Customer Experience

What Customers Say About You vs What They Actually Do

First published Feb 9, 2023Updated September 7, 20269 min read
Andrada Vonhaz
Andrada Vonhaz
Published: Feb 9, 2023Updated: Sep 7, 2026
Speech bubble with a star rating next to a blue shopping cart holding purchases
Quick Answer
What customers say about you is the opinion they publish or report: reviews, ratings, survey answers, support messages and social posts. You find it by reading your own reviews and tickets, monitoring the web with tools such as Mention, Tagboard and Google Alerts, and asking directly with on-site and post-purchase surveys. Treat all of it as stated preference. It tells you the language, the motives and the complaints, but not the behavior. What customers do on your site is revealed preference, and the two often disagree. The reliable method is to collect what customers say with surveys in Omniconvert Explore, turn each recurring statement into a hypothesis, then run an A/B test to see whether changing it changes what shoppers actually do.
Key Takeaways
  • What customers say is stated preference and what they do is revealed preference. Both are real data, and they answer different questions.
  • BrightLocal's Local Consumer Review Survey 2026 reports that 97 percent of consumers read reviews for local businesses, so the opinions you never read are still shaping your sales.
  • Your own reviews and support tickets are the cheapest and most specific feedback you own. Read those before you buy a listening tool.
  • You cannot control what customers say, but you can decide the three to five sentences you want them to repeat, then build the service that earns them.
  • A complaint is a hypothesis, not a conclusion. Confirm it with an A/B test before you rebuild a page around it.
97% read reviews (BrightLocal 2026) 70,000+ Omniconvert experiments 23.2% average uplift with Explore 7,000+ websites analyzed

What your customers say about you is every opinion they publish or report: star ratings, written reviews, survey answers, support messages, social posts and comments. You find it by reading your own reviews and tickets, by monitoring the rest of the web with tools such as Mention, Tagboard and Google Alerts, and by asking directly with on-site and post-purchase surveys.

The part most teams skip is what to do with it afterwards. What customers say is one kind of data, and what customers do on your site is another. They come from different places, they disagree more often than you would expect, and neither one is a lie. This article covers where to find what customers say, how to read it honestly, and how to confirm it against behavior before you rebuild a page around a comment.

What "what customers say about you" actually means

What customers say about you is the set of opinions they state in public or in private: reviews and ratings, survey and NPS answers, support tickets, chat transcripts, social posts and word of mouth. It is self-reported data. It carries the reasons, the emotions and the exact language customers use, which no analytics report contains, and it is the fastest way to find out what your brand looks like from the outside.

It arrives in three forms, and they are not interchangeable.

  • Solicited feedback. You asked: surveys, NPS, review requests, interviews. You control the question, so you can aim it at a specific page or moment.
  • Unsolicited feedback. They chose to speak: public reviews, social posts, forum threads, blog comments. You do not control the question, which is exactly why it surfaces problems your survey never thought to ask about.
  • Service feedback. They needed help: tickets, chats, returns, complaints. This is the most concrete of the three, because every item is attached to a real order that went wrong.

All three describe experience. None of them measures it.

Say versus do: the gap you have to plan for

What customers say is stated preference, the reasons and intentions they report. What customers do is revealed preference, the clicks, scrolls and purchases recorded on your site. Stated preference explains motives and gives you language. Revealed preference proves behavior. When the two disagree, customers are not lying, they simply cannot fully observe their own decisions, so use what they say to build hypotheses and what they do to settle them.

The gap is ordinary and predictable. Shoppers say price is the reason they left, then buy the more expensive bundle. They say they want more choice, then abandon a 40-item category page. They rate a checkout "fine" in a survey and drop out of it twice the same week. People report the reason that sounds sensible, not the reason that operated.

The practical consequence: never treat a survey answer as a finding. Treat it as a candidate explanation that has to earn its place.

