Metrics are critical in order to gauge the performance of both support teams and the technology solutions behind them in any project. In our customer case studies, we frequently talk about milestones such as our customers reaching deflection rates of X%, yet what do these terms really mean? As you progress with your conversational AI journey, which key customer experience metrics can you see improve with AI? In this second iteration of our ‘AI for CX 101’ series (Part 1 covers the initial steps in deploying an AI solution), we dive into the key AI-centered metrics to hone in on, to help you hit your CX and AI targets with precision.
The Top 6 Conversational AI Metrics that Matter
1. Deflection Rate
Deflection rate refers to the percentage of customer support requests that are resolved by AI, those that would otherwise be serviced by agents. This includes both:
Full deflection – In such cases, a customer receives a response from the AI, such as details on a hotel’s cancellation policies, thus obtaining a full resolution to their query (case, closed)!
Assisted deflections – Although the AI is able to identify the scope and intent of the customer query, depending on the use case, it may not be authorized to respond with a complete answer. This is an instance in which the AI and human agents work together, in ‘co-pilot’ mode. For instance, for an item that is being returned, the AI may not be authorized to cancel an order and issue a full refund to a customer. In this case, the customer may be asked additional questions, such as the date of purchase. Acting as an assistant who is conducting research prior to a presentation, the AI is gathering key pieces of data to arm the human support agent with to eventually take over. So, even though it may not be capable of fully deflecting the customer query, the AI is still significantly moving the needle, saving valuable agent time, and ensuring that the agent is armed with full context.
Why it matters:
The deflection rate metric has its benefits, as it provides an indication of the impact that your AI solution is having on your customer experience functions – both your support agents and ultimately, your customers.
2. CSAT
CSAT score measures customers’ sentiment towards your product, service or a specific interaction. It is important to separate the CSAT into two parts, to give credit where credit is due: the CSAT score that is attributed to the AI should encompass the AI-only use cases that took place without human intervention, while, if a human agent handled the ticket, the score should be attributed to them. What constitutes a satisfactory CSAT score? “While 60% is a good starting base for CSAT ranges to begin, a score near 80% is the “holy grail,” Partho Nath, Netomi’s Head of Applied AI, noted.
Why it matters:
Key to customer retention, the CSAT score can provide insights into where and when your company is at risk of losing customers. If a customer provides a negative CSAT score because their query was not sufficiently addressed, this is an opportunity for businesses to refine their workflow to include additional customer use cases, and identify areas for improvement. Another consideration is the context of the issue itself. For instance, is a customer providing a negative score because they don’t agree with a certain business policy or an item arrived damaged, or are they basing their feedback on the support interaction?
3. Classification Rate
This refers to the volume of tickets understood by the AI – how many conversations, chats or emails did the AI understand and therefore could make an attempt at responding to?
An AI that is “well-behaved” (in the words of Partho) will not attempt to answer each and every query that comes its way, thus potentially sending the customer down the wrong path. Rather, it will first make a judgment call on whether the conversation is one in which it can confidently identify and map to one of the business workflows. Our Conversational AI Benchmarking Report revealed that Netomi has the highest accuracy in comparison to other AI platforms, meaning that the AI is responding accurately, thus causing less user frustration than if it provided a response that was incorrect or irrelevant. Netomi was also found to have the highest out-of-scope accuracy, meaning that it understands which topics it has not been trained on and follows the appropriate behavior (such as escalating a customer query to a human agent or directing them to another channel).
Why it matters:
The classification rate measures the total volume of tickets handled by your AI, and it indicates if there are additional topics or use cases that can be brought under the purview of the AI, those that it may not be authorized to currently handle. For instance, perhaps the AI has not been trained on issuing refunds, yet, as this is becoming a fairly common query asked by your customers, perhaps it is time to consider bringing this use case under its scope and focus.
4. Goal Completion Rate (GCR)
Oftentimes, users may exit a support conversation, perhaps if they do not have a specific detail of their query right in front of them, or if something else interferes with the task. Yet how many users successfully completed the journey, completing the goals you originally set for your chatbot to meet? For instance, for an airline, this could involve changing a flight, and for a retailer, finding an order status.
Why it matters:
To provide an indication of whether a customer ended their journey successfully, Netomi’s AI platform asks for feedback. If a customer remained until the end of the workflow, we can safely assume that they have been successfully helped. Focusing on this metric can provide some surface-level insights, which can warrant further digging: why didn’t the user complete their support journey? Were there any moments of friction along the way? How can these be removed?
While not directly related to the performance of the AI itself, these final two metrics pertain to the capacity of support teams, and most importantly, the time it takes for the resolution of customer queries.
5. Average Resolution Time (ART), also known as Average Handling Time (AHT)
This is the average time it takes an agent to resolve a customer conversation. Here, you can identify potential areas for improvement and reduce resolution, such as making enhancements to your company’s knowledge base to make it easier for customers to utilize options for self-service, or removing any operational efficiencies that impact support agents performing their jobs. This also ties into smart conversational design, and reimagining the resolution paths for certain queries. By looking at the average resolution time per topic, you might be able to identify ways to streamline the journey. For instance, if a customer wishes to cancel a flight, they could be asked whether or not they purchased a refundable ticket, in order to cut down on the amount of text sent by the AI.
