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Chapter 8

Measuring Social Customer Service


Social customer service is not merely an added channel to the service ecosystem, but rather the catalyst that’s redefining how legacy channels interact with their audience.

What Does Success Look Like to You?

Customers’ expectations have changed, as have their patience, options and communication styles. Archaic phone, IVR, email and chat functionality will not cut it anymore. Don’t get it wrong, your customers may still defer to these older channels, but when they do, how they interact with you is different.

Social has grown up and the units of measurement have evolved beyond the “softer” numbers that we evaluated with Social’s inception. ART (Average Response Time), FRT (First Response Time) , AHT (Average Handling Time) are the expected benchmarks in social media customer service. However, social brings an entirely new level of expectation evaluation that the older channels simply could not measure well—customer sentiment.


the emotion behind a social media mention online. A measurement of the “tone” of a conversation. Is your audience satisfied, irritated, irate or happy?

Sentiment is all about context. The humanity that drives every service engagement is not binary and cannot be measured accurately as such. There is a difference between a customer who was on hold for 30 minutes, re-channeled 4 times and had to fight to get resolution and a customer who was handled quickly, efficiently and received even more than they expected from a brand. It all comes down to sentiment.

Forrester reports that companies struggle to provide consistent cross-channel experiences, with only 23% rating their ability to do so as ‘effective’ or ‘extremely effective’. This suggests that a large number of companies have not yet applied measurements that can be used across channels as a benchmark, or are not yet using a dedicated social customer service platform for analysis.

Below we have outlined the most important metrics to measure:


Inbound volume: Count of incoming messages on all social channels. Allows you to understand the bigger picture, and for calculating the percent of customer service issues compared to the total number of social inbound messages

Response volume: Count of responses issued by your brand.

Volume by category: Count of messages by interaction type. This includes broad categories such as marketing messages, PR messages, and customer service messages. It also includes subcategories within these such as the number of issues related to deliveries, product, website, etc. Make sure that this categorization matches your organization’s existing system used in the contact center for other channels such as phone and email, enabling you to match ‘apples to apples’.

Case/conversation volume: Count of groupings of messages pertaining to individual customer issues. By grouping messages into meaningful customer conversations, it is possible to count how many customers the agents are interacting with, as opposed to just how many messages they have responded to. Focusing on customer issues versus individual messages makes metrics like handling time and sentiment conversion far more meaningful.


Measuring volumes makes other key performance indicators (KPIs) meaningful; however, volume does not constitute KPIs on its own, as it does not measure performance.

You cannot control inbound volumes or your volumes by category. Rather, these metrics are important for providing a baseline from which to understand your other metrics. It’s hard to understand what a change in handling or response time means unless you can match them up with changes in volume over social channels.

Average Response Time & First Response Time

Average Response Time (ART): Average time elapsed between all customer messages and agent replie

First Response Time (FRT): Average time elapsed between initial customer messages and initial agent replies. This can be compared with the metric of Average Speed of Answer (ASA) on traditional channels.

To illustrate the difference between the two, it’s helpful to look at the timeline of an interaction between an agent and a customer.


Regardless of channel, response time is a key driver of customer satisfaction, with First Response time particularly important over social. Even when an issue cannot be resolved immediately, it is important that an agent show the customer—and everyone who might see the post—that the company has heard the message and is working on a solution.

Because of Average Response Time and First Response Time’s close relationship to customer satisfaction, these two metrics typically provide the foundation of your Service Level Agreement (SLA). A strong internal SLA for response time ensures consistency across the team by providing a clear target for response time—both amongst agents and for your social customer service operations as a whole.

It is crucial that you are able to measure these metrics and performance against SLAs in real-time. If you have a sudden spike in volume, you need to be able to reallocate resources in order to bring the SLA down to baseline.

Response Time and First Response Time also enable you to compare your team’s performance in and out of operating hours. Many operations, especially in their nascency, are not able to scale to 24/7 social customer service. As a result you want to be sure that your hours of operation match customer expectations; if you see that your response time in business hours is wildly off from your response time overall, that can present a business case to shift or expand your hours to be more in line with customer expectation.

Average Response Time and Average Handling Time

Handling Time

Handling Time (HT): Amount of time agents spends processing an issue. Handling time covers all activity, including elements such as reading, tagging, marking sentiment, looking up customer account info, making notes and drafting responses.

Average Handling Time (AHT): Average amount of time agents spend processing issues over a given period. AHT can be measured for individual agents or multiple agents if they’re handling the same issue (i.e. not re-routed, frequent shift changes, assignments, etc.).

Total Handling Time (THT): Total time agents spend processing issues over a given time period. Average Handling Time is slightly different for social than on more traditional channels, in which one issue is dealt with at a time. On social, you might respond to one tweet and not return to an issue until the customer tweets back hours later.


Handling Time is one of the first truly cross-channel metrics for social customer service, enabling you to compare the performance of social against other channels. If it takes 10 minutes to resolve an issue via email and five minutes to resolve an issue on social, you have a solid justification for the ROI of your social customer service operation.

Handling Time is an important measurement in evaluating agent performance. If you have an agent whose Average Handling Time is significantly off from his peers, that might mean it is time for some coaching from the manager. Handling Time also enables you to measure the effect of process changes you have made in your organization. For example, if you want to add an approval workflow for your agents—in which a manager spot checks 20% of all issues—you can track and benchmark the impact of the change on your Handling Time.


Sentiment: Qualitative assessment of customer satisfaction based on the tone and content of messages.

Sentiment Conversion: Change in sentiment as a result of brand interaction. While individual sentiment is important to track, it doesn’t give you a story to tell. The story comes from being able to actually see and quantify the conversion rate from negative to positive.


Measuring sentiment conversion enables you to analyze the level of service you’re delivering, as well as the impact of any changes implemented, such as releasing a new tone-of-voice guide. Sentiment can also contribute to an ROI model, enabling you to measure revenue protected by improving customer sentiment.

The diagram below shows a sequence of interactions between a brand and customer, resulting in a successful sentiment conversion.

Measuring Sentiment

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