When someone asks ChatGPT for a product in your category, it doesn’t always crawl websites in real-time.
Its first move is to pull from what it already knows about you and your competitors from its existing knowledge.
Clear and recognizable entities in AI training data are just as important as having the most authoritative and optimized website.
This shift means your webpage might rank #1 in classic search, but if your brand isn’t well-structured for entities, AI might overlook you entirely in the answer.
The rules we’ve relied on for decades don’t fully apply when machines create answers. They draw on their own knowledge and real-time data from sites, including yours.
You’re about to learn what this means, why it matters, and what you can do about it.
What Are Entities in AI Search?
An entity is a “thing” that search engines and AI models can recognize, understand, and connect to other things.
Think of entities as the building blocks that AI uses to construct answers. In other words, gigantic relational databases.
Let’s use email marketing company Omnisend as an example.
Through the lens of a database, Omnisend isn’t just a website with pages about email marketing. It’s a network of connected entities:
Use cases: “welcome series,” “abandoned cart recovery”
Here’s what the entities look (hypothetically ) like to a large language model (LLM):
These records become the foundation for AI answers.
LLMs do more than just find keywords on your page. They also retrieve entities, place them in vector space, and choose the ones that best answer your question.
Vector space explained: It’s a mathematical method that AI models use to understand relationships between concepts. Imagine a 3D map where similar items group together. For example, “Apple,” the company, is close to “iPhone” and “Tim Cook.” Meanwhile, “apple,” the fruit, is near “banana” and “orchard.”
For example, ask Google: “What’s the best email marketing tool for my Shopify store?”
You’ll see brand entities like Klaviyo, Omnisend, Brevo, Mailchimp, Privy, and MailerLite mentioned. This makes sense because the entities are closely related in the AI’s understanding.
Notice: the brand mentions aren’t linked to the websites. It’s just building the answer and then linking to the brand SERP on Google.
Why Entities Matter More Than Websites
AI models are constantly mapping relationships between entities when serving up answers.
When someone types “best email marketing tool for Shopify,” LLMs spread out the query. They turn that one question into multiple related searches.
Think of AI doing lots of Google searches at the same time.
The system simultaneously explores “What integrates with Shopify?”, “Which tools handle abandoned carts?” and “What do ecommerce stores actually use?”
Your brand can appear through any of these paths, even if you didn’t optimize for the original query.
Classic SEO relied a lot on keyword density and page authority.
But AI uses dense retrieval, where it’s looking for semantic meaning across the web, not just word matches on your page.
Dense retrieval explained: AI systems focus on meaning, not just exact keywords. They find related content, even if different words are used.
A Reddit comment that clearly explains “We switched from Klaviyo to Omnisend because the Shopify integration actually works” carries more signal (assuming the model prioritizes authentic discussions) than a page stuffed with “best email marketing Shopify” keywords.
The AI understands the relationship between the entities (Klaviyo, Omnisend, Shopify) and the context (switching, integration quality).
PR folks have been fighting for this moment: mentions without links still count.
For the longest time, we’ve obsessed over backlinks as the currency of SEO.
But AI systems recognize when brands get mentioned alongside relevant topics, using these as relationship signals.
So when Patagonia appears in climate articles without a hyperlink, when Notion shows up in productivity discussions on Reddit, when your brand gets name-dropped in a podcast transcript — these all strengthen your entity in AI’s understanding.
Here’s a real example that clarified this for me:
Microsoft OneNote often shows up high in AI recommendations for “note-taking tools.”
In ChatGPT:
In Perplexity:
And in Google AI Overviews:
But EverNote dominates Google’s number one ranking spot for “note taking tools”.
Why?
OneNote’s integration with the Microsoft ecosystem means it gets mentioned constantly in productivity discussions, enterprise software comparisons, and Office tutorials. This creates dense entity relationships in AI training data.
Evernote, by contrast, has focused on SEO and earned strong backlinks that dominate traditional search rankings.
How Entities Get Recognized
So how does Google (and other AI systems) actually know that Omnisend is an email marketing platform and not, say, a meditation app?
The answer sits at the intersection of structured data, human conversation, and pattern recognition…at massive scale.
Entity Databases and Product Catalogs
Google maintains what they call Knowledge Graphs and Shopping Graphs.
Other AI systems have similar entity databases, just with different names.
The idea is the same: huge databases that map every product, company, and person along with their attributes and relationships.
When Nike releases the Pegasus 41, it doesn’t just become a new product page on Nike.com. It becomes an entity in Google’s Shopping Graph, connected to “running shoes,” “Nike,” “marathon training,” and hundreds of other nodes.
The system knows it’s a shoe before anyone optimizes a single keyword.
Human Conversation as Training Data
AI systems learn just as much from informal mentions as they do from structured markup.
When an Outdoor Gear Lab review casually mentions testing Patagonia’s Torrentshell 3L against the expensive Arc’teryx Beta SL, that relationship gets encoded.
When a podcast guest says, “I moved from Asana to Notion for task and project management,” this competitive link adds to the training data.
Reddit and Quora have become unexpectedly powerful for entity recognition. (Google explicitly stated they’re prioritizing “authentic discussion forums” in their ranking systems.)
A single comment on why someone picked Obsidian over Notion for knowledge management matters more than you might realize.
These platforms capture what websites struggle to do: real people sharing real decisions with real context.
Multimodal Recognition
AI systems extract entities from audio and video. They do this by turning speech into text through transcription.
Every mention in a transcript, every product on screen, and every comparison in a talking-head segment is processed.
A 10-minute YouTube review of project management tools turns into structured data that compares ClickUp, Notion, and Asana. It includes feature comparisons and maps out use cases.
The New SEO Power Dynamic
You can’t game entity recognition the way you could game PageRank.
You can’t manufacture authentic Reddit discussions. You can’t fake your way into natural podcast mentions. The system rewards genuine presence in genuine conversations, not optimized anchor text.
Think about what this means:
Your engineering team’s conference talk that mentions your product’s architecture? That’s entity building.
Your customer’s YouTube walkthrough of their workflow? Entity building.
That heated Hacker News thread where someone defends your approach to data privacy? Entity building.
We’ve spent the longest time optimizing for robots. Now the robots are optimized to recognize authentic human discussion. (Ironic.)
5 Ways to Optimize Your Brand for Entities (Not Just a Website)
Using Omnisend as an example, here are five approaches for evaluating and optimizing entity presence in AI-powered search results.
1. Assess Your Entity Foundation
To start, you need a baseline understanding of your current entity relationships.
For Omnisend, this means mapping how AI systems currently categorize them relative to competitors.
Begin by verifying schema markup across key pages.
Testing Omnisend’s homepage with the Schema Markup Validator shows they use Organization and VideoObject schema.
And the Organization schema is relatively basic.
Omnisends competitor, Klaviyo, uses Organization schema as a container for multiple software offerings.
