Data Trapped to Data Driven: How Counter Culture Coffee Built a Prioritized AI Roadmap

Summary

Counter Culture Coffee is one of the most respected specialty coffee roasters in the US, serving wholesale partners, grocery retailers, and direct-to-consumer customers. Leadership saw AI as a way to support that growth without adding back-office overhead. The open question was where to start. The Gnar ran an AI Transformation engagement that mapped how the business runs today, found where AI could remove waste from sales, operations, and finance work, checked whether the data was ready, and laid out the order to pursue them. The findings were presented to Counter Culture's board.

The Challenge: a growing business, data spread across many tools

Like many companies that grow channel by channel, Counter Culture built its tool stack function by function. NetSuite serves as the ERP and system of record, Shopify runs direct-to-consumer and B2B commerce, and Zoho supports account management and service. Around them sit dozens of specialized tools for marketing, fulfillment, and operations, with Google Sheets and Excel doing important supporting work.

That setup served the business well, but it made cross-functional questions harder than they needed to be. NetSuite is deeply customized to fit how Counter Culture operates, so pulling a reliable number often depended on the few people who knew exactly which fields to use. Some core reference data, like the rotating coffee lineup, was maintained in spreadsheets and entered into other systems by hand.

For AI, that matters. An assistant is only as reliable as the data it reads, and it has no way to know which of two similar fields is the right one. Before investing in AI builds, Counter Culture wanted a clear picture of which opportunities were worth pursuing and what had to be in place for them to work.

The Solution: Artificial intelligence and ERP automation

The Gnar's AI Strategy & Roadmap engagement answers one question: where will AI pay off, and what has to be true first? For Counter Culture, a senior Gnar strategist led the work, with weekly working sessions alongside leadership.

• Interview. 15+ interviews with leadership, department heads, and the operators who run the day-to-day, across finance, operations, coffee procurement, sales, marketing, and data.
• Map. Every system and data flow, end to end, with NetSuite at the center.
• Identify. 79 AI and automation opportunities, catalogued across seven capability areas. Workflow and task automation led with 17, followed by insight generation and analytics (14) and generative content and marketing (13).
• Rank. Every opportunity scored on the same five dimensions: financial ROI, operational efficiency gains, implementation complexity, data readiness, and cultural readiness. Scoring counted only recoverable value, and weak data readiness capped an opportunity's score regardless of its upside.
• Sequence. Remove barriers first, then quick wins for internal champions, while The Gnar builds the larger automations.

The process also tested its own assumptions. Coffee procurement initially looked like a market-timing opportunity. A full year of contract data showed the team was already managing that well, so the recommendation shifted to what would help most: a single, real-time view of the coffee position across contracts, importers, and warehouses.

Inside the systems and data map

The systems map grouped more than 60 tools by function: e-commerce and direct-to-consumer, marketing and creative, operations and finance, account management, and IT and security. Then it traced how each one connects to the core systems. Two insights shaped the roadmap:

• NetSuite is the hub, and that is a strength. Commerce, fulfillment, and retail EDI already flow into a single system of record, which gives AI a natural place to plug in.
• Many tools work from exported data. Outside the core integrations, most tools either stand alone or rely on exports, which is why spreadsheets carry so much of the load.

The companion source-of-truth map reached a clear conclusion: the data foundation is largely sound in the hands of the system experts who know it, but it needs guardrails before wider use across the company. A handful of master-data sets were maintained in spreadsheets or kept in more than one system, which meant manual re-keying and reports that did not always match.

The recommendation was to give each of those data sets a single home in a core platform, NetSuite or Zoho, based on which team owns and uses it most, and to retire the spreadsheet and duplicate copies. The rule of thumb behind it: master data is edited only in its system of record, and every other system reads from there.

The Results: a ranked roadmap and a clear first step

Counter Culture left with a prioritized portfolio rather than a wish list, and a shared view of what to do first.

• $1.5M in potential savings across the top 10 initiatives, each with a score, an owner, and a place in the sequence.
• Value on four fronts. Of the identified projects, 27 grow revenue, 29 free up capacity, 13 cut costs, and 10 strengthen control.
• The leverage point, identified. Governing a trusted set of NetSuite data, with agreed definitions and clear ownership, unlocks three complex builds at once: a plain-language query assistant, an executive scorecard, and automated board reporting.
• A faster month-end close, much of it through configuration. Many of the gains come from NetSuite capabilities Counter Culture already owns, with AI reserved for reconciliations and accrual worksheets.
• A better view for coffee procurement. A consolidated position tool gives buyers one view of contracts, importers, and warehouse inventory, and a foundation that later supports demand planning.
• Quick wins with owners. 34 projects ready to start and 8 already underway, led by five internal champions from IT, finance, and operations team members using Claude.