What is deflection rate?
Deflection rate measures the percentage of customer enquiries an AI assistant can resolve without human intervention. It deflects routine queries away from your teams, so they have more time to work on higher-value tasks, which can significantly increase efficiency, boost team morale and improve customer satisfaction.
Increasing your deflection rate can help improve other customer service metrics, like Net Promoter Score (NPS), goal completion rate and average handling time, as well as reduce your cost per call and escalation rate, since customers are getting immediate, accurate, helpful responses to their queries from an AI-powered assistant 24 hours a day in 130+ languages with real time engagement that’s both prompt and convenient.
How do you calculate your deflection rate?
To calculate the deflection rate, divide the number of enquiries resolved through self-service tools like AI assistants (R) by the total number of enquiries received (E), and multiply by 100 to get a percentage.
Deflection rate formula
R ÷ E x 100 = deflection rate %
For example, 98 queries out of 100 in total resolved entirely using a next-gen AI assistant:
98 ÷ 100 x 100 = 98% deflection rate
Calculation frequency
You can calculate your deflection rate monthly, weekly or even daily. It depends on your industry and approach, if your business is seasonal or cyclical, if you have product or service releases that invite a lot of customer questions, or you’re making changes to your organisation ― you decide. The most important thing is to calculate your deflection rate consistently over time using the time span that gives you the most valuable insights into the effectiveness of using self-service options and how this impacts your business.
By tracking and monitoring the deflection rate regularly, your teams can gauge the performance of your AI assistant accurately and so identify areas where you can improve it. Comprehensive AI-driven data can transform your customer insights and help make sure you’re providing the best experience possible.
Why does the deflection rate matter?
Deflection rate directly impacts your operational efficiency, how you allocate your resources, and your customer satisfaction score. That’s because using AI automation leads to a faster first response time, which is good news for customers, but deflecting routine enquiries is also good for your human agents.
By improving the deflection rate, you open up many opportunities for your support teams to enjoy non-stressful interactions with customers, and when an AI assistant is handling the monotonous, repetitive queries, your teams are more available to focus on the sensitive, challenging or unusual enquiries that need their skills and experience to resolve them before the customer becomes unhappy or irate.
The more your AI assistant learns about your organisation (directly through your customers via the topics they most want to talk about), the more it will be able to do for you. Not just sending information, but through integration with all your go-to business systems, like HubSpot and Jira, it can carry out tasks and transactions for you too, dealing with enquiries end-to-end, further increasing your deflection rate.
Reducing customer service costs
With the average cost per call for contact centres in the UK sitting at £6.26, you’ll immediately reduce your operational costs when you increase your deflection rate, since the cost of an AI-powered response is mere pence (you can estimate your saving upfront using our handy calculator).
London’s Barking & Dagenham Council saved £48,000 in their first six months after introducing an AI assistant to handle missed bin enquiries, and leisure providers Mytime Active saved the cost of having to hire two extra agents to deal with routine enquiries.
"The ability to deliver such high levels of accuracy without needing further interaction from the contact centre has helped us reduce our wait times considerably and know that queries that come through will be things that need direct answers from the contact centre team. Without [our AI assistant] our call volumes would have continued at an exceptionally high level and we are confident the system has saved us the equivalent of 2 additional heads due to us being open 7 days a week."
John Branigan
Director of IT & Transformation at Mytime Active
What is a good deflection rate benchmark?
In the past, a good deflection rate could have been as low as 20% and peak at 50%, but a new generation of AI assistants with deeply complex features like natural language processing (NLP) and large language model (LLM) capability has changed this for good and our AI assistants average a 96% success rate.
A 96% success rate means the AI assistant has understood nearly all of the requests from your customers and been able to resolve their issues without any input from your contact team, simply deflecting them away. With more training, AI assistants can get even higher rates, like Mytime Active currently at 97% and both Legal & General Insurance and Barking & Dagenham Council at 98%.
The 3 do’s and don’ts to consider
To find a level of success as high as 96%, there are three important things to note in the age of AI automation:
1) DON’T overload your AI assistant
You can launch an advanced AI assistant in less than ten minutes and it can go live with as little as three main flows (flows are what we call a question and answer set). You don’t need to train it on everything you think your customers will want to know because as soon as your AI assistant is live and chatting with real customers, it immediately starts to learn this and deflect those queries away. Simply set it live and let it learn.
2) DON’T aim for a 100% success rate
There will always be questions asked of your AI assistant that aren’t relevant to what you do or are simply better off handled by one of your team in person over live chat or the phone, so 100% isn’t a necessary or realistic goal for your success rate. You’ll also need to account for these non-queries in your deflection rate, since they’re not enquiries you’ll ever want to train your AI assistant to answer or deflect.
