East of England Co-op

Leveraging LLMs and Pyramid Analytics to Transform Travel Data Reporting

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East of England Co-op, the largest independent retailer in the East of England with a £385m turnover and a broad portfolio of businesses—including food stores, funeral services, security, property and travel—has embarked on a data modernization journey. At the heart of this transformation is Darren Tuffs, the BI Developer and team lead, whose technical development work and team training have helped modernize the East of England Co-op’s use of data across departments

THE CHALLENGE

The travel division of East of England Co-op, consisting of 25 branches, had long struggled with fragmented and unreliable destination data. Their booking system, nearly 20 years old, allowed agents to input destinations using unstructured free-text fields. This resulted in entries ranging from “JFK” to “cream tea for two,” with no enforced data standards or validation. A cascade of patchwork solutions followed—Excel spreadsheets with nested VLOOKUPs and Google Sheets meant to interpret and correct these entries. This system lacked scalability, introduced human error, and ultimately provided limited visibility into travel trends.
Adding to the complexity, frontline staff had no access to their legacy BI tool, WebFOCUS, which in itself was challenged in that it was difficult to use and resulted in very poor user adoption— leaving decision-making hampered by inaccessible or inaccurate data. Darren and his team recognized that a complete overhaul was necessary to move from reactive fixes to proactive insights.
The East of England team went through a full RFI and RFP process. Two vendors eventually made the shortlist, and at the end, Pyramid was chosen.
“The thing about Pyramid Analytics that stood out was the partnership – we are a partnership business and put great value on that, and it has really shone with Pyramid. They did an excellent job of addressing our needs and talking to us and helping us really make the right decision”, said East of England Co-op’s Technology Officer, Rob Smith.


THE SOLUTION

The turning point came with the adoption of Pyramid Analytics, the integration of Large Language Models (LLMs) and the building of the semantic layer. Darren’s team leveraged Pyramid’s modeling features and integrated LLM node to standardize the destination field, extract key location details, and make that data accessible to analysts and business users. Their innovative solution has significantly improved reporting accuracy, reduced manual work, and opened the door to more advanced analytics and decision-making.
For instance, Pyramid visualizations now let the team map European travel trends at a glance, showing where customers are going and helping guide them toward more relevant, high-demand routes based on emerging travel patterns.

CONCLUSION

Buoyed by the success in travel data cleanup, Darren is expanding the use of LLMs to other areas—specifically colleague feedback analysis. By extracting emotional sentiment, wellbeing flags, and themes from open-text comments, the team aims to uncover hidden insights about employee engagement and morale, potentially identifying issues before they escalate.
This project underscores the power of blending a modern analytics platform with Generative AI. What began as a messy Excel/VLOOKUP nightmare is now a fast,  scalable, and intelligent data workflow that enhances operational visibility and decision-making.

The East of England Co-op has demonstrated that even legacy systems and inconsistent data entry processes can be transformed with the right combination of tools and expertise. By embedding LLMs into their data pipeline and leveraging Pyramid Analytics’ modeling and reporting capabilities, they have laid the foundation for faster, cleaner, and more actionable AI-driven analytics.

“The thing about Pyramid Analytics that stood out was the partnership – we are a partnership business and put great value on that, and it has really shone with Pyramid”

– Rob Smith , Technology Officer, East of England Co-op

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