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Overview
Miconex, through its Town and City Gift Card programmes, facilitates local economic growth by partnering with Local Authorities (LAs) and Business Improvement Districts (BIDs) to encourage local shopping over online or out-of-town retail centres.
With over 200 of these gift card programmes across the UK, Republic of Ireland, the US, and Canada - driving a record-breaking £15.9 million of local Gift Cards sales in 2024 - it’s safe to say that Miconex faced some challenges in interrogating all of that transaction data to produce actionable insights.
Challenges
- Inefficient Manual Reporting: Miconex relied on time-consuming manual work to extract, validate, and analyse transaction data.
- Data Inconsistencies and Missing Insights: Transaction reporting lacked detailed insights, including breakage tracking, spend patterns, and merchant-level breakdowns.
- Large Data Sets with Limited Accessibility: Millions of transaction records across multiple programmes were difficult to process and analyse in their existing setup.
- Need for Automation and Better Analytics: Miconex needed a solution that would automatically extract, validate, and process data, making insights readily available.
To summarise the above points, analysis and interrogation just aren’t viable.
Our Solution
To address these challenges, Team Bravand’s go-to Analytics Engineer, Michael Ifiegbu, designed a scalable and automated data processing system that streamlines Miconex’s reporting workflow.
Key Solution Components
Automated Data Extraction:
- Fetching data from the gift card processor’s systems via APIs, webhooks, or Python-script-based CSV extraction.
- Daily extraction and validation of large transaction files.
Data Transformation and Validation:
- Cleaning and structuring raw data using DBT Cloud.
- Validating transactions to ensure accuracy in reporting.
- Resolving discrepancies in transaction counts and missing metadata.
Centralised Data Storage and Processing:
- Google BigQuery serves as the primary data warehouse.
- Secure, scalable storage with real-time query capabilities.
Advanced Data Visualisation and Reporting:
- Google Looker Studio Dashboards for interactive reporting.
- Custom dashboards to analyse spend patterns, breakage, and programme performance.
- Ability to filter and segment data by merchant, programme, and location.
Task Scheduling for Continuous Updates:
- Automated daily data extraction and monthly dashboard updates.
- Ensuring up-to-date analytics without manual intervention.
Results and Impact
- 80% Reduction in Manual Workload: Automated processes eliminated tedious data entry and manual validation.
- Improved Data Accuracy and Insights: Enhanced tracking of spend patterns, breakage, and merchant-specific performance.
- Scalable and Future-Proof System: Google BigQuery and Data Studio provide flexibility for future reporting expansions.
- Empowered Business Decision-Making: Miconex can now track KPIs such as, for example, "Total spend at M&S across all programmes" instantly, compared to manual searches across multiple files previously.
What’s next for Miconex?
This design has the potential to really help Miconex operate with greater efficiency, accuracy, and scalability in data reporting.
By integrating automated data validation, centralised storage, and dynamic reporting tools, Miconex will have the ability to make informed, data-driven decisions, supporting the growth of local economies worldwide.
Talent in Action: Michael Ifiegbu
This project also highlights the impact of emerging talent through Bravand's Fresh Meet programme.
Michael came to us with a Master's in Big Data Analytics, real capability, and a genuine desire to help others break into the industry - but without the commercial track record that most employers wanted to see before taking a chance. It's the experience catch-22 in action: you need experience to get experience, and qualifications alone don't unlock the door.
We were introduced through a mutual contact in the Sheffield tech community, spoke about his background and ambitions, and brought him in as a freelance Analytics Engineer on the Miconex data project. He got straight to work - auditing Miconex's existing reporting infrastructure, validating millions of transaction records across multiple data sources, identifying gaps and discrepancies, and producing a detailed proposal for a fully automated analytics pipeline that would transform how the business interrogated its data.
The work was thorough, technically rigorous, and clearly presented to a non-technical client. He impressed everyone he worked with. Michael became Bravand's go-to for anything data engineering, machine learning and AI-related - and in March 2025 he accepted a role as Technical Support Executive at Airship/Toggle, one of South Yorkshire's most respected tech firms.
The brief gave him the commercial proof point he needed. The rest was already there.
Working on a data or reporting challenge?
If your team is spending too much time wrangling data and not enough time acting on it, we can help. Get in touch with the Bravand team to talk through what's possible.
