TL;DR: Yes. And no. AI is changing the way content can and should be created (two different things) and will change the way buyers choose to find information.
Underneath, however, nothing much has changed about the buyer's journey itself.
Confused? Well, the B2B buyer’s journey can be complex and convoluted, and now there are several pieces moving at once.
Let’s dig in.
The buyer’s journey tracks a prospect from whenever they first begin to think about a challenge that your solution can help solve to when they become a loyal customer, advocating about your brand and solution to others.
We published a handy guide to the key concepts and benefits of B2B buyer’s journey mapping to help explain things.
In our definition, the buyer’s journey breaks into five stages:
1. Awareness – learning about their challenge and deciding whether it’s worth looking for a solution.
2. Evaluation – finding and comparing potential solutions to decide which, if any, are worth pursuing (or whether it’s better to stick with their status quo).
3. Selection – answering any remaining questions, convincing the rest of the team, negotiating terms, and making a final purchase decision.
4. Implementation – putting the solution they’ve just purchased into action, hopefully solving the original challenge, and delivering the expected value (or more). This stage is sometimes broken into installation and commissioning.
5. Loyalty – becoming a repeat customer and, ultimately, developing sufficient respect for the brand and its solutions that they will become an advocate and tell others to make a similar purchase.
While this nomenclature is handy for labeling prospects as they progress toward becoming a customer, and later an advocate, the real power of the buyer’s journey lies in using it to plan your content marketing strategy.
By understanding what the buyer needs to learn to progress from one stage to the next, you can supply them with relevant, helpful information along the way.
Done effectively, this can greatly improve the chances of any given prospect completing their journey as well as increasing the overall percentage of prospects who do so.
In addition to discerning what the buyer needs to learn, you can also map where they go to find such information, and what tactics and technology you can employ to meet them there and convey the information effectively.
I don’t need to tell you that artificial intelligence (AI) enabled apps and tools are popping up everywhere. It’s an incredibly adaptable and pervasive technology.
I even heard a rumor that there’s an AI tool for people living under rocks. LOL.
So, it would be reasonable to assume that AI has found its way into the buyer’s journey.
And indeed, we see AI at work in 5 main areas:
1. Buyers using AI to find information instead of seeking it on the channels that they would previously have frequented.
2. Buyers using AI to parse the information they find in support of superior decision making.
3. Solution providers using AI to better understand the buyer and their buying journey.
4. Solution providers using AI to produce content.
5. Solution providers using AI to provide customer support.
Each of these applications is impacting both the buyer and the solution provider, though not necessarily to the same extent or in an exclusively positive way.
A decade ago, salespeople held sway over the flow of information about their company’s solutions.
To get to the juicy details, buyers were forced to interact with salespeople, either in person or over the phone.
This gave the salesperson an opportunity to engage, persuade, and occasionally pressure the buyer into choosing a particular solution.
As the internet increasingly made information accessible online, buyers began looking there first. Solution providers that chose to upload their information gained mind share and market share. Those that did not risked obsolescence.
Then COVID lit a fire under the whole process.
Overnight, buyers moved from central offices to remote working.
End-to-end digital buying processes rapidly displaced legacy approaches.
Older generations of buyers retired and were replaced by Millennial and Gen-Z digital natives.
Suddenly, the salesperson was left with very little control. Everything—from search, to evaluation, to negotiation, to purchase—was expected to take place online.
The last thing a buyer wants to do these days is interact with a salesperson.
As we preach from our soapbox, content marketing has become mission critical for solution providers wanting to ensure that their brand and solutions are top of mind for prospective customers.
AI assistants will soon be doing most of the heavy lifting when it comes to researching and evaluating challenges and potential solutions
Then, along came AI-assisted search.
While still in its infancy, it’s clear that AI assistants will soon be doing most of the heavy lifting when it comes to researching and evaluating challenges and potential solutions.
Whereas today a vendor might track visitors to their website and social media channels to help spot potential buyers, tomorrow it will be AI agents hoovering up the content to help answer their buyer master’s questions.
You won’t be writing content for human readers anymore. You’ll be writing it for AI algorithms to parse and present to those readers.
Your buyers won’t be visiting the same channels—websites, social media, print media, trade shows, etc.—in search of information when they can obtain it in seconds by prompting AI to do the legwork.
Is this a good thing or a bad thing?
On the one hand, human readers are fickle, flighty, and prone to misinterpretation. AI will read every word you write, not get distracted by a push notification on its phone, and is largely incapable of misconstruing what you’ve presented.
On the other hand, the primary motivation behind most content production—that of inducing a desired emotional reaction in the target audience—is largely defeated. AI doesn’t feel. AI applies logic and rationale first, rather than using it to justify a decision that’s already been made based on emotion.
Score one point for the buyer, who can avoid being emotionally manipulated and make their purchasing decisions based entirely on facts, features, and expected value.
Deep customer understanding lies at the heart of effective content marketing strategy.
First, you must identify which group of companies represents your ideal customers.
Next, you must describe the buying committee that acts on behalf of those companies when making a purchasing decision.
Third, you must create detailed descriptions of the buyer personas who make up the buying committee.
And finally, you should create buyer’s journey maps for the key personas that your company must engage and influence to win their company’s business.
To reflect the realities of your target audience, buyer personas must be based upon solid research and real-world data, not assumptions or stereotypes.
AI can help here by collecting and analyzing customer data from across the internet, using sources like social media and review sites to create a more accurate representation of your buyer.
This doesn’t absolve the customer-facing team from doing their homework and putting in the hours to create detail journey maps, but it provides a much stronger starting point than was the case before AI came along.
