OpenAI doesn’t have much of an awareness problem. ChatGPT is already one of the most recognizable products in technology, and many of the people involved in an enterprise purchase have probably used it themselves.
OpenAI's B2B marketing strategy includes a somewhat surprising choice for a company with such widespread recognition. Leila Woodington, OpenAI’s head of B2B marketing for EMEA,said at a Semrush Spotlight panel in London earlier this month that field marketing is currently the company’s strongest channel. OpenAI also works with a carefully selected group of creators and influencers who genuinely love its products.
For a company with that much existing attention, the strategy raises an interesting point about B2B marketing. Getting people to recognize a product is one thing. Helping them understand why it belongs in their business is another, and the person delivering that explanation can matter just as much as the message.
Brand Awareness Isn't Enough for B2B Marketing
The difference between knowing ChatGPT and buying OpenAI for an organization is enormous. Woodington explained that enterprise adoption can involve convincing several executives and figuring out how the technology should work across thousands of employees.
That isn't necessarily a problem another million impressions can fix. An IT leader may care about security and deployment, while a marketing leader wants practical use cases and an executive wants evidence that adoption will create value.
OpenAI can explain those things itself, but buyers also look to people who understand their industries and the problems they deal with every day.
It's one reason field marketing makes sense for a company like OpenAI. In-person conversations give potential buyers room to ask specific questions, work through concerns, and understand how a product fits their organization. The same thinking helps explain why creators have a place in the strategy.
A Creator Can Be an Interpreter
In B2B creator marketing, professional expertise often matters more than broad appeal. Creators build audiences around what they know, and that knowledge is part of why people listen.
Someone who regularly discusses software development can explain an OpenAI launch through problems developers actually recognize. Another might have spent years covering marketing technology, giving them a different perspective on where the product fits.
Their value comes partly from the relationship they've already built with the audience. People follow them for particular reasons, and those expectations influence how their recommendations are received.
Woodington said OpenAI brings in creators who care about its products when something new launches. The company appears to be thinking carefully about who helps explain those launches to different audiences, rather than focusing on reach alone.
Local Expertise Matters
OpenAI is taking a related approach by building local marketing teams in the markets where it operates. According to Adweek, those teams include people who understand local languages, cultures, and trade organizations.
Local teams can help OpenAI understand how businesses in different markets approach AI adoption, from the questions they ask to the concerns they raise. This knowledge can shape how the company introduces its products and communicates with potential customers.
Personalization often focuses on changing the message for different audiences. But understanding an audience also means knowing where people go for information, whose expertise they value, and what kind of explanation they need. For complicated products or purchases involving several decision-makers, knowing who your audience trusts matters even more.
Choosing Creators for Their Expertise
Finding a creator with the right professional expertise takes more than knowing which industry they cover.
Consider a company marketing enterprise security software. A technology creator might understand the product well enough to describe its features, but someone who regularly discusses cybersecurity, deployment, and compliance can put those features into context. They know the questions IT leaders are likely to ask, the concerns that come up during implementation, and which details matter when a company is deciding whether to adopt something new.
Marketers can learn a lot from the subjects a creator regularly covers, the questions their followers ask, and how they respond to those conversations. Those details offer a better picture of the expertise a creator brings and whether they're equipped to explain a product to the people evaluating it.
Audience intelligence can help marketers make those decisions. Through RAD Amplify, RAD Intel's creator marketing business, brands can work with a team that uses AI-driven audience intelligence to match creators to specific audience segments based on demographic, psychographic, and behavioral insights.
Audience fit is only part of the decision. Marketers also need to consider how well a creator understands the product they're being asked to discuss. Someone who regularly covers enterprise security may be better equipped to explain a new security product than someone who's only discussed the subject in sponsored posts.
What OpenAI's Strategy Means for B2B Marketers
OpenAI is an unusual example because few companies begin with its level of recognition. Yet its approach to enterprise marketing still includes in-person events, local expertise, and carefully selected creators.
Even when people already know a product, they may need help understanding how it fits their work, what problems it solves, and whether it's worth adopting.
For marketers building B2B creator programs, expertise should be part of the selection process from the beginning. Look at what creators know well enough to explain, the conversations they've already had with their audiences, and whether they understand the concerns that come up when someone is considering a new product.
OpenAI's approach is a reminder that even a familiar product can take work to explain to business buyers. The right people can help make that explanation more useful, especially when the decision involves several stakeholders with different priorities.
