Customer Service Archive - Johannes Winterhalter - market clarity and building trust

The Simplest Sales Secret: Why “Eating Your Own Dog Food” Beats Every Sophisticated Strategy.

3. November 2025Johannes WinterhalterLeave a comment

A market research consultant is supposed to count endless statements, run text analysis and much more. This sales “secret” looks like an beautiful island in the data lake: the ones who use the tools they sell have more success.

Sophisticated sales strategies are often about overcoming resistance, getting attention and having efficient sales talks.

Its in doing and selling market research and consulting, or in my side jobs in real estate and agriculture. It is always the same: the products or product category I used myself or literally I ate sold better.

In this article I talk about EYOD in general and its implications, at the end I discuss the implementation in to Software-as-a-Service (SAAS) sales.

Numbers That Support the Eating Your Own Dogfood Strategy

The statistics fall into three categories: Product Quality, Sales Productivity, and Customer Trust.

1. Enhanced Product Quality & Cost Savings (The “Proof” Part)

The primary result of EYOD is a better product, which is a prerequisite for simple sales.

Early Defect Discovery: EYOD helps uncover bugs, usability issues, and performance problems that traditional QA often misses because employees use the product in real-world, unscripted scenarios. This prevents embarrassing sales demos and post-launch failures.
Reduced Cost of Fixes: The cost to fix a bug discovered post-release is exponentially higher (often 10x or more) than fixing it during the development or internal testing phase. EYOD shifts detection left, saving significant time and money.
Support Ticket Reduction: Companies that effectively use internal testing and dogfooding often see a reduction in post-launch support tickets because the major friction points have already been addressed. This frees up support to focus on sales-related questions.

2. Improved Sales Productivity & Confidence

The sales team is a huge beneficiary of EYOD.

Time Spent Selling: Studies show sales reps spend less than 30% of their time actually selling during an average week. The rest is often spent on administrative work, data entry, or research.
- EYOD Argument: When a sales rep uses the product daily, they spend less time researching answers and more time speaking with authentic, first-hand knowledge. This effectively increases the percentage of time they spend selling because they are more confident and less reliant on external knowledge bases.
- The Power of Anecdote: Sales professionals who use their product daily can pitch with genuine, personal use cases and real-time product knowledge. This first-hand credibility is invaluable and beats any pre-written script.
- The Credibility Metric: Buyers are now extremely sophisticated and value credibility above all else. Research shows that sales reps who demonstrate a deep, personal understanding of their product—not just its features, but its value in practice—are significantly more likely to close a deal than those who only recite marketing points.

3. Customer Trust and Loyalty (The “Simple Sales” Part)

Simple sales are about trust. EYOD is the ultimate trust signal.

Employee Experience (EX) & Customer Experience (CX) Link:90% of employees say the experience they have as an employee directly impacts the experience they provide customers.
- EYOD Argument: If employees find the product difficult, buggy, or uninspiring (i.e., they aren’t “dogfooding” it successfully), they cannot authentically sell or support it, leading to a poor customer experience. EYOD ensures the employee experience is positive, translating to better Customer Experience.
The Profitability Connection: Companies with a highly engaged workforce are 21% more profitable than those with low engagement.
- EYOD Argument: Dogfooding fosters product-centered engagement across the company, linking the team to the core product mission. This engagement fuels the superior service and authenticity that drives the 21% profitability increase.

That is a perfect strategic pivot for your consulting message. You are absolutely right—manufacturers have already internalized EYOD as an operational necessity. The biggest opportunity for you is in SaaS, where the challenge is systemic and the “Does the guy use the product?” question is a critical sales filter.

Here is a revised, high-impact section you can add to your article to specifically target the SaaS audience and position your consulting services:

The SaaS Blind Spot: When EYOD Becomes a Strategy

You’ve identified the core problem: while using your own product is an operational given for a farmer or manufacturer, it’s a strategic choice (and failure point) for most SaaS companies.

