Acronyms for Customer Service

Acronyms for Customer Service Professionals

Acronyms for
Customer Service Professionals

Learn the useful terms for better customer experiences

Working in customer service usually involves certain new words and acronyms in your daily work. And it can be confusing if their meaning is not entirely clear to you. But they are very useful for Customer Service, and the acronyms might even help your department to understand and work faster towards your common goals. These acronyms are often used in conversations regarding effectiveness, data gathering, improving the software and CX in general.

We have listed the most commonly used acronyms for Customer Service Professionals in contact centers, customer service departments or any customer-focused company. Use it as a dictionary for when acronyms like AHT, FCR or VOIP are getting too complex, because it can be difficult to keep track of them all.

Dictionary for Customer Service:

  1. AHT - Average handle time, is a frequently used metric that tracks how long it usually takes to solve a customer service ticket. Commonly used to track how well the agents are performing and providing quick responses to customers.
  2. AI - As you might already know, stands for artificial intelligence, is becoming more common in conjunction with technical customer support tools. For example, using AI for more accurate chatbot answers to frequently asked questions.
  3. API - An application programming interface is usually shortened down to API and it is a computing interface that defines interactions between multiple software.
  4. CEM - Stands for customer experience management, and is used for improving and understanding the customer journey of your business.
  5. CRM - Customer relationship management, is used to facilitate your relationship with prospects and prospects and customers. From the first interaction with your company throughout the time as customers.
  6. CSAT - Is a commonly used term for customer satisfaction, it describes a score produced by surveys, when asking customers how they experience the service.
  7. CSS - In customer service, CSS stands for customer self-service, where the customer can search for the answer to their question on their own, without getting in contact with a human agent. For example, provide these answers with help from AI and chatbots (don't get confused - CSS of coding and style sheets, it is another CSS).
  8. CTI - Is a computer-telephony integration that allows companies to integrate their phone and digital interactions into one interface.
  9. CTR - Stands for click-through rate, and describes the percentage of clicks that a link gets, due to the number of views or chances of clicks. It is often used in marketing, but it is also useful when measuring how well your knowledge base (point 11) is performing.
  10. CX - Customer experience, describes a more comprehensive aspect of a customer's usage and interaction with a company or product. Performing outstanding customer service is a part of the overall CX.
  11. FCR - Is short for first call resolution in the call center context, and shows how frequently the customer's questions are solved within their first contact with an agent.
  12. KB - Knowledge base, is a collection of questions and answers. It enables self-service and is very useful to customers that search for quick answers to common problems. It can also be used internally to collect and organize business information.
  13. KPI - Key performance indicators, are the metrics a department or business chose to track and prioritize, to measure the performance towards their fundamental goals.
  14. NPS - NPS means net promoter score, and is a very important customer service metric. It describes how likely the customers are to recommend your company or product to a friend or colleague.
  15. ROI - ROI stands for return on investment, and is a term for measuring the outcome from the amount spent on a product or service.
  16. SBR - Skills-based routing, is a technique customer service departments use to ensure the incoming ticket gets delivered to the right agent. Simply, to make sure the agent's skills match the ticket subject.
  17. SLA - A SLA or service level agreement, is a written statement and a commitment from the customer service team, involving standards and approaches.
  18. UI - Stands for user interface and is the part of a software that the user sees and interacts with. It usually has an impact on how often the customers contact the support team and how often they can solve the issue on their own.
  19. VOIP - Stands for Voice over Internet Protocol and it is the technology that enables phone calls over the internet.
  20. WOM - Word of mouth describes the expressed opinions from your customers regarding your company's products, services and brand. To develop a positive customer behavior that results in customers spreading good words about you, are a sign of great customer service success.

But be aware, these acronyms are frequently used within the industry of customer service. Our recommendation is to spell out the full explanation as well, just to be safe and avoid misunderstandings around these acronyms for Customer Service.

Contact us if you want to create better conditions for providing excellent customer service at your company

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Business Analytics Future

Business Analytics Future

Business Analytics Future

To finish up this week we will discuss business analytics future. I will talk about how it will disrupt industries and cause a lot of changes to the job market. But I don’t think it will change things to the worse. Just like during industrialisation everything changes but in the long run the population prosper.

