Problem

WWriters and publishers have categorically different needs when it comes to data and levels of immersion in it. Working with paper documents can discourage writers and is not efficient or practical for publishers.

Approximately 98% of writers in LitRes only publish one book. These writers use financial data to boost their self-esteem and are content with seeing positive trends. Publishers, on the other hand, analyze the data more comprehensively to gain insights for new books or to time the launch of advertising campaigns or book releases. However, both parties use the same interface..

Plan

The back-end development team and I worked with the legal department for several weeks to determine what data we could obtain and how. After that, we focused on moving the entire document process online to make it easier for new and old writers to contribute, and to improve the detail and visualization of financial reports.

Research

The study revealed that less than 6% of writers/publishers provide the majority of funding and use the data judiciously. Simply observing dynamics and trends is insufficient for their needs. Therefore, we provided detailed charts and data exports to meet their requirements. However, for the remaining writers, trends and dynamics are the primary areas of interest.

Hypothesis

I suggested the idea of displaying general information, trends, and dynamics immediately, while also allowing for the option to delve into each specific block or customize the workplace based on individual needs.

Solution

The graphs depict the dynamics of the major categories of interest. In many cases, writers only need to view the orange pluses. For in-depth analysis, large graphs can be superimposed on top of one another.

Realization

Each element is adaptive, and you can interact with it by changing its size or place in the grid.

Problem

Many writers give up because of the lengthy legal process necessary before they can upload their book.

Solution

We designed a simple online registration process for users, allowing them to download the book immediately after filling out basic information. However, they are not able to sell the book unless they provide necessary legal information. The book is only available for free download.

LitRes Reader

Overview

Any user can upload a book from their computer to LitRes, where it will be added to their list of purchased books. Users can then download the book in any format to their computer or read it using the built-in reader, which is synchronized across all devices. If available, users can also access an audiobook from the point where they stopped reading.

Problem

The reader has been designed to be as flexible as possible. Users can customize fonts, background colors, text, height, and line length. However, users may unknowingly ruin their experience by making inappropriate adjustments.

Research

After conducting a study, it was found that people unknowingly compromise their user experience by using non-contrasting background colors and fonts that are too small when the book is wide. Typography is a whole science that cannot be ignored.

Solution

To address this issue, we developed an algorithm that compensates for the baseline and format of the book depending on the reader's chosen scale. We also picked safe colors to ensure sufficient contrast and prevent eye fatigue, while limiting the reader's freedom.

Personal Info

Overview

Over time, we have collected a lot of user information and needed a place to display and edit it. Additionally, we have found that LitRes marketing promotions work well, and have experimented with several. Some of these promotions can be set up in a user's personal account.

Afterwords

Back then, we worked in Sketch and spontaneously reinvented atomic design. To avoid creating conflicting versions in the master file, whoever was editing it at the moment held a yellow soft toy in their lap. It may have looked funny from the outside, but it was still better than using Photoshop.

In numbers

We conducted numerous A/B tests every day, and only one out of the 20 hypotheses we tested was successful. For each of the 20, we were confident and believed it would be a game-changer. The lesson we learned is that you are not your users, and it is essential to use more than two analytics systems to verify hypotheses.