3) DO keep scaling your AI assistant (and never stop)
Your deflection rate should continue to go up over time and you can help this along by using integration to make your AI assistant smarter. Connect up your AI assistant with all your favourite tools, like Jira, HubSpot or Zapier, and it’ll be able to deflect more queries for you by completing tasks and transactions on your behalf, becoming more and more valuable to your teams every day.
“We chose EBI.AI as our provider because they promised a hassle-free process to deploy an AI assistant on their platform, and they absolutely delivered. Their implementation was seamless, exceeding our expectations. We noticed an instant reduction in email enquiries, thanks to their solution. What surprised us even more was the high success rate from the start, and it's only been growing. Our members have effortlessly embraced and interacted with our AI assistant, and we're excited to expand its usage even further in the upcoming year.”
Rachael Pearson
Head of Marketing and Digital for The Camping and Caravanning Club
Increase your deflection rate
You can launch an AI assistant in minutes and scale it fast:
- Use all the features available to you need to grow your AI assistant quickly
- Use our integration templates, so you can quickly start automating tasks and processes like customer feedback, signups, bookings, cancellations and appointment reminders
- Deflect queries on every channel, from your website or app, phone lines, social or messaging platforms and smart speakers
Anyone on your team can create and manage an AI assistant, you don’t need any technical skill to get started.
How do you work out your cost per call (and save money using AI)?
What is cost per call?
Cost per call calculates what it costs your company, on average, every time you handle a customer enquiry over the phone. Understanding the financial impact of every customer interaction on your business helps you optimise your operational costs to suit demand and your budget.
By effectively managing and reducing your cost per call, you can improve your financial performance, allocate resources more efficiently, and enhance overall customer service quality, leading to increased customer satisfaction scores.
How do you calculate cost per call?
In the UK, the average cost per call is £6.26. You can work out yours by dividing the total operational expenses related to call handling by the total number of calls your teams receive, and when you’re working out operational expenses, be sure to consider the true cost of hiring support agents to handle those calls. This includes holiday and sickness pay, pension contributions, induction and training, technology and equipment, as well as tax and recruitment.
Once you know your cost per call, you can find ways to reduce it, and business leaders now frequently turn to AI to accomplish this, feeling excited, optimistic, and motivated by the level of change it brings. To see what saving you can make, use our handy savings calculator.
Rethinking cost per call in the age of AI
Since 2020, chatbot use has doubled, and with large language models (LLMs) like GPT arriving in 2022, AI is no longer an alien buzzword ― industry leaders in every sector are aware of it. That means your customers are getting more comfortable all the time using and accepting AI automation as they grow ever-familiar with it. For Legal & General Insurance, even before 2020, 83% of customers using their AI assistant were already turning to it first over traditional methods of contact like phone and email.
What’s important now is to compare your cost per call for every enquiry your support teams handle to the cost of having an AI assistant handle them for you.
“The average cost per call is around £6 in the UK and we’ve reduced this to 5p per enquiry with our next-generation AI assistants. Barking & Dagenham Council, for example, worked out they were spending £4.60 on every call coming into their contact centre. In their first six months after the launch of their AI assistant, they saved £48,000 and went on to expand their AI-powered service to five more departments at no extra cost with a ROI of 533%.”
Abbie Heslop
Head of Customer Journey at EBI.AI
With the rapid advancement of powerful AI assistants, cost per call is starting to take up far less significance in what we call the customer service pie. Now you can handle all the routine, repetitive, monotonous enquiries using an AI assistant, there’s no need for cost per call to dominate your customer service budget.
Using an AI assistant you can:
- Solve enquiries for pence not pounds
- Handle customer enquiries 24 hours a day, not just when your support teams are online
- Serve customers on every channel
- Respond in 130+ languages, instantly
- Improve accuracy of responses too, leaving no room for human error
When a more sensitive or unusual enquiry demands the attention of your human agents, simply use live chat to immediately pass the customer over from your AI assistant to one of your team members, so they can benefit from their empathy and experience to fully resolve their issue.
Launch an AI assistant for free
If you’ve already worked out your savings and want to give an AI assistant a try, you can get one live in less than ten minutes using only your website URL.
Our advanced platform has all the features you need to scale your AI assistant quickly, cutting out the need to hire extra agents to cut down high call volumes and associated call costs, and transform your customer service, starting today.
How to calculate your call volume (and use AI to reduce it)
What is call volume?
Call volume is a metric used in customer service to show the total number of incoming calls handled by your customer support teams over a specified period of time. It’s an essential metric for assessing the workload and overall efficiency of your customer service operations.
However, with the rapid advancement of AI, call volume is no longer a tally you tot up and then simply cope with if the volume becomes too high. There are now easy, affordable ways to actively manage call volumes to bring them down and deflect any stress away from your teams, improve overall efficiency and reduce overwhelm.
How do you calculate your call volume?
