Currently, there has been a transition from customer service that was handled by operators to a digital system. While some companies have traditional phone operators, others have support on websites or applications. Many of these customer service models are disconnected and have caused companies to frustrate customers or even lose business as a result. What has greatly changed is the possibility for Artificial Intelligence and Machine Learning to be integrated into these flawed customer service models to solve problems and increase customer satisfaction while using company resources effectively.
What Does CSAT Stand for?
CSAT stands for Customer Satisfaction Score. CSAT is one of the key indicators used to measure whether a customer is satisfied with a company’s service. CSAT is important and more companies are beginning to realize the importance of its calculations in regard to customer relationships and sales.
What is CSAT?
CSAT is one of the most intuitive of the customer satisfaction survey practices. It essentially measures a customer’s overall satisfactionwith an interaction, purchase or business. The primary question that is utilized to obtain this information is:
“How satisfied were you with your experience?”
From this question, a survey scale is derived that can vary in range such as: 1 – 3, 1 – 5, or 1 – 10. The range option is up to the company to decide based on the metrics they plan to calculate to support their analysis.
CSAT is useful because consumers that are busy can interact easily and provide valuable data for companies to use when verifying employee’s performance or the company’s overall operations and customer service model.
Why is CSAT Important?
CSAT is important because companies need to have a streamlined way to know if their customer service is up to par or not. By having CSAT, companies can look deeper at a process, procedure or employee’s performance to ascertain the success of an interaction.
Another important feature of CSAT is to have it available during various parts of the customer service experience so companies can pinpoint how each phase of the customer journey is being perceived by customers and whether any improvements need to be made. Each phase of the survey is quick, which makes it easy to integrate into multiple phases of the customer’s experience.
What Types of Metrics Measure Customer Satisfaction?
When trying to figure out how to measure a customer’s overall experience through CSAT, the company has to be knowledgeable about different customer lifecycle moments that have the potential to produce valuable data about the customer experience. These moments include discovery, evaluation, purchase, user experience, bonding, and advocacy. Each of these moments will be explained in detail below.
Discovery occurs when customers see a product or service and realize it is the solution they have been seeking to a specific need or want.
Evaluation typically refers to a customer’s budget. Customers will evaluate what they can or are willing to spend and then narrow down a list of products or services that fits their specifications.
Purchase occurs when the customer gains sufficient trust in the product or service and decides to provide their financial information to acquire that product or service for their benefit.
User Experience is perhaps one of the most important statistics to measure as it measures the learning curve a customer needs in order to fully understand the product or service after purchase. An example of this can be figuring out a new iPhone or interacting with WordPress for the first time to create a website.
Bonding is a process that consists of a series of experiences derived from a customer growing attached to their new purchase and being satisfied with how it has helped them solve a problem.
Advocacy occurs when a customer spreads their satisfaction with the product or service to others through word of mouth. Once a customer reaches this point, it is a great time to provide them with a survey and find out what the company is doing right to attract more customers.
Aside from these metrics, there are other parts of a customer’s lifecycle with a product or service that companies can learn valuable data from including during user onboarding, prior to renewal, and following customer support interactions.
User onboarding is critical as it is when a customer is deciding whether or not to give your company business. The entire experience each customer has when joining your platform or making a purchasing decision needs to be studied carefully to maintain that customer’s interest. Having a survey after user onboarding is a great way for companies to see if any parts of their processes need to be improved for future customers or not.
Prior to renewal is another important stage in the customer journey as it is a great time to gauge customer satisfaction; there is still time to repair damages should they arise, and ultimately, keep the customer’s business.
Many companies have weak customer support protocols. Surveying clients following customer support interactions is something that is absolutely essential, but it must be done in a tasteful way. Timing, channels, and the specific agent interacting with the customer are everything.
When considering which model to use for measuring a specific company’s customer satisfaction, it is important to analyze the company’s business model first by asking questions such as: “What does the company actually need to know?” “Does the company sell a product or a service?” “What are the threats to the company’s existing client base?” “Does the company think they are doing well or do they know there are issues to be addressed in their customer service?” Making an honest list of these questions and tailoring it to the company’s specific business model will ensure that customer satisfaction surveys are actually targeted toward what companies need to evaluate to make informed improvements.
