Most semiconductor products’ value propositions are hidden from view. It need not be so.
Vintage camera with film: before the smartphone, consumers’ use of cameras was limited by its cost and inconvenience
Unmet needs have a funny way of going unnoticed, often for years on end. Then when something – a new product, or a new technology – emerges to enable the need to be met, we suddenly wake up to the realisation of what we had been missing. Photography is a familiar example of this. I was born in the 1960s, in the days of film cameras: I own almost no visual records of my childhood and young adulthood, because good-quality cameras, film, and film processing were so expensive. I and most other people my age had only a cheap, low-resolution camera and took few photos.
Then along came digital photography, and smartphones with a high-resolution camera built-in. And all of a sudden, we realised that what we had wanted to do all along was to take and keep pictures of everything, all the time. Photography, it turned out, was a great unmet need.
Full-spectrum information assets for all products
A similar unmet need could be about to emerge into the light in the domain of product information, again because of a generational shift in technology.
It might seem perverse to talk about an unmet need for information in the era of Wikipedia and Google search. But Google search and even AI agents can only produce answers on topics for which information has already been created online. And the amount of information that has already been created has been constrained by a) the resources available to create it, and b) the publishing resources available to distribute it.
And in both cases, technology has today practically eliminated the constraints, just as smartphones eliminated the constraint on the number and quality of pictures that consumers could take with a camera.
Constraint a), the creative capacity to produce information-rich libraries of product information, is now solved by the ability of AI agents to create any type of marketing document – an article, a product comparison table, a white paper, an application guide – instantly from a product marketer’s brief.
And constraint b), the ability to distribute the information to those who need it, can now be met by the latest sophisticated marketing automation and customer relationship management tools which manage direct communications between vendors and customers. Now, it is possible to know the product and application interests of any contact on your database, and to direct relevant new product information to them at will.
How can this play out in practice? Today, semiconductor companies ration their marketing assets. Every product has its own datasheet and a page on the company website showing basic features and specifications. But only the highest-priority new product introductions get the full spectrum of information assets, such as in-depth technical articles explaining the special value of the product, a white paper describing the product’s relationship to the application space, a video demonstrating the product in an application, a webinar backed by a slide deck.
What about all the new products which are not classified as high-priority? In general, no such assets are created – just the datasheet and a list of features published online. The full value proposition is known to the product manager, and often to expert FAEs as well: they might explain it in person to a lucky handful of key account customers. But the rest of the world remains blind to the value of the product. Worldwide, tens or hundreds of thousands of design engineers could remain ignorant of the value of a product that they would have chosen to evaluate had they understood why it was the superior choice for their application.
Technology busts the information limit
This is the unmet information need which B2B technology marketers can now meet, thanks to AI agents and online publishing tools, including marketing automation systems. By massively increasing the range and depth of the product information that they provide, marketers can not only enable more engineers to understand the value of all their products, they can also improve their company’s AI search visibility, since AI agents look for answers to engineers’ real questions – and high-quality product information should directly address the engineering issues which determine an OEM’s product choice.
This new approach to product information calls for a new mindset: embracing the era of ‘information abundance’, marketers can now provide a full spectrum of information about a product’s value proposition, not only for the highest-priority products, but for all products in a company’s portfolio. The prize for those who seize the opportunity to open new windows on to their products’ value propositions will be measured in higher numbers of leads, design wins and ultimately sales, as well as improved AI search performance.
Contact Tim Weekes Communications Consulting today for a playbook on how to harness AI agents to dramatically increase the depth and range of your company’s product information.