How Jaimy reduced customer acquisition costs (CAC) and churn by 25% with Twilio Segment

Results

The big win

Home services company, Jaimy struggled to understand why some website listings performed better than others. The company predicted greater visibility into user engagement could lead to better website conversion, but had no way to prove that hypothesis to its partners.

Jaimy turned to Twilio Segment for real-time audience insights which drove personalization and a smoother buyer journey. With the freedom to be experimental, a bigger budget to play with, and more reliable customer data, Jaimy has seen a 25% decrease in both CAC and churn. The company also saw a 25% higher activation rate after improving the onboarding process with its new customer data.

Damien Querbes is the Head of Marketing at Jaimy, a home services company that connects homeowners with local tradespeople. The company is a subsidiary of the Belgium bank, Belfius, who invested in the startup to get access to this growing market.

Jaimy is a two-sided marketplace. On the demand size, homeowners can use the platform to find trustworthy, skilled traders to help with home improvement projects. On the supply side, skilled tradespeople can find a steady stream of work quickly and efficiently.

When Damien moved to Jaimy, the startup was struggling with high engineering costs and a lack of unified data. If they wanted to test new tools, they had to outsource a team of specialists to manage it. This prevented them from creating better customer experiences in the platform, which would subsequently help both buyers and suppliers find even more value in the marketplace.

Damien knew this was an issue Twilio Segment could solve. In his previous role at Ubeeqo, one of the many Europcar Mobility subsidiaries using Twilio Segment, he used Twilio Segment for real-time audience insights which drove personalization and a smoother buyer journey.

Here’s how Damien built a business case for Twilio Segment and helped Jaimy lower engineering costs, and reduce both customer acquisition and churn by 25%.

Lack of data unification and costly engineering resources

Jaimy is no stranger to data. They use machine learning to find patterns in their data and calculate the right estimates for jobs, which helps save users time by eliminating unnecessary site visits or lengthy cost negotiations.

However, the startup still struggled with a unified data infrastructure. Jaimy used Mixpanel to identify and predict behaviors that correlate with retention, while Damien preferred Google Analytics. With data coming in from different sources, there was no consistency when collecting, analyzing, and acting on their data. This impacted the credibility of their insights.

Damien explains:

“With different results coming from different reports and different sources, it was a risk to make critical business decisions based on the information we were gathering.”

The lack of unified data was also expensive. To centralize all their information and support the startups growing list of integrations, they needed more engineering support.

Say Jaimy wanted to build dynamic audiences to create more personalized experiences and reduce customer acquisition costs (CAC).

They would need to hire a specialized team of developers to integrate the startup’s CRM, Freshsales, with Intercom and Redshift. This would cut into Damien’s already limited budget, and prevent them from investing in more strategic and customer-focused needs. Damien knew that to quickly add new integrations and continue to move fast, all data needed to pump into a single API across all the business platforms.

That’s where Twilio Segment came in.

Using first-party behavioral data to reduce CAC and churn

Inspired by his previous results using Twilio Segment, Damien put a use case together for the platform to get buy-in from the C-suite.

To do this, he compared the costs of building a tech stack with Twilio Segment, versus the estimated costs of building and maintaining integrations without it. He showed how Twilio Segment was compatible with all of the startup’s business-critical systems, and would eliminate the need for expensive engineering support. It also showed how Twilio Segment could help reduce churn and CAC by 25%.

Damien’s case was quickly approved. With all of Jaimy’s data sources compiled in one place, Damien and his team could better track user interactions and provide targeted communication with them. They were also able to visualize each buyer's journey in real-time inside Twilio Segment.

The startup could now understand:

• Where their best customers came from

• How they interact with the business

• What features people use most

• Browsing history in the platform

• Customer spending habits and average order values

Knowing that they could rely on this data, the team was able to Twilio Segment buyers and traders based on their behavior. They could also better spot patterns in each Twilio Segment’s behavior and create targeted communications to increase user engagement.

Twilio Segment also helped Damien’s team turn raw data into actionable information such as:

• Demographics (gender, age, occupation, etc.)

• Psychographics (personal attitudes, values, interests, etc.)

• Geographics (country, state, city, town or county)

• Technographics (preferred technologies, software, and mobile devices)

Now that all their data was in one place, the team could request specific pieces of user data, such as where someone lives or how much they buy. This helped them create lookalike audience personas for targeted ads, and continuously update them, making sure campaigns stay relevant and drive user acquisition.

New confidence in data accuracy with Twilio Segment

Using Twilio Segment, Jaimy no longer requires expensive engineering support. As Damien said:

“With Twilio Segment, you become free from your engineering team, allowing you to test tools without waiting for technical support. This freedom helps you play around with ideas when you please, driving innovation faster than ever before.”

Twilio Segment also lets the team action on more precise data, faster, and fine-tune the user experience so they can maximize the platform’s use. 

A new confidence in data accuracy also helps them report findings to key stakeholders and get buy-in for new campaigns, thanks to the ability to show clear marketing attribution.  

With the freedom to be experimental, a bigger budget to play with, and more reliable customer data, Jaimy has seen a 25% decrease in both CAC and churn. The company also saw a 25% higher activation rate after improving the onboarding process with its new customer data.