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Why customer support teams need analytics for Slack conversations

Slack is where many customer support teams spend so many hours of their day. The conversational data that is created in this platform can be utilized to accelerate onboarding and productivity, particularly for rapidly scaling customer support teams. Ignoring its utility is grave mistake, so let’s review the opportunity to make the most of conversations in Slack.

Slack is the modern Work Operating System

When companies choose a platform for communication and collaboration, Slack tends to meet the bulk of their needs. It is highly extensible and streamlines communication in a way that other tools have yet to beat. The customer support function fits tidily into the Slack ecosystem with numerous integrations and a faster way to communicate with team members. Even better, for Customer Support teams, Slack has introduced shared channels (via Slack Connect) as a way to securely interact with customers, partners and vendors. This further cements Slack as a foundational operating system for work.

Top 3 Challenges of Customer Support Agents

Having knowledge in the right place at the right time

Having access to the right knowledge at the right time, is critical to the daily success of customer support agents. Ensuring that customers are feeling delighted with the overall experience provided by the support team depends on the depth of agents product knowledge. They can’t be expected to remember everything off of the top of their head, so having an instantly accessible knowledge repository is an important arrow in the agent’s quiver. Without a dependable and accessible knowledge base, the resulting outcome is that support agents begin asking more questions in Slack, which increases distraction and reduces productivity across the entire team. That extra noise in Slack is problematic, but as we have suggested, there is a silver lining – more on that later.

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Rapidly scaling teams

Growth is good, right? Right? Well, maybe better said, growth is a nice problem to have. It validates your company strategy and product, and it improves team morale and confidence – but not without a cost. Growing your customer support team creates a challenging set of circumstances. It increases pressure on both existing, senior agents as well as the newly onboarded team members. Again, newly onboarded customer support agents ask a lot of questions in Slack when it is the lowest perceived path of resistance to to resolving a customer issue.

A culture of sharing internal company knowledge

When there is a lack of cultural emphasis on knowledge sharing, valuable internal knowledge either loses value from underutilization, or eventually walks out the door – and both are costly to the company. A culture of knowledge sharing places emphasis on quality documentation and transparency. Slack plays a role in this knowledge transfer too, both for requests and distribution.

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Slack conversations: An analytical gold mine

What do all of the conversations in Slack reveal about your organization? In short, the chatter on Slack is the collective pulse of your company. Conversational topics and trends reveal details about the state of knowledge sharing amongst employees. It reveals where knowledge gaps exist, derived from which questions are being asked, and how often these questions are being repeated. The data reveals shortcomings of knowledge sharing, employee training/onboarding process, and even the effectiveness of SOPs.

When we zoom in on the Customer Support function and consider all of the Slack related conversation data, a great opportunity presents itself. With a robust analytics tool integrated with Slack you can identify all of the hidden deficiencies that are carving productivity losses into your customer support team’s metrics. By periodically analyzing conversational data captured in Slack, you can truly understand the challenges encountered by agents on a daily basis.

The role of NLP in conversational analytics in Slack

When you have a massive trove of unstructured conversational data available to you in Slack, its nearly impossible to make sense of it all without some kind of tool to assist in collating the data. Enter Natural Language Processing (NLP) powered artificial intelligent technology. NLP is tech that can be trained to identify patterns in conversational text so that it can be utilized for numerous purposes, including deep analytics. With natural language being an obvious component of Slack conversations, utilizing a tool that will identify trends

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Slack isn’t just a foundational work technology that enables smooth communication and collaboration. It retains a trove of valuable data that can drastically reduce your operational costs. Explore an NLP powered Slack analytics tool today!


You can add robust Slack conversational analytics to your toolset with Obie with just a few clicks. Request a demo of our analytics dashboard and the rest of our knowledge management suite.