Your Customers Don’t Love You—They Tolerate You. Here’s Why That Matters.
Look, I hate to be the bearer of bad news, but your customers don’t actually care about your brand. Not really. Sure, they might say nice things in a survey, drop the occasional five-star review, or even gasp follow you on LinkedIn. But when it comes down to it, most businesses are just background noise in their customers’ lives.
And yet, companies spend fortunes trying to measure something as fragile as "customer loyalty" using outdated, misleading metrics. You know the ones:
✅ Customer Satisfaction Scores (CSAT) – Because answering "How satisfied were you with our service?" on a scale from 1-10 is obviously the key to business growth.
✅ Net Promoter Score (NPS) – A single-question survey that assumes people really sit around thinking, “Would I recommend this company to a friend?” (They wouldn’t. Not unless it’s a pizza place.)
✅ Churn Rate – Which tells you that people left, but never why.
None of these metrics tell you what your customers actually think.
If you’re going to all these lengths to collect customer feedback, wouldn’t you rather get the truth?
Why Your CSAT Score Is Lying to You
CSAT scores are the corporate equivalent of a polite nod. Customers don’t want to offend you, so they give you a 9/10. But would they buy from you again? Maybe. Would they switch to a competitor if they got a slightly better deal? Yes.
This can become dangerous because… If you’re relying on CSAT, you might think your business is thriving! …right up until you wonder why revenue is shrinking and nobody’s renewing their subscriptions.
Customers don’t tell the truth in surveys. They:
Give high scores just to get rid of the survey pop-up.
Answer differently based on mood (a good cup of coffee before filling out your survey can change everything).
Say they’re happy but then ghost your business when a better option comes along.
So, if CSAT scores don’t predict loyalty, and NPS is just a glorified popularity contest, what should you be measuring?
The Only Thing That Actually Tells You the Truth: Language
Forget numbers. If you want to know what your customers really think, listen to their words.
People reveal everything in the way they phrase things. Even when they’re trying to be nice, they can’t hide their real emotions.
🔍 “It was fine.” → Translation: It was not fine.
🔍 “The process was smooth, but it took a while.” → Translation: It was slow.
🔍 “I love the product! I just wish it had a few more features.” → Translation: I’m looking at your competitors.
This is where open-ended questions make all the difference.
A CSAT score might tell you that someone rated you 7/10—but that doesn’t explain why. If you follow up with “What nearly stopped you from choosing us?” you’re inviting honest feedback. And when you collect hundreds (or thousands) of responses like that? That’s where the magic happens.
Why Most Companies Fail at Open-Ended Survey Analysis (And How to Fix It)
Open-ended survey responses are where the real customer insights live. But because of the scale and nuance that comes with, most companies have no idea how to handle them
If you've ever stared down thousands of free-text responses, you know the pain. Most businesses either:
❌ Ignore open-ended questions because they seem impossible to accurately analyse.
❌ Burn money on hiring a poor soul to manually read and summarise them (slow, expensive, and riddled with human bias).
❌ Use basic AI sentiment analysis, which reduces rich, complex feedback into a simplistic “positive” or “negative” label. (Not helpful.)
But - and you won’t be surprised to hear - language is complicated! Customers don’t always say exactly what they mean. They use sarcasm, imply things without stating them outright, and rely on context that AI sentiment trackers just simply cannot pick up on.
Now, Let’s talk Leximancer.
Instead of forcing customer feedback into rigid pre-set categories (which introduce bias), Leximancer automatically builds a thesaurus from your data. That means:
✅ Understands how words evolve in context – "cheap" can mean "affordable" or "low quality" depending on how it's used. Leximancer doesn’t assume—it learns from the data itself.
✅ Groups related words automatically – Customers might say “slow,” “takes ages,” and “not fast”—Leximancer sees the connection, even when the phrasing is different.
✅ Finds the patterns you’d never think to look for – Sometimes the problem isn’t the loudest complaint—it’s the theme that keeps showing up in unexpected places.
✅ Works without pre-set dictionaries or human bias – Other tools tell your customers what they mean. Leximancer lets them speak for themselves.
Unlike traditional text analysis tools that impose external dictionaries or coding schemes, or having an “educated guess” after looking at your survey responses, this inevitably introduces a tonne of bias (and mate, let’s be honest, when it comes to your own company of course you’re going to have a lot of bias!). Leximancer works directly with your customers’ words, on their terms.
Instead of drowning in survey data, you get clear, unbiased, and reproducible insights, showing not just what people are saying, but how different themes are interconnected across your customer base.
Because if you’re going to ask for feedback, wouldn’t you rather know what people actually mean?
How Businesses Actually Used This to Avoid Disaster
💫 The SaaS Company That Thought Customers Loved Them (Spoiler: They Didn’t)
A software company had stellar CSAT scores, averaging 9.2/10! So imagine their shock when their churn rate spiked. Turns out, customers weren’t happy, they were resigned.
Leximancer revealed that while feedback contained words like "satisfied" and "smooth," it also included recurring themes like frustration, workaround, and complex.
Customers weren’t leaving because they hated the product. They left because they tolerated it until they found something easier to use. The company simplified onboarding, made key features more intuitive, and stopped mistaking politeness for loyalty.
💫 The Retailer That Realised “Convenience” Meant Something Else Entirely
A major retailer believed their customers loved the “convenience” of their stores. But Leximancer picked up on something interesting… customers repeatedly mentioned “close by” and “only option” when talking about shopping there.
Translation? People weren’t going there because they loved the store. They went because it was the least annoying choice available.
So, what did the company do? They improved customer experience, expanded delivery options, and made loyalty rewards actually worth something. Suddenly, they weren’t just the closest option, they were the preferred one.
Let’s Be Honest—Do You Really Know What Your Customers Think?
Ready to stop relying on vanity metrics and start making smarter business decisions?
👉 Try Leximancer today and start uncovering the truth in customer feedback.
Reach out to me at supportteam@leximancer.com to see it in action.
