Sample application.

Alder & Borough is a London-based omnichannel retailer of premium fashion, footwear, and home goods. The company serves style-conscious customers through a mix of flagship stores, a transactional e-commerce site, a mobile app, clienteling tools that connect online behavior to in-person support from store associates, and always-on email and paid media programs.

The business is headquartered in London and trades primarily across the United Kingdom and Ireland, with digital commerce reach into selected European markets, including Paris, Amsterdam, Zurich, and Barcelona. Its growth strategy is built around connecting in-store service, digital commerce, and loyalty into one seamless brand experience.

Before selecting Adobe, Alder & Borough had a great deal of customer data stored in individual channels, but no cohesive way to activate cross-channel data and insights E-commerce, loyalty, in-store purchases, service interactions, and campaign engagement data all lived in separate systems, which prevented teams from seeing or actioning on full customer journeys.

The underlying data silos led to fragmented and high-friction experiences. Customers received inconsistent offers across web, email, and store channels. Campaigns had to be planned in batches, which made them too slow for fast-moving retail moments such as new-season launches, stock drops, promotions, and cart abandonment. The team also struggled to personalize at scale because the demand for content couldn’t keep pace with production (including manual approvals) and segment updates took too long to be useful.

Alder & Borough selected Adobe applications to unify data, orchestrate journeys, and personalize experiences. Adobe Real-Time CDP and Adobe Journey Optimizer were especially important because the unified data could provide a real-time customer view and then be activated to trigger relevant experiences and messaging across channels. Integrations between Adobe Experience Manager and Workfront also helped streamline content and workflow bottlenecks that were slowing execution.

Alder & Borough’s Adobe ecosystem integrates across several categories of business systems: cloud infrastructure and data ( Microsoft Azure, Snowflake), enterprise and commerce operations (SAP S/4HANA, retail POS and inventory systems), CRM (Microsoft Dynamics 365), and analytics (Power BI). These integrations ensure loyalty, service, and e-commerce systems all feed into the same underlying customer data foundation — giving downstream Adobe tools a consistent base to build on.

Alder & Borough uses Adobe products and embedded AI capabilities to turn fragmented interactions into coordinated journeys. AI features in Real-Time CDP stitch and segment customer data from multiple sources. Journey Optimizer’s features combine those profiles with pre-defined journeys (which AI also helps define) to trigger the next best message or action based on live behavior, channel preference, and product affinity.

Experience content gets a boost when Adobe’s generative AI capabilities are combined with Experience Manager Sites, Assets, and Adobe Target to automatically generate, store, and deliver content variations based on audiences and segments.

AI is now helping the business move faster and work smarter. Business users use AI-powered tools to explore audience performance, identify anomalies in buying journeys, and get recommendations for content or segmentation changes without relying on technical teams for every request. The result is a more agile operating model, with more relevant experiences for customers and less manual work for internal teams.

The biggest journey issues were caused by disconnected channels. A customer might browse online, see a different offer in email, and then receive no follow-up in store. Cart abandonment, browse abandonment, and stock-related journeys were especially weak because the brand could not quickly react to customer intent.

Another pain point was that store associates did not have enough visibility into what customers had viewed or saved online. That made it difficult to execute in-store concierge shopping experiences in a relevant way. The company also lacked timely triggers for moments like back-in-stock, replenishment, and category re-engagement, missing opportunities to convert demand when intent was highest.

AI-driven identity resolution in Real-Time CDP now stitches these previously siloed signals into a single, real-time customer profile, replacing the batch segments that used to take days to update. Journey Optimizer's AI-based decisioning uses that profile to determine the next best message or action across web, app, email, and clienteling — so customers receive fewer irrelevant messages and more useful prompts based on what they're actually doing in the moment, not what a stale segment said last week.

This AI-enhanced approach has also changed how internal teams work: business users now use AI-powered features in the Adobe applications to explore audience performance, spot anomalies in buying journeys, and get recommendations for content or segmentation changes — without needing to route every request through a technical team.

Browse-to-buy recovery
When a customer views a product several times, adds it to basket, or abandons checkout, Real-Time CDP captures the behavior and Journey Optimizer’s AI-based decisioning triggers a relevant sequence based on loyalty status, product category, and channel preference. Adobe Target updates the homepage and category modules to show the exact product family the customer was browsing, along with complementary items and size-availability messaging. If the customer does not convert, the journey shifts to email or mobile push, with AI-based send time optimization to avoid over-messaging.

Store-assisted clienteling and endless aisle
If a customer searches for an item online, checks store stock, or engages with a store associate, that intent is added to the customer profile and used to inform the next interaction. Store associates see AI-powered next-best product recommendations — personalized suggestions, alternative sizes, and ship-to-home options generated from the customer’s full online and in-store behavior. Customers then receive a follow-up journey that reflects the in-store conversation and surfaces related products or replenishment items. This has connected physical retail with digital follow-through in a more organic way.

Alder & Borough’s shift to customer-centric orchestration has improved both revenue and operational efficiency while significantly improving customer engagement and satisfaction. Personalized journeys now perform materially better than generic campaigns, and the company can launch and optimize them much faster than before.

Key results, and the capabilities that drive them, include:

• Journey Optimizer's AI-based decisioning has delivered a 2.0x uplift in conversion rate for personalized journeys versus generic campaigns.
• Data and audiences from Real-Time CDP trigger cart and browse recovery flows in Journey Optimizer that have improved recovered basket revenue by 31%.
• AI-powered cross-sell and recommendation journeys (Journey Optimizer + Adobe Target) have increased average order value by 18%.
• Personalized digital journeys have driven a 26% increase in loyalty enrollments.
• Streamlined content and workflow via Experience Manager and Workfront integration has reduced campaign build-and-launch time by 40%.
• Real-Time CDP's real-time audience updates have cut activation lag by over 70% — audience updates that previously took days now happen in near real time.
• AI-informed store-assisted clienteling journeys have driven a 15% increase in repeat purchase rate among customers exposed to follow-up.

The broader impact has been cultural as well as commercial. Teams now work around customer intent rather than channel silos, which has made the business faster, more coordinated, and more relevant at every stage of the journey.