To calculate call volume, count the total number of incoming calls (C) over a specific time frame, usually a day, week or month. Then divide this total by the number of hours your teams are online (H) to find the average call volume per hour.
Call volume formula
C ÷ H = call volume
For example, if you take 7,000 calls a week Monday-Friday and your teams are online for 40 hours in total, your call volume would be:
7,000 ÷ 40 = 175 calls per hour
Using call volume to analyse performance
If you know your call volume is 175 calls per hour, you can start to figure out if you have enough resources to handle your volume. Monitoring volume alongside other metrics can help offer extra insight into how well your teams are able to cope with demand:
- Average response time to see if you’re prompt in answering all calls
- Escalation rate to see if you’re getting many complaints
- First contact resolution to check calls answered are fully resolved
- Repeat contact rate to see if customers have to call in more than once
A persistently high call volume and poor average response time or high repeat contact rate, for example, might suggest the need to increase your support resources or optimise your workflows.
Improving performance
If you find call volumes are higher than you can comfortably handle or contact teams are overwhelmed, your focus will be on reducing call volumes and associated stress. Using AI is fast-becoming the go-to aide for business leaders looking for new ways to handle high call volumes, especially if your budget is tight, you don’t want to spend the lions share of it on recruitment, or simply don’t have a consistent need for more staff. Crucially, AI can help you determine if all the calls you receive are necessary in the first place or if you can deflect them away from your teams to lessen their workload, especially of repetitive enquiries and mundane tasks.
Making the transition to AI-powered services
Like many organisations, your telephone communications might currently command the largest piece of what we call the customer service pie. In this case, customer service operations are all hinged on standard business hours, but if your support is only active for 8 hours a day between the hours of 9am-5pm, it leaves 16 hours where customers are unable to get the help they need. Using an AI assistant keeps your support open 24/7 and is a far less expensive ‘pie strategy’.
The move to AI-powered services doesn’t have to happen overnight, either. You can have a warm handover and start by routing your phone queries through AI-driven IVR. Rather than a traditional IVR system that forces customers to choose from a list of set options to find the team they need to speak with, they can simply say what they need. Using natural language processing (NLP) capability, a next-generation AI assistant can recognise what they’re asking for and route them through to the right department straight away.
On top of that, you can add AI telephony, where the AI assistant solves the problem independently over the phone without having to put the customer through to your teams at all. Of course, if the query is unusual, sensitive, or needs strategic thought, you always have live chat available to pass your customer through to a human agent and the dedicated skills and expertise they offer.
Leisure providers, Mytime Active, transformed their customer service in just six months with the introduction of AI-powered support.
“Without our AI assistant our call volumes would have continued at an exceptionally high level and we are confident the system has saved us the equivalent of 2 additional heads due to us being open 7 days a week.”
John Branigan
Director of IT & Transformation at Mytime Active
Maintaining your success
Using AI to manage customer queries can transform your insights, so you’re not only reducing your call volume, but actively working on your customer service mindset to make the customer experience better overall.
You don’t have to rely on manual mathematics any more to make sense of your metrics. Using an AI assistant it becomes easier to see what customers want to speak to you about most often and get instant feedback on their experience to track your customer satisfaction score (CSAT) or NPS. You can then use what you learn to plug any bottlenecks in support and fix all the problems you can.
Everything you need to know shows up on one central dashboard, pulling in data from every channel your AI assistant appears on to encourage more real time engagement with customers to continuously top up your knowledge.
“Having an AI assistant can help reduce the number of enquiries you have overall, resulting in your support agents having more time to provide a better quality experience for your customers,” says Aaron Gleeson, Implementation Lead at EBI.AI. Like JLL property managers who use an AI assistant to help reduce their routine maintenance tasks.
“Because the property AI assistant takes on more routine tasks like maintenance requests and contract information, it frees up our property managers to concentrate on the overall service and maintenance of the building, providing a better experience for tenants.”
The right way to measure results
When you make the shift to AI automation, it’s important to make sure you track call volume before and after the launch of your AI assistant as well as document any shift in the type of customer queries you get. That way, you can see the true impact and value, both strategically and financially, of using AI automation to support your customers and help grow your business.
Barking & Dagenham Council saved £48,000 in their first six months after launching a next-gen AI assistant and their return on investment quickly reached 533%. With AI assistants now available to everyone at a totally affordable rate, a high call volume can soon become a thing of the past for you too, alongside reduced support costs.
Launch an AI assistant today
You can get started with just your website URL and your AI assistant is ready in less than 10 minutes!
What is issue resolution rate and what’s a good benchmark?
What is issue resolution rate?
Issue resolution rate measures the percentage of customer enquiries your contact teams have resolved. It shows how effectively your agents, chatbots or AI systems address and solve customer issues. A high issue resolution rate shows you’re doing well at this, leading to improved customer satisfaction and loyalty.
