15 Social Media Customer Support Metrics You Need To Track (& How To Improve Them)

Jul 12, 2021 14 min read

Identifying & measuring the right customer support metrics will assist your brand greatly in monitoring the brands's customer service efforts & performance.

Demonstrating a solid set of customer service KPIs guarantees a new business's stellar performance. Besides, consistency in tracking these metrics empowers brands & businesses to provide high-quality service.

However, measuring the benchmarks of customer support is intricate, as each day your brand may have dozens of tickets lined up in the pipeline. The entire process of tracking the metrics demands a comprehensive & classified approach.

We have segmented different social media customer support metrics based on productivity, performance & support quality to offer you an all-inclusive strategy guide. Dive deep into the article to understand how to establish explicit measuring systems & tactics to improve your existing social media customer service process.

What Are The Top Customer Support Metrics To Track?

Potentially there are several different customer support metrics. Among them, you need to pick only the essential metrics that precisely help you assess performance, focus on customer issues, guide you through planning your resource allocation, & pinpoint necessary improvements in the systems.

  • Customer service KPIs can be segmented into three categories based on the measurement criteria: productivity, performance & quality.

  • Productivity KPIs measure the completion of the quantity of work, performance KPIs measure the facet of the work & quality KPIs track the impact of the work.

Productivity Metrics

Productivity KPIs are the basic set of KPIs that helps brands to understand & analyze the completed work amount within the support function. Check out the following vital productivity metrics:

1. Automated Resolution Rate

Automated resolution rate is the customer support metric that tracks self-serviceability. As per stats approx 70% of customers prefer self-service. Automation is done through AI-powered formats such as chatbots, voice assistants, etc.

Automated customer support is beneficial in situations where customers seek answers to repeated direct questions or status updates. It also works best when the customer seeks help to find a specific resource.

  • Automated support resolution rate is calculated by the total number of closed tickets divided by resolution by an AI-powered customer support chatbot. Also termed bot deflection, it is time-efficient & human resource-efficient.

  • To improve the automated resolution rate, update your FAQ and help center page. Make sure to keep your data refreshed continuously.

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2. Customer Demand Per Hour

Customer demand per hour represents the demand for support at different hours of the day. With this metric, you can monitor & analyze the day or week and month customer support tickets that see a surge.

For example, clothing brands or cosmetics e-commerce business monitor a rise in customer support during the time of festivities. Most of the e-commerce sites' customer support demand increases exponentially during sales.

  • Use these analytics to plan a strategy to ensure quality customer support during the time of surge. Ensure that customers are satisfied with your service even in the rush hour.

  • It specifically helps to enrich your brand images & impact sales. The surge differs depending on the business or the industry.

Customer Demand Per Hour

3. Measuring Tags

The customer support metrics measure the terms or phrases and keywords used by customers in their queries.

These metrics help to analyze the questions and the topics your customers are most frequently asking. You can track the question segments that the customers often ask.

Statusbrew 'Tag Insights' allows users to asses the tag activity, and impart comprehension on volume, reach & performance patterns.

Measuring Tags

  • Receiving too many queries about a particular section indicates that you must fix issues as soon as possible. Track the category and create a process to make it easier to find relevant information.

  • Work on the chatbot and help page. Also, use the data to understand ways of communication of your client & accordingly train your customer support staff to enhance quality.

4. New & Repeat Tickets

The volume of new tickets metric denotes the number of tickets created on your help desk; it depicts the growth of the business in a subtle way. The increasing volume of new tickets means your customer base is increasing & hence the demand for support is also increased.

Ensure to measure the metric periodically such as daily, weekly & monthly. To get an accurate number check out all the tickets raised over phone, emails, chats, social media, etc., and other modes of communications.

A high number of repeat tickets by customers may indicate that they are not satisfied with the resolution.

  • To get the actual number of repeat customers, subtract the number of unique users from the total new tickets created.

  • Reduce the number of repeat tickets by proactively communicating with your customers. Share products guides, up-to-date knowledge, and other required information with them.

New & Repeat Tickets

5. Resolved Tickets Per Agent

Resolved tickets per agent metric represents the numeric of successfully resolved tickets by your customer support team agents on your helpdesk over a particular time frame. With the metric, you can draw support team productivity performance.

