Case Study

High-growth SaaS company realizes increased free-trial-to-paid conversion rate

In order to grow their business, e-commerce software company Bigcommerce was looking to increase the customers generated from free trials. However, in order to optimize their bottom of the funnel conversion strategy, they needed an understanding of how their free-to-paid conversions were currently performing.


About Bigcommerce

Bigcommerce is an e-commerce platform based in Austin, Texas. They enable fast-growing businesses to easily and rapidly launch professional online stores. Its 50,000+ customers include Yeti Coolers and Gibson Guitar.

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Bigcommerce's challenge

Bigcommerce, an e-commerce software company, was in search of a partner to help manage its free-trial autoresponder campaigns and increase free-trial-to-paid conversion rates.  

In order to accomplish this, Bigcommerce needed support setting up analytics that would aid in identifying free-to-paid performance. Additionally, the team’s reporting and analytics of trial registrants to paid conversions were built from manually updated spreadsheets. This process was inefficient and vulnerable to human error. The ultimate goal was to generate insights from these new analytics to better understand and optimize trial conversions to grow the business.

New Breed's solution

New Breed’s team worked closely with Bigcommerce's demand generation team to identify opportunities from the initial trial sign-up through the remainder of the free trial.

To identify these opportunities, we needed to establish data points they could map to metrics and analytics that demonstrated trial sign-ups over time, trial conversions and conversion rates broken down by persona. To make this process easier, we suggested building out custom reporting dashboards that captured the data and metrics associated with free trial signups in Salesforce.

We followed the successive process: data > metrics > analytics > insights > growth strategy.


First, our team identified the data we needed to collect from the 15-day free trial in order to determine conversion analytics. We wanted to analyze conversion rates, so we used the sign-up form and contact properties to collect and map data of registrants between its marketing automation software (Hubspot) and its CRM platform (Salesforce).

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The data we collected was then used to calculate persona-specific conversion rates. With the information we gathered, we worked to measure conversion rate by day. We also used the information as an opportunity to identify new metrics and measure the success of the free trial. For example, on which day is a lead more likely to convert? Some of the most impactful business growth opportunities came from trial user behaviors, new trial behavior metrics and common conversion activities. By determining these new metrics, we were able to identify historical trends that highlighted improvements for both marketing and sales teams.


With these metrics in place, we built Salesforce dashboards to enable clear and insightful tracking of the trial's performance over time. This step of the process came in two different versions: manual dashboard creation and automated dashboard creation (within Salesforce). Based on the metrics we wanted to calculate, we created visuals broken down by trial starts, trial conversions, conversion rate by week and by persona or experience level.

Once this automated dashboard was in place, our inbound strategist was able to shift his focus from collecting clean data to analyzing it. By avoiding manual data input and updating, we were able to trust the data and generate insights from the user's behavior.


By overlapping sales, marketing and MRR analytics, we were able to answer key questions and gain additional insights that we could apply back into the nurture campaigns.

Before we began working with Bigcommerce, they were utilizing ‘basic analytics,’ such as overall free-trial conversions for a period of time. When leveraging only these types of analytics, it's easy to make incorrect “data-driven” marketing decisions. By becoming more granular, as we did in our analytics dashboard for them, we were able to pinpoint exactly where the solution laid.

Instead of focusing on customer growth alone, we analyzed revenue growth and the increase in monthly recurring revenue from the trial. We then used this information to further break down new weekly MRR from trial and non-trial sources. Additionally, we broke down data by each persona and plan type purchased.

Growth Strategy

In the end, we took our analysis and applied the connections made to how we could help Bigcommerce improve. We worked together to create a growth strategy that leveraged targeted marketing of Bigcommerce's highest value audience.


Since working with New Breed and setting up the custom free-trial dashboards in Salesforce, Bigcommerce was able to make better decisions about the trial performance. Together we increased free-trial-to-paid conversion rates by 14%. As a result, Bigcommerce is attracting more qualified trial users and customers. Additionally, Bigcommerce was able to shift its focus onto potential customers with a higher MRR and CLV, allowing them to boost predictable revenue. As a result, the utilization of these trial conversion dashboards has become pivotal for the demand generation team and its success.


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