Source: Omniconvert
Signal What it is good for What it cannot tell you How to confirm it
Reviews and ratings Recurring product and delivery failures, in customer language How many silent buyers had the same problem Match complaint themes against return and repeat-purchase rates
On-site surveys Objections at a specific page or step, while the visit is live Whether removing the objection changes the outcome A/B test the page change the answer implies
NPS and its follow-up A trend line everyone understands, plus stated reasons Which touchpoint caused the score Segment the score by source, device, product and order history
Support tickets Concrete failures tied to real orders Problems from customers who leave rather than complain Compare ticket themes with drop-off points in analytics
Social and web mentions Reputation, competitor comparisons, unprompted praise Whether the loudest voice represents your buyers Check whether the theme also appears in owned feedback
Behavioral analytics What people actually did, at scale Why they did it Ask, with a survey aimed at that exact step

Why it matters to know what customers say about you

Knowing what customers say about you tells you what to fix and in what order. It shows where your service misses expectations, what competitors do better, which needs are about to become standard, and which complaints will become public bad reviews if nothing changes. It is also cheap: every fix you make is aimed at a problem a real buyer already described, instead of at a guess.

Think about how you buy. You ask a friend which restaurant is good. You read the reviews of a television before Black Friday. Your customers do the same, and they do it about you. According to BrightLocal's Local Consumer Review Survey 2026, 97 percent of consumers read reviews for local businesses, and the share who say they always read them rose from 29 percent to 41 percent in a year. That survey covers local businesses rather than all of eCommerce, so read it as a direction rather than a benchmark for your store, but the direction is not in doubt.

You learn more about your own business

Feedback tells you what is going wrong, where, and for whom, and it also tells you what already works so you stop redesigning it. Your job as a seller is to meet demand you did not invent, and the fastest description of that demand comes from the people who paid.

You learn more about your competitors

Your customers shop your competitors too, and they will tell you about it. When someone explains why they left another store, read it closely: why did they stop buying there, and what made them choose you? Their competitor reviews are a free audit of what a rival offers that you do not.

You can anticipate what customers will want next

Praise ages. If customers currently love your next-day delivery, and two competitors now offer the same, the compliment is about to become the baseline. Take what makes people happy today and improve it before the market forces you to.

You prevent bad experiences from spreading

No store is perfect, and a single bad review is not a crisis. A repeated bad review is, because it is public, permanent and read by the majority of buyers before they decide. Reading feedback weekly turns a pattern into a fix while it is still small.

Where to find what customers are saying

Start with the feedback you already own: your product reviews and your support tickets. Then widen the net with a media monitoring tool such as Mention for posts, comments and press mentions, a hashtag tracker such as Tagboard for campaign and event conversation, and Google Alerts for keyword mentions across the web. Finally, ask directly with on-site and post-purchase surveys, the only source where you choose the question.
  1. Read your own reviews and tickets first
    Sort by the lowest ratings and by the reviews that contain a suggestion, then list every complaint that appears more than twice. This costs nothing, it is specific to your catalog, and it usually fills a quarter of your roadmap.
  2. Monitor mentions across the web
    Mention tracks who talks about you across social platforms, blogs, review sites and press, and it does the same for competitors and category terms. Use it to catch conversation that never reaches your own properties.
  3. Track your hashtags around campaigns and events
    If you run a branded hashtag, or one for an event or promotion, Tagboard collects and displays the posts that use it. This is the fastest read on how a campaign landed while it is still running.
  4. Set up Google Alerts for brand and product terms
    Alerts for your brand, your key products and common misspellings deliver new web results to your inbox. It is crude compared with a monitoring platform, it is free, and it catches the article nobody told you about.
  5. Ask directly, at the right moment
    Listening only collects the opinions people volunteered. Surveys in Omniconvert Explore let you ask a specific question at a specific step, on-site during the visit or after purchase, so you learn about the pages nobody writes reviews about.
  6. Put it all in one list, grouped by theme
    Feedback in five tools is feedback in no tool. Once a month, merge everything into a single list grouped by theme, with a count next to each theme. Frequency, not volume of words, is what tells you where to start.

