in Blog

September 08, 2020

Product Design – Best Practices For Your Business


Edwin Lisowski

CSO & Co-Founder

Reading time:

9 minutes

Designing a product entirely from scratch is a big challenge. On the one hand, it’s an extremely exciting and fascinating process that results in great market success if everything goes according to the plan. On the other hand, the list of things that can go (or rather be done) wrong is quite long. That’s why software development companies stick to principles of product design, minimizing the risk of failure. In this article, we are going to show you what practices of product design you should implement in your software development company to make sure that your apps and software are as good as possible.

The basic commandments of product design are, in essence, quite straightforward. They are as follows:

  • Solve real problems
  • Keep it simple
  • Plan everything you can
  • Optimize the development process
  • Pay attention to ensure high quality
  • Amaze customers by offering them more than they expect

Every program and every application should be developed according to these principles. However, when it comes to AI, there are several more facets you should take into account. Let’s analyze these basic rules of product design first, and then we will focus on designing products that are supported by AI or machine learning algorithms.

Product design:

Solve real problems

That’s the ultimate rule, not just in product design, but in business in general. Your products have to solve real problems of real people. Otherwise, it’s just art for art’s sake that no one will be interested in. Don’t start with an idea or a vision. Start with a problem. Make sure that, from square one, your product is customer-centered and, above all, helpful.

Keep it simple

Today, we live in exponential times. We don’t have time and work a lot. Your products should be tailored to these circumstances. Don’t overdo. Keep your product as simple and as easy to use as it’s possible. It’s better to design a product that offers just 2-3 features but refined to the last detail than a product that offers ten features but not thought out or adequately polished.

Product Design, hands, project, cooperation

Pplan everything you can

Every successful product has a design consisting of every aspect, every possible risk, and every stage of work. If you have everything thought out and planned, it’s unlikely that something along the way can go seriously wrong. Naturally, it’s almost impossible to foresee everything or take into consideration every possible problem, but the more things you have planned, the better your chances are.

Optimize the development process of product design

When it comes to product design, many software houses start with the MVP version of their apps and programs. Designing a Minimum Viable Product is a terrific way to optimize the development process. You don’t have to build the fully-fledged version of your app immediately. Start with something simple, something that will be sufficient to show it to your potential customers and investors. The MVP version should have at least the most significant functions and features so that your stakeholders can get acquainted with your product and test it before they buy it. A multitude of software development agencies design the MVP version first, and when it turns out that it was a success–they move it to the next level.

Pay attention to ensure high quality

Naturally, thousands of apps don’t look that good or don’t work the way they’re supposed to and are still commercially available, and people buy them. But that happens very rarely, and even if you succeeded with such a low-quality product, you would be very limited when it comes to possible reach and sales. It’s very simple–if you want to sell thousands (millions?) copies of your app, it should be designed with high quality in mind. The high-quality products are usually more successful, and, if you have competition, that’s the best way to ensure your customers that purchasing your products is profitable.

quality is the best business plan

Amaze customers by offering them more than they expect

That’s a fantastic way to win your target audience. Many e-commerce companies utilize this strategy. For instance, they throw some freebies into every order. The company doesn’t spend so much money because freebies are usually cheap to buy, but it’s an exciting opportunity to be remembered by your customer and create a positive customer experience (CX)–another crucial element of every product design.

With this introduction done, we can switch to ground rules of AI/ML product design.