How do you calculate your issue resolution rate?
To calculate the issue resolution rate, divide the total number of enquiries you resolved by the total number of customer inquiries, then multiply the result by 100. This simple formula means your team members can track and report on how efficiently customer issues are resolved, even without data analysis expertise. For instance, if a team resolves 85 out of 100 enquiries, the issue resolution rate would be 85%.
What is a good issue resolution rate benchmark?
A benchmark for a good issue resolution rate typically ranges between 70% to 90%. Achieving and maintaining a high issue resolution rate within this benchmark shows operational efficiency, superior customer service, and effective use of chatbots and AI technologies.
It’s helpful to measure First Contact Resolution (FCR) alongside this metric, to see how many of your enquiries are solved first time.
Rethinking issue resolution rate strategies to suit the age of AI
Without the help of AI, you might be relying on email surveys, phone calls, or long distance in-person meetings or video calls to try and work out why some issues are left unresolved. It’s important to work out where there are bottlenecks in your systems, so you can improve your issue resolution rate if it’s low, but all of these methods of gathering feedback and information are time consuming and that time could be spent working on higher value tasks.
Bring an AI assistant into the mix and it’s far easier to work out where any problems lie. You’ll be able to consistently gather data from chat based conversation to transform your insights and find out why some customer issues are not resolved:
- On our platform you can filter your data to inspect unresolved issues and view past conversations (with personal information automatically redacted) to see where the service fell down. You’ll not only see for yourself exactly how a conversation flowed; what was asked for and what the response was, you’ll have real data to go on, not just human memory.
- If an issue needs to be escalated, you can seamlessly transfer them to a human agent using live chat. The best part is, your manager can see the chat based conversation so far, so will already know what the problem is. Not only will the customer not have to repeat themselves, you can also be sure to escalate them to the right manager in the right department.
- Using API integration, you can link up your AI assistant with your go-to business system, so you can automatically log support tickets using a tool like Jira at any time of the day or night, ready for your teams to pick them up and start working on a resolution straight away.
Naturally, if your issue resolution rate is low, you’ll want to investigate overall service delivery. Using an AI assistant will help with this, since you’ll have one central store for all your customer data across all channels, meaning you have a constant finger on the pulse of customer communications, so can start to work through your issues and turn things around.
“Our AI assistant helps us capture vital intelligence to improve the services that really matter to our customers. For example, data demonstrating that parking is the most popular topic right now, helps us make the relevant changes and allocate resources more effectively.” ~ Andy Cooper, Customer Services Manager at Coventry City Council
Launch an AI assistant today
You can get started with just your website URL and your AI assistant is ready in less than 10 minutes!
What is average response time and how is it affected by AI?
What is average response time?
Average response time measures how long your teams take to respond to customer queries and helps you evaluate the effectiveness of your customer interactions. A quick response time is vital for maintaining a high customer satisfaction score and building trust.
Fast response time can also lead to greater business success. Responding promptly to an online shopping query can help make that sale and so increase sales overall, and through speedy yet reliable customer support you can encourage greater customer loyalty, all of which helps boost your brand.
How do you calculate your average response time?
To calculate your average response time, add up all your response times for each interaction your contact teams deal with and divide this total by the number of interactions overall.
Total response time ÷ Total interactions = Average response time
This simple calculation shows you how quickly your teams engage with customers. If your teams respond to 250 queries and it takes 1,000 minutes altogether, your average response time would be 4 minutes per query.
Why does the average response time matter?
Your average response time can directly influence Net Promoter Score (NPS) and brand reputation, since customers don’t like to wait for support. They also won’t recommend you to others if they’re always waiting for a long time to get through to or hear back from your contact teams. In fact, Forrester found “63% of customers will leave a company after just one poor experience, and almost two-thirds will no longer wait more than 2 minutes for assistance.”
Regular tracking of your average response time can help identify and release bottlenecks around support, relieving pressure from your teams to better please your customers. This goes some way to showing you provide exceptional service and stand out in a competitive marketplace, especially where others are failing. The Institute of Customer Service says “companies that have maintained higher customer satisfaction than their sector average have achieved stronger revenue growth (7% points more),” so it’s good for your bank balance too.
What is a good average response time?
In the past, a good benchmark for average response time in customer service has typically fallen within a few minutes, but Microsoft found “some UK customers are waiting up to 85 minutes to speak to representatives at some of the country’s largest providers of consumer goods and services”. Where high call volumes are becoming unmanageable, business leaders now routinely turn to AI to speed up support services.
Using an AI assistant, enterprises can now provide customers with instant responses ― hundreds and thousands of them all at the same time, and at any time of the day or night, in 130+ languages, on any channel. This can include your website, social media channels, messaging platforms, apps, phone lines, and smart speakers.
