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9 Live Chat Support Metrics To Follow To Satisfy More Online Shoppers

A person using a laptop computer for Live Chat Support Metrics.

Many live chat campaigns don’t consider the power of analytics and reporting. And, stores that don’t follow their support metrics miss out on the opportunity to empower their future decisions. Find out which tactics help and which tactics harm your Shopify live chat by understanding what really goes on behind the curtain.

Here, you’ll learn the following:

  • Why live chat support metrics are crucial for your online store’s success
  • 9 metrics you should follow to fully-understand your support operations
  • How each of these metrics can help your eCommerce business grow

If you’re ready to learn more about how to maximize your live chat efforts, read on.

First, How Do Support Metrics Enhance Your Live Chat Operations?

If you already monitor your store’s live chat metrics, you won’t question how analytics and reporting enhance support operations. Gorgias users typically see a 30% decrease in ticket resolution time when they use our platform. And, some implement informed strategies that can decrease first-response time by up to 78%.

However, when you don’t measure your successes and failures, customer support operations can never be optimized. And, without optimized processes, you can’t meet modern consumer expectations.

So, What Do Online Shoppers Expect From Live Chat Support?

Before you look into analytics and reporting for your live chat operations, it’s good to get a baseline. Here are some statistics that highlight what your shoppers expect from your live chat support operations.

  • 42% of customers want a response within 60 minutes on social media (Convince & Convert).
  • Customers expect a response within 45 seconds for live chat (Com100).
  • 53% of customers are willing to wait only three minutes to talk to an agent on the phone (BizFluent).

People want to get things done as quickly as possible. Ultimately, it’s best to start where you are and work on improving internally. But, when you know how you stack up to the competition, it can help. Next, take a look at the metrics you should follow.

Now, The Live Chat Support Metrics You Need to Follow

To get a complete understanding of where you stand and where your customer support team can improve live chat efforts, here are the metrics you should follow (in no particular order).

1. Tickets Created

How many total tickets are being created within your live chat operations? The number of tickets created is central to your live chat operations because this can help you determine nearly every other metric you need to look at. Tickets created will represent how many tickets have been created in a certain timeframe or throughout the lifetime of your business.

Tickets statistics dashboard for a specific timeframe
Tickets statistics dashboard for a specific timeframe

And, based on this number, you can find percentages, conversion rates, and discover ways to make the user experience of your brand even better.

2. Tickets Replied

How many tickets are your agents actually replying to? Tickets replied will represent how many tickets were replied to in a certain timeframe or throughout the lifetime of your business. Shouldn’t your agents reply to every ticket that comes in? The answer really depends on your operations.

If there’s a chance that a shopper could accidentally send you a message, then no, your agents will not reply to all of them. There’s no need to answer a question your customer, Bob asks when it looks like this: “kafhlkadsjhfgjcas alskjf lska.” In this case, Bob surely didn’t mean to send a message in the first place.

And, spam messages aren’t typically replied to. Your agents shouldn’t spend time visiting every SEO agency, web development, or adult website that’s solicited through your live chat communication channel.

This metric, when compared to your tickets created may tell you if you need to come up with an anti-spam strategy to save time. And, it can help you determine whether or not you need to use a more user-friendly chat support platform. Eventually, all tickets should be replied to or closed. If not, you should be concerned and support operations need to be tightened up.

3. Tickets Closed

How many tickets are being closed/resolved? Tickets closed represents the number of support tickets that were closed during a certain timeframe or throughout the lifetime of your business. This metric provides details about the ability of your agents to resolve problems. For accuracy, a ticket that is closed multiple times should not be counted more than once.

Not all tickets that are replied to will be closed as quickly as they should. For example, you may send a customer a return shipping box that they do not send back to you. And, this type of support can fall to the wayside. Make sure you do not have too many tickets open at any given time. And, when you do, your agents should diligently work to close them in a timely manner.

4. Messages Sent

How many total messages are being sent via live chat? Messages sent is a metric that showcases how many total messages were sent. This data can then be broken down to determine how many messages are sent per ticket on average. eCommerce support agents should avoid excessive communications and try to minimize the number of messages sent to resolve a ticket.

For clarity, messages sent is not the same as tickets created. One ticket could involve many messages between the customer and the support agent. This message is worth watching because you don’t want your shoppers to deal with lengthy conversations that drag on for weeks. They want their questions answered right away, and that should be your goal.

5. First-Response Time

How long does it usually take for an agent to respond to a customer on live chat? First-response time is a measurement of the mean average time it takes to reply to a customer’s message for the first time. You can use this metric to determine the typical amount of time it takes to get in touch with your shoppers when they open a new ticket. And, since they expect you to reply swiftly, this should be your goal.

