Hawaiian Airlines built its business on a niche route network: inter-island flights and services to, from, and within Hawaii. That focus shaped everything, including how the marketing team measured performance. Jake Wood, Digital Media Analyst, led both the marketing data work at Hawaiian and for Alaska Airlines, post-combination.
The challenge: eight people, eight days, one monthly snapshot
Before Supermetrics, getting a centralized view of marketing performance was a manual exercise. Multiple teams pulled numbers from multiple accounts and copied them into Google Sheets. Start to finish, it took eight people and eight business days to produce a single month-level snapshot covering 22 metrics and dimensions.
That timeline created two problems. The first was accuracy. Copying and pasting performance data by hand introduced errors, which meant more back-and-forth with the agency to reconcile numbers.
The second problem was visibility. A month-level view hid everything that happened inside the month. If a sale or a holiday campaign launched mid-month, the team could not see how long it took to ramp up or how it performed day to day. Meanwhile the requests coming in were getting more complex, and simple questions like "how did the last seven days go?" could not be answered without a significant team effort requiring every agency to collectively export performance from each advertising platform.
Then the Alaska combination multiplied the problem. Hawaiian and Alaska served different audiences on different routes, and both needed tracking in one place. The account count went from around 30 to more than 50 overnight. Two organizations also meant two sets of naming conventions and two ways of describing the same data, and the reporting had to stand up on schedule regardless.
The solution: daily, analysis-ready data in BigQuery
Hawaiian used Supermetrics' Marketing Intelligence Platform to connect 50+ advertising, social, Google Search Console, and other accounts to BigQuery on an automatic daily schedule. The data lands flat and analysis-ready, so it goes straight into production reporting without cleanup.
That structure changed who could use the data. The team went from 22 metrics and dimensions at a month level to more than 100, refreshed daily. Marketing analytics still owns the reporting, but other departments now build on the same tables.
The SEO team is one example. Working from the Google Search Console tables Supermetrics delivers, they built a self-service dashboard covering every query Hawaiian's websites appear for: total impressions by keyword and URL, clicks, click-through rate, and ranking, plus indexing and error alerts.
Maintenance stopped being a job in itself. Instead of watching 50-plus connections for failures, which would have needed a dedicated data quality analyst, the team gets an email when something disconnects, along with the steps to fix it.
Security cleared quickly too. Supermetrics is SOC 2 Type II compliant and passes data straight through to Hawaiian's own warehouse rather than storing it.
The result: 500+ hours a month saved, and a foundation for AI
Automating the reporting process saves Hawaiian more than 500 hours every month across internal teams and agency partners, and for some months, even more. Those hours came out of copying, pasting, checking, and correcting numbers that now arrive accurately and consistently because they're pulled straight from the source.
The bigger payoff is what the team does with the time and the data. Reporting moved from a monthly retrospective view weeks behind, to a daily view that is always current, so campaign decisions are made on the latest data while campaigns are still running. And the analytical scope expanded from 22 metrics to 100+, which means when an executive asks an unexpected question, the answer is usually already there.
It also made AI viable in a way it simply hadn't been before. Hawaiian's marketing data now sits in one warehouse in a clean, consistent format, which is the prerequisite for training agents that give reliable answers.
Because everything lands in BigQuery, the team connects Gemini directly to it and is building AI assistants customized for individual teams. They're also trialing Supermetrics' Gemini marketing intelligence analyst agent. In practice, colleagues bring the assistant into meetings and ask questions in the moment, getting an answer grounded in real analytics without waiting for an analyst to write SQL or open a dashboard.
For a team that doubled its scope without doubling its headcount, that's the difference between reporting on what happened and answering what to do next.
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