Boatsetter increases return on ad spend by 100%+ and scales AI

"The value of Fivetran and dbt isn't just about moving data faster — it's giving every team the same, increasingly in-depth understanding of the customer journey. Gaining that deeper understanding helped Boatsetter to improve return on ad spend by more than 100%, support 2 marketplaces with a lean analytics team, and use AI where it matters most: creating better experiences for guests and boat owners.”
— Mark Stange-Tregear, SVP of Data & Operations at Boatsetter/Getmyboat

Boatsetter and Getmyboat, which merged in January of 2026, form one of the world's largest peer-to-peer boat rental marketplaces, connecting millions of guests with boat owners across more than 700 destinations worldwide. Unlike traditional ecommerce businesses, every booking depends on a complex mix of customer behavior, geography, seasonality, pricing, weather, and boat availability. To continue to grow efficiently, Boatsetter needed to understand not only what customers booked, but how they discovered, evaluated, and chose those experiences.

When Mark Stange-Tregear joined Boatsetter as SVP of Data & Operations, there was rich data, and huge potential to gain visibility into customer lifecycles. Customer, marketing, business, and transactional data were siloed, and challenges with pipeline reliability and inconsistent reporting made it difficult to get the data that was wanted to make key business decisions. Without a complete view of the customer journey there were challenges in identifying the marketing investments that were truly driving bookings, understanding where marketplace demand was outpacing supply, and how to put trusted customer insights into the hands of the marketing and operations teams responsible for acting on them.

As Boatsetter looked to continue scaling the business — and later integrate Getmyboat following the merger — it needed more than better reporting. It needed a data foundation that could seamlessly connect information across the business, create a consistent view of customers and bookings, and deliver deeper insights so that marketing, operations, and future AI initiatives could all work from the same reliable information.

Building a complete view of the customer journey

The goal wasn't simply to modernize Boatsetter’s data platform — it was to understand the complete customer journey and make those insights available wherever decisions were made. To do that, the company rebuilt its data platform around a cloud-native architecture designed to automate data movement, standardize business definitions, and put customer insights to work.

Fivetran automatically ingests data from Boatsetter's operational systems, product databases, marketing platforms, customer engagement tools, and third-party applications into Snowflake, creating a unified view of customer behavior, booking activity, and business performance.

dbt platform is then used to transform that raw data into governed business models while serving as the operational backbone of Boatsetter's analytics environment. Beyond centralizing business logic, dbt provides orchestration, upstream and downstream testing, lineage, and alerting — eliminating the need for separate tools while giving the team confidence that reporting, marketing, and AI all rely on consistent, validated data. Following the Getmyboat merger, Boatsetter also adopted dbt Mesh to manage analytics development across both organizations while maintaining shared business models.

Rather than rebuilding audiences and customer attributes in every downstream application, Boatsetter uses Fivetran Activations to deliver the governed customer models built in dbt directly into Google Ads, Meta, and HubSpot. This gives business teams access to the same validated customer and marketplace data used for analytics, without maintaining separate models or logic across their day-to-day tools.

“The real breakthrough with Fivetran Activations came when customer journey data became part of every marketing investment decision. We stopped asking, ‘What happened?’ and started asking, ‘Where should we invest next?’”
— Mark Stange-Tregear, SVP of Data & Operations at Boatsetter/Getmyboat

Teams use Tableau and Hex for reporting and interactive analytics, while the same governed customer models support AI use cases including customer journey analysis, owner recommendations, internal analytics assistants, and marketplace operations.

Turning customer insights into measurable business growth

Understanding the complete customer journey enabled more strategic decisions across marketing, product, and the owner ecosystem. By connecting website behavior, booking history, marketing interactions, and customer communications, Boatsetter gained new visibility into how guests discover, evaluate, and book experiences. With Fivetran Activations delivering those insights into the platforms where campaigns are managed, marketers could more precisely identify which audiences, channels, and moments in the booking journey were most likely to convert — and reallocate spend accordingly.

As a result, Boatsetter improved return on ad spend (ROAS) by more than 100% year over year. Instead of broadly investing in customer acquisition, the company now uses customer insights to target high-value audiences, reduce ineffective advertising spend, and generate more bookings from every marketing dollar. 

That understanding now informs owner acquisition, inventory planning, and AI-driven experiences across the entire marketplace. The company has:

• Saved an estimated 200 data engineering hours every week, allowing analysts to focus on solving business problems instead of maintaining pipelines.
• Integrated Getmyboat's priority data sets in just 6 weeks post-merger by scaling analytics with dbt Mesh, accelerating post-acquisition reporting and decision-making.
• Improved owner acquisition by identifying where customer demand was highest.

The same customer intelligence that improved marketing performance now powers AI across the business. Boatsetter uses Snowflake AI functions directly within dbt to enrich its data models with customer sentiment analysis and common question detection as part of every data build. AI-enriched models are starting to power owner pricing, intelligent trip replacement, and emerging agentic capabilities that automate routine work. Rather than replacing people, AI helps owners improve performance, matches guests with the right experience, and helps employees make faster, more informed decisions.

"Because Snowflake AI functions are integrated directly into our dbt models, every recommendation starts from the same business logic that powers reporting. That lets us confidently automate the evaluation of pricing, listings, customer sentiment, and marketplace operations without maintaining separate AI pipelines."
— Mark Stange-Tregear, SVP of Data & Operations at Boatsetter/Getmyboat

Looking ahead, Boatsetter is working with Big Context & Co, a new player in the space, to manage data context and deliver data agents and a range of other AI-based tools to employees. Boatsetter plans to extend Fivetran Activations beyond today's marketing and HubSpot use cases and sees dbt evolving beyond analytics into the knowledge layer for both employees and AI agents, giving every decision and recommendation the same standardized business context.

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