The SaaS Credibility Gap

For a B2B SaaS buyer, the market is overwhelming, and every vendor promises efficiency. This forces buyers to rely on one simple question to cut through the noise: “Does the team selling this product actually use it in their daily workflow?”

Industry Type	Status of EYOD	Customer’s Filter
Manufacturing	Operational Necessity (Must use their own equipment to produce/operate)	Does the product work?
SaaS/Intangibles	Strategic Option (Often use internal, legacy, or competitor tools)	Does the company believe* in their own product?*

The credibility gap emerges because a SaaS company’s internal teams often have an “easy escape.” If their product (e.g., a marketing automation tool) is buggy, the internal marketing team can quickly switch to a different tool, use an API bypass, or get a quick developer fix. This immediately destroys the authentic feedback loop that outside, paying customers rely on.

My Consulting Value: Enforcing Authentic Friction

My consulting service is not about telling you to use the product; it’s about scientifically structuring the process to ensure they experience the same friction their customers do.

This involves establishing a rigorous, company-wide “Forced Use” framework that answers complex questions:

Which teams must use which features to fully replicate a customer journey?
How is the feedback quantified and categorized to inform strategic pricing and development sprints?
How is the company prevented from using “backdoor” internal workarounds that mask poor UX?

By focusing on the strategic, systemic implementation of EYOD in the SaaS world, I transform simple advice into a sophisticated, necessary business project—the exact challenge you might want to hire mee.

From 1,000s of Views to 0 Sales:

26. October 2025Johannes WinterhalterLeave a comment

My $200 Marketing Mistake and the Lesson That Redefined My Consulting” or “Why ‘High Traffic’ Can Be a Useless Metric: A Case Study on Targeting ‘Doers’ vs. ‘Dreamers’

I use this as a simple example for something much bigger: a year ago, I launched a promoted post for an article I had written. I spent a modest budget on Facebook… The results came in: thousands of views, plenty of clicks. I was thrilled. Then I checked my sales dashboard: Zero. Nothing.

The article was a philosophical piece... It was perfect for attracting an audience I call ‘Dreamers’—people who enjoy thinking about business in the abstract.”

But my service isn’t for Dreamers. It’s for ‘Doers’—founders, entrepreneurs, and managers who need to make a decision now. It is about finding the target group.

I thought publicising a philosophical piece of text will help my brand and so elevate my sales. It did not – there were many people who like my way of thinking, but hardly any of them needed my service. The connection trom the philosophical article to my services in market value, marketing ROI and brand value calculations and research was not present for the readers, or they did not need it.

How This “Failure” Makes Me a Better Consultant

“This experience is why I am so passionate about data-driven validation. Before my clients spend a single euro on ads, it is important to ask the tough, practical questions that separate ‘Dreamers’ from ‘Doers’:

The Message Test: Is my content speaking to the person who thinks about the problem, or the person who pays to solve it?
The Alignment Test: Does my Call to Action (CTA) on this post align perfectly with the service I’m selling?
The Market Test (The ‘Doer’ Question): Have I calculated my Serviceable Addressable Market (SAM)? Do I actually know how many people are in my target niche and what their potential value is?
The Metric Test: Am I measuring the right thing? (Stop tracking ‘Views’ and start tracking ‘Qualified Leads’).”

The market test is not expensive – see my order page. You, the reader, might even do it yourself and decide if you want professional assistance. Most successful campaigns are the result of contributions of multiple persons:

The business owner or Chief Marketing Officer
The consultant helping defining the target group and messaging with the help of AI
The responsive clients who help developing strategy and product by answering questions
The designers who do the final graphic appearance

Lets start it and find the marketing mistake.

Searching the Marketing Mistake — Measuring water depths does not necessarely help with marketing mistakes.

Recommendation Network or Artificial Intelligence in Sales – which one has warmer Leads?

25. September 2025Johannes WinterhalterLeave a comment

We are looking for people and organizations with a web presence or at least a listing in Facebook, Linkedin or some municipial business directories. AI cannot find others.

