There are various text analytics models like Medallia and Qualtrics. These work incredibly well, but there’s one big problem. These models miss 98% of customer issues. But why is that so?
According to McKinsey’s 2022 State of Customer Care Survey, a comprehensive and holistic customer care strategy includes simplifying customer experience (CX) while reducing call volumes and costs. The study indicates a broad approach to customer service, where digital and live interactions are both crucial for understanding and addressing customer needs.
Customers want more real-time access to support reps including live chat on websites and webinars, according to SuperOffice’s 2023 statistics. The report claims that 41% of customers expect live chat on websites and more than half of all customers prefer chatting in real-time and online rather than calling in or filling out an email request.
Customers willingly share their feedback and detailed reviews about the products or services. However, 79% of customers who use online feedback are ignored (Harris Interactive). Why?
The biggest reason is that Medallia and Qualtrics don’t work systematically or analyze a wide range of channels. These popular Voice of Customer Tools have many benefits. But people often get stuck on which is the best? When the question should be how to utilize them to their fullest potential and their limitations.
So keep reading to know more about this. Let’s get started.
Primary Issues With These CX Tools
Let’s say, you’re running a business focused on improving customer experience by collecting feedback through various channels like survey’s, product reviews, and chatbot transcriptions. From your perspective, everything is perfectly fine. You’ve got a LOT of data to work with. Some items appear more important that others, more urgent. You even hire an analyst team to review it all, which takes months of time. A few good insights come of it, but nothing seems easily actionable or impactful.
You spend months working with the text data to find the gemstones in your customer feedback, and at the end of it all your burnt out, impatiently asking for pinpoint insights that can help tell you where to dedicate resources for the most impact. You think you found a few good items to action, so you do
But it doesn’t. Customer complaints keep piling up and before long you realize not only were you actioning problems that were reported months ago, but new problems have arisen in the time it took for you and your team to find and act. You feel defeated.
Your point of view is not enough, and neither is your analyst team. What do you do?
You’re Focused On Wrong Channels
Suppose your customers leave reviews on Google Maps. But you’re looking for your audience reviews on Glassdoor. You’re also running customer experience survey’s but the responses are low and don’t tell you too much. Why?
You think you’re analyzing the wrong channels. So, you pivot and start ingesting information from all those sources at once. The more, the merrier, right? How overwhelming! So, you begin looking for solutions to help you aggregate this data in one place…
Medallia and Qualtrics have built businesses based on surface-level insights. These are gathered from supplemental channels such as NPS and relationship surveys.
However, there’s a surprising fact about it: These channels can only capture 2% to 5% of customer issues. It means you don’t have data of 95% to 98% issues your customers are facing. It can potentially risk your company’s reputation and revenue, if you’re using customer feedback to analyze and predict trends.
But why?
- The total volume of NPS and ad hoc surveys is low. Several spotty responses. This is because the survey’s have potential to be designed poorly and will affect the quality of responses you get from your customers. If you put low-effort into your survey questions, why do you expect high-effort answers?
- Low-quality data are available and bi-modal because of selection bias among the responders. If you only ask certain people for their opinions, you won’t get the full picture.
Some of the popular responses are either good NPS score, bad NPS score, or no comment. There’s no detailed description regarding why the customer loves or hates the product or service. So, finding the core problem customers are facing can be extremely difficult. Customers are not always willing to happily share reviews. So, you’ve got to strategize how to get them to open up (we will talk more about this in another article).
When you’re connecting with customers through support emails and live phone calls, you can gather details of customer experience. It tells the issues customers are facing and how to resolve these problems. It analyzes and captures the most relevant and useful data.
Belief: NPS + Ad hoc surveys = Full representation of customer issues
But that’s not true at all. It provides a very limited view of what’s happening in the field. This information is not enough to find the problems your customers are facing.
Text Analytical Models Aren’t Advanced Enough or Focus Too Heavily On One Angle
You might wonder. It’s no problem. Medallia and Qualtrics can assist in live chat and email support. That’s how easily they can solve this problem. Right?
Well… half right. The truth is: it isn’t entirely practical. Because not all text analytics models can break down speech or conversation properly. So, the result will be a messy conversation that will be hard to understand. The major reason behind this is that the pre-built models and features are too rigid, such as:
- Keyword clustering
- Topic modeling
- Classifiers
They can listen to limited categories only. It results in a lot of blind spots.
Let’s understand it better with an example:
Let’s suppose there’s a “customer service feedback analysis tool.” It’ll include predefined topics based on popular keywords like “product quality,” “customer service,” or “shipping experience.” These keywords (we call them concepts) are relevant to the tool but only provide generic metrics such as total mentions or overall sentiments.
You’ll have to manually read the survey to identify these words. It completely nullifies the purpose of using automation tools. Understanding feedback, analyzing it, and then processing it is time-consuming for humans.
These models are designed in a way to carry out simple tasks only. These include assigning tags to articles, categorizing them, or adding descriptive insights that align with the conversation. But when it comes to NLP applications, their ranges are very limited, which is a huge problem. Some of the failure points of these models are:
- Poor Grammar: Struggle to interpret feedback accurately. Has too many grammatical errors, misspellings, acronyms, or slang.