How to Calculate CSAT score?
Even though the CSAT score is derived from basic calculations, there is a great deal of valuable information residing in simple statistics. Some sample answer choices that are used in CSAT surveys are: very unsatisfied, unsatisfied, neutral, satisfied, and very satisfied. It is up to the company to decide what exactly they want to put on those survey answers and what data they are hoping to obtain from the survey.
Depending on the number of answers allowed on the survey, companies can take the average for a base customer satisfaction score. For companies that want to get a number from 0 to 100, it is best to divide the number of satisfied customers by the number of satisfaction survey responses and then times that number by 100. From this calculation, it will be possible to get a percentage of satisfied customers.
How to Improve Customer Satisfaction
In order to improve customer satisfaction a company has to take a realistic and unbiased look at their protocols and processes. They have to ask tough questions and value what their customers think in order to grow their business model to adapt to their needs. Companies that do not do this lose touch with their customer base and in turn, lose business to competitors. The next logical step a company must take, assuming they have already conducted their customer satisfaction surveys at various stages of their customer lifecycle, is to analyze the results of their survey.
An important, yet often forgotten piece of the CSAT puzzle is that the analysis of CSAT scores should factor in global location. This is particularly true for multinational firms in markets around the world. If a local team member is not able to provide valuable insights, it can cause setbacks about what products and services are appropriate for which markets. Surveys also need to be constructed based on where the customer is located. This can have linguistic variations or cultural insights that can be useful to a company knowing which of their products and services are appropriate for their corresponding markets.
After investing in a customer satisfaction survey, a company’s next major hurdle is answering the question, “What’s next?” Where companies mismanage resources is often by neglecting valuable data from customer service surveys. Often times, this data never gets analyzed and presented to senior management. This next part of the process is pivotal to use company resources responsibly, maintain customer satisfaction, and learn from prior mistakes.
What CSAT Analytics can Tell you
Once the CSAT scores have been calculated, it is important to look deeper at the different surveys to see common trends that occur at pivotal parts of the product or service’s lifecycle. These trends then need to be discussed by analysts and a report should be prepared with potential causes of common issues and also, recommended solutions. It is important that companies not only focus on what they are not performing well on. For example, the survey results should be used to show what positive practice and policies customers are also responding to. The combination of this information should be presented to senior management so they remain close to the customer experience. Any disconnect here can cause major blindspots in strategic planning and budget allocation.
Once information has been presented to senior management, new policies must be integrated to target strengths and weaknesses for areas of improvement. It is vital that companies continue giving surveys after the first round to test for customer satisfaction. Periodic surveys are the way forward to make sure quality continues to be outstanding and customers are satisfied with the experience at every stage of the customer lifecycle.
A common question companies ask is if there is technology that can compliment CSAT scores to further improve customer satisfaction? Due to the incredible developments with Artificial Intelligence and Machine Learning, customer service is starting to be successfully handled by advances in those technologies.
The accuracy of how Artificial Intelligence and Machine Learning can process information and cater to the customer’s needs is also getting better with time. In fact, by 2020, it is predicted that many customer call centers will be facilitated by Artificial Intelligence and Machine Learning practices. This is largely due to an increase in the volume of data and business transactions on the internet.
Due to this enormous expansion, companies have to find additional ways to sort through relevant data to continue periodically improving their customer service relating to their products and services. Traditional chatbots and customer service centers will be entirely transformed by new Artificial Intelligence and Machine Learning technologies.
Companies that take the time to invest in understanding their CSAT score and tailoring their surveys to learn valuable information about their business will have higher customer satisfaction and retention rates in the long term. They will also have better data for Machine Learning algorithms. Companies that adapt with the market and are open to how Artificial Intelligence and Machine Learning can improve their customer base, service, and sales numbers will be ahead of the curve.