“Marketing is a one-way street. Public relations, however, is a two-way street that allows communication back and forth with audiences.”
This quote echoes a message that bounced around the walls of the PR agencies I worked at early in my career. The sentiment is accurate, but its spread fell short, likely because its arbiters were PR practitioners (LOL). But all these years later, as a result of discussions on generative AI, the idea has experienced a resurgence, particularly in the marketing sphere.
These days, conversations on generative AI in marketing typically revolve around marketers coping by calling themselves “prompt engineers” and CEOs exploring ways to gut content creation budgets.
But lurking underneath these developments is that message those old PR sages relayed to me all those years ago. The best way to engage prospects and create customers is via two-way conversation. A give and take — a dialogue instead of a monologue.
Because for too long, organizations have been standing on a ledge shouting in one direction. And if that’s been a struggle until now, imagine the near-future nightmare ahead of us: shouting one-way messages into that same void 一 now expanded to infinity in size 一 due to the ever-growing, endless amount of garbage produced by generative AI.
As It Turns Out, Those Old PR Sages Were Right All Along
Let’s get one thing straight. One-way conversations aren’t evil. They serve an essential purpose. They are your brand story, messaging and value proposition 一 all of which, in turn, drive your content efforts, advertising and social media output.
Perhaps most important, they form the foundation of your SEO strategy, which is crucial for being discovered by search engines.
So yes, while these one-way conversations are vital, it’s often presumed that once found via search, potential customers will have everything they need to make an informed purchasing decision.
And that’s bad news for many organizations because we’re fast approaching a critical point where providing customers with the information they need, instead of the information we think they need, will be more dire than ever.
This urgency exists because humans are changing how we ask the machines questions and businesses are simply unprepared for the shift.
The Problem with Modern Search in the Age of Generative AI
No longer are the questions of Who, What, Where, and When the primary focus of user queries.
For instance, an individual will typically search for products (Who), services (What), restaurant locations (Where) or operating hours (When). A request is made and information gets sent back via a one-way street.
Searches like this are performed daily by decision-makers with purchasing power researching B2B products and services.
But generative AI has changed the search game by introducing answers to deeper questions that tackle Why and How. Hence, generative AI is changing how we talk to the machines.
Why and How questions require a two-way conversation, often with several back-and-forths before a user is satisfied with the response. Even with Generative Search Results (GSR) currently in use by “Big Search,” there is a ceiling on the level of information and satisfaction that it delivers.
So you’re a B2B organization. What does this all mean?
Think of it this way. Who, What, Where and When queries are made by top-of-the-funnel prospects. Why and How questions, however, are posed by middle and bottom-of-the-funnel prospects — individuals who are serious about purchasing and need answers to deeper questions.
“Big Search” will always answer the simple questions. They’ve been doing it for years via enhanced descriptions, rich snippets, knowledge graph panels and everything else schema markup enables.
But in-depth answers to real-world business challenges will always be in demand. And it’s up to organizations to deliver those answers via a modern customer search experience that acknowledges search engines will always provide better answers to simple questions and highlights the importance of a smooth transition to your website where through content, demos, interactive tools and other resources, you can demonstrate the depth of your expertise and the promise of your product or service.
Wait a second. Doesn’t that sound exactly like SEO as we’ve always known it?
YES.
It just requires some upgrades and a shift in mindset around what generative AI in marketing and search can mean for your organization.
The Way You’ve Been Viewing Generative AI Is Wrong
To truly use generative AI in a way that helps you achieve strategic goals, you need to throw out the idea that tools like ChatGPT are nifty gifts to the executive gods that save money by writing free blogs and resource articles.
If anything, modern content needs to be more in-depth, more specialized and requires more expertise. This Is how to win in modern B2B SEO. This is how prospects determine who to trust. This is how you lead them to your website.
And once they are there, you must facilitate a two-way street search experience that delivers answers to their specific Why and How questions. Any other move shows the world you are satisfied with doubling down on a dying search and discovery model and aligning with customer preferences isn’t what you care about.
In order to rise to this occasion, organizations must adopt generative AI as a means to add intelligent search to your website.
To power such an application, they must tap into the robust data strategy they’ve developed, refined and perfected over the past quarter century to enhance user engagement and ultimately drive conversions.
Yes! It’s all about the data strategy.
How Your Data Strategy Powers Intelligent Search On Your Website
Okay, Let’s assume you’re part of one of the roughly 1/3 of companies (as evidenced here, here and here) that actually have a data strategy or deliver on one. Good news — you’re on track to not be buried by generative AI.
If you do not currently have one, while not great, there’s still time. Some resources so you can start can be found here and here.
Developing your data strategy might sound daunting, but the only lift required of you and your team is gathering and organizing data that likely already exists. The hard part of this process — providing structure, making sense of the data, and delivering insights that positively impact your bottom line — can often be managed by generative AI. Don’t believe me? Just ask Amazon.
How To Think About and Maintain A Modern Two-Way Search Experience
It’s important to remember the basics of search engine optimization and how search works to understand how to best use generative AI in marketing efforts, especially when it comes to building a two-way search experience.
Focus on Keyword Intent.
Understand the intent behind the inquiries you receive. Remember, the benefits of generative AI here stem mainly from intent keywords that capture How and Why inquiries from users.
- Example: The query “Why I need XYZ product for my business” can likely be addressed by the data points stacked neatly in your warehouse. However, the query, “How can XYZ product help me meet sales goals by Q4?” That inquiry should be handed over to a biz dev or sales rep immediately.
- Key Takeaway: It’s vital to understand when a chatbot or a human should answer a query as it could mean the difference between a quick bounce and a customer conversion.
The Riches Are In The Niches.
An old SEO adage. This means long-tail keyword queries with commercial intent will show up far less than short-tail informational keyword searches, but long-tail keyword queries with commercial intent are much more likely to convert to customers. Ensure your generative AI responses embrace this.
- Example: Suppose you run a startup specializing in SaaS-based project management tools. Many queries for “project management software” will likely come in. But you need to be ready for queries such as “project management tool comparison guide” or “cost of project software for remote teams” because the users behind such queries are much further down the funnel and more likely to convert.
- Key Takeaway: Beyond just recognizing the value in long-tail keywords, a plan for actively nurturing conversion paths is essential. These paths must be strategically mapped out with specific understanding of search intent.
Generative AI Requires Continuous Learning.
Iteration and optimization are necessary to build out intelligent search for your prospects and customers. Generative AI applications are not static and require learning through interaction. To ensure performance, embrace this continuous learning process and aid the application by helping it adapt to the new insights it gathers and your customers’ evolving needs.
- Example: By embracing a continuous learning and improvement mindset, an AI application has enough time to compile customer interactions and gather feedback to determine that users are most often interested in learning about the unique product features found in your SaaS project management tool. As a result, the application can adjust and become adept at delivering concise answers and helpful information that improve the customer experience and lead to more closed deals.
- Key Takeaway: We all want results in the form of more leads and more closed deals to be delivered yesterday. It takes patience and vigilance to achieve desired results.
Remember that the full-circle search experience starts with a one-way dialogue via search engines and ends with a chat experience on your website that uses internal data to answer the Why and How questions that close deals.
By adopting this strategy, businesses can align their generative AI efforts with user intent, creating a richer and more engaging customer experience.
It will also eliminate the hundreds of hours of company-wide meetings dedicated to discussing where to place a menu icon on a homepage, since customers won’t need to manually search for anything anymore.
Can you even imagine? That might be the biggest victory of all.