QuillBot's User-First, Data-Driven Approach Boosts Signups by 30%

In 2017, our founders wanted to find a way to help students learning English improve their writing. Today, our brands—QuillBot, Scribbr, and LanguageTool—are on a mission to make written communication better and more efficient. To date, our personalized AI tools like our AI Detector, Paraphraser, Grammar Checker, and Summarizer have empowered 56 million people around the world to learn and improve their writing, enabling better communication across languages and cultures.

As the founding engineer and current product and engineering lead, I had a front-row seat during the company’s transformation from a fledgling startup to a leading AI writing platform with over 35 million monthly users. Today, my team focuses on measuring customer attribution and revenue—and data is paramount to our work.

We didn't have much data visibility when I started. We couldn't determine how customers interacted with our product, which features they valued, and where they dropped out of the user journey. Trying to understand customer behavior and track conversion paths felt like solving a puzzle with pieces scattered across a thousand spreadsheets. We could see the anomalies but couldn’t pinpoint where something went wrong or why customers got lost in the funnel. That lack of visibility prevented us from optimizing our product and marketing efforts. We needed a better way to interpret data.

Analytics gave us a clear path forward

Our search for better analytics capabilities led us to Amplitude Analytics, and our data visibility improved almost instantly.

We now had a clear view into how customers navigated through our funnel, from their initial engagement with the product to buying a subscription. Our key priority has always been creating a user-friendly platform that could cater to a diverse range of writing needs. Amplitude provided us with detailed insights into user interactions and engagement, making it easier to acquire new users, improve engagement, and increase revenue.

My first big aha moment with Amplitude came when a member of our Amplitude customer success team showed us the Data Tables feature. It was revolutionary—we could suddenly compare and break down events and metrics in a single view. Given the richness of our dataset, in which we typically analyze multiple metrics simultaneously, the Data Tables feature was a breakthrough that unlocked critical insights and transformed our approach to growth. It allowed us to not only streamline QuillBot’s analytics but also set the company on a path toward becoming fully data-driven, with each department using real-time data to inform decisions.

My next breakthrough involved attribution, one of my team’s key measurements for identifying which sources drive the most valuable customers to QuillBot. None of our previous attribution tools delivered that information with certainty. Using Amplitude Data Tables to merge quantitative and qualitative data, my team could reconstruct the entire user acquisition process to identify the most successful touchpoints. That information helped the company better understand which marketing channels yielded the highest ROI and allowed us to optimize our marketing strategies accordingly.

Accessible data enables improved self-service

Amplitude played a vital role in helping our company become more data-driven. Before we were large enough to need PMs, engineers and designers used to directly monitor feature performance in Amplitude. Now, even more teams benefit from Amplitude’s visualizations and real-time data capabilities.

Our marketing team, for example, reduced customer acquisition cost by syncing Amplitude with our ad platform to track performance and optimize ad spend. Additionally, our AI research team runs constant A/B tests to track ML model performance over time.

Amplitude also allows us to maximize our collective efforts by providing insight into how we’re tracking against our company-wide KPIs. Using dashboards to track metrics such as user engagement, retention, and subscription conversion enables us to identify issues and work together to take corrective action quickly.

One such instance involved our account creation rate. Before Amplitude, we would have noticed our account creation rate dropping but wouldn’t have been able to identify where the problem originated. Amplitude helped us quickly identify the problem, and the analytics offered ideas for improvement. Repeated experimentation inspired by these ideas led to a 30% boost in signup rates.

Apart from fostering a more data-driven approach, Amplitude has cultivated a more product-driven, user-centric mindset across the organization. These shifts have accelerated product development and resulted in substantial quantitative and qualitative outcomes. Over a four-year period, we’ve seen marked improvements in key metrics, notably increases in ARR and in our active user base. These results, due in part to the insights provided by Amplitude’s self-serve analytics, have enhanced our scalability and positively impacted our bottom line.

A valuable partnership keeps us competitive

Wherever we go on our data journey, our Amplitude customer success team, consisting of Josh Brown and Serene Gan, remains by our side. They proactively explained the nuances of the platform and have shown us how to optimize it for QuillBot’s specific needs. I know they’re listening to me when I ask for new features because they get built and shipped fast.

That partnership is invaluable to us, especially as we strive to stay ahead in the crowded and quickly evolving generative AI market. To grow market share, QuillBot has to continue expanding our offerings and delivering more value to customers. The data-driven approach that Amplitude has empowered us to take is critical in this work. By surfacing the features and capabilities that customers want, Amplitude helps QuillBot stay competitive.