Klaviyo’s approach maintains brand-level authority while declaring specific software categories and capabilities. This potentially gives them stronger entity associations for queries about email marketing, SMS marketing, and marketing automation.
Next, check your entity presence in major knowledge sources like Wikidata and Crunchbase.
On Wikidata, Omnisend’s records are OKAY.
There’s basic info, like what Omnisend does, the industry, inception date, URL, and social media profiles.
But Klaviyo, again, is all over it. They have multiple properties for industry, entity type, URLs, offerings, and even partnerships.
There’s a clear opportunity for Omnisend to update its Wikidata with more details.
2. Test Query Decomposition
AI systems break down queries into entities and relationships. Then, they may try multiple retrievals.
For example, in Google Chrome, I prompted ChatGPT:
“What’s the best email marketing tool for ecommerce in 2025? My priority is deliverability.”
In the chat URL, copy the alphanumeric sequence after the /c/ directory. For me, it was 68d4e99e-4818-8332-adbd-efab286f4007.
Note: You need to be logged into ChatGPT to get this sequence
Right-click on the page and click “Inspect”.
Choose the “Network” tab, paste the alphanumeric sequence in the filter field, and reload the page.
In the “Find” section, search for “search_model_queries“. Then, click on the search results.
Each decomposed query represents a different competitive pathway.
Omnisend might surface through deliverability discussions, but miss general tool comparisons.
Mailchimp could dominate broad searches while competitors own specialized angles.
This explains why you appear in AI answers for searches you never optimized for. The semantic understanding creates visibility through unexpected entity relationships rather than keyword matching.
You can check this yourself. Run the extracted queries in separate chats and note which brands appear where.
But maybe don’t build a strategy around exploiting this technique.
The methodology depends on undocumented functionality that OpenAI could change without notice.
Important finding: Simple queries produce simple results. When I prompted “Best email marketing tool for ecommerce,” it triggered exactly one internal search with basically the same language. No decomposition.
3. Map Competitive Entity Relationships
Traditional SEO competitive analysis asks “Who ranks for our keywords?”
Entity analysis asks “When do AI systems group us together?”
I tested this with Omnisend to understand when they appear alongside different competitors.
I ran 15 variations of email marketing queries through Google AI Mode to see which brands consistently appear together.
Note: I tested logged out, using a VPN set to San Francisco, in private browsing mode to minimize personalization bias.
I began with simple terms like “best email marketing for ecommerce” and “abandoned cart recovery tools.” Then, I tried different angles like “email automation for Shopify stores.”
Here’s what I found:
Query Context
Omnisend Present
Most Co-Mentioned
Klaviyo Present
Ecommerce email
5/5 queries
Klaviyo, Mailchimp
4/5 queries
General email
5/5 queries
Mailchimp, Brevo
2/5 queries
Deliverability focus
2/5 queries
Brevo, Mailchimp
0/5 queries
Omnisend appeared in 12 of 15 total queries — stronger entity presence than I expected.
But mentions shifted dramatically by context.
In ecommerce discussions, Klaviyo dominated as the top tool.
In general email marketing, Mailchimp took over as the main reference point.
The mention order revealed something important. Klaviyo appeared first in 5 of 5 ecommerce queries, with more positive language around their positioning.
Omnisend routinely ranked second or third. This suggests they’re part of the discussion but not at the forefront.
Here’s what’s interesting:
Klaviyo completely disappeared from deliverability-focused queries while Omnisend maintained some presence.
This shows entity relationships are radically contextual.
Being the leader in ecommerce email doesn’t mean presence in deliverability conversations.
4. Optimize For Entities in Your Content
Entity recognition works best when it has context-rich passages. This helps AI systems extract and understand information more easily.
Take generic descriptions like “Our automation features help ecommerce businesses increase revenue through targeted campaigns.”
An AI system may struggle to identify which product you mean, its automation features, or how it compares to others.
Compare that to: “Omnisend’s SMS automation integrates with Shopify’s abandoned cart data to trigger personalized recovery messages within 2 hours of cart abandonment, without requiring manual workflow setup.”
This version establishes multiple entity relationships (Omnisend → SMS automation → Shopify integration → abandoned cart recovery) within a single extractable passage.
LLMs prefer to use their training data for answers. But when they pull info from the web, strong entity connections help a lot.
You’re reducing friction for both bots and human readers.
As a test, run key passages from your most important pages through Google’s Natural Language API to see what entities get recognized. This can also be video scripts.
Content with strong entity density tends to get cited more often than content requiring additional context.
5. Build Strategic Co-Citations
Entity authority builds through consistent mention alongside relevant entities in trusted sources. This moves the focus from link building to building relationships where natural comparisons happen.
For Omnisend, this means being present in authentic discussions. It’s about genuine comparisons, not forced mentions, that strengthen specific relationships.
A Reddit thread comparing “Klaviyo vs Omnisend for Shopify stores” carries a different entity weight than appearing in generic “email marketing tools” content.
The specific context (Shopify integration) strengthens both brands’ association with ecommerce email marketing.
The most valuable co-citations happen in:
Reddit discussions comparing tools for specific use cases
YouTube reviews demonstrating multiple platforms
Industry roundups grouping tools by specialization
Podcast discussions of marketing technology stacks
This Reddit thread shows strategic co-citation in action. The original post creates dense entity relationships (Klaviyo → Omnisend → pricing → Shopify store). While the comment adds even more context (pricing concerns → business scaling → “pretty good” user experience).
The discussion goes way beyond optimized content. It’s genuine decision-making that strengthens both brands’ entity associations with ecommerce email marketing.
This approach emphasizes genuine participation. Your category is discussed and evaluated by actual users who make real decisions. This is better than having artificial mentions in content made mainly for search engines.
Moving Forward with Entity SEO
If you’ve built a strong brand across various channels, you’ve laid the foundation.
Quality SEO is still crucial.
Genuine mentions in industry talks, real customer chats, and multi-channel distribution matter too.
Begin with your key product line. Organize it well, track its appearances in AI responses, and then expand to other entities.
AI answers are taking over search. More people are turning to Google AI Overviews, ChatGPT, and Perplexity for recommendations.
And if your brand isn’t showing up in those AI answers? You’re missing out on a huge (and growing) slice of your market.
That’s why Semrush built the AI SEO Toolkit. It’s a major unlock for marketers trying to understand how AI is impacting their
business.
Today, I’m going to show you how to use it — step by step — with a real example.
TL;DR: Measure Your AI Search Visibility
Here’s what you need to know about Semrush’s AI SEO Toolkit:
What it does:
Tracks how your brand appears across ChatGPT, Google AI Overviews, Google AI Mode, and Perplexity — showing which prompts include you and where you’re missing
Provides prompt tracking, content audits, and competitor comparisons
What it costs:
$99/month per domain (no trial)
Step 0: Start With a Brand
Before we analyze anything, let’s pick a brand to make this walkthrough concrete.