AI product design

Although designing an AI product is pretty much the same as any other software, there are some additional principles you have to bear in mind. The very first question you have to consider is data acquisition. After all, each AI-fueled app needs data to operate. Especially machine learning algorithms are trained on specific sets of data that enable them to do their job correctly and accurately. You have to know what data you need, where you can obtain it, and how you should use it to train your AI/ML model. But other things require your attention:

User onboarding

In general, AI products are typically used for more demanding or complex tasks. That’s why the proper user onboarding procedure is indispensable. Your clients/users have to understand (at least to some extent) how your product works, what data does it collect (remember about the sensitive subject of personal data!), and what outcome it produces. It is considered a good practice to ask for permission to collect data and explain how it will be used.

user onboarding, project design, people, computer, conversation

Operation and visualization of product design

You have to design the way your software will look and work. Will it be activated by a button or a voice command? How will the user know that it’s activated? Will it be presented in the form of a dashboard? Or maybe in a special sidebar? If you are building a future prediction app, you’ll need some charts and graphs to show trends and predictions. What are they going to look like? These are just several of the many questions you have to answer before you start coding your future product.

Another crucial element is the visualization of outcomes/results. Depending on the type of information your users will get, you have plenty of ways to show them. You can use:

  • Scores
  • Colors
  • Numbers (percentage)
  • Charts

And various combinations of them.


Keep in mind that, most likely, your users won’t be particularly familiarized with artificial intelligence or machine learning. You should educate them (but don’t make them feel dumb!) and explain the results or data they obtain. If you use credit scores, explain what they mean and how they can be improved. Explain why a specific outcome was predicted and on what basis. If you find it hard to explain or describe a specific outcome, use examples. For instance, if the user gets a score of 0.5, show them some examples of other situations with the same result. That will help them understand the outcome more thoroughly. And, again, UX improves!

explanation, hand, laptop, project design

Keep user in charge

This part is essential. However, your AI product can be smart or functional; always keep in mind that you are building this tool for people to use. Users/customers should be your first concern. That’s why, once you present the outcome on the interface, allow people to interact with it as with other items. Include the “dismiss” button, or allow them to generate a report. Don’t let users think that, at some point using your product, they hit the wall and can’t do what they intend to.


This point is especially vital when it comes to chatbots, virtual assistants, and other conversational algorithms. In short, you have to design the way they will communicate with users. Will they be friendly and casual or rather educated and professional? Remember that communication can also be visualized by symbols, signs, or even an interactive virtual character. Is that going to be a man or a woman? What are they going to look like? What voice will they be using?

chatbot, mobile phone

Product design: settings

That’s another element you can easily overdo with. Your program’s behavior should be tailored according to the number of predictions and features it offers. Remember the “keep it simple” rule? Users easily get lost and discouraged when they see thousands of different settings and options. The less work is on the user’s side, the more likely they will willingly use your app. If you feel that more functions should be implemented after all, possibly you could think about two different versions of your product? A straightforward one (for “home” users) and a more complex one (for “professional” users).

Provide support

Don’t ever make your customers feel left without a backup. Technical and customer service support is an absolute necessity for every AI/IT product. Later, when the user base grows, you can create a community that supports each user with their problems. Many frameworks work this way. But at first, you should offer professional support, accessible in various ways (phone, email, chat).

Moreover, you should design a flow where a user can provide actionable and understandable feedback for the AI/ML model and understand how it will improve results.

customer support, call center, man, smile

AI product design – Prototyping and testing

Like in every web/mobile product design, we recommend a strategy based on prototyping and frequent tests. We have already told you about the MVP approach. It’s all about creating a prototype, an initial version first, without the need to invest large amounts of money.

And then, there’s the testing part. Generally speaking, when it comes to AI product design, tests should be as frequent as possible. Tests should help you (and your client) understand if your product’s functionality matches previous agreements. It is also vital to test many scenarios in different environments and circumstances.

The goal is always the same–to uncover possible faults or inconsistencies BEFORE the product reaches the market.

Finally, you should check data your product operates on for possible biases. With the MVP approach and frequent tests, you minimize the possibility that your product will have significant faults or glitches.

If you’re currently designing an AI-based product–we are at your service! Addepto has vast experience designing various AI products, both for ordinary users and complex business intelligence projects. With our help, no AI project is too complicated.

ai consulting services


AI Software

Artificial Intelligence