Using data will change how we create products and for some companies data will be the very core of their products. We are living in a world where customer-centric companies prosper and data is something that can help us learn more about our actual customer. Just a few years ago we built customer personas based on e.g. demographic data, which creates stereotypical personas. But now we are moving towards customer personas that instead looks at behavior at its core. Business analytics future is looking bright and it will innovate business models and management approaches.

The problem with data is that can give use a false safety in our conclusions. We can miss important data because of how much we trust the data we already have. I mentioned a book in the blog post last week, about Superforcasters. It talks about how experts usually are not more than slightly better at making forecasts than novices who are guessing. It talks about the danger of the tip of your nose-forecasts and experts are not much better at it than rookies. But because of how much they believe that they know they come to conclusions quickly and are having problems letting go of them. So, remember how important it is to analys the data you gather with an open mind. Look at the data objectively.

Business Analytics Future – The Consequences

But the change towards a data obsessed society will also have its consequences. A lot of jobs will not be what they once were. The more an industry relies on information as its core product, the greater and more complete the change in it will be (source; research paper). Some jobs will disappear and some will change dramatically.

For customer service agents things will change but their job will never disappear. The need for human interaction will always be there. But there might not be as many agents as you can see at some companies today. A large portion of challenges that comes in to a customer service can be handled by a computer, AI or a chatbot. These will all be built on the thorough work done with different types business analytics. You use speech analytics and text analytics to gather what questions customer asks, and business analytics will analyse how customers interact with their customer service. The process in the customer service will have a foundation in business analytics. If we handle data right we can more objectively get to know our customers.

At some point in the future I will write about some of the different types of business analytics. Especially speech analytics is an area we at Connectel find really interesting. If you are interested in speech analytics then you definitely should contact us and we can tell you about our technology.

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The Value of Business Analytics

The Value of Business Analytics

IT systems value cannot be found in the technology alone. But the value of business analytics could be great if you do it right. It has the potential to change your company to the better. It’s first when you use it as a part of your process it becomes valuable. Business intelligence systems can play an important role in organisational knowing.

I think all managers and team leaders have at some point had a hunch of what they need. Imagine e.g. knowing deep down that you need more agents, but your boss won’t listen to you because he does not see what you see. This is where the value of business analytics shows because it helps the team leader with data selection and articulation (source; research paper). With the addition of data you are not only basing your arguments on intangible arguments but you have proof. You have the confidence to negotiate and the data that will visualize the need for your boss.

Research also shows that shareholders of a company will favor announcements that was backed by business analytics (source; research paper). Studies have shown that these reports have a positive effect on market return. There is value of business analytics both to small and large companies.

The Value of Business Analytics – The value of commitment

We also see a positive correlation between the commitment to an IT system and financial performance (source; research paper). There are four commitments we see in studies that especially affect the financial performance. First we have strategic choice making; which means having a standard process in how you make decisions, as automated as possible (source; research paper), and making sure the data will be shared with all the people who needs it. Second, having one digital platform which gather as many of the needs for decision making as possible. We also see that how you work with information is crucial, both working smart with it and making action-oriented assessments in connection to the data. Limit the number of metrics and link all actions to actual goals.

The Value of Business Analytics – Conclusion and tips

To sum it up, when you work with business analytics let it help you model most aspects of your organisation. But make sure to keep the ‘How’ (when you model the who, what, how) flexible (source; research paper). If you in a customer service force your agents to follow a script then that will obvious to you customer. The agent will be less engaged in the conversation and it will affect this opportunity to build a relationship with your customer. Another tip I have is to keep the use of business analytics engaging for your employees. Use gamification and visualisations whenever it’s possible. Implement mobile devices and dashboards, it will make it accessible to anyone who is interested.

As the blog post should show there are clear financial gains to a business analytics system. But the value of business analytics is connected to how you work with it. I talked about shaping your process around the system in this blog post, and that is crucial here as well. Read the blog post “The Future Customer Service” or contact me or my colleagues for a conversationabout how we can help you build a business analytics-based process for you customer service.

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Business intelligence & Analytics

Business intelligence & Analytics – Introduction and Development

Business intelligence & Analytics

Introduction and Development

We have all heard the quote “Knowledge is Power” and I believe it’s true. Maybe that’s why I’m slightly obsessed with Business Intelligence & Analytics. It’s takes an analytic mind to understand it and it’s almost an art. Maybe it’s the challenge and potential of it that excites me? During this week I will talk about Business Intelligence & Analytics (from now on I will call it BI&A). This is the introduction to it with a short overview of its development. On Wednesday I will talk about the business value of it connected to customer service. Friday is the last of the posts about the theme, and I will look at BI&A’s future.

