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Streamlining Slack data review.

My Role:  IC Lead Product Designer

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Company:  Logikcull
 

The Team:  Product, Engineering, Data Science, Executive team, Sales, Customer Success.
 

User Goal: Legal professionals require an efficient and cost-effective solution to accurately ingest and process Slack's JSON data into a comprehensive, easily reviewable format, ensuring effective collection and analysis of critical evidence.
 

Business Goal: Unlock new business opportunities by simplifying Slack eDiscovery, offering efficiency, accuracy, and cost savings to in-house legal teams, and over 65% of Fortune 100 companies.​


Outcome: Design transformed complex Slack data review into an intuitive process, making it a strategic asset for efficient evidence discovery, unlocking new business and growth opportunities.

Slack.png

Legal teams face difficulty in efficiently handling Slack's complex data for discovery.

Slack's Widespread Use:

  • Over 30 million daily users.
     

  • Used by small businesses and over 65% of Fortune 100 companies.

     

  • Serves as a central workplace communication hub.

     

  • Workplace Instant Messages (IMs) are increasingly vital evidence in lawsuits.

     

  • Extracting and analysing Slack data for legal discovery is complex.

Technical Slack Data:

  • Slack data is stored in complex JSON format, which is difficult for legal professionals to interpret.

     

  • A single Slack message can generate pages of complex code.

     

  • Extracting relevant data from Slack for legal discovery is a complex and time-consuming process. Analysing the extracted data to identify crucial evidence is a significant hurdle.

Security compliance:

  • Exporting and storing Slack data locally exposes sensitive information to potential security breaches.
     

  • Maintaining data integrity and chain of custody becomes challenging when data is stored outside of a secure platform.
     

  • Legal teams need the ability to directly ingest Slack data into secure review platforms, bypassing the risks associated with local storage and manual processing.

Problem statement:


Thanks to Slack, more businesses are moving communication away from email and into chat. But many legal professionals don’t know how to handle Slack JSON data in litigation. Legal teams are used to documents, not chat. But chat is taking over.

Goal:


Design a robust solution that empowers legal professionals to rapidly ingest, effectively search, and efficiently review extensive Slack communication JSON data, significantly reducing time, cost and complexity in eDiscovery workflows.

JSON example

Slack JSON data, a legal professionals nightmare.

User research validated the need for Logikcull's Slack data solutions.

Google Meet

User research meetings & customer advisory discussions.

I utilised direct access to engaged users, including our customer advisory board, by scheduling research calls through a public calendar. These calls provided valuable user insights and early design feedback, which significantly accelerated our understanding of the Slack data challenge and facilitated rapid solution development, leveraging existing UX patterns.

Market research and competitor analysis

Analysing the market and competitors revealed familiar SaaS patterns, despite the absence of a direct equivalent solution. These insights enabled a more informed design approach, leveraging existing models to address the specific challenge.

Customer feedback drives RICE scored feature development.

  • The product roadmap and feature creation are driven by customer needs.

     

  • Feedback is gathered through various channels, including direct customer interactions and platforms like Intercom.
     

  • Internal teams (Customer Success, Support, Sales) contribute insights from direct customer engagement.
     

  • All feedback is consolidated within Productboard.

     

  • Productboard is used to prioritise features based on potential impact.

     

  • Features are evaluated using the RICE scoring framework (Reach, Impact, Confidence, Effort).

Research

User stories and requirements

As a legal professional . . . 

User research

  1.  I want the ability to integrate with Slack data so I can avoid manual export and imports.
     

  2.  I want a direct integration with Slack engagement cloud so I can perform a more targeted collection.
     

  3.  I want to discover as many file types as Slack provides.
     

  4.  I want to discover any type of conversation a custodian might have had.

     

  5.  I want a platform that quickly and easily transforms Slack's JSON data into a reviewable format, so I can streamline the discovery process and save time.

     

  6.  I want a platform that enables me to thoroughly review Slack data in a user-friendly format, so I can confidently gather and analyse evidence for legal proceedings.

