Background

Clay.com is a Sequoia-backed Series A company automating prospecting work traditionally done by SDRs & BDRs. This case study explores how they leveraged Pylon to help them build a scalable, unified customer support process for their Slack Community, Email, and In-App Chat.

Clay’s primary means of support for their thousands of users has been their Slack Community. They started the Clay community Slack to create the easiest direct interface with customers.

Fast forward 2-years and the community is vibrant with 5K members.

Their support team includes 3-dedicated team members led by Matthew Quan.

Challenge

Clay offers support through their 5,000 member Slack Community and through a support email with almost all support questions coming in through their community. They have a 3 person full-time support team solving almost 2,000 questions per month.

They faced a variety of challenges including:

• No unification across their community and email support. One team member would keep a closer eye on their support email inbox while helping the rest of the team with the community support questions.

• Lack of the basic support tooling. They had no way to view all customer issues, assign them, set up any automations, get alerts for missed SLAs, add tags, set fields on issues, or even see relevant customer data while responding to customers.

• No metrics. They didn’t know how many issues were being created, who was answering them, first response times, resolution times.

• They had also been getting requests from users to offer an In-App Chat experience but there was no way they could offer it before addressing their current operational challenges.

Clay was able to solve all of these problems thanks to the help of Pylon.

Results

Clay’s support team now operates completely out of Pylon where they can see a consolidated view of all of their customer issues.

They get complete unification across their community, email, and in-app chat messages.

For those messages they can now leverage support system functionality including assignment, private notes, viewing customer plan data from HubSpot while responding to issues, SLAs, and exporting issues data.

The metrics they pull include analytics on support volume, first response time, and resolution time. This is filterable by date ranges, accounts, groups of accounts (based on their HubSpot data), issue assignee, and custom fields.