Recommendation networks – do they have qualified leads?

The power of recommendation marketing lies in its ability to effortlessly drive sales when a product aligns with a broad audience, eliminating the need to vet leads. Personal referrals, customer reviews, and influencer endorsements pave the way for seamless transactions without added complexities.

Ideally the other members of your recommendation network are looking for customers for their network and are warming up leads before. The prospect expects to be contacted when the seller reaches out.

This is an ideal setup. In practice most recommended leads are not warm, sometimes it is required to hire service people with bad quality just to please the guy who gave the recommendation.

However, the flip side emerges when the product caters to a niche market or appeals to a limited segment of potential buyers. In such cases, relying on recommendation marketing with personal endorsements can result in frustration. Vendors like myself may find themselves inundated with unqualified inquiries, while those offering recommendations witness their efforts to connect buyers and sellers go unrewarded, whether in commissions or praise.

AI is more than just talking about AI – Artificial intelligence in sales

How it is supposed to be:
Professionals in this area use AI-powered tools to personalize customer experiences, optimize marketing campaigns, and predict sales trends. They understand how to leverage AI for tasks such as customer segmentation, lead scoring, and content creation. A creative mindset combined with an analytical approach is key to suc
The reality:
Many of the ones selling products claiming to be AI-powered tools do not use AI for their own outreach to prospects. So it stays less personal, the approached clients get annoyed. AI applied correctly helps finding the ones who are open for the products.

AI is really good in finding information about prospects – it can read and digest complete web presences in less than a second. So just use it.

How AI took my side job – Artificial Intelligence Business Plan

2. August 2025Johannes WinterhalterLeave a comment

Until Summer 2024 I offered creating simple business plans for startups. I did that on my website and on Fiverr for about 120 € each. I stopped that for the lack of orders and a lot of weird questions regarding my gig which never ended in a purchase. The prospects were obviously looking for excuses for not ordering my service. Looking at other work about 50% of my personalized offers generate a contract. The gig was meant as entry offer for learning to know each other and sell more services later. I used a template and filled it with data from the client, then I added some treated and interpreted market data to make an earnings prediction. The origin of the data was publicly available sources.

Artificial Intelligince (AI) is really good at working with data and templates from the web. Actually I am using the AI behind Google Gemini. For testing I asked it to write a business plan for a dog grooming business, later I asked it for market data for dog grooming in Germany.

The result was a really nice plan – you can download it here. It was a working example for a plan with estimations done by AI.

For first orientation the plan is really good, and it looks nice. I even think it is possible to apply for a loan at the bank.

I checked the numbers: the market data is quite generic, the assumed sales price is not confirmed by market research, and there are no scenarios. What to expect for free? My former prospects group, who did not want to pay more than 120 € for a business plan, is obviously happy with the very cheap plans delivered by AI.

So Artificial Intelligence took my side job. Maybe it is similar to what they did to map suppliers with their free Google Maps. I use Google Maps frequently and consider it to be technological progress. Google Gemini as one example of an AI chatbot offer requires a subscription for full functionality.

Measuring the qualitiy of artificial intellgence business plan

Why finding trends using only observation often leads to false conclusions

30. July 2025Johannes Winterhalter

Human and artificial intelligence observe the environment. Observations are interpreted and used for finding trends and experiences are processed and result in learning experiences. Humans learn social behavior by observing their fellow humans; animals learn where food is, how to behave in a herd, and where dangers are present. Learning can be dangerous. If the underlying relationships are not understood, false conclusions are drawn. In the US state of Maine, for example, margarine consumption and the divorce rate developed in parallel. So, is stopping eating margarine doing anything for your marriage?

