Designing Dashworks for Slack

In Q4 of 2023, we launched our Dashworks Slackbot autoresponder. This product aimed to tame the chaos in QnA based Slack channels by detecting questions and answering them in seconds using company knowledge. In this blog post, we'll explore the nuanced UX journey, the inception of powerful analogies, and the decisions that transformed Dashworks Slackbot into a pivotal player in channel conversations. An overview of how we seamlessly integrated into the customer journey, ultimately elevating productivity by 73% for customers.

Identifying the Channel Conundrum

‍This journey kicked off with a deep dive into the chaos of questions inundating Slack channels, particularly in help and QA domains. In most teams, a handful of administrators and knowledge experts bear the responsibility of answering all inquiries. This process can be repetitive, and time-consuming. In most cases, the asker has to wait for a while before getting an answer. A common pain point we observe across teams, regardless of their size. Dashworks had already tackled the challenge of retrieving information from company knowledge via its web app. With this feature, our goal was to meet our users where they worked. At the source of action.

Inspiration Strikes: The Subject Matter Expert Analogy

We spent a lot of time considering how the bot will manifest itself in a channel. Would it answer every question? Do people need to specifically tag the bot to get an answer? The key question we kept asking was how can this seamlessly fit into this user journey.

We created the analogy of a subject matter expert. This was thoughtfully designed to make sure that this new process wasn't drastically different from their current experience of asking questions in channels.Users post a question, trusting that a subject expert will see and answer it. Our bot would operate like just another subject expert, responding only when it knows the answer to a question. The key difference is that it will do so in seconds. This human-like interaction was carefully crafted to encourage collaboration and trust.

Design process like no other: Designing within Slack

Unlike most features I have designed, this one had to be completely built with Slack UI. Leveraging the Slack Builder Kit, I immersed myself in understanding components, interactions, and possibilities to craft a UX closely mirroring our web app experience within the Slack context. A blend of UI/UX and conversation design to create a simple experience for the user.

Tight Feedback Loops: Real-Time AI Training

To enhance the bot's efficacy, we built tight feedback experiences. Admins and experts could provide real-time feedback, training the AI when an answer fell short. This iterative process ensured continuous improvement, making Dashworks Slackbot a dynamic and learning entity within the channel. All of this was again designed and built leveraging the Slack builder UI.

Impact and closing thoughts

The journey of designing Dashworks Slackbot was a symphony of analogies, user-centric design decisions, and cutting-edge technology. By infusing subject matter expertise, democratizing access, and building real-time feedback loops, we attempted to significantly improve how teams collaborate in Slack channels. Dashworks Slackbot stands not just as a product but as a testament to the potential of thoughtful UX design in shaping the future of collaborative productivity. Welcome to a new era of channel collaboration, where Dashworks Slackbot seamlessly integrates expertise into the heart of your conversations.

Early signs are promising. We're seeing our bot automatically resolves up to 45% of questions. It reduces total time spent waiting for answers and providing answers, by up to 73.6%. Additionally, 40% of all our customers now use Slackbot 🥳 It's pretty amazing to see the remarkable impact our product has in making collaboration a breeze and boosting productivity! By seamlessly fitting into our customer’s user journey, we're improving how people work together in a way that does not feel out of place or too new to get used to. This demonstrates the remarkable outcomes achievable when user-centricity is prioritized in technological innovation.