CX is suffering, but text analysis empowers companies to harness AI and deliver better customer experiences to improve retention and growth.
Customer Experience is Suffering
In June 2024, Forrester reported that CX quality among brands in the US sat at an all-time low after declining for an unprecedented third year in a row. Several factors contributed to the decline. These included:
- “Brands’ inability to provide seamless customer and employee experiences
- Underwhelming digital experiences using chatbots
- Consumers’ concerns about their personal financial situations, society, and the economy at large.
With Accenture finding that 37% of people think companies are prioritizing higher profits over better customer experience, there’s clearly a lack of trust and a feeling that companies may not care about the customer experience.
How much should companies be concerned? Answer: A lot. McKinsey found that companies that care about customer experience tend to have 2X the growth of companies that don’t.
Caring about the customer experience is good business. However, companies are struggling to meet customer expectations. The best way to combat low customer satisfaction is to listen to what customers have to say—in their own words.
The Open Text Feedback Challenge
Businesses solicit feedback in surveys, polls, social media posts, reviews, and more. And that feedback comes back to you in two different ways:
- Structured feedback: Answers to survey questions using radio buttons or checkboxes.
- Unstructured feedback: Any text response sent to you via survey, social media, review site, or other sources.
Structured feedback (the type coming to you from limited selection options, like the radio buttons or multiple choice you create in your survey) can be useful because it is quantifiable. You take notice when someone rates you a zero. But structured feedback doesn’t tell you the full story of the customer’s experience. Without understanding the why behind the number, you don’t have much to act on.
By contrast, unstructured feedback is full of valuable insights and sentiments. However, sorting, tagging, and analysis are obstacles to understanding that feedback and making it valuable to your business.
In short, unstructured feedback is often the best representation of the customer experience, despite current challenges with quantifying that feedback. Businesses need to harness this unstructured feedback to improve their overall customer experience.
AI-Powered Text Analysis to the Rescue
Text analysis helps business professionals understand what customers really think and feel — in their own words.
In effect, text analysis is crunching words into numbers, transforming that qualitative feedback into measurable, actionable quantitative data.
Text analysis platforms are often powered by artificial intelligence (AI) and the large language models (LLMs) that underpin the technology. If you want to improve your customer experience, look for these five AI capabilities in any text analysis platform you select.
Conceptual themes and phrases
Your AI-powered text analysis platform should perform two approaches. A “top-down” approach that continuously classifies feedback based on a collection of strategic pre-defined themes. The second is a “bottom-up” approach that continuously extracts and clusters what users actually say in their own words.
Most importantly, your AI-powered platform should understand the emotions that users express. The combination of these approaches allows you to have a high-level understanding of the biggest positive/negative impacts on customers while giving you the details needed to take necessary action.
Insight assistant highlights
Your AI-powered LLMs should summarize the most important points expressed by users. This delivers comprehensive and context-rich summaries of customer feedback, reducing the need for extensive manual review and enabling faster decision-making.
Anomaly detection
Sometimes things go wrong (or right). Your AI should alert you to key anomalies in the data, so users can quickly investigate emerging issues before they become full-blown problems.
Translation
AI has evolved in a big way when it comes to translations. Your AI platform should be able to continuously translate customer feedback to and from any language quickly. This will enable you to understand feedback from customers all over the world.
Impact analysis
Your AI-powered text analysis platform should give you in-depth, granular analytics that helps you measure the impact of customer sentiment on key Voice of the Customer metrics. These include high-level scores, like NPS or Net Sentiment, as well as key business outcomes, for example, SaaS customer retention or physical product returns. Ensure your platform comes equipped with impact analysis to both measure sentiment and prove value to the business.
Why Text Analysis Matters
Before AI-powered text analysis, tagging feedback with sentiment was a manual, time-consuming process. Businesses, therefore, resorted to traditional checkboxes and radio buttons to collect quantifiable customer feedback. But checkboxes and radio buttons can hardly encompass the entirety of the customer experience.
Text analysis turns this model on its head, empowering companies to collect unstructured feedback data — the most valuable feedback available — to understand what is going right and wrong with their business.
Only by understanding customer themes and sentiment at scale will companies identify how to improve their customer experience and reap the valuable rewards of being a customer-obsessed business, like the 2X revenue growth reported by McKinsey.
AI is no longer a “pie in the sky” technology. A great AI-powered text analysis platform can make it easy to understand your customers in their own words, and turn that understanding into business impact.
Alchemer empowers you to do more with feedback. From a one-time survey to a powerful feedback program, Alchemer gives customer-obsessed teams the clarity to move from asking to action, driving your business forward. Expect more from feedback.