How to check what customers say against what they do

Turn each recurring statement into one sentence that could be false, change the page so the complaint no longer applies, and run it as an A/B test against the current version with a revenue-related metric. If the variant wins, the complaint described a real obstacle. If it does not, the complaint was honest but was not the reason people leave, and the search continues.

This is the step that converts feedback into money. A comment on its own is a story. The same comment, written as a hypothesis and tested against the live site, is a decision you can defend.

  1. Write the complaint as a falsifiable hypothesis
    "Shoppers abandon the cart because the delivery cost appears too late" can be wrong. "Customers want a better experience" cannot, so it is useless.
  2. Change one thing that removes the obstacle
    Show the delivery cost on the product page. Keep the rest of the page identical, or you will not know which change did the work.
  3. Run it as an A/B test with a money metric
    Conversion rate, revenue per visitor or completed checkouts. Satisfaction with the new page is not evidence that the new page sells more.
  4. Read the result by segment
    A change often helps mobile visitors and does nothing on desktop, or helps new customers and annoys returning ones. A flat average hides both.
  5. Feed the answer back into the next question
    A losing test is not a wasted test. It removes one explanation, which narrows the next survey question to something sharper.

Ask on-site, then prove it with an A/B test. Omniconvert Explore combines surveys, NPS and experimentation in one platform.

See Explore →

Deciding what you want customers to say about you

You cannot control reviews, but you can decide which sentences you want customers to repeat, then build the service that earns them. Write three to five statements such as "They always keep me informed" or "They solve problems fast", make each one true in the operation, and ask for feedback at the moment the customer has just experienced it. Existing customers who repeat those sentences become your cheapest acquisition channel.

The trick is not to discourage reviews or silence criticism. It is to choose the praise you intend to deserve. For an eCommerce business, the shortlist usually looks like this:

  • They have the best products.
  • They always keep me informed.
  • They are problem solvers.
  • They respect me.
  • I trust them.

Pick three. For each one, name the process that produces it, the person who owns it and the moment the customer feels it. "They always keep me informed" is a shipping notification schedule and a support reply time, not a value on an About page. Then ask for the review immediately after that moment, because a customer who has just been kept informed writes a different review than one asked six weeks later.

NPS and how to choose NPS software

Net Promoter Score asks how likely a customer is to recommend you on a 0 to 10 scale, then sorts answers into promoters, passives and detractors. The score is a simple trend line the whole company understands, and the follow-up question is where the value sits, because customers explain the score in their own words. Choose software with a true 0 to 10 scale, flexible triggers, a follow-up question, segmentation and trend reporting.

Word of mouth still sells, so knowing whether customers would recommend you is worth measuring. Market research metrics are often complex; NPS is not, which is why it survives. A falling score is an early warning that the experience is slipping. A rising one is evidence that a customer-centric strategy is working. Because it is measured the same way every time, it is comparable from one quarter to the next.

The score alone is thin. Its usefulness comes from the free text underneath it and from segmentation: an NPS of 40 that hides a 10 among first-time buyers is a very different business problem from a flat 40 everywhere.

When comparing tools, check for:

  • A true 0 to 10 scale, so your score is comparable with everyone else's.
  • Flexible triggers, so you can ask after delivery or after support contact, not on every page view.
  • Follow-up questions, so respondents explain the number.
  • Segmentation, by traffic source, device, product, order history and customer value.
  • Readable reporting, showing the trend and the verbatim answers side by side.
  • A path to action, ideally a survey tool inside the same platform as your testing tool, so an answer becomes an experiment without an export.

If retention is the reason you are asking, connect the answers to customer value. Nexus by Omniconvert segments customers by recency, frequency and monetary value, so you can read what your highest-value customers say separately from everyone else's opinion.

Frequently Asked Questions

1How do I find out what customers say about me?

Read your own product reviews and support tickets first, because they are free and specific. Then add a media monitoring tool such as Mention to catch posts, blog comments and press mentions outside your site, a hashtag tracker such as Tagboard for campaign and event conversation, and Google Alerts for keyword mentions across the web. Finally, ask directly with on-site and post-purchase surveys, which is the only method that lets you choose the question.

