Audience profiles, like the ones you can enrich with Reddit data, are not enough for your digital marketing strategy. Your strategy depends completely on mapping your audience to conversion channels and intents.
In an ideal world, sure, we could put together a list of people, reduce them to a few general archetypes, find them online, and start blasting messages. In the real world, those archetypes don’t accurately represent your customer base, and they’re a constantly moving target.
Meanwhile, AI is making the story more complicated by adding another layer to how people discover, evaluate, and purchase products/services.
That’s why, if you haven’t already, now is the time to start deepening your understanding of your customers and their journeys.
Understanding a Customer Journey
Now I’m not saying that audience profiles are fruitless. I believe they serve as useful tools and benchmarks for making messaging decisions or understanding the customer journey.
But they are only a part of the broader picture. Before a consumer ever finds your brand, they first have to realize they have a problem; discover or recall a solution; and find you online or in the wilds of real life to have a real impact on your business.
And the mission isn’t simply to construct a timeline; it’s to construct a million different alternate universes.
Blue shoes will be a perfect example of this. So let’s pretend for a moment that we sell blue shoes. We have a great audience profile, but we need to go beyond that, so we start with something easy.
Start With Search Intent
Intent is not obvious, but it can be effectively triangulated using keyword data. This is why I’m so thankful to have started my career in SEO, because it exposed me to one of the most powerful tools in the digital marketing arsenal. Keyword research.
Mkay, so why would keyword research help us identify customer intent? Well, primarily because it’s an instance of inbound marketing, meaning people initiate the action instead of being interrupted and/or persuaded.
So, let’s fire up the good ole’ Google Search Console (GSC) and pull some data!
If you haven’t already set up an account, reach out, and I’d be happy to set you up with an account for free. The Process is easy, and it benefits you 1000x in your SEO/AEO strategies.
Also, a word of warning: GSC only displays the first 1,000 rows of data. This is fine for small businesses, but not for larger organizations with larger websites and a significant search footprint. If that’s your situation, I recommend you utilize Data Studio, another Google product, where you can connect your search data and pull unlimited rows.
Now you can either manually identify clusters or use AI.
If you are doing it manually, I recommend setting up a split screen and cataloging the examples you find. It can also help to segment the data in a few different ways; one is looking at all the longest queries you were able to uncover. These can serve as a good point of investigation. Otherwise, you can look at queries that are new, queries where you rank on the second page, or queries where you rank well as a good point of reference. All of these segments help you understand your site’s performance and the keywords themselves.
Otherwise, AI is effective at identifying intents. Simply using a prompt like the one below could help you expedite the process.
{Prompt Example AI Agenerated}
Connect Intent to Performance
The biggest issue with many marketing strategies is that they don’t connect intent to conversions, and it’s not because marketers are lazy. Although we do like a long weekend, the reason is because there isn’t an inherently obvious process. Google Analytics 4 (GA4) keeps search data separate and GSC is fundamentally different, so it doesn’t track conversions or events.
Meaning there is no obvious way to segment key events by query.
There is a workaround, though: landing pages can serve as a bridge, allowing us to attribute conversions to general intents. Of course, multiple intents exist per page, but it gives you a starting point. So let’s return to our fake example, which I just bought a domain for, blueshoes.com
We have the GSC queries; let’s also pull some GA4 data.
If you’re unfamiliar, GA4 allows you to add key events natively in the platform. Configure the key events and go to Reports -> Generate Leads -> Landing Page
Now export that data, and let’s match the landing pages from GSC to those in GA4.
Using landing pages as a proxy for intent performance is incredibly powerful because it helps you shape your strategy and decide where to allocate resources. Making it easier to identify which intent clusters are associated with stronger outcomes
Identify the Channels Customers Actually Use
Search intent gives us one piece of the journey. The moment before action, but it doesn’t tell us exactly where that potential moment could happen. Or the moments leading up to and, perhaps more importantly, after the action is taken.
GA4 acquisition reports are one place to start. Look at which channels are bringing people into the site and which channels are associated with conversions.
Break this down further wherever possible, by segmenting by landing pages or by specific events. This can help you answer questions like, do organic visitors behave differently from paid search visitors? Does social generate a lot of interest in specific topics? Are returning visitors more likely to engage or trigger conversion events?