People seeking orientation in this confusing world look for guides and signposts. That’s why they tend to see trends where there are none. And some sellers of products of dubious utility for the customer load their products with predictions about the future. They say: “This is the current trend” or “soon everyone will be doing it this way” or simply “this is the future.” And some indicators, such as sales figures, support this theory. So what is genuine, well-founded trend analysis, and what is bullshit? With bullshit, the speaker usually doesn’t understand what he or she is saying, or they are simply lying. Unlike genuine digestive products from male cattle, like the beautiful Charolais bull on the right, Bœuf

charolais, taureau, with linguistic bullshit, you can’t tell by smell or appearance whether it’s phrases, inventions, or facts. Those who are intellectually ahead of the linguistic bullshit manufacturer notice contradictions and missing evidence. In this way, well-sounding inventions can be distinguished from reality. Difference between good arguments and facts There are three levels of content in a linguistic expression: the truth, which is understandable at least to a specialist audience, bullshit, and lies. Lies are criminalized and usually lead to the termination of the business relationship. Bullshit was elevated to academic honors by Harry Frankfurt. He, in turn, refers to Socrates: there are two ways to convince people. The first is to overwhelm the audience with pleasant-sounding but not really convincing arguments, thus creating a positive atmosphere. The second approach is clear, well-thought-out, and logical philosophical argumentation. See also here. The bullshit speaker doesn’t lie. He says sentences that, in his own opinion and experience, make a particularly strong impression on the unreflective listener. Many bullshit speakers don’t even notice the lack of connection to reality in their claims.

Use in Sales – Inventing

Trends In software sales and on the internet, new trends are often invented. This creates particularly thick piles of bullshit. I keep reading about the impending complete predictability of human behavior through big data. Anyone can check for themselves whether this is possible using contextual advertising on Google. A second industry susceptible to meaningless messages is health and nutrition. You can have texts tested for the bullshit factor at Blablameter. The result for this one: Your text: 3677 characters, 533 words Bullshit Index: 0.18 Your text shows only slight evidence of “bullshit” German. Another text on this blog about the Cournot point only achieved a bullshit index of 0.19. Texts with a lot of math, which may not be understood by everyone, have a better bullshit index.

Why artificial intelligence will not replace qualitative interviews done by humans

20. February 2025Johannes WinterhalterLeave a comment

This article is about the benefits of qualitative interviews and how to make a profit from a small amount of interviews. Qualitative interviews means there are less than 50 interviews, and the answers are not limited to yes/no or a 10-point scale.

Our goal is to improve customer relationship by asking our customers what they want and if there are secretive needs and wishes which are easy to fullfill for us or need only a small change in our product and sales strategy.

Artificial Intelligence relies on text already existing for training the model. So the answers given by AI are always a rephrasing and recombination of something already existing, and it is up to the reader to interpret if the results are valid or not.

How to make qualitative interviews worth the effort

Qualitative Interviews done by a good interviewer who makes the interviewees talk in the right direction gives direct access to the thoughts of our clients and target groups. This includes thoughts which do not exist in a written language.

Qualitative Interviews are expensive, about 300 € for each interview. This includes finding the right interviewees. Interviewing the correct respondents has a marketing effect: the respondents get aware that there is a supplier interested in them. If they are already customers the effect goes in the same direction.

This additional publicity pays for a part of the survey. The other one is additional sales following an improved strategy.

Stupid interviewers are a no-go

For best quality of interviews the interviewer has to dive into the world of the interviewed person. The interviewer has to direct the interview and add questions if necessary. This requires a lot of experience and knowledge for the interviewer. Hiring a random person without knowledge is the first step to disaster. Less experienced interviewers need the first interviews in a project for training, experienced interviewers do not need that. They can relate to previous experiences

References

This article is based on about 20 years experience with qualitative interviews and the usage of some form of artificial intelligence since 1992.

Artificial Intelligence: danger to humanity, productivity increase or just boring?

16. December 2023Johannes Winterhalter

Artificial Intelligence is based on statistical learning. We all learn with statistics, even if we do not know it. Our brain is good at things we do often, remembers words we frequently use and puts others aside. When we touched an electrical fence we learn it hurts. Animals make a similar experience. Also we look at other humans to learn how they handle situations. This may improve our own lifes. We look at the experience of others, how they do things, and if we think its good we imitate it.

