The way writers connect with their online readers is broken. Quillytics started as a small project to fix this in 2019 by Laszlo Mari.
Quillytics presents all of the most crucial reader statistics in one platform, helping writers avoid jumping between various tools and not finding the real reasons behind user interactions.
Quillytics is designed first and foremost to be useful, with our second priority to be entertaining. We put significant focus on presenting every piece of information in our application perfectly, creating countless design iterations, and learning about user behavior every day.
Our mission is simple: We want to be the tool creators turn to when they want to know what readers truly feel while reading their content.
In the future, we want to become the tool content creators list their ideas in, interact with their readers, draft content, and make their fans be a part of their creative process from the very first moment. We want to be a part of content going viral, and we want to be a motivation for newcomers to start sharing their knowledge. We want to be a place where readers come for engaging and meaningful content and communicate with like-minded individuals.
In 2019 I worked in New York for a couple of months and decided to go to meetups to talk to people in various fields apart from tech. During these meetups, I got to know journalists and their tools they use to evaluate their content’s performance. All of them, including one from The New York Times, confirmed my assumptions about how they track content: they mainly look at the number of page opens, ad clicks, and time spent.
At Quillytics, we think there's a gap in the market. Countless tools show the number of people who clicked on your article and how much time they spent on each page, but essentially all other statistics are derived from these two pieces of information. There must be a reason why so much good content gets lost on the internet even with these advanced tools around.
During one of the weekends in NYC, I started experimenting with tracking complex user interactions on online content. By looking at scroll positions, mouse movements, and rare events such as mouse clicks or highlights, and the speed of all of these interactions, I worked out how to tell how engaged readers are on a paragraph-by-paragraph basis. Our team spent almost all of 2020 on this task alone, and we finally worked out how to reliably tell if a paragraph on a page is engaging or not. Our code is fast and doesn't slow webpages down, and setting everything up takes less than 3 minutes as our system recognizes many user preferences automatically.
Our flagship features include:
- Highlighting where readers start scrolling through your content (high chance of disengaging)
- Highlighting where readers leave your content (disengage)
- Showing a detailed breakdown of your users’ engagement across paragraphs, highlighting areas that most readers did not read
- Highlighting where your most engaged users come from based on geolocation, and internet sites (including social networks, we will write a separate blog post about how our feed works)
- Automatically recording edits on your article and measuring the change in the above metrics
- Looking at spikes in activity & engagement on social networks and notify you if a piece of content is about to go viral
Some of these features are still a work in progress, but we expect them to be added within the coming weeks. Even for a medium-sized blog, we have to ingest and analyze millions of events, so we will dive deeper into our architecture and technologies soon on this blog.
We will also start handing out Quillytics Awards quarterly to each writer segment (small hobby blogs; medium blogs; large blogs & magazines). I'm especially excited to encourage small, engaging bloggers to create more content and not just look at visitor numbers. We also have a massive discount (up to 70% off) to non-profits who constantly work with marketing agencies prying for their marketing budget but deliver mediocre results because they are looking at the wrong numbers.
I hope Quillytics won't stand on its own in the analytics space, but other companies will also innovate to make the ecosystem work better for the people that depend on it, the creators who put their time and effort into sharing knowledge. I hope the focus of the space will shift towards engaging with the audience, as Twitter and Clubhouse show that this is the right direction.