6. Average First Response Time (FRT)
This refers to the amount of time that has elapsed between a customer raising a ticket and an agent first responding to it. How long does it take for a company to provide an initial response to a ticket? Research has found that the average first response time is 12h 10m, yet 75% of customers expect it within five minutes! By looking at the Average FRT, the customer service team can see how this decreases overall because the chatbot is adding value.
As AI has 24X7 availability, working around the clock outside of standard working hours, it significantly lowers the FRT, making that five-minute window quite feasible.
Every company wants to grow. The easiest way to do that is to keep your existing customers. To retain customers, you need to make them happy. Happy customers turn into long-term and profitable loyalists. And in short, long-term and profitable loyalists go a long way toward improving your CSAT score.
How do companies actually know how happy their customers are with their products, services, and experiences? They measure their customer satisfaction score – or their rating for Customer Satisfaction.
Throughout the entire customer lifecycle, there are many moments that add up to a person’s relationship with and feelings towards a brand. This includes in-store and online shopping experiences, customer care interactions and learning to use a product itself. Without a doubt, every one of these standalone touchpoints are important.
That’s why customer experience and support professionals hyper-focus on customer satisfaction score (CSAT). CSAT measures how well your company is delivering against your customers’ expectations in these independent moments.
In this post, we will dive into everything you have ever wanted to know about your scores. Jump to specific sections or scroll down to read the entire post.
CSAT scores are the most popular and straightforward way to measure customer satisfaction. The metric measures sentiment towards your product, service or a specific interaction.
Companies often take a pulse after key milestones in the customer lifecycle. For example, after a first purchase, prior to the renewal or following customer support interactions.
It’s important to realize that CSAT differs from Net Promoter Score (NPS), another popular metric. NPS measures loyalty, the probability that someone will buy again and recommend your company to other people.
So what exactly drives satisfaction?
In short, people are satisfied when their expectations are met. Like many things, expectations are fluid and change based on situational context and stage of the customer journey. For example, if you spring for a first-class ticket on a flight, you are going to expect more personal and proactive service from flight attendants. On the other hand, when you purchase a basic economy seat, you expect attendants to simply ask what you need during their food and drink service. In Economy airline travel, there’s no expectation for a glass of champagne before takeoff.
Circumstances change expectations. When measuring CSAT, it’s important to understand the different circumstances of your individual customers to glean actionable insights.
Why Is CSAT Score Important?
Customer retention is fundamental to a thriving business.
This is because it’s cheaper to keep your current customers than attract new ones. Studies report that 70% of companies say this is true.
CSAT can provide insight into where and when your company is at risk of losing customers. In the same vein, it can uncover opportunities to optimize experiences. If used regularly, it gives businesses a pulse for how your company is performing and helps you understand your customer. Of course, you need to look at and measure the entire journey, not solely flashpoints along the way. It can help you realize where your processes are working and where you need to make changes.
Think about this with customer service. In the last year, 78% of U.S. consumers have stopped doing business with at least 1 company or scrapped a planned purchase based on poor customer service. Moreover, 31% reported doing this multiple times. That is to say, only one instance of poor support can lead to immediate customer attrition. And so, understanding what makes people unsatisfied with customer support can identify a few things. Firstly, where more training needs to be done. Secondly, where there’s an opportunity to be proactive. And lastly, where processes need to change.
Impact of Low Customer Satisfaction: Almost half of the consumers have stopped doing business with at least one company in 2019 due to poor customer service.
In essence, a person’s short-term happiness or unhappiness with your company following their customer interaction is indicative of future spend and lifetime value.
Learn how to automatically resolve customer service inquiries at the industry’s highest rate over messaging, chat, email, and voice with our helpdesk AI solutions.
How Do You Calculate And Measure CSAT Scores?
CSAT is often measured by completing customer satisfaction surveys. Surveys are completed through a brief, single question form asking how a customer feels following their most recent experience. This can be done through an email, chat, phone follow-up question, or through traditional paper or postcard satisfaction surveys. It’s typically immediately following an interaction when the experience is top-of-mind.
Customer satisfaction survey questions often look like the one we offer below:
How satisfied are you with your recent purchase/support interaction/service?
Extremely Satisfied
Somewhat Satisfied
Satisfied
Not Satisfied
Very Dissatisfied
On a scale of 1-5, how satisfied are you with your recent purchase/support interaction/service?
<Very Unsatisfied> 1 2 3 4 5 <Very Satisfied>
To calculate your CSAT, take the number of positive responses (i.e. Extremely and Somewhat Satisfied) and divide by the total number of responses. Then, multiply by 100.
For example, say you gather data from 200 customers. If 160 customers scored satisfaction a 4 or a 5, here’s what you would do.
160/200=0.8 (80%)
In this example, the company’s score is 80%.
Additionally, companies will often leave a place for people to add specifics as to why they scored the way they did. This unconstrained feedback in particular can provide invaluable insight into things that can be improved.
How Do You Use Your CSAT Score
For customers who reported being unsatisfied or dissatisfied, carefully review their entire interaction. You’ll first want to identify what happened. Next, see if there was an opportunity where your company could have been proactive. Finally, determine what information could have provided a more pleasant experience. For example, did someone reach out with questions while setting up your product? Or, is there additional information you could have preemptively provided to ensure a smooth, successful set-up?