Response times instantly shift from minutes down to mere seconds.
Adapting to AI to improve average response time
Like many organisations, your telephone communications might currently command the largest piece of what we call the customer service pie and response times hinge on standard business hours of 9-5. The problem is, if your support is only active for eight hours a day, you’re not responding to people for the other 16 hours.
Using an AI assistant keeps your support open 24/7 and is a far less expensive ‘pie strategy’ when you consider the typical UK cost per call is £6.26 according to ContactBabel.
Introducing AI the easy way
AI might be everywhere now, but you don’t have to panic or rush change in your organisation. You can have a warm handover to AI-powered services and simply start by routing your phone queries through AI-driven IVR to speed up your average response rate. Rather than a traditional IVR system that forces customers to choose from a list of set options to find the team they need to speak with, they can simply say what they need using AI. With natural language processing (NLP) capability, a next-generation AI assistant can recognise what the customer is asking for and route them through to the right department straight away with no wait time at all.
On top of that, you can add AI telephony, where the AI assistant solves the problem independently on behalf of your teams over the phone. There’s no time wasted transferring your customer through to an agent and you automatically increase your goal completion rate too, where an AI assistant solves routine customer service queries at top speed. Your teams can then give greater attention to solving more the complex, unusual, or sensitive queries effectively and efficiently that demand their unique skills and experience.
Leisure providers, Mytime Active, transformed their customer service in just six months with the introduction of AI-powered support.
“The ability to deliver such high levels of accuracy without needing further interaction from the contact centre has helped us reduce our wait times considerably and know that queries that come through will be things that need direct answers from the contact centre team. Without our AI assistant our call volumes would have continued at an exceptionally high level and we are confident the system has saved us the equivalent of 2 additional heads due to us being open 7 days a week.”
John Branigan
Director of IT & Transformation at Mytime Active
Measuring your results during a switch to AI
Because you’re measuring how long it takes to respond to customers in seconds with an AI assistant, rather than minutes over the phone (or days for email), be mindful of logging the difference in performance as you introduce AI. Look at your average response time without an AI assistant and directly compare this to the average response time after you’ve launched one to see clearly the value it’s adding to your business.
Financially, you’ll also want to measure your return on investment, which you can do before you even sign up for an AI assistant using our handy savings calculator.
Use an AI assistant to speed up service
You can launch an AI assistant today using only your website URL and it’ll be ready in less than 10 minutes to start rapidly reducing your average response time.
How to calculate and improve your Customer Satisfaction Score (CSAT)
What is your Customer Satisfaction Score (CSAT)?
You can use CSAT as a metric to measure how happy or satisfied your customers are with your products or services. It usually comes from surveys or feedback channels where customers rate their satisfaction levels based on their experience.
This metric is key for understanding customer perceptions of your brand, identifying areas of your service that can be improved, and ultimately boosting customer loyalty and customer retention.
Why is CSAT important?
CSAT directly reflects the quality of your service, so tracking this metric helps your teams gauge the effectiveness of interactions with your customers and identify patterns or issues affecting satisfaction levels. You can then make data-driven decisions to enhance your overall customer experience.
- A high CSAT score shows customers are typically delighted with your service, leading to repeat business and positive word-of-mouth reviews ― often tracked separately with Net Promoter Score (NPS)
- A low score can highlight problems and pain points that need your urgent attention to prevent customer churn
How do you calculate your customer satisfaction score?
Calculating CSAT involves collecting feedback from customers through surveys or rating systems where they typically rate their satisfaction on a scale of 1 to 10, where 1 is ‘Extremely dissatisfied’ and 10 is ‘Extremely satisfied’. The average of these individual scores gives the overall customer satisfaction score.
If a business gets ten ratings from ten different customers of 7, 8, 6, 8, 9, 2, 6, 7, 9 and 4, the average satisfaction score would be (7 + 8 + 6 + 8 + 9 + 2 + 6 + 7 + 9 + 4) ÷ 10 = 6.6. Rounded to the nearest number, CSAT here is 7.
What is a good CSAT benchmark?
While customer satisfaction scores can vary across industries, 7-8 is a fair score on a 10-point ratings system, where customers are generally satisfied. A score of 9 or 10 is excellent, indicating the majority of your customers are highly satisfied with the service they receive. By setting a key customer service goal to keep CSAT above 7, you can strive to meet or exceed customer expectations, leading to better customer relationships and increased business success as a result. AI has become a true ally for business leaders to start excelling at this with ease.
