Part 52 -AI-Buddy.....What does an online store actually sell?
The customer buys a product – but the online store has to sell far more than the product
The simplest answer seems obvious.
An online store sells products.
A bookstore sells books. A clothing store sells clothes. A sports store sells sports equipment. An electronics store sells technology.
But from the customer's perspective, the reality is more complicated.
The customer rarely comes to the online store because the goal is to buy a product page.
The customer is trying to solve a need.
She might need a jacket that keeps her dry in the mountains. A printer that works in the home office. A gift that's appropriate for a ten-year-old. A camera that's easy to use. Or new running shoes because the old ones no longer work.
The product is the solution the business offers.
But before the customer buys, the online store must help her understand:
Is this the right product for me?
What is the difference between the options?
Can I trust the information?
Can I trust the business?
What does it really cost?
When will I receive the item?
What happens if I choose wrong?
Thus, the online store does not just sell a physical product.
It also sells information, security, relevance, availability, service and help in making a decision.
And as artificial intelligence increasingly becomes part of how people search, compare and choose products, this knowledge becomes even more important.
This applies to Amazon and the world's largest online stores.
But it applies just as much to the small specialty store with five employees.
Maybe even more.
Because a small or medium-sized online store cannot necessarily compete with the largest in terms of assortment, marketing budget or technology.
But it can compete on knowledge of the products, customers and the needs the products are intended to solve.
Magne & the Friend
Magne
Friend...
Now we have left the content strategy and entered the online store.
The buddy
Yes.
And I have a question for you.
What does an online store sell?
Magne
Products.
This one will be short.
Heh heh.
The buddy
Are you sure?
Magne
If I run an online store that sells running shoes...
So I'm selling running shoes, right?
The buddy
What does the customer buy?
Magne
Running shoes.
The buddy
Why?
Magne
Because the customer needs new shoes.
The buddy
Why does the customer need new shoes?
Magne
Maybe she should start running.
Maybe the old ones are worn out.
Maybe she'll run a marathon.
Maybe she needs better cushioning.
Or hiking shoes.
The buddy
Now suddenly you're not just selling shoes anymore.
Magne
No...
Now I sell solutions to different needs.
The buddy
That's where e-commerce starts to get interesting.
The customer starts with a need
Magne
So we should start with the customer and not the product?
The buddy
Yes.
Businesses tend to organize the world by products.
The customer does not necessarily organize the world in the same way.
Magne
How does the customer think then?
The buddy
Maybe:
My legs are freezing.
I need a gift for my husband.
I'm going to paint the house.
I have started running.
I need a PC for my studies.
Magne
While the online store responds:
"Here are 487 products."
The buddy
Heh heh.
And leaves the rest of the work to the customer.
The product catalog is the business's perspective
Magne
But we must have categories and products.
The buddy
Of course.
The product catalog is required.
But it often represents the business's way of organizing its assortment.
Magne
While the customer comes with a problem?
The buddy
Or a desire, a goal, a situation or a task.
It's not always a problem.
Think about someone who is about to buy their first espresso machine.
Magne
Then I can show you fifty espresso machines.
The buddy
But the customer may wonder:
How big a machine do I need?
Do I need a built-in grinder?
How difficult is it to clean?
What is the difference between fully automatic and semi-automatic?
How much should I pay?
Magne
And all of that is actually part of the purchase.
The buddy
Yes.
The product alone does not necessarily answer the questions that
stands between the customer and the decision.
The online store sells security
Magne
So what is the first thing we sell besides the product?
The buddy
Security is a good candidate.
Magne
How do you sell security?
The buddy
Through many small signals.
Precise product information.
Clear price.
Delivery information.
Return conditions.
Contact options.
Good pictures.
Credible customer reviews where used.
Information about the business.
And that the website actually works as expected.
Magne
So security doesn't lie on one side?
The buddy
No.
It occurs throughout the entire customer experience.
The online store sells help in choosing
Magne
But what if the customer already knows exactly which product she wants?
The buddy
Then the task may be simple.
But many customers don't know that.
They are between options.
Magne
And then they need help.
The buddy
Yes.
Comparisons.
Size guides.
Explanations.
Filters.
Recommendations.
Areas of application.
Advantages and limitations.
And maybe eventually a digital customer advisor who can ask questions back.
Magne
So does the good online store do some of what the good store employee has always done?
