Sigma Computing, San Francisco, California, United States: Sigma's Customer Service Team

An essay of up to 650 words

Total 649 words used.

At Sigma, we are obsessed with providing the best-in-class customer support and we have the proof points to show how we’ve consistently improved the customer experience over time. Using our own product and expertise in the data space, Sigma’s support team is uniquely positioned to connect and aggregate data, optimizing the support experience in a way most companies and teams cannot. We believe that great support is part of the product.

When Sigma support was faced with addressing a rise in support response times due to a 99% increase in its customer base year over year, the team turned to the product to help them model and scale their growth appropriately. In this real-world example, we took the following actions:

• We identified how many incoming conversations each new customer (company) was going to bring in, and what staffing we’d need based on sales projections. We also identified the different ticket volumes we get from new users compared to existing users, baking that into our calculation. 
• We created a live dashboard that shows real time data on support ticket volume, response, and resolution times, current CSAT rating for the day and how it compares to the last 24 hours, week, and month.
• We set up an email report that summarizes the day’s responsiveness to conversations, as well as the day’s CSAT scores.
• We collected metadata from support tickets such as the user sentiment, root cause of the issue, and how the issue was resolved. We then used a tagging system to identify product friction and inform our roadmapping process. This surfaced things that typically wouldn’t even be flagged as bugs, but in aggregate were areas where we could make improvements. 
• We implemented a practice of including Support Engineers in engineering planning meetings to provide valuable insights and trends from customer tickets.
• We closely monitor product feature releases to identify any documentation gaps or the need for additional materials. All this ticket volume data, along with new bug tickets and requested features from customers, is tracked using Sigma. 

Using Sigma’s quarterly sales projections, expected ticket per Support Engineers per day, and some assumptions about efficiency improvements, the team could forecast support needs for the coming year! In quickly addressing those needs, the team beat each respective goal achieving the following metrics:

• Customer satisfaction rating of 4.84 (out of 5)
• Initial response time averaging 23 seconds 
• Average time to resolve at 1:08 hours 
• 88% closed chats on 1st contact
• A TSE Efficiency (chats per hour) of 2.21 

Year over year, the team supported a 15.9k increase in live chats created. Meaningful projects that were completed to achieve those goals and scale effectively include:

• Launching an internal QA for chats and JIRA bugs as well as a pilot to improve operational efficiency 
• Tailoring support insights to various team interests 
• Hosting monthly virtual user meetups 
• Developing impactful content to boost community engagement 

In 2023, support also added attributes to Sigma support conversations. Support Engineers tag and classify conversations so that we can analyze these quantitatively. Information such as the issue type, the method of resolution, as well as the root cause is added, and the metadata gets synced into Sigma so that we can run interesting reports, such as:

• Areas that get significantly more questions than others. 
• Areas that suddenly emerge, i.e., a new product change that was introduced and might be causing issues/excitement.
• Areas that we can create more documentation for, or compliment with a tutorial.

The team is now focused on introducing AI and workflow optimizations, adding additional proactive monitoring and efficiently expanding into new time zones. Achieving these milestones is remarkable, but what sets Sigma’s support team apart is the range of challenges this team handles with ease and enthusiasm. From providing rapid responses to diverse queries using analytics, addressing cloud data platform latencies and attending to unique privacy concerns, they are agile, data-informed and solution-driven.

Total 144 words used.

1. CSAT score of 97% (world class standard is 95%)
2. In 2023, the team conducted 536 technical advisory office hour video calls marking an increase of +192 calls (+55.8%) year over year.
3. Mean time to resolve: 1:08 hours (world class standard is 9:15 hours)
4. AVG response time: 42 seconds (world class <60 seconds)
5. Percent of conversations answered <1 minute: 85% (world class standard is 80%) 
6. Improvement in efficiency per agent by 31% 
7. The team proactively manages and curates content for the online Sigma Community page empowering users to explore and ask questions of our data. There, users can interact with other users, share knowledge and get answers to their questions.
8. 1.3k likes of the Sigma Community page. 
9. 1k+ categorized topics authored on the Community page and 8k+ posts created. 
10. Hosted 15 virtual and in-person user meetups in SF, NY and Denver!