Attribution reports can provide additional clues about which channels appear earlier or later in the conversion process. For example, if you’re seeing that social doesn’t convert at a high level, then you
You can also supplement your first-party data with information from the platforms themselves. Google Ads, Meta, LinkedIn and other platforms provide varying levels of audience and campaign data that can help validate assumptions about where your audience spends its time.
The important thing is that we’re not simply saying:
“Our persona is 35 years old, so they’re probably on Instagram.”
We’re looking for evidence that a channel actually plays a role in the journey.
Research What Happens Inside Those Channels
Once we know where customers are showing up, we can start studying what they’re doing there.
This is where traditional audience research becomes extremely valuable again.
- Search Reddit, YouTube, TikTok, and Instagram
- But don’t forget other platforms like Discord, WhatsApp, and Twitch
It’s important to answer a few questions:
- Where does your audience show up the most?
- What are they saying inside those channels?
- What groups do they frequent?
- Where do they need help?
- How often and when are they active on these channels?
For blue shoes, maybe Reddit conversations reveal that people frequently complain about brightly colored running shoes looking dirty after only a few weeks. Maybe YouTube reviewers spend an unusual amount of time discussing whether certain shoes work for wide feet. Maybe Google’s search results are dominated by comparison articles rather than product pages for a particular query.
These are signals, and provide one of the final pieces of the puzzle, as we start to better define our audience’s journey.
Build the Journey From the Evidence
Now we can finally start assembling our customer journey.
Instead of starting with a persona and inventing a neat funnel around them, start with what you can actually observe.
You might have something like:
Intent: Comfortable blue shoes for standing all day
Search behavior: “best blue shoes for standing all day,” “comfortable blue work shoes,” “blue shoes with arch support”
Entry channel: Organic search
Landing content: Comfort-focused buying guide
On-site behavior: Reads comparison guide → views two product pages → checks sizing information
Conversion: Purchase
Supporting research: Reddit and review analysis repeatedly identify cushioning, arch support, and durability as major concerns
Suddenly, our audience profile has context.
We haven’t just described who this customer might be. We’ve started documenting the problem they’re trying to solve, how they express it, where we can reach them, what information they need, and which behaviors correlate with a business outcome.
And you can repeat this exercise across dozens of intent clusters.
Some will represent early research.
Some will represent comparison shopping.
Some will be extremely transactional.
Others may have surprisingly little search volume but consistently produce valuable customers.
That is where the customer journey starts becoming useful for marketing decisions.
Separate What You Know From What You Think You Know
There is one final step that I think is especially important.
Mark the difference between observed behavior and inference.
Some things we can actually observe:
- Someone searched a particular query and our page appeared
- A channel generated a visit
- A user landed on a particular page
- Visitors engaged with particular content
- A particular landing page or channel generated conversions
Other things are inferred:
- Why someone searched
- What emotional trigger motivated them
- Exactly where they were in the buying process
- Whether one channel caused them to use another channel
- What they were thinking before converting
And then there are hypotheses:
- People researching comfort probably need comparison content before seeing products
- Reddit may influence users who later search for our brand
- Visitors researching sizing may respond well to a fit calculator
- Certain informational searches may eventually produce higher-value customers
Those hypotheses shouldn’t be discarded.
They’re incredibly valuable.
They just need to be treated as hypotheses.
Test them.
Create the content. Change the landing page. Run the campaign. Track the behavior. Conduct the survey. Measure what happens.
Then feed what you learn back into your understanding of the audience.
Your Audience Is a System, Not a Persona
This is ultimately why I think audience research needs to evolve beyond personas.
A persona can still be useful. Knowing someone’s job, concerns, priorities and general characteristics gives marketers a convenient way to think about the people they’re trying to reach.
But the persona is only one layer.
What matters is connecting that person to the needs they express, the questions they ask, the channels they use, the content they encounter and, ultimately, the actions they take.
And increasingly, AI will sit somewhere inside that process.
Someone might ask ChatGPT for recommendations before ever searching Google. They might encounter an AI Overview that summarizes five websites without clicking one. They might use AI to compare two products and then navigate directly to the brand they choose.
We aren’t going to perfectly observe every one of those interactions.
That’s okay.
The goal isn’t to create a perfect diagram of every possible customer journey.
The goal is to progressively reduce the extent to which your marketing strategy is based on assumptions.
Start with what you can observe.
Use qualitative research to understand what the numbers can’t explain.
Clearly label what you’re inferring.
Then test those assumptions against real behavior.
Your customer journey will never be finished.
But with every new signal, it can become a little less imaginary.