The buddy
Exactly.
It helps the customer move from:
“I need something.”
to:
“This is right for me.”
Here small online stores have an interesting opportunity
Magne
But buddy...
How is a small online store supposed to compete with companies that have huge technology budgets?
The buddy
It doesn't have to compete on everything.
Magne
What can it compete on?
The buddy
Knowledge.
Consider a small specialty store that has been selling hiking equipment for twenty years.
The employees may know an incredible amount about mountain boots.
Magne
Who needs which models?
What is suitable for wet mountains.
The difference between a day trip and a week trip.
The buddy
Just.
That knowledge can be far more valuable than a product text that simply says:
"Waterproof mountain shoe. Available in sizes 36–46."
Magne
But then the knowledge has to get out of the employees' heads.
The buddy
You hit on something very important there.
It must be made available digitally.
The invisible capital moves into the online store
Magne
Wait a minute.
Now this is starting to sound familiar.
The buddy
Heh heh.
It should.
Magne
The knowledge employees have about products.
Their experiences.
Understanding customers.
The ability to explain differences.
All that we call...
The buddy
The invisible capital.
Magne
So the online store can actually make human knowledge available digitally?
The buddy
Yes.
And there lies a huge opportunity.
Especially for small and medium-sized businesses with a lot of specialist knowledge but limited resources.
Then comes artificial intelligence
Magne
And now AI is coming in the door?
The buddy
Yes.
But not first.
Magne
Not?
The buddy
First we need good knowledge.
AI cannot make bad product information great just by being AI.
Magne
Garbage in, garbage out?
The buddy
The old principle still lives.
If the product data is incomplete, the sizes unclear, and the descriptions generic, even a digital customer advisor has a poor starting point.
Magne
So product knowledge becomes the raw material?
The buddy
Yes.
AI can help us make it accessible in new ways.
But the business still needs to know what it is selling, who it is helping, and why the product fits different needs.
From search field to conversation
Magne
What happens if the customer instead of searching for:
"men's waterproof mountain boots size 43"
writes:
"I'm going to hike for five days on the Hardangervidda plateau in September. I'm carrying a heavy pack and my feet get wet easily. What should I choose?"
The buddy
Then you see where e-commerce could be heading.
Magne
The product catalog alone is not enough.
The buddy
No.
The system must understand the need and connect it to relevant product knowledge.
Magne
Then the online store becomes more like an advisor.
The buddy
Yes.
And that's precisely why content, product data, and human expertise are becoming increasingly difficult to separate from the product itself.
Academic specialization
The product is only one part of the customer's value proposition
In marketing, the term value proposition is used to refer to the overall value the business offers the customer.
In e-commerce, this value rarely consists only of the physical item.
The customer is considering a combination of, among other things:
product characteristics,
price,
availability,
information,
delivery,
risk,
service,
trust,
and how easy it is to complete the purchase.
Two online stores can therefore sell the exact same product and yet offer the customer very different value propositions.
One can make the decision difficult.
The other can make it simple.
The customer buys a solution to a task
A useful perspective is to distinguish between the product the business sells and the task the customer is trying to solve.
A customer does not necessarily buy a drill because she wants to own a drill.
She might want to hang up a bookshelf.
This does not mean that the product is unimportant.
This means that product information becomes better when the business understands the context in which the product will be used.
For the online store, this involves a transition from just describing:
What is the product?
to also explain:
Who is it suitable for?
What need does it solve?
When should it be used?
How does it differ from the alternatives?
When should the customer choose something else?
Information reduces uncertainty
Online shopping has a fundamental challenge that physical stores do not always have to the same extent.
The customer often cannot:
touch the product,
try it,
see it from all angles,
speak directly with a staff member,
or examine it physically before purchase.
The information must compensate for part of this distance.
Good images, precise specifications, sizing information, explanations, comparisons, reviews and guidance can reduce uncertainty.
This means that product information is not just marketing.
It becomes part of the service the online store provides.
Small and medium-sized businesses don't need to copy the largest ones
It can be tempting for a smaller online store to look at large marketplaces and try to imitate them.
But a specialized business may have other competitive advantages.
It can know the products better.
It can know a specific customer group better.
It can understand a narrow application area better.
And it may have employees with experience that is not found in the product supplier's standardized product text.
