With a previous marketing vendor, The AA faced significant challenges in achieving its ambitious campaign goals related to new customer acquisition.  

Running campaigns to acquire new customers for its award-winning breakdown service, The AA team focused on a combination of prospecting, winning back former customers, and cross-selling to existing product holders. However, its existing marketing tools presented limitations, including slow data processing times, lengthy campaign execution, and an inability to easily test and optimize multi-channel strategies. 

The team needed much better speed-to-market time and needed the ability to test the omnichannel impact of campaigns on the customers being acquired.

In North America, Havanianas relies on effective email marketing to engage customers and drive sales through its direct-to-consumer ecommerce business.

Previously relying on an external agency to manage its ecommerce operations and email marketing capabilities within its Salesforce Marketing Cloud (SFMC) instance, Havaianas sought the flexibility that would empower its team to take greater control of its email marketing internally and scale the program more effectively.

As the UK’s leading arts and crafts retailer, Hobbycraft serves a passionate and highly diverse customer base, from casual DIY enthusiasts to professional creators. With a catalog exceeding 27,000 SKUs across painting, baking, knitting, and countless other creative categories, the company’s approach to ecommerce needed to reflect the same inspiration and variety as its stores.

As Hobbycraft expanded its online presence and doubled down on digital growth, it recognized that its existing search and merchandising setup wasn’t keeping pace with evolving shopper expectations. In particular, the brand faced several obstacles to delivering an artful product discovery experience:

• Limited scalability with a rule-based setup. The brand’s previous solution relied on rigid, rule-based configurations that demanded perfectly structured and enriched product data. With tens of thousands of SKUs, even small data inconsistencies led to broken results and unpredictable customer journeys.
• Unreliable search experience across large, varied assortments. Broad searches like “paint” or “stickers” often surfaced an unbalanced mix of products — such as kids’ kits alongside professional supplies — without any logical hierarchy or category intent. This made it difficult for customers to find what they needed quickly and confidently.
• Manual, high-effort merchandising processes. Traditional tactics like pinning or boosting offered limited control and required constant updates, especially when products went out of stock or campaign priorities shifted. Hobbycraft wanted to empower its merchandisers to guide the experience where it mattered most — ensuring curated variety in top search positions — while letting AI handle the rest. 

To best serve its customers and continuously meet their short-term coverage needs, Dayinsure strives to build an ongoing relationship with its audience. 

But doing so was a challenge with its previous marketing technology. Dayinsure needed to fully understand its customer base — what they wanted, what incentives they looked for, their preferred way to connect with Dayinsure, and more — to build customer relationships that went beyond the first purchase. 

At the same time, the brand needed to automate reengagement campaigns and effectively leverage its customer data. Manually segmenting audiences and building workflows took up too much time and team bandwidth, driving Dayinsure to seek out a more advanced solution.

TFG has always had a customer-first approach, which is why it wanted to find new ways to create personalized experiences for its customers without being intrusive. The company was aware of recent advancements in AI technology that would open up new ways to connect with customers. In particular, the organization wanted to explore using conversational shopping as a solution.  

However, since conversational AI is still a new technology, TFG had concerns: What would it be perceived as assisting with? Would the solution just provide stock answers (that any algorithm could spit out)? Would it hallucinate and provide inaccurate results? Would it be a closed system? 

TFG needed a solution that could properly address these concerns while also driving consequential business impact.