Boosting CSAT with the help of AI
A low satisfaction score doesn’t mean you’re not trying. In fact, the opposite can be true. You might face budget restraints that prevent you from being able to provide the quality of service you’d like to give to your customers, ultimately leaving them dissatisfied. Or maybe you don’t have the technical capability to improve, or are slowed down by legacy software systems that frustrate not only your customers, but your teams too. Using AI, business leaders now have no barriers to making real headway:
- These days, even the most advanced AI platforms are affordable for everyone and organisations in all sectors are saving money by switching to AI-powered customer services. Barking & Dagenham Council saved £48,000 in their first six months of using an AI assistant while simultaneously increasing customer satisfaction by 67%
- Using API integration, a smart AI assistant can also do more for you than simply send out information. They can carry out tasks and transactions too, opening up opportunities for your support teams to focus on making improvements to your offers and services to lift CSAT, rather than spend time answering repetitive or monotonous queries they can likely handle in their sleep
Measuring CSAT effectively
How we satisfy customers is dramatically changing. If you decide to launch an AI assistant, make sure you look at what CSAT was before you introduced AI automation as well as after, so you can compare the two. This will help you identify where AI most improves the experience for your customers and your teams, so you can learn from it and continue to make changes that have the greatest impact on your satisfaction score and key customer service goals.
“There are lots of ways to improve CSAT you might not immediately think of, from setting key objectives as SMART goals to keep teams on track, to personalising customer experiences using the most innovative methods. When asking for feedback, you should also always follow up with a qualitative question, so when a customer gives you their numerical satisfaction score, ask “Why do you feel that way?” You then know the reason for the score they give and can go on to improve or maintain their experience. With an AI assistant, you can ask for this feedback instantly, with real time engagement at the end of every conversation.” ~ Abbie Heslop, Head of Customer Journey at EBI.AI
Launch an AI assistant today
Using our advanced platform, AI Studio, it’s easy to set up question and answer sequences (we call these flows) and include a request for a CSAT rating at the end of every exchange.
In the video below, you see the AI assistant answering a question about which laptop to use for gaming and the request for a CSAT rating at the end.
How to create this flow in AI Studio:
- Sign up for or log in to AI Studio
- Go to the Content tab and check you’re on the Flows tab
- Create a new flow called ‘Ask CSAT score’
- Add a Question: ‘How satisfied are you with the customer service support you received today?’
- Add Valid options 1-5
- Click Show options to user (so they can quickly choose a response)
- Hit Publish
Once you’ve set up a new flow for CSAT, you can link it to any of your other flows, which means your AI assistant will automatically ask for the CSAT rating at the end of those sequences:
- Go to any of your existing Flows and select Link to flow
- You can also filter your requests and only ask for a CSAT rating at the end of conversations where customers said the response was helpful 👍
Ready to automate CSAT?
Sign up today and let your customers guide your decisions. Getting instant feedback from them while they’re in the moment will transform your insights.
What is Net Promoter Score (NPS) and what impact does AI have on your results?
What is NPS?
Net Promoter Score (NPS) is used to measure customer loyalty and satisfaction based on the question: “How likely are you to recommend our product or service to a friend?” Customers give a rating between 0-10, where ‘0’ is not at all likely and ’10’ is extremely likely, showing how they feel about your organisation.
How do you calculate NPS?
To calculate NPS, you first need to segment your survey respondents into three categories, depending on the rating they gave your organisation in answer to the question “How likely are you to recommend our product or service to a friend?”
1. Promoters (rating you 9 or 10/10)
These are enthusiastic, loyal, and satisfied customers who rate your company, product or service highly. They’re likely to continue buying from you and using your products or services, and will happily recommend your company to others. Promoters can help drive growth by spreading positive word-of-mouth publicity.
2. Passives (rating you 7 or 8/10)
These customers are neutral or indifferent towards your company. They might be satisfied with your product or service, but aren’t as enthusiastic as your promoters. Passive customers aren’t likely to spread negative messages about your company, but they’re also not vocal advocates. If a competitor offers a better product, service or price, they’re just as likely to switch as they are to stay.
3. Detractors (rating you 0-6/10)
These are unhappy customers who aren’t pleased with your product, service or overall customer experience. They have the potential to damage your brand and hinder growth through negative word-of-mouth commentary. Paying close attention to detractors can help you identify areas where you can improve your offer and increase your overall customer satisfaction score.
After you’ve segmented your audience, you’ll follow a formula to work out your NPS score as a percentage.
What’s the formula to calculate NPS?
To work out NPS, subtract the percentage of detractors (D) ― people who tear down your brand, from the percentage of promoters (P) ― people who build up your brand, to get your overall score:
P – D = NPS
For example, if 70% of your audience are promoters rating you 9 or 10 and 15% are detractors rating you 0-6, your NPS will be 55%:
70% – 15% = 55%
In this instance, the remaining 15% of your audience are passive (rating you 7 or 8 out of 10) and so have no influence on NPS, since they’re unlikely to either recommend or criticise your organisation to others.
What’s a good NPS benchmark?
According to SurveyMonkey’s study of 150,000 organisations, the average NPS is 32%.