When we throw generative AI into the mix, the challenge of getting prospects’ eyeballs onto your relevant, helpful content becomes greater than ever.
Buyers are inundated with a tsunami of similar-sounding material. Thankfully for them, they have AI to provide a flood barrier that only allows a controlled amount of information through.
Solution providers must compete with floods of rapidly generated content, making it hard to get seen or heard above the cacophony.
For many marketers, it’s tempting to slip into a click-bait mindset and simply follow suit.
A disproportionate amount of marketing energy goes into the short-term generation of likes and clicks, instead of into developing well-crafted content that enhances your brand and supports your customers at each stage of their buyer’s journey.
AI-generated content seldom translates into measurable engagement. There are too many zero-click outcomes.
It provides plenty of specs, features, and benefits, but lacks educational value and fails to provide the buyer with a bridge to the next stage in their journey.
A true test of content leadership is offered by the value it provides to the audience.
The key lies in original thinking.
Human writers—whether AI-assisted or not—do more than just echo others’ opinions and ideas; they offer unique insights that relate to the buyer’s needs.
They create educational content that leads the buyer, step by step, through researching and evaluating solutions toward a purchase decision that’s right for them.
Nevertheless, the process of producing and editing that content can certainly be enhanced using AI tools.
Since a typical B2B buying journey involves multiple decision-makers, each with their own pain points and interests, you must produce content covering a wide range of subject matter and in multiple formats. AI tools are useful here to help with ideation, topic coverage, and exploring new formats.
Employing tools like ChatGPT as a research assistant is nothing short of revolutionary. It takes seconds to find and summarize contextual information that it would take a human researcher hours, if not days, to locate.
And having an AI-powered writing tool improve the readability of your drafts leads to published output that’s easier to ingest, understand, and recall.
AI-powered analytics can help you to continuously evaluate and improve the performance of your content.
And last, but not least, AI-powered chatbots and help desk apps can help your customer success team deliver faster, more accurate answers to customer questions.
Your knowledge base, which includes FAQ and more sophisticated technical answers, is an often-overlooked element of content marketing. Making such information available to customers during the implementation stage of their buyer’s journey is a vital step in ushering them on to loyalty and advocacy.
Once again, there’s danger in letting AI do too much of the work.
Unless the bot is extremely well trained, it will be prone to giving inane, if not incorrect, answers that frustrate the customer and simply delay their interaction with a human agent.
Some humans don’t want to deal with a bot in the first place, so you must always offer a shortcut for them to reach the humans behind the screen.
Finally, AI lacks the intuition needed to see beyond the customer’s immediate question and spot a more fundamental, underlying issue that needs to be addressed.
High-performing human agents excel at this task, leaving customers in awe of their ability to diagnose a situation and find solutions to problems they didn’t even know they had.
While the underlying buyer’s journey hasn’t fundamentally changed, AI is rapidly transforming the world of content marketing that feeds it.
The new world of content marketing revolves around human-AI collaboration.
As we’ve seen, this applies to both the solution provider who is producing the content and the buyer who needs the information it contains.
AI-assisted ideation and curation saves time and effort in producing a comprehensive content library and maximizing the performance of individual pieces.
AI-assisted content creation can deliver astonishing productivity gains and provide contextual depth that would previously have required a prohibitive amount of research.
AI-assisted research and recommendations will fundamentally impact the way buyers find, compare, and select solutions—no matter how that makes solution providers feel. Can vendors afford to not put the information online in a vain attempt to force buyers to interact with their people?
We must learn how to work with AI, not against it
The productivity gains offered by AI are too attractive to ignore; instead, we must learn how to work with AI, not against it.
Use AI to generate content ideas.
Use AI to create first drafts, which you can then edit and augment with authentic, unique ideas and opinions.
Use AI editing tools to improve readability, achieve a consistent voice and tone, insert appropriate images, and ensure compliance with brand guidelines.
But never hand AI the keys and let it fly solo.
Minor differences in prompts can result in vastly different outputs. And without human guidance, AI will generate content that falls short of the level of quality you would otherwise achieve.
Predicting the future of a fast-moving space like artificial intelligence is a fool’s errand. Ironically, it’s something even the AI tools won’t attempt.
However, when it comes to B2B buying and content marketing, there are a couple of intriguing possibilities.
First, the B2B buying process might become increasingly automated, to the point where human category experts become a thing of the past.
Instead, trained AI algorithms will take a list of items to be procured and scour the internet for everything from specifications to pricing to availability and lead times.
Based on this information, purchase orders will be created—probably, but not necessarily, approved by a human—and issued to production management algorithms on the vendors’ side.
In this scenario, solution providers must make all the requisite information available online—including access to pricing and inventory—otherwise the buyer’s AI will simply exclude them from the process. The term “approved vendor” will take on a whole new meaning.
A second possibility is that we will see a pendulum swing back toward human connection, authentic communication, and trust-based purchasing.
Some of these elements have survived the digitalization wave and AI’s rise to this point, albeit in isolated pockets rather than the mainstream.
There is evidence to suggest that Gen-Z buyers are more attuned to authenticity and trust-based relationships than their predecessors, presumably in a visceral reaction to the flood of internet sewage they have had to endure.
This could tap the brakes on AI’s march to content domination and help create a quasi-stable middle ground where human-AI collaboration can flourish.
It’s a scenario that gives us hope and sustains our faith that two humans can still cut a better deal, all things considered, than two emotionless computer algorithms.
I’m sure we will be writing many more AI-assisted blog posts on the topic!
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Image credits: Adobe Stock