I went to Exploding Topics, browsed the ecommerce category, and picked Petlibro — a trending startup that sells smart pet feeders and water fountains.
I have zero affiliation with Petlibro. This isn’t sponsored. I just wanted a brand that’s growing fast and has enough search demand to make this example interesting.
Step 1: Get Your Search Baseline
Before we look at AI, we want to know how Petlibro is doing in traditional search. It’s super valuable context that will help us understand how they’re performing in LLMs.
Enter the brand’s domain name and look at the last 18 months. Looking at petlibro.com, they’ve been growing a TON.
They get most of their traffic from the U.S., rank for more than 25,000 keywords, and have a domain Authority Score of 43 with backlinks from 2.8K referring domains.
And they rank well in traditional SERPs for a bunch of highly relevant category and product keywords.
So they’re a real brand that’s already doing a good job with SEO. And good search engine optimization often correlates with good AI optimization.
If your brand has so far neglected SEO, now is the ideal time to tackle that with a solid AI SEO strategy (which this audit will help you form).
Step 2: Check Your AI Visibility
Now for the fun part.
Back in the Semrush dashboard, look for AI SEO in the sidebar.
Enter petlibro.com, and a few minutes later, your Brand Performance dashboard will be ready for review.
On the right side, you can see the Share of Voice versus Sentiment Score.
The most interesting thing I noticed right away is that Petlibro has relatively low Share of Voice (6%) in regular ChatGPT, without Search.
That’s because ChatGPT 5 without search enabled has a training data cutoff of September 30, 2024.
And as we saw in traditional search, Petlibro has been growing a LOT in the last year.
Fortunately, they’re performing much better in SearchGPT, Google AI Mode, and Perplexity. All three of which use live search to generate their answers. For example, Petlibro’s Share of Voice in Google AI Mode is 27.8%:
Pro tip: Keep this in mind when analyzing your own brand too. These tools might not have your newest content in their training data. This can affect your apparent visibility, so be sure to check your visibility when search is enabled (as search-powered experiences are becoming more common).
This tab gives you a broad overview of your brand’s visibility. The next step will help you get more granular.
Step 3. Gauge Visibility at the Prompt Level
You can get prompt-level details by heading to the Visibility Overview tab.
Note: Things are evolving fast in the AI SEO space. This tool is brand new at the time of writing, so there isn’t much in the way of historical data right now. But tracking your visibility here over time will help you understand how well optimized your site is for an increasingly AI-based search landscape.
Scroll down and you’ll be able to quickly understand:
Your top-performing topics
Opportunities to improve your brand’s visibility
Popular sources for prompts relevant to your industry
Where your competitors are being cited that you’re not
Where you are being cited as a source
Click on any of the topics (or select Prompts) to see exact prompts and the AI response that you appear as part of.
To get more data on the prompts your rivals are appearing for that you’re not, head to the Narrative Drivers tab. First, you’ll see your brand’s Share of Voice by platform.
This gives you an overview of where your rivals are winning on each AI platform. But we want to scroll down to Share of Voice and switch to the Average Position view.
You can then toggle each competitor individually to get a better idea of how you perform against key rivals over time.
This view essentially gives you a snapshot of your brand’s visibility for key prompts.
To understand which prompts you are and are not appearing for compared to your rivals, you want to scroll down to the Breakdown by Question section.
You’ll see your position, which is where you show up in the answer snippet compared to your competitors.
You can see which ones your rivals appear for that you don’t by using the filters:
For example, Petlibro isn’t appearing for a few prompts that multiple competitors are mentioned in:
Identify the most relevant queries you want to start appearing for, and do this for each AI tool (using the toggle at the top left).
Note these down somewhere, as these will help frame your AI optimization strategy. Think of this part like the keyword research stage in a traditional SEO campaign.
Step 4. Review Your Brand’s Trust Factors
Next, you want to understand where your brand is doing a good job of appearing trustworthy to both your users and the LLMs themselves.
To do this, head back to the Brand Performance tab and scroll down to Key Business Drivers.
This essentially shows where your brand is strong compared to your competitors in various areas that help convey trust to users.
It might look overwhelming at first.
But basically:
The numbers illustrate how often key business drivers (i.e., trust factors) appear in answers where your brand is also mentioned. The bigger the number, the better.
(Look for the trophy icon to see where you’re currently ahead of your competitors.)
For example:
Searchers may value smart home integration when selecting a smart pet feeder.
When AI tools mention PetSafe, they also sometimes mention the fact it has these features.
This makes the brand more likely to appear in AI search responses when a user is looking for smart pet feeders with features like smart home integrations.
If Petlibro offers this, the brand needs to do a better job of conveying that in their content, or they’re going to struggle to appear in AI responses for relevant prompts.
Meanwhile, PetSafe is being mentioned for this kind of user prompt:
Go through this tab and identify trust factors you want to appear for.
If you spot areas competitors are strong but you’re not being picked up, make sure you:
Include trust factors and unique selling points on your website homepage
Add mentions of relevant features to product pages
Write helpful FAQ questions on product pages and blog posts that cater to these trust factors
Step 5. Audit Brand Sentiment in AI Tools
The next step involves diving deeper into how AI tools (and by proxy your users) perceive your brand.
To do this, we’ll head to the Perception report and scroll to the Key Sentiment Drivers section.
This will show you Brand Strength Factors and Areas for Improvement.
This is a great snapshot to see where you’re already doing well. And where you might need to focus new efforts on improving your brand’s perception in AI responses.
Brand strength factors are essentially areas where the AI tools talk positively about your brand.
In Petlibro’s case, these are factors like app connectivity, mechanical jams, and customer support.
Pro tip: Look for anything that’s not accurate here. You don’t want AI tools to be recommending your brand for things you don’t offer — this will just lead to disappointed customers.
The areas for improvement are areas where you might want to:
Create optimized content to make it clear to customers what you offer
Optimize your existing product pages to better reflect their strengths
Improve your products or services to better meet your customers’ needs
That final point is worth emphasizing. Semrush’s AI SEO tools don’t just give you content ideas.
You can use the insights you gain here and the prompts real users are inputting into AI tools to understand where you can improve and expand your products/services.
The future of marketing is truly collaborative across departments. And these kinds of insights can help align both your SEO/content teams and your product and marketing divisions.
This can lead to a better user experience on your site, a better product for your customers, and increased business growth.
Pro tip: At the bottom of most of these tabs, you’ll also find “AI Strategic Insights.” These are AI-powered suggestions you can use immediately to boost your AI visibility.
Step 6. Identify More Content Ideas
Step 6 is to find more ideas for creating new content and optimizing your existing pages.
First, head to the Questions tab and scroll down to the Query Topics section.
Answer these questions with new content or in your existing content.
For example, Petlibro could create a blog post titled “How to Stop Your Cat Shaking Food Out of Its Feeder.”