For dissatisfied customers, identify ways to court them to try and maintain a positive relationship with them. Can you offer free shipping on their next order if this one was delivered late?
Equally important, you’ll also want to learn from your satisfied customers. What are the key components that led to expectations being met? Did you offer the right tools at the right time? Did you quickly resolve an issue within 2 minutes on social media?
In summary, don’t just look at your percentage. Make sure you dissect the outliers to learn how to exceed customer expectations in the future.
How to improve my CSAT Score?
Customer service is one of the micro-moments that dictate customer loyalty and future spend. As mentioned earlier, one instance of poor service is enough to deter a major portion of your customers to move their business elsewhere. As customer service continues to establish its foothold as a business driver, companies need to meet expectations for customer support. Satisfaction, as you may remember, comes from expectations being met.
So what do people expect today? In short, quick, convenient resolutions on their channels of choice. For example, in our recent study, we found that:
Nearly Half: Expect not to wait for a resolution
47%: Expect convenience
61%: Expect quick resolution
While that may sound simple, companies are finding it harder to meet these quick-rising demands. And even more, scale personal interactions across customer support email, chat, social and voice channels. In fact, more than 50% of U.S. consumers have not seen any improvement in customer service over the last 12 months.
Another way to improve the results of your surveys? Work on improving the response rates of your surveys. According to research done in 2015 by the American Customer Satisfaction Index, “response rates for paper-based surveys were around 10% and the response rates for e-surveys (web, wap and e-mail) were averaging between 5% and 15% – which can only provide a straw poll of the customers’ opinions.”4
Improve CSAT Score with AI
Bringing AI customer service into the workforce enables companies to automatically resolve over 50% of incoming tickets immediately, within seconds, according to our customers. These repeatable, everyday tickets are not routed to human agents. Instead, agents focus exclusively on more complex and subjective issues. All tickets – the simple and complex – are resolved faster. Logically, bringing speed to support will increase CSAT.
One of our clients, the Canadian airline WestJet, has seen an increase of 24% with its virtual agent Juliet resolving issues immediately on Facebook Messenger. Juliet is helping people understand how they can fly with skis, how much it costs for a checked bag and flight status within seconds. Customers, all-too-often packing last-minute or stuck in traffic to the airport, are thrilled to get their pressing questions answered without a long hold time or desperate website search.
Comparing CSAT to other popular consumer grading measures
CSAT differs from other popular customer service metrics that are used by companies. When companies use all of these metrics together, they will have a very rich understanding of how your customer support organization is functioning and delivering against customer expectations.
Click here for more information on customer support.
CSAT vs. NPS
Net Promoter Score, or NPS, is used as a way to capture customer feedback. It measures loyalty and the probability that someone will recommend your company to other people.
NPS looks at overall, long-term brand perception, whereas CSAT measures short-term happiness with a specific incident. NPS can be an indicator of growth potential for a company because peer recommendations carry so much weight in our society that is social media-obsessed. Nielsen actually found that “more than eight-in-10 global respondents (83%) say they completely or somewhat trust the recommendations of friends and family.1”
On NPS surveys, customers are asked a simple question: On a scale of 1-10, how likely are you to recommend [company] to a friend/colleague? Your customers will fall into one of these categories:
Promoters are people who rate your company with a score of 9 or 10. Promoters are your enthusiasts and loyalists.
Advice for how to treat promoters:
Keep these customers happy as they are the ones that will be recommending your brand to their friends and family.
Give them referral codes or links that they can send to their friends to let them earn points or discounts for the new business that they bring in.
If it makes sense, involve promoters in product research and selection, for instance, a meal kit company could ask them which recipes they’d like to see on the menu.
Passive customers are people who rate your company a 7 or 8.
Advice for how to treat passive customers:
Push passive customers to promoter status by asking for a feedback survey on what could be improved and acting on what they tell you.
Like promoters, companies can also provide passive customers incentives in the form of referral codes or links that they can send to their friends and family to encourage recommendations and endorsements.
Detractors are customers who rate your company with a score of 0-6.
Advice for how to treat detractors:
Analyze your interactions with detractors to see if you can identify why they are unsatisfied.
Are there any trends that you can identify? If there are particular instances that occurred throughout someone’s life cycle, say consistently late deliveries, technical issues or wrong items delivered? If so, address the issues, apologize and communicate how the company is making changes so issues don’t happen again.
It’s important to remember that you’re not going to have a fan in every customer, so you also need to realize when you’re not going to change someone’s mind and walk away.
CSAT vs. CES
Customer Effort Score, or CES, measures how much effort a customer puts into completing a task, including resolving a support ticket, making a return, etc. CES measures a specific instance.
Measuring CES is important because customers expect effortless, convenient experiences. Customers are more likely to churn if the experience is difficult. In fact, research has shown that “96% of customers with a high-effort service interaction become more disloyal compared to just 9% who have a low-effort experience.2”
You can reduce effort in a variety of ways. Such as minimizing time spent to get a resolution, the number of times a person has to reach out or total back-and-forth interactions.
To determine CES, you’ll ask your customers, On a scale from “Very Easy” to “Very Difficult”, how was your experience? If you find that you have a low CES score, identify how to remove obstacles and friction from the interaction.