- Scores below 32% show there’s room for improvement, signalling the need for strategic changes to better your overall customer experience
- Scores between 44% and 72% are good, showing you have satisfied customers and plenty of potential for growth
- Scores above 72% are excellent, reflecting a high degree of customer loyalty and satisfaction
Striving for a high NPS and maintaining a customer focused mindset can help build longer-lasting business relationships and encourage loyalty to flourish.
Why does NPS matter?
A high NPS means customer retention is likely to be good, which often goes hand in hand with higher profitability and sustained business success.
Equally, monitoring NPS over time can help you identify any dips in customer feeling, so you can address customer dissatisfaction if it crops up. In recent years, AI has become a strong ally for business leaders keen to gather detailed feedback, since it can help you improve customer engagement, getting more feedback in the moment, more often, and in greater detail to reinforce NPS ratings.
Gathering NPS feedback in the age of AI
Gathering NPS feedback has traditionally involved actively sending out surveys to customers, manually collating the results and then pulling together reports by hand. Now, you can easily and affordably launch an AI assistant to do this for you.
Companies like Mytime Active leisure providers are already using an AI assistant to answer 97% of their customer queries. When you add an AI assistant to your team you can train it to ask customers how likely they are to recommend your brand to others as often as you want it to as an instant, efficient way to easily gather customer ratings for NPS. Human agents then spend less time acquiring customer feedback and have more time to take action on everything they learn, ready to improve NPS overall. For Barking & Dagenham Council, customer satisfaction went up by 67% just six months after the launch of their AI assistant.
- AI assistants can handle an extraordinarily vast amount of data, so it doesn’t matter how many tens of thousands of customers you have or how many millions of transactions are handled
- You can use just one AI assistant across multiple channels, from your website or mobile app to social media and messenger platforms, but all your results sit in one central place for easy viewing
- No human agent, no matter how experienced or smart they are can handle data at the speed of AI, so calculations are made faster than lightning, saving your teams the time it takes to manually pull together reports, plus there’s no risk of human error in the calculations
- Your NPS data is constantly being topped up whether your teams are online or not, since an AI assistant works for you through the day and night
- You can also control when your AI assistant does or doesn’t ask customers for their rating, so if you’re already working on an escalation for a disgruntled customer, they won’t be left feeling more irritated by a request for NPS feedback
Gather qualitative data too
Possibly the best part of using an AI assistant to ask for feedback from customers is you can follow up to ask why they give the rating they do ― instantly, at the end of every request for an NPS rating. Since this is real time engagement with customers in a conversational setting, you can get the truest sense of their feeling right there in the moment to help you make sense of the NPS rating they give.
“Traditionally, the downside of using NPS ratings is you’re lacking qualitative feedback to understand why a customer has given you that score. With an AI assistant, you can ask a follow-up question to find out from the customer, ‘What’s the reason for giving that score?’ and give you expanded feedback, in their own words, and on any element of your product or service that matters most to them. The fact the feedback is conversational allows it to be more natural and literally ‘straight from the horses mouth'."
Abbie Heslop
Managing Director at EBI.AI
Launch an AI assistant today
Using our advanced platform, AI Studio, it’s easy to set up question and answer sequences (we call these flows) and include a request for an NPS rating at the end of the exchange.
In the video below, you see the AI assistant answering a question about which laptop to use for gaming and the request for an NPS rating at the end.
How to create this flow in AI Studio:
- Sign up for or log in to AI Studio
- Go to the Content tab and check you’re on the Flows tab
- Create a new flow called ‘Ask NPS score’
- Add a Question: ‘How likely are you to recommend our product or service to a friend?’
- Add Valid options 1-10
- Click Show options to user (so they can quickly choose a response)
- Hit Publish
Once you’ve set up a new flow for NPS score, you can link it to any of your other flows, which means your AI assistant will automatically ask for the NPS rating at the end of those sequences:
- Go to any of your existing Flows and select Link to flow
- You can also filter your requests and only ask for an NPS rating at the end of conversations where customers said the response was helpful 👍
What is customer effort score (CES) and how does AI help improve it?
What is customer effort score?
Customer Effort Score (CES) measures how easy or how difficult your customers find it to interact with your company’s services or support. If it’s difficult, customers can quickly become frustrated or dissatisfied, which can increase your escalation rate or customer churn. Low CES is good, implying a seamless customer experience, which can lead to increased customer satisfaction scores, greater loyalty, and good customer retention for overall healthier profits.
How do you calculate CES?
