achetent pas sans elle (Cisco 2024)
- Un cadre legal protecteur rassure : 59% des consommateurs disent que des lois fortes sur la vie privee les rendent plus a l'aise pour partager des informations dans des applications IA (Cisco 2024)
- La personnalisation elle-meme est attendue quand elle est consentie : environ la moitie des consommateurs (US 55%, UK 52%) disent s'inscrire souvent ou parfois a des services personnalises (Periscope by McKinsey 2019)
Red lines
- Le message declenche quelques secondes apres une recherche ou un achat : deuxieme ou troisieme cause de malaise selon les pays (Periscope by McKinsey 2019)
- Le suivi de localisation percu comme de la surveillance : 40% de malaise en Allemagne et au Royaume-Uni (Periscope by McKinsey 2019)
- Le mesusage des donnees personnelles par l'IA, devenu la premiere inquietude des consommateurs, a 53% et en hausse (Qualtrics 2025)
Sources: McKinsey & Company 2021 · Periscope by McKinsey 2019 · Cisco 2024 · Qualtrics 2025
How to replicate
Inference, not sourcedData prerequisites
- per-user onsite behavioral tracking
- near-real-time product price feed
- email identifiers / web push and SMS opt-in
Org prerequisites
- an e-commerce team that runs the journeys
- a catalog with price variations to exploit
Possible stack
- Insider
- any omnichannel engagement platform with cart and price-drop triggers and AI segmentation
The plan, step by step
- Step 1Connect the signals: onsite behavioral tracking (views, wishlist, cart) and product price feedDeliverable: Events and prices flowing in near real time into the platform
- Step 2Collect web push and SMS opt-ins and establish the legal basis for profiling (GDPR)Deliverable: Channels activated with traced consents
- Step 3Arm the cart-abandonment journey: multichannel reminder (email, web push, SMS with promo code) at optimized timingDeliverable: Cart journey live on a test segment
- Step 4Add the price-drop alert: notification within 24h when a tracked product drops by at least 10%Deliverable: Second journey live, segments refined
- Step 5Measure recovered revenue and conversion by segment against the period without journeysDeliverable: ROI readout by journey and segment extension plan
First step: Connect per-user price and cart tracking, then first arm the cart-abandonment journey before adding price-drop alerts.
The same pattern, proven in other industries
Function of Beauty
personalized product formulation by algorithm from a quiz
Henkel
genAI content supply chain for one-to-one personalization at scale
Hims & Hers
AI-driven personalized treatment routing on intake data (MedMatch)
Sources
- S1 Slazenger gained 49X ROI thanks to Insider's omnichannel marketing solution Interested party archive pending
- S2 5 omnichannel marketing examples and case studies (with results) - Insider Interested party archive pending
An error, newer info, a source?
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