When a customer is looking for the right product, they need much more than a name and a price. What does the product do, what is it suitable for, and is it the right choice for my needs?
In the past, the answers were found together with a salesperson in a printed product catalogue. Today, product information travels across websites, online stores, resellers and countless other digital channels. It can include everything from product features and use cases to images, documents and commercial content.
When the information is in order, it is easier for customers to find, understand and choose the right product for their needs. Ultimately, product information management is also about building the customer experience.
Software company Adeona, based at Spektri, has been following this development for decades. The company was already automating the work of transferring product information into printed catalogues early on. The channels have changed and multiplied since then, but the goal has remained the same: the right information should be available in the right place when the customer needs it.
Now, another major change is under way.
Product information is no longer used only by people. AI-powered shopping assistants can search for products, compare alternatives and suggest solutions on behalf of the buyer.
This means the machine needs to understand more than what a company says about its product. It also needs to understand what a person is actually looking for, for what purpose and why – and connect that need with a suitable product.
The ‘AI tsunami’, as Adeona CEO Patrik Palatz describes it, is making an old issue newly relevant: the better a company knows, structures and describes its products, the better the starting point for AI to understand them as well.
Good data is becoming more valuable
The AI transformation is creating strong demand for product information specialists such as Adeona. AI can do a great deal, but the quality of its output depends on the information available to it.
According to Palatz, companies that have already taken care of the quality of their product information are in the best position for the change. The information needs to be correct and sufficiently rich, but also presented in a way that allows its meaning and connections to be understood.
AI is not the only change increasing demand for Adeona’s solutions. Companies face growing requirements concerning what they need to know and communicate about their products. Regulation related to areas such as sustainability, the circular economy and cybersecurity is increasing the need to keep information up to date and under control.
Technology and requirements change, but the idea behind Adeona’s work has remained the same. The company has long sought to automate repetitive tasks for its customers: machines handle the work they do better than people, while people retain the choices and decisions that require judgement.
AI is now changing how far this division of work can go. At the same time, it gives new importance to an old question: is your company’s own information in good enough shape for a machine to use it?
Expertise can be found next door
Adeona’s particular expertise lies in identifying bottlenecks related to product information in companies’ data, processes and tools. Palatz has a low-threshold suggestion for other companies at Spektri: if you are wondering whether your company could manage its product information better, you can come and talk about it even without a specific agenda.
At Spektri, Adeona works closely with Taito United, and Vieser is one of Adeona’s public customer references. New connections between neighbours also happen by chance. Recently, a meeting in the queue at Spektri’s lunch restaurant led to a conversation that the participants decided to continue over lunch to explore possible collaboration. And there is plenty to talk about with Patrik beyond product information and AI – including music, sports, coffee and dogs. So feel free to say hello!