CSAT vs. DSAT
The exact opposite of CSAT is Customer dissatisfaction (DSAT). DSAT measures whether your customers are dissatisfied with an experience. Companies often don’t think about DSAT, but it’s important. This is because the damage a dissatisfied customer could have goes well beyond the individual not ever purchasing from you again. People talk to their friends and post on their social media channels about poor experiences. In fact, Americans are telling an average of 15 people about poor service3.
To track DSAT, you’ll analyze the data from the same question in which you ask how satisfied a person is with experience. On a scale from 1-10, your dissatisfied customers are the ones who responded 1-5. Once you identify your dissatisfied customers, you can analyze their entire experience to identify what went wrong and address the issues.
Don’t waste your resources by giving detractors referral codes or links. Because at this point in time, they are not going to recommend your business.
CSAT Score Benchmarks for 2020
Companies are putting more focus on the customer experience as a part of the usual market research. Benchmarking CSAT scores against industry averages is a good way to see if your efforts are enough. But how do you know what a good score is?
Benchmarks depend on many factors, primarily your industry. Some industries have notoriously low scores due to the nature of their business. For instance, airlines have a lot of aspects of their service outside of their control, such as weather events and other delays. Even longer lines at TSA security checks can negatively impact a person’s perception of flight experience. The airline, though, had nothing to do with security delays.
The same holds true for your home internet and cable provider. Service might become interrupted by things outside of the company’s control (for instance weather or downed utility lines). In short, customers don’t always look at the full picture, but rather zero in on the company that they are paying.
The American Customer Satisfaction Index has outlined benchmarks by industry. It also looks at how they change year-over-year. According to the organization, breweries have the highest CSAT at 84%. On the other hand, internet service providers and subscription television services have the lowest at 62%.
A few other industry CSAT score benchmarks include:
Personal care and cleaning products: 83%
eCommerce: 81%
Banks: 80%
Internet Travel Services: 79%
Supermarkets: 78%
Apparel: 77%
Hotels: 75%
Airlines: 74%
To summarize, keeping track of how your score is performing against industry benchmarks is something you should be closely tracking.
While this is not the only way to measure your customer service performance, it does offer valuable insight into an important dimension of your customer support. Before you can improve your support organization, however, you need to know your baseline and set a goal for the next 3 months, 6 months, etc. Create an actionable plan on how you’re going to reach these goals and improve CSAT, such as reducing resolution time, implementing more self-service options, offering proactive support and being available on more channels.
CSAT is a valuable tool. And we can boost it an average of 20% in 6 months. Interested? Let’s chat.
In this post, we’re covering everything you need to know about customer satisfaction (CSAT) surveys, including:
Customer satisfaction surveys defined
Are these surveys still relevant?
Types of surveys
Customer satisfaction survey templates and examples
For your business to survive and thrive, measuring customer satisfaction is key. You need to take frequent pulses on how your customers feel about your brand, products, services and interactions to identify pain points and benchmark your performance over time. Customer satisfaction surveys are an incredible tool that marketing, support and product teams can leverage to understand how well they perform in their customers’ eyes.
Let’s dive in.
What is a Customer Satisfaction Survey?
Customer satisfaction surveys are questionnaires that measure customer sentiment towards a product, service or a specific micro-level interaction like a customer service interaction or online shopping event. CSAT surveys can be time-based (i.e., sent one day after purchase or three months post-purchase) or event-based (i.e., at the end of a free trial or onboarding process).
Are these types of surveys still relevant?
To grow your business, you need to know how you’re performing against expectations and uncover customer pain points and points of friction. CSAT surveys provide incredible insights into how a customer perceives your brand and products and can indicate future loyalty and spend.
CSAT surveys are the most direct way to understand if you’re meeting customer expectations. Today’s customer journey is complicated and loyalty is fragile. One poor experience can be enough to drive even your most loyal customers away.
These surveys enable brands to flag where things go wrong in the customer journey. They allow you to improve your product, services and operations to retain customers.
Without leveraging CSAT surveys, you’re operating in the dark. Getting feedback directly from the customers you need to impress and asking them directly for things that can be improved is essential to be a company that competes on customer experience (CX).
The benefits don’t stop there, though. Surveys like this also make customers feel appreciated and listened to. It can also help you identify champions who could be asked (or incentivized) to post reviews or refer friends.
To download a copy of our 2021 Customer Service Benchmark report, visit here.
Types of customer satisfaction survey questions
Generally, CSAT surveys include between 6-8 questions. There are a few common types of survey questions, including closed-ended questions, which see a person select a response from predefined answers, and open-ended questions, which see a person respond in their own words.
There are benefits to both types of questions. Closed-ended questions provide clean data that can be used for rich analysis and benchmarking. Open-ended questions provide qualitative data, reveal new insights and alert an organization to problems or opportunities they had not yet thought of.
In your surveys, it’s important to mix question types to encourage participation and minimize perceived effort.
