Delivered 50+ loyalty insight projects in mere minutes
Cut analyst dependency by 50% for business storytellers
Segmented ~270 retail brands into 4 profiles in 3 hours
Diagnosed a $2M category revenue variance in 30 minutes
Guided a 14-store inventory reallocation in half a day
Myer uses BigQuery data agents to deliver 50+ projects, cutting analyst dependency by 50% to free teams for strategic work.
Myer uses BigQuery data agents to deliver 50+ projects, cutting analyst dependency by 50% to free teams for strategic work.
Modernizing 126 years of retail loyalty data on a trusted foundation in BigQuery
For more than 126 years, Myer has stood as one of Australia’s most iconic department store retailers, serving millions of shoppers across nationwide stores and digital channels. At the heart of its customer engagement strategy is MYER one, a flagship loyalty program where members earn two points for every dollar spent across a wide range of partners to redeem against reward vouchers, alongside birthday and exclusive rewards.
To power data-driven retail operations, Myer migrated its legacy on-premises data warehouse to Google Cloud and BigQuery in 2018. Within a dedicated loyalty environment, the customer analytics team processes terabytes of transactional history spanning billions of sales records over multiple years and millions of customer profiles, alongside 104 BigQuery AI models, behavioral analytics, and performance insights for brand partners and targeted marketing campaigns.
However, years of organic growth created operational bottlenecks across the loyalty environment. More than 3,500 complex SQL queries had accumulated directly inside the BigQuery interface, structured around various business lenses rather than a unified customer view. Insights business partners and marketing storytellers depended heavily on specialist analysts for data pulls, waiting days or weeks for answers, while unoptimized queries scanning billions of rows risked triggering a centrally managed hard limit on data processing for cost control.
We purposely created a BigQuery data agent over aggregated transaction and loyalty data with zero custom instructions, zero metadata, and no column descriptions. The productivity gains our domain experts achieved in weeks would have taken over 12 months manually, and adding context and knowledge graphs will unlock more.
Marty Barter
Head of Data and AI Capability, Myer
“Our biggest challenge is not lacking data, but knowing where to find it after years of organic growth,” says Marty Barter, Head of Data and AI Capability at Myer. “Using agents and Knowledge Catalog to curate complex data assets, we archived roughly 100 terabytes of data to reduce costs and completed an eight-week mapping exercise in minutes—before creating a BigQuery data agent in Gemini that unlocked over 12 months of productivity gains.”
Delivering 50+ retail insight projects in minutes with BigQuery data agents
Working within Google Cloud’s Agentic Data Cloud, Barter configured the data agent using Conversational Analytics in the BigQuery UI and connected it into Gemini across millions of customer profiles and billions of sales records. Previously, answering a stakeholder question took three weeks on average—and another three weeks for a follow-up, long after commercial opportunities had passed. Two insights business partners trialed the agent alongside marketing storytellers, cutting onboarding from months to weeks, halving analyst dependency by 50%, and keeping projects moving during analyst leave.
Across more than 50 delivered projects, our insights business partners turned weeks of data gathering into minutes while cutting analyst dependency by 50%. They segmented 270 brands in three hours, diagnosed a $2 million revenue variance in 30 minutes, and guided a 14-store inventory reallocation in hours.
Marty Barter
Head of Data and AI Capability, Myer
Across more than 50 delivered projects, insights business partners using the BigQuery data agent turned weeks of manual data gathering into minutes while automatically pruning partitions and columns:
- Segmented roughly 270 retail brands into four distinct customer profiles in just three hours instead of weeks of manual work, and profiled cross-shopping behavior for an exited brand in 20 minutes.
- Diagnosed a $2 million category revenue variance across customer demographics, products, and stores in 30 minutes, while quantifying customer leakage, tenure, spend migration, and cross-category shopping across Home, Tech, and Toys.
- Parsed store, customer, and product demographics in under half a day following competitor store closures—creating a 14-store stock reallocation strategy that won immediate executive approval to move inventory.
Barter also connected a 300-attribute product table—covering size, color, material, and clearance tags—where within ten minutes of multi-turn prompting, the agent analyzed promotional buying patterns and generated body-shape styling recommendations to lift online conversion.
“The BigQuery data agent not only answered the first stakeholder question in seconds, it answered the next ten follow-ups within minutes while surfacing statistical significance automatically,” says Barter. “Turning competitor store closures into an approved 14-store inventory reallocation in under half a day shows how data agents drive immediate commercial outcomes.”
Scaling from conversational insights to intent-driven agentic engineering
Building on 50+ delivered projects across millions of loyalty members and 270 brands, Myer’s Customer Data Intelligence team is redesigning its loyalty data around a unified customer lens. Extending the initial trial in the BigQuery UI and Gemini, the team is integrating Google Cloud’s Knowledge Catalog to build rich metadata and a business glossary in a single interface—guaranteeing consistent terminology and metrics across business units while expanding data agents to hundreds of merchandise, inventory, and supply chain users, and potentially stores.
To modernize deep-rooted processes across its 126-year history and scale multi-agent workflows, Myer is advancing three interconnected initiatives:
- Establishing AI Champions across the business to identify process bottlenecks while building a collaborative repository in Google’s Agent Registry to train teams on self-service multi-agent workflows.
- Using Google’s Antigravity environment to shorten development lifecycles to hours—allowing organic curiosity to turn a simple pipeline documentation agent into multiple MCP servers, three security agents scanning code and packages using the OSV API and Terraform hardening tools, and a human-in-the-loop workflow where “Agent-Ready” Jira tickets trigger agents to build Dataform and Terraform solutions with Confluence documentation for Git peer review.
- Partnering with Vivanti on an integrated AI copy generation tool for richer website product descriptions and SEO, alongside a proof of concept creating realistic homewares lifestyle imagery to lift conversion.
As self-service agents absorb routine reporting, Myer’s analysts are shifting from writing boilerplate SQL and Python code to driving intent-driven outcomes—defining business intent, orchestrating agents, and curating semantic knowledge graphs.
“Whether a BigQuery data agent helps an insights partner reallocate stock across 14 stores or an engineering agent picks up an ‘Agent-Ready’ Jira ticket to build a Dataform pipeline, our people are becoming intent-driven orchestrators,” says Barter.
Rather than writing boilerplate SQL and Python code, our specialists are shifting to intent-driven outcomes—defining business intent and orchestrating specialized agents that log Jira tickets, build Dataform pipelines, and write Confluence documentation with human-in-the-loop Git review so teams focus on strategic customer and retail priorities.
Marty Barter
Head of Data and AI Capability, Myer
Founded over 126 years ago, Myer is one of Australia’s largest department store retailers, serving millions of shoppers nationwide and online alongside its flagship MYER one loyalty program.
Industry: Retail
Location: Australia
Products: BigQuery, Conversational Analytics, Gemini, BigQuery AI, Knowledge Catalog, Dataform