- Ignores Semantics: Lack of semantic understanding, thus leading to poor and inaccurate analysis of how a thing is said.
- Can’t Tell New Topics: Since models have predefined categories, they may overlook new issues or trends. Unable to find new topics or see sentiment over time.
- Uninterpretable Results: The analysis output is devoid of context, which makes decision-making and action-planning difficult.
Wow. Do you feel helpless and confused yet? Don’t worry. Keep reading.
Provides Limited & Poor Insights
Many individuals think that comparing Qualtrics and Medallia among other text analytics tools is enough. It’ll help you find the perfect model for your business needs. But it’ll only lead to choosing a model with high-level categorization, which has basic features of sentiment analysis. You’ll have to do a lot of legal work manually. It’ll make you wonder…
Isn’t it defeating the primary purpose of purchasing an AI text analytics tool?
The purpose of analyzing customer feedback is to find customers’ issues and their issues. Not yours. Please, read that again. Here’s how it goes:
Analyze customer feedback → Identify issues → Strategize how to improve it → Act to make customers happy
But for this, you need a real-time list of specific issues. So, basic insight reports won’t help and lack actionable insights.
What Is Luminoso Daylight™?
Luminoso Daylight™ is an AI text analytics platform that helps you comprehend your customers by breaking through all the noise. The platform is an end-to-end solution that utilizes machine learning research and neural networks. Thus improving your results faster and with pinpoint accuracy. The technology was founded out of the MIT Media lab with a focus on debiasing results for the most accurate insights. It can also ingest data from many different sources at once in record time.
We ensure you have the data that helps you understand your customers’ deepest needs, problems, and desires. With this, you can drive critical business decisions with confidence.
Luminoso’s award-winning AI technology goes beyond just analyzing your customer feedback. It explains the ‘how’ and ‘why’ behind the customer responses. Thus, it empowers you to communicate better and innovate in a way that truly resonates with your customers.
Luminoso = AI-powered text analytics + Natural language understanding (NLU) + Sentiment analysis → Redefine how you interact with your customer feedback
Let’s understand it better with a use case.
In the use case, Daylight™ was used to listen to over 10,000 employee feedback survey results. At first, the platform identified positive feedback regarding company benefits and travel bonuses. Everything looked generally pretty good for the multinational corporation conducting the survey. They were about to pat themselves on the back for good behavior when an ugly insight reared it’s head: a manager’s name came up associated with negative sentiment.
Only a handful of employees had complained about their managers behavior, but if it had been overlooked or ignored the situation could have escalated to legal ramifications. Instead, the company was able to address the concerns swiftly and discreetly.
Better yet, the employees who felt safe enough to express this concern in their survey felt as if they’d been heard and they remained anonymous to protect their well-being.
Situations like this are found everywhere, if we listen hard enough. You might be asking, how did the company get employees to open up? I can’t even get customers to tell me about my product!
Good point. It’s all in the delivery and execution of the survey – see this 25-minute video to learn more about how to make a safe place for employees and customers to give you their feedback.
If you don’t have 25-minutes, here’s a 2-minute simple exercise to help improve the feedback you get from customers and/or employees.
What Does The Luminoso Daylight™ Experience Look Like?
Luminoso Daylight™ is not a simple AI tool. It’s software through which users can create surveys, upload their own data, and/or scrape data from the web from places like Amazon, Reddit, and Glassdoor. It also offers comparative analysis views, sentiment over time and a generative AI chatbot to make your data more accessible. Compare different crucial data subsets to find the key differences. It’s a helpful feature in benchmarking or monitoring changes over time.
Because we know relying on Medallia And Qualtrics Aren’t Enough In 2024. Luminoso Daylight™ adopts an approach which is 10x more effective and faster.
With a broad view of data, you can easily make high-level decisions. Conduct concept-level sentiment easily with maximum accuracy. Moreover, there are many integration options, and you can say goodbye to manually analyzing customer reviews. The major problem is cross-team collaboration. With Luminoso, it’s easy to share URLs to preconfigured dataset visualizations, thus speeding up the process.
What If I Already Subscribe To Medallia Or Qualtrics?
Luminoso Daylight™ is extremely effective when used in tandem with other tools. For example, our platform can help speed up Medallia’s implementation to save on costly pro-service hours. Our AI engine covers all the loopholes and blind spots created or overlooked in these systems, making it one of the most powerful tech-stacks on the market today.
You can easily import and analyze your customers’ data daily.
Through its integration with Medallia and Qualtrics, Luminoso streamlines the data analysis and interpretation process. Thus empowering users to derive actionable insights more efficiently.
Ready To Use Luminoso Daylight™?
Luminoso Daylight™ is an incredible tool for teams to get started with no-code AI text analytics and concept-level sentiment. Contact us today if you’re ready to take your business to the next level and incorporate real customer feedback. We’ll analyze your company’s customer reviews and show you real and unbiased data.
Want to take the first step?
Book your personalized demo, and let’s discuss how Luminoso Daylight™ can significantly help your business.