This knowledge can be systematized and made available through:
product descriptions,
buying guides,
comparisons,
questions and answers,
professional articles,
video,
customer service,
and eventually AI-based advisory solutions.
For a smaller business, content strategy can therefore also be a way to scale expertise.
One good explanation can help many customers.
Structured product information is becoming more important
When product information is to be used across websites, searches, filters, comparisons, and AI-based solutions, structure becomes important.
It's not always enough to have one long product text.
The business may also need clear data fields for, for example:
material,
goal,
weight,
compatibility,
size,
area of application,
maintenance,
technical characteristics,
and other product-specific attributes.
Then the same knowledge can be used in several ways.
The customer can filter.
Products can be compared.
Systems can retrieve certain properties.
And an AI-based advisor can gain a better knowledge base.
AI changes the interface – not the customer's basic needs
Artificial intelligence can make it possible to move from traditional menus and search fields to more dialog-based customer experiences.
But the customer's fundamental questions don't go away.
The customer still wants to know:
What is right for me?
What is the difference?
Can I trust this?
What do I get for my money?
What happens after the purchase?
Technology can change how questions are asked and how answers are delivered.
But the business still needs the knowledge that makes good answers possible.
Product data and product knowledge are not the same thing
This distinction is becoming increasingly important.
Product data often describes measurable or structured characteristics:
weight,
goal,
material,
price,
color,
stock status,
model number.
Product knowledge puts this information into a meaningful context:
Why does weight matter?
Who is the size suitable for?
When is this material an advantage?
Which model should the customer choose?
What compromises does the choice involve?
It is when data is combined with context and experience that the online store begins to approach consulting.
From online store to knowledge-driven commerce
It points towards a broader understanding of e-commerce.
A modern online store can be considered a combination of:
product catalog,
information environment,
decision support,
service channel,
transaction system
and eventually maybe
digital advisor.
This doesn't mean that all online stores need advanced AI.
A small online store can go a long way by starting with something much simpler:
Make the knowledge you already have about your customers and products available to the customer.
It is a good starting point for both humans, search engines and future AI solutions.
What does the online store sell?
The product is only one part of the total value
The online store offers | What the customer actually gets | Example |
Product | A solution to a need | Mountain shoes for a demanding hike |
Product information | Understanding | What distinguishes the models from each other? |
Guidance | Help choosing | Which model suits my needs? |
Comparison | Decision support | What do I gain by choosing A over B? |
Clear conditions | Reduced risk | What happens if the size is wrong? |
Delivery information | Predictability | Will I receive the item before my trip? |
Expertise | Security and relevance | Why is the product recommended for this particular application? |
Customer service | Help when information is not enough | Can I ask someone before or after the purchase? |
Good customer experience | A simpler process | I find, understand, choose and buy without unnecessary friction |
AI-based consulting | Personalized help on a larger scale | The customer describes the need and receives relevant options explained. |
From product catalog to knowledge-driven online store
The same item can be sold in very different ways
Product-oriented online store | Knowledge-driven online store |
Shows what the business has | Helps the customer find what the customer needs |
Organizes primarily by product categories | Combining products, needs and applications |
Describes the product's features | Also explains why the characteristics matter |
Gives the customer many options | Helps the customer understand the differences |
Product data is mainly located in the catalog | Product knowledge is used across the customer experience |
The customer must largely interpret the information themselves | The online store offers decision support |
Employees' knowledge can remain in their heads | Professional knowledge is documented and made digitally available |
KI is used as an addition if necessary | AI can use structured knowledge to help the customer |
What can a smaller online store start with?