They could also update their product pages to highlight that their feeders support different portion sizes for morning and evening meals, and add an FAQ section answering common branded questions.
To understand what content you might want to create (and which prompts are actually worth optimizing for), enter the relevant ones into tools like ChatGPT. (Make sure you enable web search.)
The example below returns a lot of scientific papers, so it would likely be a tough one for Petlibro to appear for.
But there is a Reddit thread in there too. Which means a Reddit marketing strategy could be worth exploring to boost visibility for these kinds of prompts.
This next one is a more likely candidate, and we can see PetSafe (a competitor) gets cited as a source. (And Reddit appears again too.)
There is also a product carousel with links further down — none of which are from Petlibro.
So this would definitely be worth digging into to see why PetSafe (and the other products) are being recommended:
Do the product pages do a better job of conveying trust signals?
Are they more descriptive?
Do they have FAQ sections that answer the prompt’s question?
Bottom line:
You need to look closer than simply the prompts themselves to understand why other brands are being recommended ahead of yours.
But once again, if you scroll to the bottom, you’ll find AI-powered insights that can give you a head start.
Turn Your AI SEO Audit Insights Into Action
An AI SEO audit is a vital first step to make your brand AI ready. And Semrush’s AI SEO Toolkit gives you everything you need to get started.
But the audit is just the first step. Use these resources to turn what you learn from the tool into action for your brand:
AI has infinitely sped up the hype cycle in marketing.
So when the term “vibe marketing” came onto the scene, you may have rolled your eyes for a moment before you said, “I have to try this.”
In basic terms, vibe marketing means using AI to run entire marketing workflows. Usually, this involves a combination of:
Vibe coding: No-code AI tools where you type what you want (e.g., “Build me a landing page”), and the tool spins it up
AI agents: Always-on assistants that handle background tasks, like checking your inbox for leads or updating your CRM
And whether or not they consider themselves “vibe marketers,” many teams are already doing this.
In a survey of marketing teams doing $100m+ in revenue, GrowthLoop found that more than a third of those teams use AI to optimize campaigns or predict customer behavior.
And those embedding AI into their processes report more effective strategies.
So, is vibe marketing the next wave of marketing methodology? Or just more AI hype?
In this guide, we’re diving into real-world case studies that show how marketers are using AI in their daily workflows.
Plus, we’ll test the hype against reality based on my own experiments and the perspective of industry experts.
Vibe Marketing vs. Traditional Marketing
With vibe marketing, things like campaigns, segmentation, and competitor analysis can happen in the background. So you can focus more on creative work and strategy.
Here’s how it stacks up against traditional marketing:
Task
Traditional Marketing
Vibe Marketing
Campaign creation
Weeks of strategy, briefs, handoffs, and approvals
Concepts, landing pages, and emails drafted in hours
Audience segmentation
Manual data exports and persona-building
AI builds real-time dynamic segments
Competitive analysis
Manual research on competitor websites, social feeds, reports
Automated data scraping and AI summaries
Performance reporting
Hours compiling data into slides
Real-time dashboards + plain-English insights
This all sounds incredible, and it’s all technically possible for marketing teams today.
But here’s the catch: AI workflows are still clunky and experimental.
Hootsuite reports that while 83% of marketers say their AI budgets have increased, 4 in 10 companies waste at least
10% of their AI budget on tools that didn’t deliver.
Bottom line: Don’t expect AI workflows to run your marketing overnight. Sometimes building them takes longer than doing the task manually (I learned that firsthand — more on that later).
So, what does vibe marketing look like when it does work?
6 Examples of Vibe Marketing in the Wild
Vibe marketing can seem like a vague concept.
But when we talk about using AI to automate social listening workflows, follow up with inbound leads, or run competitive analysis, all of a sudden this ambiguous concept takes on real-world meaning.
We’ll see six examples of brands using vibe marketing in their daily workflows.
Plus, how you can copy these ideas into your own strategy.
1. Build Enterprise-Level Campaigns Without Reliance on Technical Teams
The biggest slowdown in most campaigns isn’t the marketing work itself. It’s the wait for other teams to deliver what you need.
At the job site, Indeed, those delays stretched to an average of 3.5 months per campaign.
Even simple requests — like defining an audience segment — meant analysts had to pull data from their warehouse. Then, engineers had to reformat it before marketing could use it.
With vibe marketing, the team broke that bottleneck.
They used the AI platform GrowthLoop to turn raw customer data into ready-to-use segments.
Now, their team can type a plain-English prompt (e.g. “nurses in the U.S. who searched jobs in the last 30 days but haven’t applied”) and instantly generate that segment.
Instead of waiting a whole quarter to get in front of job seekers, the team can now react to hiring needs in almost real time.
Try It Yourself:
If you’re on an enterprise team already using a data warehouse tool, GrowthLoop’s makes it easy to type a goal, generate audiences, and send them directly into campaigns.
On the other hand, let’s say you keep customer data in a CRM or spreadsheet — names, emails, recent purchases.
With a tool like Clay, you can import those leads and use the built-in AI to enrich them with more data.
Then, you can create campaigns that automatically go out based on that enrichment.
For example, when a company has received funding in the last three months, they can be automatically added to a campaign.
In seconds, you’ve got a list ready to target.
What makes this powerful isn’t just faster data access.
It’s the AI layer that turns raw information into something marketing can actually act on, without waiting on anyone else.
2. Automate Social Listening Workflows
Getting a lot of mentions on social media is great — until it isn’t. Some social media managers can spend hours every day sifting through comments and posts that tag the brand.
More than just being a tedious task, this is completely unsustainable.
Which is exactly what Webflow’s two-person social team realized.
Between Reddit, X, YouTube, and forums, they faced 500+ daily mentions. But only a handful actually needed a human reply.
Finding those few was like looking for needles in a haystack.
So, they built an AI workflow to do the sorting for them.
The system scans every mention, tags it by sentiment and urgency, and pushes the important ones straight into Slack.
Out of 500+ daily posts, the team now sees just 10–15 that matter most — and responds within the hour.
Pick one high-volume channel — maybe Reddit, X, or even a busy community forum.
Use a tool like Gumloop or Apify to pull in mentions of your brand. Then, run them through an AI categorizer to flag sentiment and urgency.
Start small, check the tags for accuracy, and only then scale to other platforms.
Note: To take this workflow a step further, add a tool like ManyChat or Yuma.ai to generate automated responses to posts and DMs. Entrepreneur Candace Junée did this and saw a 118% increase in leads while saving 15 hours per month answering Instagram DMs.
3. Create On-Brand Content Assets
Ever tried to turn a 40-page technical document into a blog post or campaign copy?
The content is there, but shaping it into something clear — and in your brand’s voice and style — takes time.
At Pilot Company, with multiple sub-brands and channels to manage, that challenge multiplied.