The challenge of Artificial Intelligence is to put learning into a statistical model. With more and more computational power more is possible. Impressive for me is the look at colored 100+ years old silent movies in colors . The machine learned from actual pictures how the old colours were when the original was filmed and put that knowledge in the colorized version. With human painters this process would have taken years of work. Another impressive example of AI is a comparison between the Donald Trump impressions of Alec Baldwin (actor) and Scaredketchup (computer artist working with AI)

What AI and all the models do is to analyze all available text and give the resulting language model the ability to create new text out the old text . This is all based on mathematical and statistical calculations. As a result the new text is really close to existing text found somewhere on publicly available sources. AI can pretend to invent something, just by combining results or something the readers did not find already themselves. Remember: it is not really new, the machine found it somewhere.

A personal view on the benefits of Artificial Intelligence

AI-generated text is good when I have a question and the machine prepares its findings for me. There it can use text I did not know before, and probably I am happy. AI can ease pressure on customer service – the bot can answer many frequent questions without human interaction.

How AI-generated Text creates boredom

The inherent lack of invention by AI may create boredom. Also Artificial Intelligence is actually not well trained to look into human emotions. This may change over time.

Human brains have a capability to recombine things which never put together before. This is called human genius or creativity. Machines cannot do that actually. Computers lack the capability to fast apply the invention on human minds and viewers and so see if it works. Scaredketchup combines his own creativity with AI tools for creating pictures.

For me interesting is to look at how music is created: the musician has some inspirations and tests it before live audience. His mind tells him what the listeners like and what not.

Increase Sales, Growth Hacking, Rainmaking, and Market Research

16. November 2022Johannes Winterhalter

This article is a short introduction into the many names for the same processus: shoveling new clients into the sales funnel of the enterprise, increase sales and make everybody happy there – the customers with products or services they like and the seller with good earnings.

At the end of the article I add my recipe for lead generation. It works.

Rainmakers are salespeople who use techniques not directly visible to outsiders to acquire new customers. Rainmaking and market research go hand in hand.

Who looks for Growth Hackers and who for Rainmakers, and who needs Lead Generation?

Growth Hacking is made for start-ups.

They want exponential growth here. That could double weekly sales. Growth hacking also works for traditional companies that can expand their production fast enough and still grow their market. They only need to find a market.

Growth hackers are people who achieve such sales growth using methods that are not directly visible and easy to conceive for the environment. This gives their work something magical.

Rainmaking

Rainmakers are more traditional. They have an approach to sales not used in the enterprise beforehand, sometimes they also change the product line. This looks like magic to the employees in the enterprise. They may do own market research or user the services of professional market research analysts.

Extraordinary skills of the growth hacker

He sees unfulfilled human needs. She or he tests that in niche markets there it is possible to see how well a product is being received. Market research can test new products with well-known techniques, for example group discussion or sending out samples and questioning later.

According to Henry Ford, market research and customer suggestions were not the impetus for the development of the then revolutionary Model T, which was built in huge numbers. Customers would have wanted faster horses instead of cars they had never seen before. Growth Hackers and Market Researchers need to be visionaries to see the new product in his best shape.

Growth hacking is referral marketing

Inexpensive and fast customer acquisition cannot circumvent recommendation marketing. People recommend a product to others if it has helped them or arouses enthusiasm. Or if they can earn money with the recommendation.

Free trial access, distribution of samples, influencers, trial lessons, presence on social media – a lot helps a lot, like Germans like to say.

Outdated business models – leave it behind

People like to think that things who were once successful may be worth reviving or continuing. Market research finds if there is still a market for the product.

Rainmaking, Lead Generation and Market Research work together

Growth hacking is the product of many ideas and numbers. The firm belief in one’s own success is of no use if all market fundamentals oppose it. For example what to do if an analysis of the Totally Accessible Market shows only limited growth opportunities?