Knowledge-driven e-commerce doesn't have to start with a large AI project
Question | What the business can investigate | Possible first measure |
What are customers asking about? | Recurring questions to customer service and employees | Create clear answers and product guidance |
Where do customers become unsure? | Returns, Cancelled Purchases and Pre-Purchase Questions | Improve information on the relevant products |
What do employees know? | Experience not found on the website | Document practical product knowledge |
What differentiates the products? | Differences the customer has difficulty understanding | Make comparisons |
Who is the product suitable for? | Needs, situations and uses | Describe target group and usage situation |
What is missing from the product data? | Incomplete or inconsistent attributes | Structure and quality assure product information |
What can be automated later? | Repetitive guidance and questions | First build a good knowledge base that AI can use |
Technical terms
Key concepts when talking about what an online store actually sells
English technical term | Explanation |
E-commerce | Buying and selling of goods or services through digital channels, usually with all or part of the purchasing process completed online. |
Value Proposition | The total value the business promises and delivers to the customer through product, price, service, information, availability and other benefits. |
Customer Need | A problem, desire, goal or requirement the customer tries to satisfy through a product or service. |
Product Data | Structured facts and characteristics about a product, such as size, material, weight, price, color, and model number. |
Product Information | The aggregate information that describes the product and helps the customer understand its features, use, and relevance. |
Product Knowledge | A deeper understanding of the product's features, uses, benefits, limitations, and which customers or needs it is suitable for. |
Decision Support | Information, functionality or advice that helps the customer consider options and make an informed choice. |
Purchase Journey / Buyer Journey | The process the customer goes through from the moment a need arises to when alternatives are considered, the purchase is made, and the post-purchase experience is developed. |
Conversion | When a user performs a desired action, such as a purchase, registration or request. |
Product Attribute | A defined characteristic of a product that can be used for description, filtering, comparison, or other structuring. |
Product Information Management – PIM | A system or process for collecting, quality-assuring, structuring, and distributing product information across channels. |
Digital Shopping Assistant / AI Shopping Assistant | A digital solution that helps the customer formulate needs, understand alternatives and find relevant products, in some cases using artificial intelligence. |
We have only just begun.
Magne
Friend...
I began this article quite certain of the answer.
An online store sells products.
The buddy
And now?
Magne
Now I would say:
Yes, the customer may end up buying a product.
But to get there, the online store must deliver far more.
Information.
Security.
Knowledge.
Guidance.
Decision support.
And a good experience throughout the purchase.
The buddy
Abrupt.
Magne
But now I've got a new problem.
The buddy
You usually get that.
Heh heh.
Magne
If the information, explanations and knowledge are so important for the customer to choose the product...
Where exactly is the line between content and product?
The buddy
That's where the next question begins.
Magne
Because if I buy a product because the online store convinced me that this was the right choice...
What really made me buy it?
The product?
Or the content that made me understand the product?
The buddy
Just.
And therefore we move on to:
Content or product – what is the customer buying?
For friend...
We have only just begun.
Academic background and further reading
This series also builds on my own professional journey through the Web Design study , the eMarketing study , Innovation and Commercialization and professional seminars in San Francisco and Oxford . Here you will find the background, professional environments and experiences that have followed the development from the early years of the web to today's digitalization.
Recommended literature
Developments in artificial intelligence are moving faster than perhaps any other field of study in our time. No single book can provide all the answers, but good books can provide a solid foundation for understanding the technology, the opportunities, and the challenges.
In the KI-Kompis series, we therefore recommend a selection of books that illuminate artificial intelligence from different perspectives – technology, strategy, management, innovation, ethics, digitalization and practical application. Together, they provide a broader understanding of how artificial intelligence affects people, businesses and society.
Click on the book icon to see the full literature overview with recommended books on artificial intelligence.
Recommended books from our library
AI Snake Oil
Writers: Arvind Narayanan & Sayash Kapoor
Short review
Artificial intelligence is surrounded by both high expectations and many misunderstandings. In AI Snake Oil, the authors distinguish between what today's AI can actually do and what is still exaggerated or unrealistic. The book provides a fact-based and easily accessible review of the technology's strengths, limitations, and practical applications.
Why we recommend the book
An essential book for anyone who wants a realistic view of artificial intelligence. It is especially suitable for leaders, decision-makers, and anyone who wants to separate fact from hype.
Generative AI For Dummies
Author: Pam Baker
Short review
Generative AI For Dummies provides an easy-to-understand introduction to generative artificial intelligence. The book explains key concepts, shows practical examples, and gives the reader a safe start on how the technology can be used in work, education, and everyday life.
Why we recommend the book
A very good introductory book for anyone who is curious about generative AI, but who does not necessarily have a technical background.
Co-Intelligence: Living and Working with AI (Expanded Edition)
Author: Ethan Mollick
Short review
In this expanded edition, Ethan Mollick builds on how artificial intelligence can function as a collaborative partner in the workplace. With new examples and updated reflections, he shows how humans and AI can create more value together.
Why we recommend the book
One of the most practical and inspiring books on how artificial intelligence can be used in everyday life and in businesses. Suitable for managers, employees and students alike.
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