By comparing the increase or decrease of the percentage over weeks or months, you generate data-driven inferences on your team's ability to resolve customer issues quickly.

A high ratio of new ticket increases in the pipeline indicates that support agents are not performing productively. Backlog in resolving tickets ends up in lower customer satisfaction.

At the same time, if your support team is solving tickets more quickly than the estimated time, it indicates a highly productive workforce. Also, check out if the unit is overstaffed.

  • With this metric, you also check out the number of tickets individually solved by the agents and accordingly measure their productivity. Use the numbers to find out the top performer in the team & use this as an example to train the underperformers.

  • To enhance solved ticket numbers, you can use chatbots for FAQs and engage the support agents to deal with more complex customer queries.

Resolved Tickets Per Agent

6. Ticket Volume

Ticket volume represents the total number of tickets your support team receives during a set time frame. Measuring ticket volume is vital to plan work distribution among support agents, determining time frames & identifying current gaps monitoring .

Variation in these metrics caused by total conversations, including the engagements with customers via an official support ticket or through other social channels.

  • Track changes in ticket volume over time to effectively plan shifts and distribute the workload. It increases support for your team's response efficiency.

  • As a result, customer issues are resolved quickly, which increases customer satisfaction. To find ticket volume add all tickets submitted during specific time frames; it may be a single day, a week, or a month.

Performance Metrics

Performance metrics for customer support provide you a 360-degree view of your support team's performance. Check out the performance metrics:

1. Average Response Time

Average response time denotes your support team's duration to respond to a ticket raised in the helpdesk.

It is calculated as the total time taken to respond with a particular time frame divided by the number of responses for that specific period.

  • The average response time is the standard time of all responses sent by your agents during a particular time frame, such as a week, month, or year.

  • The customer support metric estimates how swiftly your agents can prioritize and respond to customer queries. Compare & analyze the average response time over a few weeks or months to identify new problems in your support desk & to improve them.

Average Response Time

2. Average First Response Time

Average first response time tracks the duration between a ticket raised by the client & the initial response made by your support team.

First response time measures your support team's efficiency by indicating the period your customers have to wait in the queue before they get a response.

Short first response times lead to high customer satisfaction as the quick first response creates a positive impression.

Zendesk says that for emails, 12 hours is an excellent first response time; for social media & live chat, two hours or less and an hour or less, respectively.

You can calculate the average first response time by dividing the sum of the first response time by the number of tickets.

  • Track the average first response time for each customer support agent along with the team average.

  • Usually, businesses measure first response time in business operational days only; here, off-hours & weekends are not included.

Average First Response Time

3. Average Handle Time(AHT)

Average handle time (AHT) denotes the average duration an agent spends on an opened ticket.

It tracks only the duration an agent works on the call itself, including average talk time, average hold time, and total follow-up time.

Though mean time to resolution (MTTR) & AHT measure the time it takes to resolve a customer's issue, AHT doesn't calculate the time a customer spends waiting while their ticket is picked up.

Average handle time is gauged by dividing the total talk time, total hold time & after-call work time by the gross number of calls.

AHT helps you to analyze the average period your team members spend per ticket they open. It depicts the performance of the agents.

  • High average handle time denotes an issue of understanding the client's requirement or the agent is not asking the right question. However, in some scenarios, AHT is high because the agents have to deal with more complex customer issues.

  • To improve AHT, put your agent on development training & set up automated replies. Also, put all the required information in one place so it is easily accessible to the team members engaged in the process.

4. Converted Tickets

Converted tickets give insight into revenue statistics. It also shows the value of customer support.

These are tickets that are followed by the support team within five days. And these tickets consist of the request question related to delivery, return, etc.

  • Analyzing the converted ticket stats gives you a picture of the amount your support team is generating by helping customers through the purchasing journey.

  • Check out the tickets per week, per month, and per year.

5. Mean Time To Resolution (MTTR)

Mean time to resolution (MTTR) OR the average resolution time (ART) denotes the average time your team takes to address a ticket. It is the time since the ticket is first opened to the time frame it is resolved and closed.

Resolution time is calculated in business hours, not clock hours. Longer resolution times represent if customers are waiting for a duration, and it impacts customer satisfaction rates & customer retention.

Average resolution time varies from company to company. High-resolution time for a long duration indicates your support system requires improvisation or your team members are working through a heavy workload.

