In B2B markets, the customer’s reliance on the World Wide Web for answers (we suggest) is fading. A new set of knowledge sources is emerging from AI-driven search engines to customised knowledgebases.

This transformation has significant implications for B2B marketers. It’s a particular challenge for those who have built their careers on online marketing implementation.

Redefining Information Retrieval

Let’s imagine in early 2025 an engineer is trying to solve a problem with one of their new designs. Where are they going to look for information? We suggest they will work through (from top to bottom) the following list.

  • Word of mouth
  • Customised knowledgebases
  • AI-based search engines (eg
  • Offline resources
  • General ChatGPT type applications (e.g. ChatGPT)
  • The World Wide Web

The question is, which will prevail? Will it be Google/Bing or the AI search engine start-ups like Perplexity. More likely researchers will use a combination depending on their needs.

Information Sources – An Overview

First, a quick overview of the advantages and disadvantages of each information source

Word Of Mouth – The natural first stop for any engineer trying to solve a problem will be to ask trusted colleagues. Has anyone had a similar problem? Can anyone provide some initial help or guidance?

Sometimes, this approach will deliver a solution. More often, it will at least provide a starting point to guide further research.

Customised knowledgebases – We expect significant growth in this area over the next few years. Knowledgebases may be internal to the business or external (provided by suppliers).

The key word is customised. These knowledgebases (of which there might be many) will be domain-specific and focussed on a particular topic.

AI-based search engines – These are starting to emerge. No clutter, no Ads (at present), and short, on-topic answers to questions with links to further resources. The experience is an order of magnitude better than the World Wide Web.

ChatGPT-type solutions – These have existed since November 2022. Unlike customised knowledgebases they are more general research tools.

With customised knowledgebases, AI-based search engines and ChatGPT type solutions, to receive a relevant answer you must ask a specific question. The prompt is key.

Offline resources – These include Ads to convert those in market, but they tend to be more awareness than lead generation based. These include print, PR, exhibitions and conferences, seminars and webinars.

Many engineers will continually educate themselves, so they are better placed to identify a solution if/when a problem occurs.

Internet – The decline in the World Wide Web as a useful research tool we discussed in our information delivery challenges and trends post. With the rise of AI-generated content the situation will only get worse.

In response, Bing has incorporated AI-driven features into their search results. Google will follow with search generative experience (SGE). At present the user experience is poor, but it should improve.

The Impact on Marketing

Social media in B2B markets is a brand-building tool at best. LinkedIn InMail has become the new cold calling. Email marketing still works well for existing customers, but as it becomes harder to be found online, it becomes more difficult to maintain or grow a prospect email list.

We suggest many small to medium-sized businesses in B2B markets started to move away from online marketing several years ago. The focus returned to Account Based Sales supported by content in both new and traditional formats. Word of mouth inside potential customers has been an area Account Based Salespeople have tried to stimulate for decades.

What is new is ChatGPT and customer proprietary knowledgebases. Currently, marketing is excluded from both. The customer decides what goes into their knowledgebases. Whereas the output of ChatGPT-type applications depends on their (massive) training data.

Marketing may have a glimmer of hope with AI-driven search engines (like PerplexityAI and Claude) that link to sources. Could this be the new SEO?

Supplier Knowledgebases

If a supplier has:

The time, resources and inclination to create (and maintain) a customisable knowledgebase that is useful to their customer base.


An existing relationship with a customer that is strong enough to persuade the customer to at least trial that knowledgebase.


Sufficient decision makers within the customer find the knowledgebase useful as a resource.

Then there is something for sales and marketing to build on, at least for existing customers. We have discussed how knowledgebases could play a crucial role in cultivating robust and well-informed relationships between B2B businesses and their customers previously on this blog.

That’s a big IF, you may say, but no more so than publishing content online (or social) in the hope a target customer finds and reads it.

Existing Customers vs Prospects

The above discussion assumes a supplier has some existing relationship with a customer. What if a new start-up, or company our engineer has never heard of has a solution.

From the engineer’s perspective, WoM and in-house knowledgebases will not help – they don’t know, what they don’t know. Supplier knowledgebases are not an option as the engineer does not know the supplier exists.

The internet is useless (as described in our the changing landscape of online search post) for finding something new from a new (not a big brand) supplier. ChatGPT and & Chat-based search engines are unlikely (in their current form) to surface something new.

What is a supplier to do? One option is to resort to the Account Based Sales and offline demand generation marketing approach that has existed for decades. Another is to promote their knowledge bases. A third is to try to penetrate (be added to) customer knowledgebases. An activity familiar to any salesperson who has tried to access an approved supplier list. Each of these options we will discuss in future posts.

Of course, the above is just a prediction and they, by their very nature, are often wrong. You could sit on the fence and watch how the situation develops. The problem is deciding when to jump off the fence and take action. Jump too late and it could take months (or years) to catch the early adopters. Jump too early and you could waste time and resources.

Learn more in our impact of AI Guide


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