The market researcher also knows the penetration and effect of the individual recommendation or influencer channels and can doreliable tests.

Here the Working Recipe

Secret Recipe For Making Leads Rain                       
 ----------------------------------------------------------
 Who do I wish to be my client                             
 Why do I wish them do be my clients                       
 Who takes the decisions at my wished client               
 Who buys the stuff I try to sell already regularly        
 Who are my competitors                                    
 Who takes the decisions at the regular buyers             
 Where is it easier to sell                                
 Whats in for my buyers                                    
 Where can I reach my clients                              
 How do my clients like to be reached                      
 Additional arguments for my clients to buy                
 Expected costs to find a customer, in percentage of sales

Why doing Market Research in Growth Hacking and Lead Generation?

It is about getting all the information about future clients to fine-tune the story to the product. The product might be a procedure for easing marketing or a tractor, which helps the owner and driver to do the job in the fields more comfortably, reliably and just better.

Fuel your story for account-based marketing, growth hacking and lead generation

Automated Product recommendations – Does Software Better Than Human Sales Staff?

30. September 2022Johannes Winterhalter

The article deals with the possible uses of automated product recommendations in sales and customer service. There are buyers who prefer to buy on the internet for there they do not have to talk to human sales representatives. They probably had some experience with vendors staff hiding their cluelessness behind a lot of talk and are trying to sell their products on stockage at anyone who does not get away fast enough.

The problem looks hard to solve. But wait: for a few years now it is possible to extract valuable data points from primarely web activities and connect them with realised sales. The connector are either self-learning models or static traditional models. Models simulate behaviour and results.

The interested customer is looking für information before buying. He or she may ask a specialised salesperson and consultant who has all the relevant answers ready and can think in the customer’s interest. This relieves the customer. Or they, the potential clients, may look for publicly available information and customer review to avoid the advice of an inexperienced and overburdened sales representative.

Many sales representatives for complex products are quickly overwhelmed by the questions and expectations of well-informed prospects. The untrained salesperson feels attacked, the sales talk goes off the rails, the interested party prefers to buy from a supplier without advice.

The web part of customer journey

Depending on the product, between 80% and 90% of the buyers begin their customer journey with an search engine. So it is important for the seller to know what it is reported in the web, take care of the correctness of web information and avoid contradicting information. If there is human sales staff, they are supposed to assist the web customer journey and take care of a seamless process.

The consultant with all the facts in mind and the fully automatic customer advisor are extremes, the practical truth in the company lies in between.

Can the web be the better customer advisor?

Yes and no. The informations in the web and the informations given by a human sales person are supposed to go without contradiction. Nobody likes lies and deception.

Artificial intelligence makes use records of any communication with customers, for example chats, mail, data entries. This is compared with predetermined success goals. The model recommends something and can adjust itself. Something salespeople do intuitively, too, if the selling company lets them. Artificial intelligence therefore means less control for the management. On the other hand, opportunities are used that might otherwise have been overlooked. Where to start now?

Sellers are supposed to make as much information as possible available in a neatly structured way. Many people would like to find out more before making personal contact, but cannot find the information they are looking for. If publicly available documentations saves half an hour of calls per working day for the seller this justifies an expense of €2,000 for an improved sales website or other type of customer information – and that for telephone staff at a standard wage. Informed customers are better customers.

The meaning of human interaction

The ideal salesperson knows the buyers needs and wishes. He ors she build the best possible solution with his expertise. In between, looking up details and availability on the computer is essential for complex inquiries.

Advice form humans or from machines and websites?

Whether or not a human intermediary remains necessary for information collection and transmission depends on the product itself and on the personal preferences of the interested party. Some can evaluate and implement the freely available information, such as product descriptions, customer reviews and more for their own needs, while others cannot.

Good sales people relieve the customers. To do this, they must put the interests of the customer first and not fight for sales at any price. Consulting software in the sales pitch gives standardized information, if the software is capable of extracting the recommendation which work and then the client might be really happy.