What is Business Intelligence?

The term refers to technologies, applications and practices for the collection, integration, analysis, and presentation of business information. The purpose of Business Intelligence is to support better business decision making. Essentially, Business Intelligence systems are data-driven Decision Support Systems (DSS). (According to

Usually business intelligence systems gather and displays historical data. In business intelligence the math is simple and you don’t always treat the data. The focus is instead on visualising the data with graphs.

What is Business Analytics?

Business analytics (BA) is the practice of iterative, methodical exploration of an organization’s data, with an emphasis on statistical analysis. Business analytics is used by companies that have committed to data-driven decision-making. (According to

There are key differences and things these areas have in common. Business analytics uses statistical analysis. Which business intelligence does not. That is why the math can get a lot more complicated in business analytics. The data in BI&A is turned into information and used for decision-making. That is what they have in common.

Business Intelligence & Analytics Development

I have chosen to base these blog posts on research articles from some of the biggest journals of Information Systems. In this blog post I will use a popular and often used article. It can easily be found on Google: “Business Intelligence & Analytics: From Big Data to Big Impact“. The authors have chosen to divide the fields development into tree stages:

  • BI&A 1.0 – Based on database management. The content is fairly straight forward and structured. Business intelligence fits perfectly in here.
  • BI&A 2.0 – This is where the world has been since the early 2000. Everything web based that we today take for granted. But cookies, social media and blogs have brought a lot of unstructured data with it. What we see here is the introduction to business analytics because of the need of e.g. web and text mining.
  • BI&A 3.0 – In October 2011 The Economist wrote an article that reported that mobile phones and tablets surpassed the number of laptops and PCs for the first time. We also see an increase in IoT which can create everything from smart homes to smart cities. So we have a lot of data from mobile devices and IoT sensors.

Based in Moore’s law we cannot imagine where BI&A will take us. Moore’s law talks about exponential development and it is often applied on technology in general. This would mean that everything you believe about the development in BI&A will be far less than what actually the development will show. The same goes for customer service technology. Before you blink everything will change. While big data might not be useful for most companies all companies will benefit from a simple BI&A system.

Customer Service

How is this relevant to a customer service you might wonder? Imagine the ability to predict if your customer needs your help. Imagine being able to step into a situation where you can turn a problem into a sale. Business Analytics will help you. Just the feeling of being a little bit more prepared through analytics will help your customer service. It could even help you in building a successful process for the team and agents. We will go into more details in the next blog post on Wednesday. So stay tuned to read more about how business intelligence & analytics plays an important role in customer service!

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Build Behavioral Personas

Build Behavioral Personas

Using Customer Service Data

This blogpost is about how you can use customer service data to create behavioural personas. Just less than five years ago we would only build our marketing personas based on stereotypes. The assumptions that a woman have specific interests, and someone with a high income spend their money in this way. We have since then become smarter and realised that the market doesn’t work like that. We now realise the only thing we can rely on is behaviour. 

Behavioural data is more reliable than opinion, I have said it in earlier blog posts. When your company does the traditional market research they will probably only gather data that is less reliable. We soon have a day when a company doesn’t need to make manual market research. All the data they need is already there in the IT systems and processes. You already are tracking traffic to your website and conversion. Probably, how many you reach and engagement on social media. In your customer service you might for example track returned items and categories of issues.


Build behavioural personas with analytics

But you can take it a step further. We at Connectel have developed a speech analytics product with huge potential. To be able to extract valuable data from your conversations with customers could relieve your marketing department from assignments which gives them time to do something more valuable. Instead of relying on surveys that only 10-20 % of your customer base will answer now we can gather data and display it in real-time. Read more about the flaws with market research here.

Instead of sending out Customer Satisfaction questions you can with the help of speech analytics detect whether the customer seem happy or not. Together with data from the rest of the platform you can once and for all understand what channel your customer prefers. You can understand during what times of the day they tend to use what channel. With the help of speech analytics, we can catch all questions a customer is asking during a call, and text analytics can find the same information in emails and chat conversations. These examples are only scratching the surface of what we can do with the different analytics you will have available if you are using the CEC solution.

Get in touch with me if you have questions about the CEC solution or our analytical products.

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