Here are the different types of questions you can use in your surveys:
Rating scale (or ordinal) questions: Rating scale questions ask the customer how they feel about a product, service or interaction by rating it on a numbered scale (i.e., 1-5). If you use a rating scale question, add context to the numbers (i.e., 1 is poor and 5 is excellent). Here’s an example of a rating scale question:
Binary questions: Binary questions limit responses to two inputs, such as yes/no or thumbs up / thumbs down. Binary questions can eliminate any ambiguity present in scale questions as everyone can perceive things slightly differently. One person’s 5 response could be another person’s 4. Here’s an example of a binary survey question:
Likert scale questions: These questions are also on a scale but measure extreme views on a 5 to 7-point scale. The medium point represents neutrality, with the lowest number (1) representing one extreme and the highest number (5) representing the other extreme. Here’s an example of a Likert scale question:
Nominal questions: When there are limited available responses, nominal questions work well. These are multiple-choice questions in which the user selects one option from a predefined set of answers. Unless there is an “All of the Above” option, answers don’t overlap. Here’s an example of a nominal survey question:
Open-ended questions: These questions allow a person to write feedback in their own words. While the insights that can be gleaned from open-ended questions are incredible, customers perceive them as requiring more effort. Limit open-ended questions to one or two in your survey. Here’s an example of an open-ended survey question:
Here are the top 17 customer satisfaction survey templates and examples for 2021
These surveys can measure feedback on customer service interactions, product and services, brand experience, as well as customer effort (CES) and net performer score (NPS).
Customer Service Questions
Overall, how satisfied were you with your interaction today?
Very Dissatisfied
Dissatisfied
Neutral
Satisfied
Very Satisfied
Did we fully resolve your issue?
Yes
No
On a scale of 1-5, did we make you feel heard and appreciated?
1 – Not at all
2 – Somewhat
3 – Neutral
4 – Yes
5 – Absolutely, Yes
How did you feel today during our interaction? Select all that apply.
Listened to
Appreciated
Frustrated
Annoyed
Other ____
How easy was it to get your issue resolved today? (Customer Effort Score question)
😡 – Extremely Difficult
🙁 – Difficult
😐 – Average
🙂 – Easy
🤩 – Very Easy
Which of the following would you describe the support you received today? Select all that apply.
Fast
Personal
Empathetic
Convenient
Effortless
Incomplete
Difficult
Other_____
Product Questions
Is this the first time you’ve used our product/service?
Yes
No
How well does our product meet your needs?
1- It does not meet my needs in any way
2- It meets my needs, but not in every way I expect
3 – Neutral
4 – It meets my needs
5 – It exceeds my expectations
How has your experience been with [product/service]?
Very Unenjoyable
Unenjoyable
Neutral
Enjoyable
Very Enjoyable
What made you ultimately choose this [product/service] over others?
Is there anything that you would change about our product/service?
Which features are the most valuable?
How satisfied are you with the quality of our product?
Very Dissatisfied
Dissatisfied
Neutral
Satisfied
Very Satisfied
Experience Questions
How would you rate the onboarding process?
😡 – Extremely Difficult
🙁 – Difficult
😐 – Average
🙂 – Easy
🤩 – Very Easy
What could we have improved with our online shopping experience?
What could we have done differently?
NPS Questions
How likely are you to recommend this [product/service] to your friends and colleagues?
Very Unlikely [1] [2] [3] [4] [5] Very Likely
Best Practices for Customer Satisfaction Surveys
When you’re developing CSAT surveys, there are a few best practices to keep in mind.
Be very clear in your messaging: Keep questions concise. Remove ambiguity and avoid using jargon.
Use a mix of open-ended and closed-ended questions: Start your survey with a low-effort, closed-ended question that will more likely entice the person and get them engaged.
Incorporate open-ended options into closed-ended questions: You don’t want an engaged customer to stop taking the survey because they don’t see a relevant answer in a nominal question. You can get around this by adding an “Other” option with a text box for a person to explain in more detail. You can also follow up on scale questions with a prompt to go into more detail. For instance, after asking: “On a scale of 1-5, how satisfied are you with your experience today?” you can follow up with people who ranked on the low end a follow-up question: “What could we have done better?”
Understand your goals for the survey: Are you benchmarking your customer experience over time? Are you looking for specific ways to enhance your product or service? Design your survey to give you the data that will be most beneficial for your team.
A/B Test: You’re probably not going to launch the most effective survey at the first shot. A/B test your messaging, timing of when a survey is sent, and delivery method in order to get the most customers engaged.
Final thoughts: Why every CX leader should consider using CS surveys
CS surveys provide invaluable feedback on how your customers perceive your products, services, support and brand. Triggering CSAT surveys at key points along the customer journey is essential for companies to compete and grow their business today. Loyalty is tied closer than ever to CX. Without leveraging CSAT surveys, you will be operating in a vacuum, unaware of friction and pain points that can be detrimental to your business. These surveys enable gathering feedback from your customer base–these will improve levels of satisfaction, customer retention, and create more satisfied customers.
To learn more about improving the customer experience, visit:
To download a copy of the full Customer Service Benchmark report, visit here.
Overview of our 2020 Customer Service Benchmark Report
Results of our inaugural Customer Service Benchmark Report
Findings reveal how the top retail and consumer goods companies deliver against customer service KPIs: availability, responsiveness, resolution time and measuring customer happiness
Analysis of how users of the most popular agent desk platforms perform against industry averages
Customer Service Benchmark
We’re excited to announce the launch of our inaugural Customer Service Benchmark Report. In this edition, we dig deep into the email customer support of retail and consumer goods companies. With top customer service now a differentiator and business driver, the state of email customer support is surprising. Some support teams wowed us with quick resolutions and going above and beyond to create satisfied customers. On average, however, retail and consumer goods companies have a long way to go.
