Fabi helps Aisle team move faster and focus on growth

Summary

Aisle, a venture-backed, fast-growing startup, helps brands turn their marketing channels into measurable retail growth. The team knew their customers were engaging with the platform but they couldn't see how. Which features were customers using? Where were they struggling? What improvements would have the biggest impact? The data to answer these questions existed, but it was trapped across multiple databases in formats that took weeks to wrangle into anything useful. For a fast-growing startup where speed defines competitive advantage, that timeline was unacceptable.

That is why they turned to Fabi.ai for powering their data analysis needs. Suddenly, everyone from the founders down to the brand managers could get the answers they needed without waiting around or wrestling with spreadsheets. 

The challenges of scaling analysis in a fast-growing retail ecosystem

As is the case in most startups, data analysis responsibilities are distributed across the team: product managers, engineers, customer success and founders. These teams need to not only analyze their data to inform their internal product and growth strategy, but also leverage this data to inform strategy and recommendations to their brand partners. Each brand has unique analytics and data demands that are important to respond to as quickly as possible for them to be able to make the best decisions to drive their promotions and sales.

As Aisle scales, so does the number of brands they work with and a growing number of ad hoc data requests from the brand team—5 to 10 per week, taking 30 minutes to two hours to fulfill. That meant an average of 15 hours a week spent on requests that didn't align with the product and engineering team's priorities, but still had to be answered.

Accelerating data analysis time by 92% with Fabi

Chirag Garg, Aisle’s sole Product Manager rolled out Fabi to simplify and accelerate data analysis. By connecting BigQuery and Postgres directly to Fabi, Chirag was able to generate dashboards and queries that used to take hours in just minutes.

With Fabi, I can build a dashboard in 10–15 minutes that would have taken me an hour or more with ChatGPT or manually. It allows me to focus on interpreting data and running tests instead of wrestling with SQL.

Chirag Garg

Product Manager @ Aisle

In addition to supercharging the product team’s workflow, Chirag said it took just 15 minutes to get Aisle’s non-technical brand team trained on Fabi. Soon, they were answering their own data questions rather than waiting on the product and engineering teams. What used to consume over 10 hours of back-and-forth each week simply vanished, freeing the product team to focus on deeper, more impactful work, while simultaneously empowering the business to provide unique, curated insights to their customers.

Tyler Goulet, who owns Aisle’s product and customer marketing efforts, is also a Fabi power user: “I'm constantly looking for stories in our data—whether it's identifying which brands are seeing the best results, uncovering patterns we can turn into best practices, or finding compelling angles for case studies and content. Before Fabi, those insights required looping in our engineering team. Now I can run those analyses myself in minutes. It's completely changed how quickly I can move from question to actionable insight, and it's made it easy to build repeatable workflows that I can run whenever I need them."

Streamlining exploratory analysis and reporting

Before Fabi, running complex queries across their brands was slow and required a deep knowledge of their database schema and SQL. The process took days of back-and-forth: understanding event tracking, writing and debugging complex SQL queries, optimizing them for performance, and finally formatting results for stakeholders. Each iteration required additional time to verify accuracy.

Fabi changed that by turning a multi-week, multistep effort into just three days of exploratory data analysis, helping the Aisle team to make faster business decisions.

Chirag also uses Fabi to power automated daily and weekly scheduled reports, pushing AI-generated summaries to Slack and Google Sheets for easy consumption by the brand team.

Our team loves the Slack automation. They get the insights they need without digging into dashboards, which is huge because managing 500 brands means time is scarce.

Tyler Goulet

PMM and Marketing Lead @ Aisle

Transforming operations with AI-powered analysis 

For Chirag, the real win wasn't just the time saved, it was how Fabi fundamentally shifted the way the whole organization works with their data. Fabi unlocked a whole new set of workflows and capabilities: 
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• Team empowerment: Non-technical brand managers now answer data questions independently and faster for their customers.‍
• Automated reporting: Daily and weekly AI-generated summaries sent to Slack for the internal team.
• Improved focus: Product and data teams spend more time on strategic growth and experimentation.
  
• Enhanced decision-making: Faster insights drive pricing, promotional, and product optimization.

Results that scale: 92% faster analysis and 50+ monthly requests eliminated 

Fabi dramatically increased the speed, efficiency, and accessibility of data insights at Aisle. By unifying visibility across BigQuery and Postgres, the team now has holistic performance tracking.

• Faster experimentation: Pilot program evaluations that used to take 2 to 3 weeks now take just a few hours.
  
• Faster analysis: Dashboards and reports that once took hours or days are now completed in just 10 to 15 minutes, cutting analysis time by roughly 92%.
  
• Reduced ad hoc requests: The brand team now answers its own questions, eliminating 40-50 monthly data requests to product or engineering.
  
• Easy adoption: Within the first month, 100% of brand managers were using Fabi for their weekly reporting.

Looking forward: Scaling insights across the business

For the team at Aisle, the next chapter is about doing more without increasing headcount. They leverage AI in all aspects of the business to fuel their growth without ballooning operating costs. Having transformed how their internal teams work with data, they're now focused on making AI a core part of how brands interact with insights.

Aisle’s vision is to make their data not just accessible, but conversational, without needing to hire an entry-level data analyst who can quickly answer specific questions, enabling teams to act faster.

In practice, this means embedding AI agents that let brands query data directly over email or Slack, and automating routine retail analytics workflows end-to-end. As Aisle moves toward this future, they're proving how AI can be a collaborator, empowering humans to focus on strategy while it handles the complexity beneath the surface.

Aisle is also looking forward to using Fabi’s Analyst Agent and MCP server to provide even wider access to insights everywhere the team works.

Ready to transform your data operations? Get started with Fabi.ai for free in less than five minutes.