Email disrupted corporate communications 25 years ago. Chat is disrupting email and it isn’t stopping there—conversation-centric collaboration is rapidly changing the way we work. Discover how we are reimagining solutions for chat.
The evolution of chat
Instant messaging has evolved into persistent, substantive conversations in the workplace. New features are expanding the reach of these apps—including files, audio, and tasks. Gartner has dubbed these “workstream collaboration tools” predicting that by the end of 2022, 70% of teams will rely on these tools as the primary means of communicating…supplanting email.
Organizations are not standardizing on a single tool—work groups are adopting multiple tools that meet their unique needs. For years discovery has responded to chat by forcing them into an email/attachment metaphor. We are reimagining the way this data is processed, searched, and reviewed.
Chat is structured data
Abandoning the email metaphor allows us to treat messages as discrete records and expand to include records for non-chat content in collaboration tools. Managing chat as structured data, we capture message and action level metadata we can use to organize, search and cull data sets.
- Action type—system, message, link, file—classification
- Message and action level deduplication
- Message and action level dates
- Bot-generated content identification
- Linked file native indexing
Little Pictures Worth a Thousand Words
Emoji Considerations in Discovery
The use of emojis in both personal and professional communications continues to grow – and those little icons are having a big impact on discovery teams. In this paper, ProSearch Product Manager Jessica Lee examines the challenges presented by emojis and tips for dealing with emojis contained in data collections for discovery.
Discrete Review Sets
Targeting content in conversational sprawl.
Chat has traditionally been reviewed in blocks—frequently 24-hour threads of chat converted to an EML file. This creates overly broad and disjointed conversations that are difficult to review. We are focusing on robust search and filtering features that allow you to define discreet sets for review.
- Create review sets across collection sets and source types
- Filter and select based on action level metadata—source, channel, content type, owner, participant, date
- Search message content
- Search emoji text labels and native attachments
- Expand your search results—by the number of messages or elapsed time—to add context to review.