Writers spent hours summarizing technical docs into usable briefs. Designers waited for copy that matched the right tone before prototypes could move forward.
And inconsistencies crept in across brands.
So, the team used Jasper to help build consistency in style and tone.
They used the tool’s summarizer to condense long technical documents into actionable outlines, and the brand-voice model to keep messaging aligned across sub-brands.
Designers could even pull realistic placeholder text without waiting on writers.
The result: Each team member saved 3–5 hours a week, freeing them up for strategy and storytelling instead of slogging through documents.
Try It Yourself:
With a tool like Jasper, you can add specific instructions about your brand voice, audience, and even include source material to show what great content looks like for your brand.
Then, you can use it to create copy and content for entire campaigns.
You can also use tools like Notion AI, Claude, or ChatGPT to turn long documentation into campaign content.
Start by inputting your brand voice, style, target audience, and any other details that might be useful. Then, upload documentation and ask the AI to turn it into specific pieces of content.
Test the tools to find your favorite. Make sure to give specific instructions on what kind of output you’re looking for.
Use AI to generate briefs, draft first passes, or speed up design prototypes — and reserve human time for the creative polish.
On paper, 500+ inbound marketing leads a day looks like a dream for a small agency.
But for Tiddle, a six-person influencer agency, it was a nightmare.
They were buried in the flood of messages, with only a few that were worth pursuing. Sorting through the noise ate up 6–8 hours a day — time that should’ve gone into client campaigns and outreach.
Instead of hiring more staff, they brought in AI.
Using Lindy, every inbound email was screened automatically.
Low-quality offers were politely declined, while promising ones were flagged and routed to the right person.
If terms weren’t a fit, the AI could even suggest counteroffers.
The team went from slogging through hundreds of emails to focusing only on the 10–15 real opportunities that mattered.
As Tiddle’s CEO, Mike Hahn, says, “Every deal we’ve closed in the last few months came from Lindy surfacing the right conversations.”
Try It Yourself:
Pick one channel where inbound volume is overwhelming (email, DMs, LinkedIn).
Define the “must-haves” for a qualified lead (budget, offer type, brand fit), then use a tool like Lindy or Clay to screen and tag incoming requests.
You can even set up conditional logic so the tool can change how it responds based on specific conditions.
Note: Small companies aren’t the only ones making use of AI for inbound leads. Ariel Kelmen, president and CMO of Salesforce, recently said that they use AI agents to handle interactive follow-ups with leads. And those agents manage the first 80% of the conversation.
5. Build Hyper-Personalization for Your Ideal Customer Profiles
“Hi [first name]…” personalization doesn’t cut it anymore. But manually tailoring every message to your ideal customer profiles (ICPs) is impossible to scale.
Oren Greenberg, a solo marketing consultant, faced this problem.
And since there was no system that fit his ideals of hyperpersonalization, Oren built his own.
He coded a workflow in Replit that filtered a 50,000-company dataset, excluded existing contacts, and generated outreach tailored to each company’s stage and challenges.
The result: outreach so specific it only makes sense for the intended recipient.
Pro tip: Hyper-personalization works only if you deeply understand your ICP — AI can’t do that thinking for you. But once you know who you’re selling to, it can scale bespoke messaging in ways you couldn’t manually.
Try It Yourself
If you’re a highly technical person with the skills and know-how to recreate something like this in a vibe-coding tool, then by all means have at it.
For the rest of us, using a tool like Clay is a fast path to get 80% of the way there.
Start by defining your ICP.
Then use Clay to pull in business data, filter it against your ICP criteria, and enrich it with extra context.
With that data in place, you can add an AI-powered column that drafts personalized outreach for each prospect.
Run a pilot batch of 50–100 and iterate until the system feels like true one-to-one messaging.
6. Run Competitive Analysis
New marketing roles often start with 30-60 days of slow discovery.
Who are the real competitors? What do customers actually care about? What language do they use?
Semrush’s former VP of Brand Marketing Olga Andrienko found a way to shortcut that process.
Before Day 1 at a new job, she suggests running an AI-powered competitive analysis.
Pull your site and the top competitors’ pages, transcribe the most-viewed YouTube reviews, and mine Reddit and forums for repeated complaints.
Then, feed that into an AI summarizer to surface frequent feature praise or criticism and real customer phrasing. Tools like Google Opal or Gemini help cross-link those insights into a positioning map.
Whether you’re stepping into a new role, launching a campaign, or scoping out a new market, the same workflow applies.
First, pick your brand and three competitors. With a scraper tool like Apify, get your website copy and grab a handful of top YouTube reviews and forum threads.
Then, feed those into a tool like Claude, Gemini, or ChatGPT to summarize and analyze the data.
Extract the top five pains and language customers use, and sketch a one-page positioning map you can bring to meetings.
That way, you start your campaign with clarity — not uncertainty.
My Disastrous Vibe Marketing Experiment (What I Learned the Hard Way So You Don’t Have To)
Giving you examples is great, but I wanted to put all this to the test and see if I could build a usable AI workflow for myself. (Spoiler: It did not go well.)
Goal: Save time replying to LinkedIn comments without losing my voice.
Constraints: Something I could test immediately, for free, and that would actually be useful.
Method: Build a workflow that scrapes comments, learns my style, and drafts replies I could approve before posting.
Time spent: 4+ hours
1st Attempt
First, I created an account in PhantomBuster, a tool that automates actions on social platforms like LinkedIn.
Then, I connected my LinkedIn account and set up the “LinkedIn Post Commenter and Liker Scraper” tool.
I asked it to retrieve only comments from my LinkedIn posts from recent days, which it did successfully.
Next, I created a new “Scenario” in Make, a no-code automation and AI agent tool, and added PhantomBuster as the start of that workflow.
Then, I built a Make AI Agent that would draw from my previous posts to learn my voice..
I added that Make AI Agent into the workflow, giving it instructions to analyze the comments scraped by PhantomBuster and produce a reply.
And finally, I added Google Docs as the final output. The idea was to create a document where I could see both the original comment and the AI-generated reply.
The whole workflow ran successfully, which I took as a win and closed up shop for the night.
But when I opened my laptop the next day to check all the wonderful replies my new AI buddy had written for me, all I found was this lovely Google Doc:
Still undeterred, I decided to try something different.
2nd Attempt
Along the same lines, I wanted to build an automated AI workflow that would scrape content from LinkedIn that I’m interested in. Then, write comments in my voice and style using my existing content as a foundation.
I used a similar workflow: PhantomBuster to scrape the content, Make AI Agents to analyze and write comments, and getting the final output in a Google Sheet.
Unfortunately, that gave me the exact same result (only this time in spreadsheet format, woohoo!):
What especially irked me was that the automations themselves were running successfully. But I still had no output.
So after more than four hours of work (and a lot of back-and-forth with ChatGPT), I finally gave up.
Could I have figured out this AI workflow eventually? Yes, I have no doubt.