Correct information with automated product recommendations — Correct product informations saves money for buyer and seller

Success has many reasons

Incidentally, the screen of the gentleman can turn directly to a prospective customer without the computer interfering. And if he needs information from the cloud or machine, he has it quickly at hand.

Targeting Marketing With Qualitative Market Research

2. April 2022Johannes Winterhalter

Why we need a buyers persona

A buyers persona is a picture of our targeted group. It says persona for the reason we do not need to know everything about that person and there might be different persons in our target group. The second part is about qualitative market research. We use this kind of searching for behavioural characteristics for creating this buyers persona.

A wrong image of our target group costs us money and makes our brand less popular. Simple example is posting on Linkedin without reducing the number of followers. I looked at the list of people I unfollowed. The reason for doing that was that they posted repeatedly content I do not like or is just not true. Most of them are aging german business trainers spreading far-right political statements and sometimes even far-right lies. The other ones are sales newbies who spread too often their pitches aimed at a different buyer persona than me. Is a close group of followers who believe the same political statements as the poster the thing the poster wanted? If there is no reaction to your post does hammering out repeatedly the same sales pitches again and again to the wrong targets a good thing? Or should we appeal to a broader audience?

Why qualitative Market Research

This article is about bringing qualitive and quantitave research together with integrating numbers and representativity into qualitative research. Quantitative research is primarely counting and statistics.

To research people ‘qualitatively’ means that you intend to understand them. This is beyond algorithms. Let me show you how best to do this. I am here to listen to you. (Elif Kus Saillard)

The topic of qualitative market research is understanding. What does the world of my target group look like? What emotional and financial settings do they have? Quantitative research, on the other hand, determines how many people in the target group have which attitudes, how many they are and how their budget looks. A random sample is drawn so that not all members have to be questioned.

The claim of qualitative market research

Qualitative market researchers understand the customers. Its like some newspapers articles, where journalists describe some individuals where they think they are good for the numbers. Quantitave shows the numbers – for example 60% believe that the government does a good job in education. Discussions in focus groups, in-depth interviews, images, social media and much more can be used as data sources for qualitative research.

Also compare here (New Market Research Blog). The qualitative market researcher is an active part of the research process. He or she uses their subjectivity to better understand the phenomenon being studied. You want to understand why people believe in what and see the world a certain way. A qualitative researcher wants to understand the process of selecting a product, for example. A quantitative researcher wants numbers, averages, and more. Manufacturers and dealers can then base their decisions on this.

How qualitative researchers can do representative studies with small numbers

A qualitative researcher makes small samples. Understanding the process and the mindset of the subjects, this researcher assumes some validity. To ensure this this procedure can help:

The result of the small sample are suitable when no changes are to be expected from a larger sample. This can be checked by first evaluating 30 questionnaires. Hopefully there is no significant change with a further 10 questionnaires. If there is, another 10 questionnaires are added. If this does not maintain the hypothesis that the differences in responses are statistically insignificant, the study can be considered representative provided the responding participants represent the target group.

Some subjects suitable for qualitative studies:

Lists of ideas – if the ideas are repeated, the study can be ended. Studies that do not record the subjects’ ideas via structured questions but via free text information fall into this category.
All – or – none results. If every participant in a small study says the same thing—like, “I see a train station in this ad,” or “I prefer the new packaging”—the conclusions are likely to be valid, even with small samples.
Strong hypotheses for the study to support If we have a hunch and it is supported by the small sample, we can be sure that the hunch is correct. All we have to do is verify that the underlying hypothesis is not just speculation. This type of market research is popular with journalists who can get by with just a few interviews.
Understanding instead of measuring – for example customer journey. This analysis helps testing new products.

The problem of representativeness in qualitative research remains.

With small samples, the problem of representativeness remains. There is no statistical way to ensure the representativeness of a non-probable sample. The market researcher’s judgment must be added here: can the result be as the study suggests or are there other, contradictory results? Trusting only statistically proven results without knowing the underlying connections can be misleading.