To calculate CES, you’ll first need to decide which specific part of your business you want to measure. This could be anything you’re focused on right now to hit key customer service goals:
- How easy it is for customers to get technical support
- How easy it is for people to use your product
- How easy it is to find information on your website
- How easy it is to place an order
Once you know what you’re measuring, ask your customers to rate how easy or difficult they found it to complete this task on a scale of 1-5, with 1 and 5 being the extremes at either side, and 3 neutral in the middle:
1 = Extremely easy
2 = Easy
3 = Neither easy or difficult
4 = Difficult
5 = Extremely difficult
You can explicitly mention “effort” in your question: ‘How much effort did it take for you to book an appointment today?’ or simply ask people how easy it was for them to complete the task.
Once you have your results, you want to determine the average score, so add up all the scores received and divide it by the total number of responses.
Say 10 customers give effort scores of 2, 3, 2, 1, 4, 2, 3, 2, 1, and 3.
That’s a total score of 23 (2 + 3 + 2 + 1 + 4 + 2 + 3 + 2 + 1 + 3).
Divide this by 10 (total responses).
23 ÷ 10 = 2.3
Rounded to the nearest number, your CES score here is 2, meaning, on average, most people find it easy to get help or information, or complete a task.
Why does CES matter?
Naturally, you want it to be easy for customers to get the help they need or information from you. Booking and buying should be easy too, to encourage people to use your services again or push up your repurchase rate, but if other metrics you track are too high or too low, CES can give extra insight into why you might have issues cropping up.
Say Customer Satisfaction Score (CSAT) shows customers aren’t overly happy with your product or services, or Net Promoter Score (NPS) confirms they’re unlikely to recommend you, a high CES can suggest customers aren’t happy or speak negatively about your business because you’re simply too difficult to use or to buy from.
Once you’ve determined where a problem might lie, you can set about fixing it. This can then help improve CES, CSAT and NPS as well as other customer service goals, like reducing average response time or increasing your upsell or cross sell rate.
By reducing the effort customers need to make to enjoy all you have to offer, you can simultaneously increase customer loyalty, since you’re showing people you value their time and their business, resulting in long-term, richer relationships to ultimately increase profits and boost your brand reputation. To make all of this easier, business owners are now turning to AI as their ally.
Rethinking CES in the age of AI
Speak to anyone who’s ever had to contact customer support about a problem and they’ll tell you a story about the time they spent ages in a call queue, got passed between departments, cut off, were given the wrong information, or didn’t receive a reply to their email. Having to make repeated calls or send multiple emails, explain their situation to more than one person or start over in a support enquiry thanks to an inefficient process or incorrect information results in high effort for customers. That’s why business leaders are using AI to help eradicate these issues.
Adding a next-gen AI assistant to your support team means business leaders in all sectors, from travel and insurance to retail and local councils are reducing effort for customers to better serve their needs:
- Responses to queries are instant and readily available 24 hours a day in any time zone and in 130+ languages, so support is convenient for everyone
- With a high quality AI platform that prioritises security, guardrails for LLM (Large Language Model) capability, and keeping a human in the loop, customer responses are always the same, every time, so the quality and accuracy of information is consistently high
- Calls can be handled using AI IVR and telephony to route people immediately to the right department, or handled via live chat in the moment by your teams where the personal touch is needed
- An AI assistant can also connect up with alI your favourite apps and platforms, so it can carry out tasks for you too, like taking bookings, handling refunds and returns, sending appointment reminders, or signing people up for membership.
How to track the impact of AI on CES
If you introduce an AI assistant to your team, be sure to compare your CES results before and after so you can clearly recognise the difference an AI assistant makes to your organisation. Before introducing theirs, Barking & Dagenham Council knew only 20% of customers were satisfied with trying to find information on their website, but using an AI assistant, satisfaction shot up by 67%.
Leisure providers, Mytime Active, who have a wide range of classes and activities across many different locations were finally able to put relevant, up to the minute information at the fingertips of their customers with no effort involved at all, transforming their customer service operations.
“The ability to take information directly from our site and present that to customers has delivered major change. Our timetables and opening times change on a regular basis and we know our AI assistant will present the latest updates when the customers ask."
John Branigan
Director of IT and Transformation at Mytime Active
Since an AI assistant is always online and engagement with customers happens in real time, you can also ask people why they give the effort score they do. This can help pinpoint areas of improvement you haven’t yet considered and move past specific pain points to reduce CES and increase customer satisfaction.
Get started today
Using our advanced platform, AI Studio, you can launch an AI assistant in minutes, and it’s just as easy to set up question and answer sequences (we call these flows), including a request for a CES rating at the end of every exchange.
- Sign up for or log in to AI Studio
- Go to the Content tab and check you’re on the Flows tab
- Create a new flow called ‘Ask CES score’
- Add a Question: ‘How easy was it for you to find out the information you were looking for today?’
- Add Valid options 1-5 (Extremely easy, Easy, Neither easy or difficult, Difficult, Extremely difficult)
- Click Show options to user (so they can quickly choose a response)
- Hit Publish