But at that point, how much time would I be saving?
Does a little time saved on writing comments justify spending hours building an AI workflow (and what should’ve been a relatively simple one, at that)?
Here’s what I learned from this experiment:
If you’ve been secretly feeling a little skeptical about vibe marketing, you were right
The folks building vibe-coded apps and AI workflows in five minutes have years of practice. The rest of us can’t expect the same speed.
The tools that are currently available for vibe coding and AI automations aren’t ready yet for the average user to just jump in and build
If someone with a background in tech (me) struggled so much with a simple workflow, imagine the challenge of something more complex
And while it’s true that others are seeing success with vibe marketing (like the examples that we saw above), there are also clear downsides.
It’s Not All a Bed of Roses: The Caveats of Vibe Marketing
Vibe marketing is like any new marketing buzzword: We all love to join in the hype, even if we don’t quite get it.
The problem is, the hype can obscure reality.
After running my own experiments, I also talked with other experts in the field. What emerged was a clear pattern — vibe marketing is powerful, but the gaps between promise and practice are real.
It’s Harder Than It Looks
The idea that you can tinker around with AI for five minutes and produce a usable workflow just isn’t feasible for the majority of us.
And yet, that’s the promise we’re seeing over and over again:
This all sounds great, but we’re marketers: We know better.
Simple automations? Sure.
But robust, real-world systems usually need engineering support or serious AI chops.
Without that, you risk fragile prototypes that break the first time they’re stress-tested.
Oren Greenberg, the AI marketing consultant we talked about earlier, told me:
“The level of hype is out of this world. Vibe coding is cool, and there are a few people who’ve built a nice small business out of it. But it’s mostly the vendors who are minting cash.”
Here’s the point: Don’t get swept up in the hype. Check the source.
The Infrastructure Is Messy
AI workflows look slick in a demo. But in practice, you have to plug into your marketing stack.
And that’s where things get complicated.
For example, you might build the perfect AI agent to score inbound leads, only to realize that your CRM can’t accept the data the way you need.
As Austin Hay, Co-Founder of Clarity and MarTech teacher at Reforge, noted in a recent interview:
“Everyone’s excited about unstructured data, but unstructured data is useless when it needs to play nice with structured systems.”
For traditional marketing teams, this means your AI workflows may not play well with your company’s established martech systems.
And if your tech’s API documentation is outdated (or worse, nonexistent), it will be nearly impossible to vibe code your way to integrations between existing tools.
AI Can’t Invent Outside its Datasets
Another misconception around vibe marketing is that you can throw any messy, undefined problem at an AI agent and it will figure it out.
The reality is less glamorous.
AI thrives on patterns it’s seen before. Point it at a well-scoped, repeatable task, and it shines.
But ask it to invent outside of its training data — or solve a fuzzy, novel problem — and you’ll end up with loops, errors, and wasted hours.
Speed Only Works When You Know Where You’re Going
AI can help you move fast. But if you don’t know what metrics matter and where you want your workflows to lead, faster will just mean getting lost sooner.
Marketers who succeed with vibe coding are the ones who define the finish line first. AI then becomes a vehicle to reach those goals faster, not a substitute for setting them.
Kevin White, Head of Marketing at Scrunch AI, put it this way in a recent interview:
“AI multiplies the abilities of people who already know their craft. Treat it as a force multiplier for your expertise rather than a substitute for it.”
Vibe Marketing Tools Free Up Time…But for What?
As more marketers build AI workflows and vibe code their way to productivity, a philosophical question arises: why?
AI workflows and automations free up time (when they work). But, what are we freeing up time for?
By eliminating the busywork, we’ve saved only the most demanding tasks for ourselves. And while creating and strategizing may be what we enjoy most, it’s impossible for most people to do that kind of mentally-taxing work for eight hours straight.
“In conversations with CMOs, it’s clear that GenAI has become a core part of how modern marketing teams operate. What separates the winners is a commitment not just to scaling the technology, but to empowering the people who use it. Those CMOs investing in tools and talent are the ones rewriting the playbook.”
Ready to Try Your Own Vibe Marketing Experiment?
Vibe marketing isn’t snake oil. But it’s not a silver bullet, either.
The hype can make it feel like anyone can vibe code and automate their way to a marketing edge. But the reality is far more nuanced.
The marketers getting real value from vibe marketing are the ones with strong fundamentals, clear goals, and often a layer of engineering support behind them.
For the rest of us, the takeaway is simple:
Vibe marketing is worth experimenting with, but it won’t replace strategy, judgment, or hard-won expertise.
ChatGPT recommends products — complete with photos, pricing, and purchase links — to its 700 million weekly users.
And now customers can complete purchases without leaving the chat.
BIG deal.
But will ChatGPT recommend your products?
That’s not automatic. And you can’t pay for placement.
What you can do is optimize your site so ChatGPT understands what you sell, trusts your brand, and surfaces your products when buyers search. This guide shows you how.
You’ll learn the eight-step framework for getting featured in ChatGPT Shopping.
I also spoke with Leigh McKenzie, Backlinko’s Head of Growth and founder of the ecommerce brand UnderFit, to get his insights on what’s actually working.
First, let’s look at how ChatGPT decides which products make the cut.
How ChatGPT Shopping Works
ChatGPT Shopping kicks in automatically for some shopping intent prompts.
While it doesn’t fire every time, I found it appears more often than not after testing 100+ prompts.
The key? Typing a prompt with clear buying intent.
Like “e-bikes that can handle potholes.”
Instead of just explaining things or offering advice, ChatGPT Shopping recommends specific products.
This includes product images, pricing, and links to online stores and websites where users can make a purchase.
Side note: The ChatGPT Shopping experience isn’t consistent. Even with the same prompt, the carousel may (or may not) show. It can also appear at the top, middle, or bottom of the chat. This variability suggests the feature is still evolving.
If your store gets recommended, countless high-intent shoppers will see your products.
For example, when I tested the e-bike query, ChatGPT gave me a brief explanation of what features to prioritize.
But it also provided a visual product carousel with eight products, each in its own card with key details.
(It looks similar to Google Shopping ads, except you don’t have to pay for them.)
Clicking on any card opens a side panel with:
Additional product photos
A list of stores, prices, and direct links
A short “why you might like this” summary
Sentiment pulled from reviews and forums
From there, users simply click “Visit” to reach the merchant’s product page.
But this experience is changing.
As of September 2025, OpenAI is rolling out Instant Checkout — a feature that lets shoppers buy directly inside ChatGPT.
This is a huge shift.
ChatGPT is no longer just a product discovery tool. It’s a full shopping destination.
Right now, Instant Checkout is only available to Etsy sellers in the United States.
But OpenAI plans to expand this feature to Shopify merchants and other countries soon.
Not on either platform?
They’re also accepting applications for merchants to build their own integrations. (More on this in Step #7.)