Key Findings of the Customer Service Benchmark Report
Zendesk users are 2X faster than other agent desk software to send a response
Salesforce users outperformed other agent desk software by 121%
Only 56% of companies have an easy-to-access email address
70% of companies that have an email address never respond
Customers are 8X more likely to get a response to an email on a weekday than a weekend
The average response time to email requests is 36 hours
Only 1 in 5 retailers respond to an email within 24 hours
Fortune 500 companies respond 1.4x slower to respond to emails than Non-Fortune 500 companies
Only 14% of companies measure CSAT
When given the chance to go above and beyond and fulfill a special request, 83% of companies failed to deliver
To download a copy of the full report, visit here.
Our Customer Service Benchmark Report Says The Agent Desk Matters: Zendesk users provide better-than-average support
Our report found that Zendesk users are 2X faster than other agent desk software to send a response. Salesforce users also outperformed by 121%.
In addition to better response times, Zendesk are 2X more likely to send a CSAT survey to gauge customer satisfaction with an interaction.
Email is preferred but is not often a choice
According to Forrester Research, “54% of customers used email for customer service last year, making it the most used digital channel for customer service.”
This is true even in the wake of companies de-prioritizing email as messaging platforms. Live chat and voice assistants like Amazon’s Alexa and Google Assistant emerged as ways to engage in 1:1 conversations and resolve issues. According to our consumer research, it’s because email customer support is more convenient. Our research also revealed it is preferred as it’s readily available across all of our devices.
Only 56% of companies have an easy-to-access, readily available email address. Nearly 64% of companies offered a Web form. 37% of companies offered both an email address and a Web form. Surprisingly, 17% of companies did not have either an email address or a web form.
There is a massive divide between response times expectations and reality
Only 20% of companies respond within 24 hours. Nearly 1 in 5 companies do not respond to emails within 48 hours. The average response time is 36 hours. This is 36X slower than customer expectations, as 31% of customers expect responses in one hour or less1.
Of the companies that respond to emails, nearly 56% respond within 12 hours and 46% within 6 hours. On average, eCommerce companies are the quickest to respond, within 11.5 hours on average. With an average response time of 62 hours, personal care and cosmetics companies are the slowest to respond.
In an interesting twist, Fortune 500 companies respond to customer emails 1.5X slower than Non-Fortune 500 companies. The average handle time for Fortune 500 companies was 47 hours to respond, while non-Fortune 500 companies responded, on average, in 34 hours.
Emails are ignored 8X MORE on the weekend
We were shocked to learn that nearly 3 in 4 companies that publish an email address ignore customer service emails.
We found discrepancies among different industry sectors. Home Furnishings is almost twice as likely to respond than other retail companies, responding 55% of the time. They are followed by Apparel (48%), Fitness, Health & Wellness (47%) and Toy & Entertainment (43%) companies. The worst offenders were Food and Beverage Companies (responding 38% of the time) and Consumer Electronics & Tech companies (only 18% of the time).
Companies respond more frequently during the week. Customers are 8X more likely to get a response on a weekday than a weekend.
To download a copy of the Customer Service Benchmark report, visit here.
Support Best Practices: Personalization and CSAT Results
Studies of customer service metrics have shown that 80% of customers are more likely to purchase a product or service from a brand that provides personalized experiences2. When a customer hits send, though, only 20% will receive a personalized response.
CSAT is one of the most important customer service KPIs. It’s how companies can ensure customers are happy. Only 14% of companies sent a customer satisfaction survey following a resolution.
Customer-obsession is alive and well
We often hear stories about agents going truly above and beyond to delight customers. We wanted to see if agents were empowered to fulfill a simple request, so we asked an agent to send a birthday message to a five-year-old whose birthday party was canceled. 1 in 5 companies go above and beyond to provide great customer service, much to our delight. Some agents went so far as to write poems and attach images and GIFs. Seeing agents empowered to do a small gesture was meaningful and one way to spur long-term loyalty and brand advocacy (the kind that pays off in revenue.
Critical Acclaim for our Customer Service Benchmark Report
The results of this Customer Service Benchmark study have been fact-checked and featured by one of the top retail writers on Forbes.
Retailers and consumer goods companies have a lot of work to do when it comes to closing the gap between customer expectations and the reality of email support. Get your copy of our Customer Service Benchmark Report here.
For more information on customer service, visit:
The 7 Best Ecommerce Chatbot Solutions and What Makes Ecommerce Bots Succeed
Automated Support – 10 Ways Customer Service Automation Works Today (Updated March 2021)
Customer happiness: it’s something every retailer strives to cultivate. Traditionally done through birthday messages with coupons, free gifts with purchase or quick-fire sales, making business decisions with a goal to increase CSAT is at the core of every retailer’s strategy.
While all of these efforts are still very much loved by customers, retail CSAT is increasingly driven by customer service.