Through a fast paced, collaborative approach, we designed and developed a streamlined Slack import

Data Architecture & User Flows

This project highlights a successful collaborative effort involving data science, engineering, and product teams. Key takeaways include:

 

  • The project prioritised quick development cycles and strong communication.
    


  • The initial phase concentrated on delivering immediate value by identifying and prioritising the most relevant Slack data.

     

  • Close collaboration with data science allowed for effective data analysis, leading to meaningful data groupings that enhanced user interaction.

     

  • Phase one established a solid base for future feature development and enhancements.

User flow

Optimizing Data Grouping for User Interaction

Untitled (2).png

Logikcull's Slack import simplifies data ingestion with API access and a guided wizard.

Integration Modal,Mode=Light,.png

The redesign focuses on how users import Slack data into Logikcull:
 

  • Maintaining existing functionality was a priority.

     

  • A manual data transfer option is still available.

     

  • The design acknowledges varying levels of Slack API access among organisations.

     

  • Users have the option to "upgrade" their experience.

     

  • Upgrading involves connecting directly to the Slack discovery API.

     

  • The API connection aims to streamline and improve the efficiency of the import process.

Connecting to the Slack API

When selecting the Slack Discovery API, users are redirected to their Slack workspace for authorisation. Depending on their organisation's settings, this step may have been pre-configured by an account owner, allowing some users to bypass this step.





  1. Connect to the Slack discovery API

    


  2. Authorise Slack workspace

     

  3. Select workspaces to import

     

  4. Select participants

     

  5. Select conversation types

     

  6. Create upload

Slack

A four step wizard simplifies Slack import configuration. Users define Workspaces, Participants, Conversation Types, and Upload settings in sequential steps.

The design solution enables fast Slack data searches with intuitive, chat-specific filters.

Million document reduction:


  • Logikcull's 'powerful simplicity' in search facets now extends to visualising chat and Slack-specific data.
     

  • Users can now filter large datasets instantly. Checking a box in the new chat search facets can reduce potentially millions of documents to just a few.

Future-Proofing for Business Growth:

  • The 'Chat' label, chosen over 'Slack', ensures compatibility with future integrations like Microsoft Teams, enabling strategic expansion and unlocking new business opportunities.

Chat filters

Through direct user collaboration, we highlighted essential search facets for Slack data. We seamlessly integrated these chat-specific facets into our customisable search environment, empowering users to tailor their search experience for chat. This user-friendly interface eliminates the need to manually sift through raw JSON files, offering a streamlined and efficient Slack data search.

Logikcull offers fast, secure Slack discovery via API and intuitive review tools.

Before:

  • Manual export and import of Slack data was currently necessary.

     

  • Targeted collection from Slack Engagement Cloud was not directly possible.

     

  • Discovering all types of file types and custodian conversations was limited.
     

  • Transforming Slack's JSON data into a reviewable format was a slow and complex process.

     

  • Reviewing Slack data for legal proceedings was not user friendly.

After:

  • Collect Slack data effortlessly with a few simple clicks.


     

  • Securely ingest Slack data directly into Logikcull, eliminating the risks associated with local storage.

     

  • Access and immediately review chat conversations from relevant sources in an easy to understand format.
     

  • Quickly identify crucial information using chat filters to surface important conversations, reactions, and attachments beyond keyword searches.
     

  • Filter Slack data based on key categories such as workspace, user, participant, company and more.

User-focused Slack updates provided a model for expanded chat data solutions.

Following the successful launch of the Slack API data import and improved search review, we continued to collaborate closely with our users to identify further areas for enhancement. A key area of focus was the in-application display of chat data. Users expressed a strong desire for a more 'native' chat view within the document viewer, which we promptly began developing.

Furthermore, user research revealed a significant need for the ability to send and confirm legal holds directly within Slack. We were proud to be among the first in the industry to implement this innovative feature.

With the exponential growth of chat data across platforms, our work with Slack provided a valuable foundation for scaling our capabilities to other platforms, such as Microsoft Teams. This has opened up significant opportunities while consistently upholding our commitment to providing users with a powerfully simple and helpful experience.

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