What Are Your Customers Trying to Tell You? Using AI to Improve Customer Insight and Digital Marketing
Insights | 2 October 2026
Companies have access to more customer data than ever before. Yet one of the most valuable sources of insight is often overlooked: what customers are actually saying.
Customers ask questions in chat, submit enquiries, discuss products and services on social media, compare alternatives on forums and share their experiences in online communities.
These conversations can contain surprisingly direct answers to questions marketers ask all the time:
What is the customer unsure about before making a purchase? What prevents them from getting in touch? What information is missing from the website? What words do customers use to describe their needs? And what ultimately convinces them to choose one company over another?
The challenge is not necessarily a lack of information.
The challenge is that the information is scattered across different channels and exists in large volumes.
This is where AI becomes particularly useful.
The voice of the customer already exists, but the information is scattered
Customer insight is traditionally built through surveys, interviews and analytics. All of these still have an important role.
At the same time, companies continuously accumulate another valuable source of information.
Customers contact customer service with questions. The same topics come up repeatedly in chat conversations. Sales teams receive requests for clarification. People comment on social media posts. Online communities compare options and ask others about their experiences.
The problem is often not that this information is unavailable.
The problem is that no one has time to read thousands of conversations, categorise them by topic and compare the findings with the content already available on the website.
AI can help with exactly this.
AI can turn large volumes of conversations into usable customer insight
AI should not be seen only as a tool for writing ad copy or blog articles.
One of its most interesting applications in marketing is analysis.
For example, we have used AI to analyse customer service chat conversations. Instead of focusing on individual conversations, AI can help identify recurring patterns across a much larger dataset.
Why does the customer get in touch? Which questions appear repeatedly? At what point does the customer need help from a person? What information were they unable to find on the website?
This changes the role of customer service conversations.
They are no longer just customer service data. They also become a source of insight for website development, content marketing and digital advertising.
What should you look for in customer conversations?
A single customer question may not tell you very much. But when the same question, concern or uncertainty appears in dozens of conversations, it can become highly relevant.
AI can help identify themes such as:
- recurring questions
- common customer concerns
- barriers to purchase or contact
- features or qualities customers consider important when comparing alternatives
- the language and terminology customers use
- products, services, pricing or processes that require more explanation
- factors that increase or reduce trust
- situations where the website does not provide a sufficient answer.
The last point is particularly important.
If customers repeatedly ask customer service about something the website should already explain, it may be a website issue rather than merely a customer service issue.
Online discussions reveal what happens before the customer contacts you
A company’s own customer service conversations tell you a great deal about people who have already reached the business.
But what happens before that?
Customers may discuss their needs on Reddit, Facebook groups, Threads, discussion forums and other online communities long before they visit a company’s website.
Analysing these conversations can provide a different view of the customer journey.
What alternatives are people comparing? What are they worried about? What kinds of experiences do they ask others about? What creates mistrust? Which features are recommended, and why?
When a sufficiently large body of discussions is analysed as a whole, recurring themes can emerge that would be difficult to spot from individual conversations.
Again, AI is most useful when it helps people find the relevant patterns within a large amount of information.
The most interesting step is comparing customer questions with the website
Simply listing discussion themes does not improve marketing.
The next step is to compare those findings with the company’s existing website.
If customers frequently discuss pricing, delivery, the buying process, differences between alternatives or whether a service is suitable for their situation, does the website answer those questions clearly enough?
AI can also support this comparison.
For example, the analysis can ask:
What do customers talk about a lot that the website barely addresses?
The answer may reveal opportunities for new service-page content, FAQ sections or entirely new articles.
Which questions could prevent a customer from getting in touch?
If the customer does not understand the price, process or next step, the issue may also be a conversion optimisation problem.
Does the company use the same language as its customers?
Professional terminology used internally may be very different from the words customers actually use. Customer conversations can reveal terms, questions and phrases that are useful for website content and search engine optimisation.
Is important trust-building content missing from the website?
References, customer experiences, explanations of the process, employee expertise, pricing logic and practical examples may matter more to customers than the company itself realises.
Customer insight should also shape advertising
These findings should not be limited to the website.
Once you understand what customers care about, what worries them and what questions they have, advertising can become more relevant as well.
An ad does not always need to begin with what the company wants to say.
It can begin with what the customer wants to know.
For example, if online discussions repeatedly highlight concerns about price, durability, service speed or whether a solution is suitable for a particular situation, those topics can also become useful advertising angles.
Customer insight can then create a clear chain:
customer conversations → website content → advertising message → landing page → conversion.
Advertising and website development are no longer separate activities. Both are built around the same real customer needs.
Don’t just ask AI: “What should we write about?”
The quality of AI-assisted work depends heavily on the questions you ask.
If the only instruction is “write us a blog post”, the result can easily become generic.
More useful questions might include:
“What problems repeatedly appear in customer conversations?”
“Which of these problems are likely to affect the purchase decision?”
“Which customer questions does our website currently fail to answer?”
“What do customers compare before choosing a provider?”
“Which factors increase trust?”
“Which three website changes would best address the needs found in these conversations?”
In this role, AI becomes less of a copywriter and more of an analyst.
In practice, the process can be surprisingly simple
Using customer insight does not have to begin with a major AI project.
The first analysis can already be valuable with a relatively limited dataset.
- Gather the data
The data could include customer service chats, enquiries, online discussions, customer feedback or other customer-generated text.
- Identify recurring themes
Which questions, problems, concerns and needs appear repeatedly?
- Compare the findings with the current website
Can customers find the answer easily? Is the information in the right place? Is it easy to understand?
- Prioritise the findings
Not everything needs to be changed. Start with themes that appear frequently and are likely to influence the customer’s decision or willingness to get in touch.
- Turn the findings into action
The result might be a new piece of content, an updated service page, a clearer CTA, a new advertising angle, an FAQ section or an entirely new way of guiding visitors through the website.
AI does not know your business better than you do
AI can process large amounts of information quickly and identify recurring patterns.
That does not mean every conclusion it produces should be implemented as such.
People still need to decide which findings are genuinely relevant to the business.
This distinction matters.
At its best, AI does not decide what a company should do. It helps uncover patterns and observations that would otherwise require significantly more time and manual work.
The expert’s role is to turn those findings into the right decisions.
Your customers may already have told you what your website is missing
When companies start improving their website or marketing, ideas often come from inside the organisation.
What should we say? What should we write about? What should we advertise?
An equally important question is:
What are our customers trying to tell us?
The answer may already exist in customer service conversations, online communities, feedback and other customer data.
AI can make that information easier to uncover – and, more importantly, easier to turn into concrete improvements in website content, conversion optimisation and digital marketing.
Want to find out what your customers are trying to tell you?
At Digizer, we can combine customer insight, AI-assisted analysis and practical digital marketing development.
For example, we can analyse the needs and questions appearing in customer conversations, compare them with your current website and identify concrete opportunities to improve content, conversions and advertising.
Get in touch and let’s find out what your customers’ conversations can teach you and how those insights can be turned into better digital marketing.
Digizer Oy is an Oulu-based digital marketing partner and a Google Premier Partner, ranking among the top 3% of Google partners in Finland. We help growth-focused companies turn marketing into a measurable source of sales, from strategy to channel execution. Digizer is part of the HT Growth Partners group.