Your customers today have heightened expectations for customer support. More than ever, customer support directly impacts loyalty and dictates where people spend their money. Consider this: 59% of consumers have higher expectations for customer service than they did just a 1 year ago and 61% have switched brands due to poor customer service. Customer service is now a way to differentiate.
Retailers must think about meeting customer demands for personal, immediate and convenient customer service to increase retail CSAT. To build brand love through customer support, focus on these core areas.
Exploring a new CRM solution? Learn more about two of the industry leaders in our Intercom vs. Zendesk review.
9 Core Areas Retailers Should Focus On To Increase CSAT
Decrease First Response Time (FRT)
Get back to your customers right away. Respond as soon as possible, even if you are simply acknowledging a person’s issue while you work behind the scenes to resolve it.
How quickly you get back to someone impacts whether a person believes your company cares and that their issue is important to you. Leverage AI with your existing e-commerce software as the first line of defense to respond in less than one second – whether it’s offering a full resolution to a question (i.e. Your order will arrive by 8 pm), gathering additional information from the customer (i.e. what’s the reason for your return?) or letting them know when someone will be in touch (i.e. Our design expert will get back to you at 8 am).
Feeling heard and knowing that your issue has been acknowledged goes a long way.
Reduce Average Handle Rate
Streamlining the entire process of resolving an issue centers on reducing the amount of effort your customers have to put in. The burden needs to be with the company, not the customer. Tailor the interaction to the channel to create a sense of effortlessness. For instance, if you’re providing support via chat, be as brief as possible and ensure the interaction has been adapted to a messaging interface (i.e. less formal, shorter messages). Even if there are more messages exchanged, don’t make your customers read long-form text in a small window. On customer support email, however, streamlining the resolution is about limiting the number of messages exchanged. If something is not resolved immediately, strive to ask for all the information needed in one shot.
Be Available Cross-Channel
Today’s consumers demand you respond to them wherever they hang out, and the number of channels is increasing rapidly. If you only support one/two channels you are behind. Your customer support organization needs to scale across email, chat, messaging and voice platforms. Read more about the importance of cross-channel support here.
In the age of Amazon Prime and larger companies rushing to maintain market share, free shipping has become a near-universal expectation. In addition to offering complimentary shipping, enable your customers to get real-time updates on their orders whenever – and wherever – they want.
Ensure the AI Retail Bot Understands What Your Customers Are Saying
As brands start to turn to virtual agents to scale customer service practices, it’s critical that AI enables people to engage in natural conversation. People don’t want to be confined to keywords, they want to ask a question and describe a situation in free text.
However, if an AI agent gets confused easily, customer frustration skyrockets. Leverage Natural Language Understanding (NLU) to decrease the likelihood your customers get a message like: “I don’t understand. Please ask in another way.” or “Please select your issue from the list below.” With an advanced NLU, your AI will be able to understand a greater variety of slang, short-form, and other utterances to accurately classify your customers’ intent and therefore, reduce frustration.
For example, someone can ask “where’s my order” in hundreds of ways – Is my package here? Where is my shirt? Is UPS coming to my house today? Virtual agents need to be able to understand the intent behind all of these is the same, just like a human would.
Offer Seamless Returns
The number of returns is surging along with the boom in eCommerce purchases. Ensure you offer a frictionless, transparent returns process and personalize the experience as much as possible. In a simple example, if a new customer is reporting that a product showed up missing pieces, acknowledge that you hate that this is their first experience with your brand, that this sort of does not happen regularly and provide a coupon for a future purchase.
Proactively Solve Potential Issues
As soon as you know about a potential issue (i.e. a package is going to be delayed), let your customers know. By telling them about an issue before they even realize it exists will make them feel like you have their back. Identify various ways to offer proactive care along the entire customer journey, for instance anticipating when a product needs maintenance or a replacement part to ensure it works well. This all feeds into a feeling that the brand has their best interests in heart, and thus, increases their affinity for a brand.
Always Offer A Human “Out”
If you are leveraging AI customer service to assist customers, make sure they can always be escalated to a human agent. Some customers will always prefer interacting with a human, and some situations will always be better suited for a human. Let your customers know how they get transferred to a human agent whether that’s a menu option in a chat, a button in an email signature or through a keyword.
Check-In
Ask your customers how you’re doing solving their issues and what can be improved. Follow up with customers to gather honest feedback, and take their feedback to heart.
Retail CSAT is tied more to customer service than ever before. In order to build brand love in an increasingly competitive retail ecosystem, retailers must meet consumer demands for personal, immediate and convenient support – on an increasing number of channels. Bringing AI into the workforce enables companies to significantly boost CSAT significantly – in one example, our customers saw an increase in over 24% in a few short months.
How AI-powered automation can deliver on a customer support organization’s most critical KPIs
It’s not easy being held accountable to customer support KPIs these days.
Agents are pulled in a million different directions; forced to jump between various systems to answer a single question while interacting with often frustrated customers. They’re having to do so on an increasing number of channels as well: email, chat, social, mobile and so on. It’s no wonder that the turnover rate in customer support is among the highest of any profession. It doesn’t have to be this way.
Meeting modern customer expectations is also getting harder to do; they expect quick, convenient high-quality resolutions on their terms. We live in an on-demand, personal world. Leveraging AI to automate support is a means to get there.
