It used to be that customers insight in could only be obtained in direct means, such as asking questions, posting surveys, poll surveys, and alike. While this was a good way to get feedback relatively quickly, it also required a lot time, planning and post analytic efforts.
Of course, there was also the issue of how trustworthy an official customer survey can be, which, in turn, depends on the customers’ honesty and whether the survey was asking the right questions.
Revuze came up with a much better and scale-able solution, which provides trustworthy results, and does it faster (almost in real time). This solution is based on real online reviews your customers place online, big data, sentiment analysis, and a cutting edge artificial intelligence technology. Not only that, but such big data analytics could impact business decisions and results in many different ways. Before we explain how the company does it, let’s first cover some of the basics.
What are customer satisfaction surveys, and how are they used?
Simply put, a customer satisfaction survey is a process in which a company is trying to discover whether or not its customers are satisfied and happy with the goods and/or services that the company provides These surveys can be conducted in a few different ways, including face-to-face, online or over the phone.
In modern times, it is not unusual for customers to be asked to participate in such surveys via email, post purchase or other online methods. An older method that can still be encountered today also includes handwritten forms.
The process is quite simple, and all that the customer needs to do is answer a number of questions regarding the company, its products, services, the quality, likeliness of repurchase of such goods or services, and alike.
The answers are then collected and used to analyze whether or not customer satisfaction is high enough or not. The results also indicate whether or not the company needs to change an aspect of its business operations, which might increase the overall satisfaction.
Net Promoter Score (NPS) definition
Survey results are measured by using a proven metric known as the Net Promoter Score (NPS). NPS is a popular metric that mesures customer experience. By using the available information, it is also capable of predicting the businesses’ growth in the future.
This method of measuring the success of a product / service has transformed the way companies and brands handle, manage, and measure customer experience. Read more about net promoter score and social sentiment here.
How surveys are used to define the net promoter score
Usually, calculations are made by focusing on answers on, key questiond, such as — how likely is it that the customer would recommend the brand to a friend, colleague, family member, and alike. The customer then are asked to place their answer on a 0-10 scale.
Those whose overall score is between 9-10 are considered loyal enthusiasts and promoters. Those whose scored 7-8 are considered passive customers, who are still satisfied, but mostly unenthusiastic. Finally, the ones which are on the 0-6 scale are considered detractors or unhappy customers. Obviously, if the number of detractors is high, the brand needs to put some thoughts on how they operate.
More importantly, this method is used to determine the percentage of extremely satisfied customers, or promoters, who are likely to introduce new individuals to the brand, and thus improve the sales, operations, and overall performance, while doing so out of sentiment alone.
How Revuze uses sentiment analysis to create an ad hoc customer survey
Revuze, is changing the way that companies measure user perception of products and services. By applying AI based sentiment analysis on your (and your competitors) online reviews. It allows anyone in the organization to access valuable consumer data whenever they need to check up on customer satisfaction.
Revuze uses online sources such as online reviews, social media monitoring, email correspondence, other surveys, data collected by call centers, as well as other sources, both online and offline. With all of this data in one place — the company can easily scan it by using its machine learning algorithms to discover new aspects and topics in each product category. All of this is done automatically and independently. Meanwhile, its self-learning technology teaches itself about your company’s products in order to maximize the value of the insight it provides.
By collecting everything of relevance, Revuze doesn’t need to know what questions to ask, and is capable of creating an ad hoc customer survey directly from the answers. This revolutionary approach eliminates the need to design surveys for a specific or and a specific purpose, which is conducted as a one-off study, or an entire program of studies. This Ad Hoc approach is now considered to be the most qualitative and scale-able form of market research.
Know what your customers think without asking any customer satisfaction survey questions
Simply put, this type of technology is innovative, advanced, and extremely helpful to enterprises and SMB’s alike, as they can discover what the customer thinks, without having to ask for feedback by applying an advanced form of text analysis.
Customers typically tend to post their insight and thoughts regarding companies’ services and products on social media and online marketplaces. Others, who might be familiar with the company in question can then provide their own comments, ‘likes,’ ‘shares,’ and other forms of endorsement of a specific opinion.
All that remains is to gather this data and analyze it, which can be done through advanced searches of specific keywords, key phrases, topics, trends, and alike. With a self learning analytics engine, and advanced sentiment analysis — Revuze does that automatically, and apples methods such as NLP and sentiment analysis to get the most accurate data regarding social sentiment and overall customer sentiment.
How Revuze applies sentiment analysis and NLP to get the customer sentiment
After the customer posts their comments, reviews and questions online, Revuze scans this data, retrieves the context and the sentiment of the customers’ responses, and identifies exacts trends and topics from unstructured data. The end result is high-quality customer feedback in a granularity which could not be previously provided in any direct form of comunication. The customer satisfaction score is then calculated and analyized.
In other words, the technology that Revuze uses specializes in locating the data, getting the context, and identifying the sentiment. Analysis of this data can tell businesses all they need to know regarding their business, the customer satisfaction levels, potential issues that need resolving, what aspects of operations need to be changed, and more.
Deep dives into the market analysis can also help reveal new opportunities, as well as risk factors that were previously unknown. Naturally, gaining this information as soon as possible could be of extreme benefit to brands and companies, as it would allow them to avoid the escalation of potential problems simply by being aware of them as soon as they are discovered by the consumers.
Businesses could choose to monitor their brand’s health performance over time through Timeline analysis or to do a specific new or old product analysis. In the case of new products, companies could gain awareness of existing customer concerns in regard to a product that has yet to be launched, or to monitor the launch progress and ensure smoother consumer adoption.
Finally, the companies would also instantly know how the product was received in period to the launch and after it was launched. This information could make a great difference in finding out previously-undisclosed issues that needs fixing or an aspect that is poorly received by the customers.
Know the voice of the customer
By knowing the voice of the customers — their expectations, preferences, aversions, and more — brands can easily understand which aspects of their business need to change. This can result in increased customer satisfaction, which can lead directly to increased sales of products, recommendations, hiring of the businesses’ services, and alike.
This is one of the best market research techniques that can produce a detailed set of customers’ needs, wants, and potential complaints, all of which get organized into a hierarchical structure. The data is then prioritized according to relative importance, as well as satisfaction with existing alternatives.
Methods such as social listening and collecting the voice of the customer also lead directly to deducing the customer sentiment and replaces older methods of getting the same insights, such as traditional surveys.
Revuze customer insights vs. customer satisfaction rating
By on going collection of customer insights and comparing it to customer satisfaction rating, Revuze can determine the sentiment towards any brand with great accuracy, which is what businesses need in order to decide how to proceed. Analyzing the market is likely the greatest advantage that a comnpany could have, and doing it properly can mean all the difference when it comes to future success.
Revuze is completely dedicated to disrupt the way customer experience is measured and collected— the firm has gathered the best minds in the big data consumer analytics industry. These great minds work together to create advanced solutions, such as the technology that Revuze is using to provide its data analysis.
Leading brands, including innovators, fortune 500 companies, choose Revuze to analyise their customer expeirnce, and providing them with context, customer sentiment, and other crucial information.
Learn more about the pros and cons of incentivzed reviews on our whitepaper.