To deal with the issue, communicate with your support team to determine where the productivity is impacted & what measures you can take to speed up the ticket-resolution process.

  • To calculate average resolution time, divide the total resolution time for all resolved tickets by the number of resolved tickets & you'll get the average resolution time.

  • Monitor this metric regularly to understand your team productivity & accordingly provide your team training to handle complex issues more efficiently.

Mean Time To Resolution (MTTR)

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6. Unresolved Tickets

The number of unresolved tickets or backlogs are open after service level agreement(SLA) time. Higher backlogs denote a higher rate of unresolved tickets and more unhappy customers. To minimize piling up tickets, set daily, weekly, and monthly goals.

There can be multiple reasons for surging backlogs. Still, either way, it indicates your service team is not performing well & they are not resolving the issues within the timeframe provided to the customer.

  • Analyze the probable cause for high backlogs such as being understaffed, missed tickets, or level of complexity.

  • Monitor the preferred communication channel your customer prefers to raise tickets, check out those channels to optimize the channels and minimize backlogs.

7. Goal Completion Rate(GCR)

GCR customer super metric tracks the number of customers that complete a marketing task such as signing up for trials or subscribing to the newsletter. It calculates the percentage of users conversion rate.

GCR varies from industry to industry. Higher GCR denotes your customers are achieving the goals you have set.

  • To improve your low GCR rate identify low-performing goals & reduce the number of steps required to achieve the goal, make the process user-friendly easier for the customers.

  • GCR is vital to understand the performance of your customer support chatbot's performance & its success rate. GCR gives you the analytics about how well your chatbot is performing towards achieving your prioritized goal.

Note: Apart from the above performance metric, one of the crucial metrics is the first contact resolution rate. This metric calculates the percentage of tickets that are resolved with a single reply.

To gauge FCR, divide the total number of requests resolved with single interaction by the total number of requests at that particular time frame.

FCR rates differ based on the number of customers, the budget allocated towards the training of the helpdesk team, and the complexity of the product.

FCR helps businesses retain customers by increasing business loyalties by solving pain points at the first customer interaction.

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Quality Metrics

Quality metrics measure the standard of your customer service, how customers perceive your effort. It brings the perspectives on the room for improvement in your customer service effort.

1. Customer Satisfaction (CSAT)

Customer satisfaction (CSAT) measures the fulfillment of the customers with the company products & services. It is estimated through survey forms filled out by customers after interacting with your helpdesk team.

Usually, survey questions include customers' experience rates on a scale. By analyzing the collected data, you can quantify the metric of client satisfaction.

Average First Response Time

Image Source:CheckMarket

  • To calculate the CSAT, divide the number of positive responses by the number of total responses & multiply it by 100.

  • CSAT is a crucial quality customer service metric as it gives you insight into how your customer's service efforts impact the customer's happiness & helps to analyze the efforts to enhance customer service.

2. Net Promoter Score (NPS)

Net promoter score represents the percentage of customers who refer a company, a product, or a service to their peers based on their perception of a business.

Customers refer to their peers depending on their customer service and customer support experience.

Companies should set a few questions for customers to ask them if they would like to recommend the company and request them to elaborate their answers by providing a reason.

Net Promoter Score

Image Source: Userlike

Based on recommendation reasons, companies can have three categories of customers, i.e., promoters, passives & detractors.

Promoters are your loyal customer base who scaled you in between 9 to 10. Passives are satisfied customers but feel improvement can be done & provides you 7 to 8.

Detractors are unhappy customers who would hardly purchase your product & they also discourage their peers from buying from your company.

  • To enhance NPS score listen carefully to customers quarries, provide them with in-depth product information, ask for feedback, and make sure to provide support on time.

  • To calculate the NPS score, take the percentage of promoters (10 - 9) and subtract the percentage of detractors (0 - 6).

Tips To Improve Customer Support Metrics

Proactive customer support is vital to enrich a loyal customer base and, in the long run, impacts the brand's revenue growth. According to stats, 90% of Americans decide to establish relations with an organization based on customer service. Hence, for your brand's success improving support metrics is crucial.