How ChatGPT Selects Products to Recommend
A shopper describes what they’re looking for (“running shoes with arch support under $150”), and ChatGPT’s AI goes to work.
It scans the web for the most relevant products based on that request.
And weighs details like product names, descriptions, features, reviews, brand authority, and other signals to find the best matches.
If your product checks the right boxes — and the information on your site is clear and crawlable — it has a chance to be recommended.
ChatGPT may also consider the user’s location and preferences when making recommendations.
Ultimately, all product recommendations must also pass through OpenAI’s safety systems.
This filters out low-quality, misleading, or unsafe products.
So, what does all of this mean for you?
ChatGPT Shopping is evolving fast — and the brands that keep up will win the most visibility.
Here’s how to ensure ChatGPT can understand, trust, and recommend your products.
1. Add Structured Schema Markup to Your Site
ChatGPT needs structured data to understand what you sell.
Schema markup is code that labels key details on your product pages (and website as a whole): name, price, description, availability, reviews, and more.
It turns raw HTML into data AI tools can parse instantly.
Without it, ChatGPT (and other AI systems) have to guess what’s on your page.
With it, they see clean, structured information they can confidently include in product recommendations.
At a minimum, your product schema should include:
Product: Name, description, brand, image, and identifiers (GTIN, SKU, MPN)
Offer: Price, currency, availability, and URL
Review: Individual reviews with reviewer names and ratings
It may look intimidating, but many content management systems — like WordPress, Shopify, and Wix — offer plugins or built-in tools that generate the markup for you automatically.
Once your markup is in place, test that it’s working correctly using Google’s Rich Results Test or Schema.org’s validator.
These tools make it easy to check that your structured data is valid, visible, and error-free.
Pro tip: Go beyond the schema basics. Add AggregateRating for average review scores or FAQPage markup to answer common buyer questions. The more context you provide, the easier it is for AI to surface your product in response to specific prompts.
2. Create and Maintain a High-Quality Product Feed
A product feed is a structured file that packages up your product details and sends them to platforms like Google Merchant Center, Shopify, and Etsy.
It includes details like titles, prices, availability, images, links, and more.
ChatGPT may use data from major platforms like Google to decide which products to recommend.
Pro tip: Want to add your product feed directly to ChatGPT? OpenAI will notify interested merchants when this feature is available. Fill out the Merchant Application form for consideration.
For example, if your Google Shopping feed is outdated, incomplete, or inaccurate, ChatGPT may return bad information about your products.
Or skip recommending them entirely.
That’s why a high-quality, up-to-date product feed is critical.
Side note: If you’re on an ecommerce platform like WooCommerce or Shopify, feeds are usually created automatically.
But keeping feeds accurate is easier said than done.
There are a lot of moving parts, like site updates, refresh schedules, and third-party tools.
And it only takes one slip for mismatches to creep in.
Here are a few common product feed issues — and how to fix them:
Product Feed Problem
Why It Happens
Fix
Price Mismatch
Feed not refreshed, sync delay
Enable daily/real-time feed updates. Use one consistent pricing source.
Inaccurate availability
Inventory updates on site, but feed refresh lags
Sync stock levels in real-time whenever possible. Double-check before campaigns.
Wrong or Truncated Title
Feed title auto-truncated or different from H1/meta
Align feed titles with on-page H1/meta. Keep product names consistent.
Incorrect image
Feed defaults to first gallery image
Set hero/product image as primary in CMS and feed
Missing reviews
Reviews hidden in JS or not in schema
Add Review and AggregateRating schema in HTML
Conflicting schema
Multiple apps/plugins overwrite each other
Use one schema source. Validate with Schema.org or Google’s Rich Results test
Automation keeps most updates in sync. And manual checks before major launches or sales help catch anything that may slip through.
Here’s how Leigh maintains a balance of the two for his ecommerce store:
“I keep all my product data in a spreadsheet. Whenever I change a product detail, I update it there first. WooCommerce uses that data to update my site’s pages and schema automatically. Then, Channable takes the same spreadsheet and syncs those updates into my product feeds. That way, my site and my feeds are always pulling from the same source, so everything stays consistent.”
3. Make Sure AI Bots Can Read Your Site
If ChatGPT can’t read your site, it can’t recommend your products.
Two simple technical issues block many ecommerce sites from showing up: hidden content and restricted crawlers.
Check for JavaScript
Many AI bots — including ChatGPT — still struggle with content that only loads via JavaScript.
If key details aren’t in the page’s raw HTML, the bot might never see them.
This includes your product descriptions, prices, and images.
Eek.
Here’s how to check if that’s happening:
Pull up a product page on your website or online store
In Google Chrome, go to “Settings” > “Privacy and security” > Site Settings
Under “Content,” click “JavaScript” and toggle “Don’t allow sites to use JavaScript”
Reload the product page you’re testing
If your product details disappear, it means they’re only loading through JavaScript.
To fix this, work with a developer to ensure all essential information is in your site’s raw HTML.
They’re onboarding merchants on a rolling basis and will reach out when you’re accepted.
Once you’re in the pipeline, you’ll need to:
Provide a structured product feed that meets OpenAI’s product feed specs. Leigh recommends starting with your existing Google feed and updating it as needed to meet OpenAI’s requirements.
Enable ACP checkout. ACP lets ChatGPT place and complete orders in your system. If you’re on Stripe, setup can be as simple as one line of code. If not, you can still integrate using Stripe’s Shared Payment Token API or the Delegated Payments Spec — no provider switch required.
Connect your payment provider. You’ll still process transactions and remain the merchant of record.
Pass certification requirements. OpenAI requires sandbox testing and end-to-end checks before you go live.
Pro tip: Even if ChatGPT Instant Checkout isn’t available for your store yet, preparing your product data, feeds, and backend now will help you move faster when it is. This should give you a head start as this feature gains popularity.
8. Track Your ChatGPT Visibility
It’s not enough to show up in ChatGPT Shopping.
You also need to measure how well you’re performing.
Start with tracking traffic.
The easiest way is through OpenAI’s built-in UTM tag.
utm_source=chatgpt.com
This is code that OpenAI automatically adds to all outbound links. And looks like this:
Set up a custom segment in Google Analytics to track and analyze ChatGPT traffic to your site.
Once that’s done, look for patterns:
Is ChatGPT traffic increasing month over month — or slowing down?
How does the conversion rate compare to other channels?
Do visitors stick around or bounce right away?
Side note: Not every ChatGPT mention will be traceable. Some users see your product in a chat and search your brand directly on Google instead of clicking. Look for spikes in branded search traffic or direct visits to gauge the broader impact of LLMs.
But traffic only tells you what happens after people click.
You also need to measure what happens before — specifically, which prompts surface your products.
To do this, it helps to understand the kinds of prompts shoppers type.
Most fall into four buckets.