2What is the difference between what customers say and what customers do?

What customers say is stated preference: the reasons, opinions and intentions they report in reviews, surveys and interviews. What customers do is revealed preference: the clicks, scrolls, add-to-carts and purchases recorded on your site. Stated preference explains motives and language. Revealed preference proves behavior. Customers are not lying when the two disagree, they simply cannot see their own decisions clearly, so use what they say to form hypotheses and what they do to confirm them.

3Why is customer feedback important for eCommerce?

Customer feedback tells you what to improve and in what order. It shows where your product or service misses expectations, what competitors offer that you do not, which needs are about to become standard in your category, and which complaints will turn into public bad reviews if you ignore them. It is also cheaper than guessing, because every fix you make is aimed at a problem a real buyer already described.

4How many consumers read online reviews before buying?

According to BrightLocal's Local Consumer Review Survey 2026, 97 percent of consumers read reviews for local businesses, and 41 percent say they always read reviews when browsing for a business, up from 29 percent the previous year. The survey covers local businesses rather than all eCommerce, so treat it as directional, but the direction is clear: most buyers read what other buyers wrote before they decide.

5How do I decide what I want customers to say about me?

Write down three to five sentences you want customers to repeat about you, such as 'They always keep me informed' or 'They solve problems fast'. Each sentence must point at a service you can actually deliver. Then change the operation so the sentence becomes true, measure the touchpoint that produces it, and ask for reviews at the moment the customer has just experienced it. You cannot control reviews, but you can control the experience that produces them.

6How does NPS help you understand what customers say?

Net Promoter Score asks how likely a customer is to recommend you on a 0 to 10 scale, then groups answers into promoters, passives and detractors. The score itself is a simple trend line anyone in the company understands. The value sits in the follow-up question, where customers explain the score in their own words. That free text is the raw material for product fixes, page copy and test hypotheses.

7What should I look for in NPS software?

Look for a true 0 to 10 scale, flexible triggers so you can ask at the right moment rather than on every page, an open follow-up question, segmentation so you can read the score by traffic source, device, product or customer value, and reporting that shows the trend over time. It also helps if the survey tool lives in the same platform as your testing tool, so an answer can turn into an experiment without an export.

8How do I test whether customer feedback is right?

Turn the feedback into one sentence that could be false, such as 'shoppers abandon the cart because delivery cost appears too late'. Change the page so the complaint disappears, run it as an A/B test against the current version, and pick a metric that reflects money rather than opinion. If the variant wins, the feedback described a real obstacle. If it does not, the complaint was real but not the reason people leave, so keep looking.

What to do this week

Spend one hour with your last 50 reviews and your last 50 support tickets, and write down every complaint that appears more than twice. That list is your backlog, ordered by how often real customers mention each item. Put an on-site survey on the two pages where the complaints cluster and ask one open question, because the words customers use are the words your page should use. Then take the single loudest complaint, turn it into a page change, and A/B test it. You will learn two things at once: whether the fix moves revenue, and whether what your customers say about you matches what they do on your site.

Andrada Vonhaz
Andrada Vonhaz
My journey in marketing and technology has always been fueled by a relentless passion for innovation. It all began in 2016 when I delved into the fundamental aspects of content and copywriting, alongside mastering social media dynamics, SEO, and PPC tactics. By combining these elements, I cultivated a deep understanding of marketing strategies, polished my project management skills, and became adept at communicating and monitoring marketing initiatives from inception to completion. My guiding principle is rooted in the belief that there’s always something new to learn and apply. It’s this mindset that drives me to continually evolve and innovate in the dynamic worlds of marketing and technology.

Ask your customers, then prove the answer

Omniconvert Explore runs on-site and post-purchase surveys, NPS and A/B tests in one platform, so a complaint can become an experiment on the same day. Across 7,000+ websites and 70,000+ experiments, brands using Explore see an average uplift of 23.2%.