1. Set Up Brand Monitoring Strategy

To improve your brand's customer service metrics, make sure to set up a monitoring strategy. It is vital to set up benchmarks for metrics according to the goal you want to achieve. While preparing the plan, remember less is more. Pick the metrics that are easy to measure.
You can use Statusbrew reporting tools for the best measurements based on normal day-to-day operations.

2. Integrate Social Channels To CRM

Integrate your brand social channels to CRM. With a CRM social media integration, any of your team members can access the customer interaction history in the helpdesk. You can quickly respond to the customer queries & quality solved tickets helps to increase CSAT.

Besides, it also allows you to monitor negative comments or mentions anywhere on social media.

Statusbrew's built-in CRM syncs all customer data to your unified inbox in Engage. It also provides you a quick view of all the previous communication with the contact & helps you to track the context of the conversation.

3. Hire Specialized Workforce

Your workforce is a significant factor in improving customer service metrics. Hire a specialized workforce who have quality knowledge & who are efficient in understanding customer queries.

Allocate budget for training programs, set a transparent internal communication system so that the team can efficacy connect. Reinvest in the support team to inject customer-oriented skills by offering two training types: soft skills and technical skills.

Upgrade their skills by helping them understand e-commerce support automation and technology & training in empathy and listening.

4. Right Use Of Internal Communication Channels

Along with solving customer problems, support metrics also help to build brand image. Utilize your internal communication channels to set up a best practice for your support team. These practices ensure your customer service is friendly and approachable.

Set up clear guidelines to prohibit intentional or accidental bias responses & ensure consistency in communication.

With Statusbrew's Slack integration, your team can quickly communicate with each other & the communication is clear; whenever you see any inconsistency directly you can guide the helpdesk team. Slack integration helps to streamline the workflow.

Right Use Of Internal Communication Channels

Image Source: Slack

5. Share Informative Links

During customer support, make sure to provide your customer with information about your products. Share informative links or guides to help them to understand how to use the products. Besides, provide your customers with easily navigable self-service content to enrich a solid knowledge base. Set up a FAQ section to help the customers to resolve fundamental issues on their own.

6. Measure & Share Data To Relevant Department

Identify and track key performance indicators such as first contact resolution, response rate, resolved issues, etc. & save it in a document format. Share the analyzed data among sales, marketing & product departments.

When data is shared with all the departments, all of your team members are aware of the ongoing situation, and in improvement plans, they also can share their ideas. Data sharing involves sharing vital information, stats, insight, details across the department to make the organization more efficient.

A data-driven organization's workforce capable of making more informed decisions and interactions. It also helps in the improvisation of the product from the last version.

 Measure & Share Data To Relevant Department

7. Dedicated Support Channel

Along with a customer support team, also keep a dedicated customer support channel within your social media platforms. Social media has numerous users, with a dedicated social channel, customers can directly raise tickets for their quarries.

Using DMs is also a quick way to solve your customer query on social media. Stausbrew Engage supports Instagram DM.

Track Top Customer Support Metrics With Statusbrew

Statusbrew's 90+ reporting metrics empower users to get insight & analyze the impact of social media customer service efforts.

With Statusbrew's 'Team Engagement' and 'Leaderboard Report', you can analyze & monitor how your customer service team handles customer queries across the brand.

Use these reports to set up team goals for the customer care ambit.

Learn More: Team Engagement Reports

Team Engagement Reports helo you track the volume of incoming conversations. You can also measure your teams' proactiveness in responding to the queries.

Statusbrew allows you to set up 'Office Hours' for your customer care agents working in different geographical timezones. You also can connect tools like Zendesk to manage support, sales, and customer engagement reliably and productively.

Learn More: Better Customer Support With Office Hours

Use Statusbrew's Team Leaderboard to benchmark objectives for social customer care, analyze the work effectiveness of helpdesk agents, gain insight & evaluate responses dynamics.

Wrapping Up

Customer support metrics guide your customer support efforts in the right direction. Once you have analyzed the metrics mentioned above can benefit you in increasing sales, enhanced customer experience, high customer retention, minimize customer churn & result in an advanced purchase rate.

With Statusbrew save time and improve customer service experience with templated responses, pull in the correct data into customer responses & measure the apt revenue-driving support metrics.

To centralize your customer support in one place with Statusbrew, book a demo today.

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Rajashree Goswami

Rajashree is a content creator & researcher at Statusbrew. She loves to create content that is expressive & communicative.

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