Tech’s Generative Search Playbook: If You Want to Be Discovered, Be Helpful

Kevin Cochrane, Chief Marketing Officer at Vultr, outlines why the key to getting discovered in generative search is, quite simply, to be helpful. This article originally appeared in Insight Jam, an enterprise IT community that enables human conversation on AI.

SEO is dead. At least, that’s what the content marketing crowd on LinkedIn would have us believe. The mass adoption of generative AI is changing how people seek information online, and marketing teams must adapt or risk being left behind.

Perhaps that much is true. But that doesn’t mean SEO is dead; it’s only evolved. With AI in the picture, SEO’s calculus of keywords and metadata isn’t as easy to hack as it used to be. But as companies ditch their old SEO playbooks and go all-in on generative engine optimization (GEO), one thing remains constant: being helpful is what gets you noticed.

An Education-Based Strategy

When people are looking for information or a solution to their problems, they want an expert. The purpose of SEO is to build authority and be recognized as the most reliable expert source on a given topic or query. Determined by the whims of an ever-shifting algorithm, authority governs how content ranks in the results page and, therefore, how visible a company is online.

In traditional SEO, authority was built through content frequency, accuracy, and credibility gained via third-party citations–those ever-valuable backlinks. Even without a strong link-building campaign and external reviews, companies could still bolster their authority with a steady flow of keyword-optimized content. Now, outside opinion carries far more weight than owned content. Third-party validation through media coverage, guest features, user reviews, and other non-self-promotional content is what drives GEO. Artificial intelligence may be assembling the results, but it’s prioritizing the real human opinions that people trust the most.

To stand out in generative search, today’s enterprise vendors need strong advocates. And to create advocates, they have to provide real value. Applicable, educational, accurate resources, such as technical documentation and tutorials, are the bedrock of a successful content marketing strategy in the generative search era.

Enterprise technology vendors have a unique advantage in that they can provide educational content to as many as four distinct audience profiles:

• The Decision-Maker: This is who ultimately decides whether to purchase your solution, typically someone in the C-suite or high up in operations. Decision-makers want to see ROI and competitive advantage, and will be drawn to case studies and data-backed testimonials.

• The Backend Developer: This audience subset is where technical documentation and tutorials are exceedingly useful. These are the people who are either using a given solution to build applications, maintaining it for their enterprise users, or both.

• The End User: Sometimes, backend developers are the end-users, as is the case with PaaS, IaaS, and infrastructure vendors. Other times, a customer’s larger workforce, or a subset of it, is the end-user. These users benefit greatly from tutorials and tips that can help them use the product to solve their day-to-day working problems. End users and developers are also more likely than other audiences to leave reviews and feedback online, so ensuring they have easy online access to resources is critical to reputation management.

• The Researcher: Journalists, bloggers, students, teachers, and other non-stakeholders who might benefit from a company’s content can be instrumental in bolstering its authority by citing a company’s resources in work published online. While researchers are not always the most critical audience, it would be remiss to overlook their influence, especially as generative engines hook into earned media.

Scaling Content with AI (The Right Way)

Consistent content production can increase a company’s revenue by up to 23 percent, and AI makes it easier than ever for companies to keep up a steady cadence and maintain their status as a current and reliable resource for browsers.

Train an LLM with a company’s messaging and editorial style, program a litany of dos and don’ts, craft a detailed prompt, and the AI can generate a blog post or report that looks convincing on the surface. It reads smoothly, captures critical information, and makes snappy statements that feel human. But a closer look may reveal that cthe ontent still needs a touch-up. A context-driven approach, balanced with AI tools and human expertise, will help tech companies scale their content endeavors with efficiency and quality.

Our marketing team at Vultr is lean, but in reorganizing our content stack for AI, we’ve been able to scale production without bloating headcount or driving up a freelance budget. Leaning on AI also frees up more time for the marketing team to better understand our customers and their needs. Then, when they create content to address those needs, AI can expedite the process, while the personal connections they’ve forged bolster their human expertise.

AI programs can be trained to optimize for SEO, but they might still be running on the old rules. Keyword stuffing doesn’t work the way it used to. Instead, one might gauge the usefulness of a blog or technical document using an LLM: prompt it with the blog and ask it to generate takeaways. If it’s not conveying the intended message, the content likely needs further editing.

AI also excels at quick iterations. Say the goal is to make multiple versions of a survey or report that highlights different portions of the data – this might be a specific industry or demographic of respondents. AI-powered analytics make it infinitely easier to analyze data in segments, and can reveal patterns and insights a human analyst might miss.

However, that final human check is crucial, as hallucinations can still arise, even as AI gets smarter. Incorrect data and insights, if left uncorrected and published online, can ultimately damage an organization’s authority, causing more harm than just a drop in search rankings. By using AI to scale and diversify content, vendors will reach new audiences with more quality resources, expanding their search footprint and increasing their likelihood of being picked up by generative search engines.

The Power of Relationships

Even in the most technical of enterprise spaces, the power of empathy and human perspective is a differentiator. Some of the best technical content starts with a casual conversation on the sales floor.

Being helpful is about understanding pain points–a primary part of a salesperson’s job. But standout content requires additional nuance. Research shows that engaging with real people, rather than white-label brand content, can make buyers feel more connected to a brand, and connection begets trust. Building real relationships with clients and prospects creates an ongoing dialogue that can inform highly specific, highly impactful content.

Think of the questions that people ask in developer forums and Reddit threads. This is the exact kind of content that generative engines are surfacing to users who want a personal perspective or have ultra-specific requests, but it also emerges from strong, trust-based relationships. The marketing team should collaborate closely with the sales team to understand buyer groups. When people want authentic content, it’s crucial to engage with the audience rather than center a strategy on broad statistics. Data-driven doesn’t mean data-exclusive – one offhand comment can illuminate a customer need that a structured survey might never uncover.

At Vultr, when creating our technical documentation, we have conversations with developers about extremely specific workflow problems and needs. These are highly precise, requiring layers of knowledge that we won’t necessarily tap in a typical marketing blog. Even then, our general marketing content can be highly technical because that is the audience we are serving. Part of establishing authority in the AI search era is about appealing to an in-group, as the forums and reviews it cites often do, and the use of jargon signals that understanding. It’s more than using keywords – it’s enterprise dialect.

But how do relationships grow when most B2B buyers prefer a rep-free sales experience? It all goes back to being helpful. Don’t try to sell something right away. Try to solve a problem, understand a frustration, and explore an issue. Then, take that dialogue back to the content desk. By becoming a source of helpful information, whether that’s technical documentation, a tutorial, or an industry report that can guide a strategy, vendors can and should offer more than just a product.

As people become more reliant on digital agents and AI search engines, providing genuinely useful information will take precedence over content cadence and keyword repetition. Moreover, it will be crucial to foster relationships with stakeholders across the user-buyer spectrum, thereby increasing your chances of receiving third-party validation, which has become the linchpin of AI search optimization.

Beyond improving discoverability, these tactics will foster long-term trust with buyers and users, helping sustain a positive brand reputation that will be reflected in search engine rankings and sales results alike.