Historical view of average first-response time
Historical view of average first-response time

The ability to see charts and graphs with historical data gives you powerful insights about how quickly you are able to reply to tickets. And, if you need to hire more agents or work people on different days, this metric will help you uncover weak areas in your communication or operations.

Furthermore, following first-response time can show you internal improvement over time. Your first-response time should become shorter over time. When you see a decrease in first-response time without a spike in website traffic, it is a cause for concern and should be looked into.

6. Resolution Time

How long does it usually take for your agents to resolve a customers’ problem? Resolution time is a calculation of the mean average amount of time it takes from when a ticket is created to when it is resolved. Use this metric to determine how long it typically takes to solve your customers’ problems. Like first-responses, they want a resolution as quickly as possible.

Historical view of average resolution time
Historical view of average resolution time

And, you can gain helpful insights about response times if you can further segment your data based on pre-sale and post-sale tickets, specific topics, and macros. What goes into your ticket resolution via live chat? Which processes weaken your strategy and which strengthen them? This metric can help you uncover the answers.

Furthermore, it can help motivate your support agents. By monitoring resolution time over time, your support team establishes a starting point. From there, they can set new goals and try to meet them, which can be fun and inspiring.

7. Agent Statistics

Which of your support agents perform the best? And, what can your other staff learn from them? Agent statistics can show you metrics about specific agents within your team. One of the most valuable pieces of data about a specific agent that you can look at is the number of tickets they close during each period or throughout all the time working with your brand.

Total Tickets Closed Per Agent]
Total Tickets Closed Per Agent

As with resolution time, agents can use agent data to set personal goals and compete with co-workers. And, during onboarding, when a new agent sees what others are doing, it can help them create reasonable expectations for themselves without a manager relaying a ton of information or bragging about the best workers.

8. Macros (or Custom Fields) Statistics

Which macros are being used and in what volume? Macros are similar to custom fields and they can help automate some of your communication within your live chat support operations. By segmenting Ticket channel: {{ticket.channel}}, Receiver email: {{ticket.receiver.email}}, Ticket customer id: {{ticket.customer.id}}, and other variables, you can automatically insert specific details about a customer’s situation with data from your records or third-party apps.

When you follow your macros statistics, you gain an idea of how well your agents maximize automation features. You can also look at which macros are used the most often and use the data as fuel for your website optimization strategy.

Macros management for live chat support
Macros management for live chat support

For example, if you notice that the shipping macro seems to be over-used, you can link out to shipping details and/or update your shipping policy page to make the information easier for customers to find. Then, you may not need to reply to as many tickets in the future.

9. Revenue Statistics

How much money is being generated via live chat support? To become familiar with how much revenue live chat generates for your online store, you will need to pay close attention to metrics in four sub-categories.

  1. Total sales from support
  2. Conversion rate
  3. Converted tickets
  4. Pre-sale tickets

With a complete understanding of the revenue statistics above, you will know precisely how much of your store’s profits are due to your live chat support.

Revenue Statistics Dashboard for Live Chat
Revenue Statistics Dashboard for Live Chat

Total Sales from Support

To find your store’s total sales from support, look at the total sum of the order amount for each converted ticket. This metric tells you how much revenue was generated from support, either for a certain timeframe or the lifetime of your business.

Conversion Rate

To find the conversion rate of live chat support, look at the ratio between presale tickets and converted tickets. Post-sale tickets related to refunds, returns, and delivery should be ignored since they are irrelevant here.

Converted Tickets

To find the number of converted tickets, look at the number of pre-sale tickets that were followed by a sale within seven days. You may want to further develop your understanding by looking at the number of pre-sale tickets that led to a sale within 24 or 48 hours.

Pre-Sale Tickets

To find the number of pre-sale tickets, segment your tickets into pre-sale and post-sale categories. Pre-sale tickets are questions that customers ask before placing an order related to availability, product specifics, sizes, etc. Post-sale tickets are those related to delivery, returns, and refunds.

Final Thoughts

What’s up with your eCommerce live chat support operations? If you don’t know, you can never optimize your processes. So, be sure to follow these metrics:

  1. Tickets created
  2. Tickets replied
  3. Tickets closed
  4. Messages sent
  5. First-response time
  6. Resolution time
  7. Agent statistics
  8. Macros statistics
  9. Revenue statistics

Then, use what you’ve learned here to motivate your agents, update your website, and create more satisfied customers — the lifeblood of your business.

Does your live chat platform enable you to view these metrics? From inside the Gorgias dashboard, our customers can see everything they need to nurture outstanding customer support strategies. Sign up for your free trial today and experience the difference.

This article originally appeared in the Gorgias blog and has been published here with permission.

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