There has been a lot of talk on how AI customer support can be used within a support organization for years, with many organizations wondering how much of it is hype…. What impact can it really have? Will it really make a difference in what’s important to your organization and customers?
When deployed correctly, AI can have an immediate and immense impact on customer service by automating responses to expensive, repeatable tickets (usually about 50% of all tickets) and uplifting agents to do their work more efficiently. The customer support KPIs that AI can improve include:
First Response Time (FRT): Customers do not like to wait. It’s pretty astounding how long it takes companies to respond; the average response time is 36 hours over email, while 75% of customers expect it within 5 minutes. Leveraging AI to automate customer service responses, whether it’s providing an instantaneous resolution or acknowledging the customer’s needs and collecting necessary information before a human gets involved lets the customer know that they are being heard. The automation effect is noticeable from day 1: our customer WestJet gets back to customers in less than 1 second.
Average handle time (AHT): Getting back to your customers quickly is one thing, but how long it takes for you to actually resolve an issue is even more important. AI-powered automation helps in a few ways:
Automating resolutions to repeatable issues: Leverage AI to respond instantaneously to the high-volume, simple queries like order status and inventory checks. Make sure your AI has the authority to resolve issues by connecting with core business systems. Set rules to minimize business risks like enabling the automation of refunds under a certain dollar amount or free upgrades based on loyalty status.
Empowering human agents to work faster: Use AI to gather data from any customer, such as account or order number, and pull information from other business systems like your CMS and OMS. The AI can package up all relevant data to pass along to an agent who can quickly review, make a decision and communicate with the customer.
Consistent Resolutions: Leveraging AI in customer support also promises to provide standardized resolutions. There is no human bias, subjectivity or bad days. A bot will review the facts and based on how it has been trained, act consistently every time. If there are any questions or uncertainties, a human agent will always be looped in.
Customer Satisfaction Score (CSAT): According to Forrester, 73% of Americans say that valuing their time is the most important thing a company can do to provide them with good customer service. In our own consumer research, we found that quality and consistency in a company’s service and experience is key. As discussed in the points above, automation delivers on all of these.
Employee Satisfaction Score (ESAT):Automation allows you to give your agents back their time: the time spent doing mundane tasks is now spent on more fulfilling and high-impact work. Agents no longer have to dig deep to find specific information needed to make a decision from various systems. AI gathers it for them before they even get involved. Agents are empowered with the information to make a quality decision quickly.
Cost Savings: The cost benefits of automation fall into two primary buckets:
Deflection from human agents: By automating repeatable tickets, you will see a significant deflection from your call centers of tickets that are never even created.
Less agent turnover: With happier and more fulfilled agents, turnover will decrease resulting in savings tied to hiring and training new employees.
We’ve worked directly with our partners to learn the pain points companies are facing to design an automated solution that is designed to create an immediate, measurable impact. Are you ready to have a customer support organization that delivers on what customers and agents need? Let’s chat.
For more information on customer support, click here.
Forrester’s Ian Jacobs recently joined Netomi’s Founder & CEO, Puneet Mehta, as a featured guest in a webinar where they unveiled how world-class companies can create real-world AI in customer service. No more buzz or hype. It’s all actionable strategies that can be used today to deploy AI that serves both your customers and employees.
Watch this video to learn Forrester’s perspective on how AI can be effective within customer service and recommendations on how you can start achieving efficiency today. Netomi’s Puneet Mehta revealed how AI allows you to create unique customer experiences in this video and Ian and Puneet together outline a Customer Service AI Roadmap here.
Puneet and Ian outlined 5 strategies for winning AI customer service:
AI Strategies, Part #1 – Automate the right support issues with AI [Watch Here]
Watch the video to learn how to:
Identify the right problems to delegate to AI
Automate issue resolution while delivering to your brand promise
Maintain human intelligence and use AI to empower agents
AI Strategies, Part #2 – Improve agent performance with AI [Watch Here]
Watch the video to learn:
How to use AI as a workforce multiplier, making work less stressful for agents
How to leverage AI to handle the prep work, so agents can focus on resolution
Different human+AI collaboration approaches and what works for your company
Ways to let AI triage and route issues to the right human agent for faster resolution
AI Strategies, Part #3 – Achieve high CSAT with AI [Watch Here]
Watch the video to learn how to:
Build an AI so you can avoid a “50 First Dates” moment with your valued customers
Design AI experiences that work for your customers—respectful, friendly, accurate
Leverage AI the right way: speedy resolution at times, and more empathetic, deeper connections for others
AI Strategy, Part #4 – Measure AI as if it were your employee [Watch Here]
Watch the video to learn how to:
The shift from technology KPIs to measuring the business impact of AI
Evaluate AI’s ability to resolve, learn, work with others, and be proactive
Go beyond surveys and take a holistic approach when analyzing CSAT
AI Strategy, Part #5 – The new approach for customer service [Watch Here]
Watch the video to learn about:
Real-life scenarios where the predictive and proactive resolution will soon be a reality
How AI can help you identify signals to anticipate customer needs
How you can reduce support tickets by resolving issues before customers reach out
This was a captivating discussion on the current state of AI in customer service. If you’re thinking about modernizing your customer service operation without disrupting current agent processes, don’t miss these highlights!
For more information on customer service, check out everything you need to know about the omnichannel experience for customers in 2022.