Price-based: “Best dog food bowl under $20,” “luxury ceramic dog bowl”
Use-case: “Dog bowl for messy eaters,” “raised bowls for large breeds”
Feature-based: “Non-slip stainless steel dog bowl,” “slow feeder BPA-free”
Problem-solution: “Dog bowl that keeps ants out,” “dog bowl that doesn’t slide on tile”
Think of these buckets as templates.
Test prompts in each category and ask yourself:
Does your product show up? If so, are the details accurate?
If not, who does — and why? (Are their reviews fresher, their authority stronger, or their copy closer to buyer language?)
Repeatedly run these checks to gather more data.
You’ll learn which prompts lead to product mentions, how your LLM visibility changes, and how buyers talk about your brand.
Rather automate this process?
Tools like Semrush’s AI SEO Toolkit let you:
Track which prompts surface your products
Monitor brand sentiment
Compare visibility in different platforms
Beyond ChatGPT Shopping: Your AI Visibility Playbook
There isn’t a magic formula for getting ChatGPT to recommend your products.
But the brands that consistently get recommended all have three things in common:
A rock-solid technical foundation
Clear, buyer-focused product copy
Strong trust signals across the web
Get these right, and you’re not just optimizing for ChatGPT Shopping.
You’re setting yourself up to be discovered across EVERY AI platform out there.
If I had a dollar for every time someone said “know your audience,” I could retire from marketing altogether.
And yet, most teams are completely winging it.
Too often, marketers equate audience research with half-baked customer relationship management (CRM) data, some social media metrics, and a few buyer interviews.
But that’s just organizing information you already have.
Real audience research means discovering what you don’t know yet.
It’s the exact words people use when they’re frustrated. The solutions they’ve already tried and dismissed. The moment they decide to trust one source over another.
When you get this right, you move from guessing what might work to creating content from what your audience is already telling you.
In this guide, I’ll show you how to find those insights across five key channels, with practical tactics you can use right away.
Download our free Audience Research Tracker
As you go through these methods, I’ll show you how to capture insights in our Audience Research Tracker and turn them into actionable content ideas.
Why You Can’t Skip Audience Research
If you’ve ever lost hours scrolling TikTok or binge-watched “just one more episode” on Netflix until midnight, you’ve experienced the power of audience research.
Platforms like Netflix, YouTube, and TikTok own our attention because they know us better than we know ourselves.
They’ve built this advantage by making audience research a core function.
Netflix, for example, treats “Consumer Insights” as one of its nine core research areas, which shows just how pivotal understanding users is to their success.
For these winning brands, audience research isn’t an afterthought.
It shapes everything: what gets built, how products are positioned, and which messages resonate
And the payoff is massive — delivering experiences tailored to your customers that keep them coming back for more.
In stark contrast, many marketing teams run on fragments.
SEOs chase keywords, social focuses on engagement, and product marketing fine-tunes messaging. Everyone has a piece of the puzzle, but no one can put it together.
As a result, campaigns are designed for specific channels instead of real people.
Done well, audience research can close this gap to:
Sharpen your messaging that customers find relatable
Prevent wasted spend by showing you where people actually are
Speed up creative cycles by giving teams validated insights to work with
In short: This research legwork aligns marketing with real customer needs, winning customer trust in the process.
And the good news is you don’t need Big Tech’s expensive resources to pull this off.
I’ll show you how to conduct audience research and out-empathize the competition with your existing team and budget.
5 Channels to Conduct Audience Research for Content Marketing
Your buyers are already telling you what they want. You just need to listen carefully.
Let’s learn how.
Make sure to download our tracker and jot down all the information from your audience research techniques.
Tap Into Intel Within Your Company
Some of the most valuable audience insights are already within your reach, sitting with your sales and customer success (CS) teams.
These groups are on the front lines.
They regularly interact with prospects and customers about their frustrations, aspirations, objections, and goals.
For marketers figuring out how to conduct audience research, collecting these insights is a great starting point.
Here’s how:
Source of Insight
How It Works
What You’ll Learn
Listen to conversations
Sit in on sales demos, onboarding calls, or quarterly check-ins
Use a simple template to document key takeaways
How buyers describe challenges
Words and phrases they repeat
Factors they prioritize
Sync with frontline teams
Run regular sessions with sales, CS, product, and marketing to share notes
Common challenges
Objections that block deals
Features customers love or struggle with
Interview & survey customers
Conduct 1:1 interviews with prospects and customers
Use surveys to validate patterns
Why buyers looked for a solution
Their decision-making process
Alternatives considered
Listen and Capture First-Hand Conversations
The fastest way to understand your audience is to literally listen.
Sit in on a sales demo, a customer onboarding call, or a quarterly check-in meeting.
This will bring you raw insights you can’t get from surveys, like:
The way buyers frame their challenges
The decision factors they prioritize
The words they repeat
But listening alone isn’t enough.
You need a simple system to document the key takeaways from every conversation and share them across teams.
Here’s an example of what that might look like for a fictional coffee brand:
Our Audience Research Tracker will help you distill these conversations into meaningful content opportunities.
You can jot down recurring problem statements in your buyers’ language and identify their biggest pain points.
Then, prioritize ideas based on our four key parameters like urgency, business value, and more.
Sync with Frontline Teams
Another way to capture these insights is by regularly connecting with your customer-facing teams.
When teams work in silos, each one only sees a part of the puzzle.
This creates a disconnect in your customer experience because no one has the whole picture of what buyers want.
That’s why it’s worth setting up regular cross-team sessions for marketing, sales, customer success, and product teams to compare notes.
These sessions can surface insights that no single team could uncover on its own.
Interview and Survey Customers
Besides internal data, hearing directly from buyers can give you a deeper, more reliable understanding of what drives their decisions.
Customer interviews provide essential context about the why behind their behavior.
You can find out:
How they first discovered your product or category
What pain points pushed them to look for a solution
The decision-making process they followed
What alternatives did they consider
With surveys, you can validate these insights and see which ones apply broadly versus one-off anecdotes.
The bottom line: Before spending anything on new research, look inward to collect and process information you already have.
Use Reddit for Unfiltered Conversations
Unlike other social media platforms, Reddit gives you access to candid and often brutally honest conversations.
Take this post on frustrating skincare routines.
It voices raw and real emotions that people face when dealing with skincare challenges.
And in the comments, there are even more stories and nuanced perspectives.
They offer crucial insights about the audience, like “skincare feels like a tough road of trial and error” and the “emotional toll of poor skin health.”
So, how do you use Reddit to know your buyers better?
Start with the Right Filters
Reddit’s filters make it easy to sift through posts and find what matters most.
You can sort results by:
Relevance: Best for finding posts that match your keyword directly
Top: Surfaces the most upvoted posts over a time period
Hot: Shows recently trending posts with the most upvotes
Comment count: Sorts posts with the most comments
New: Shows you the freshest discussions
Plus, you can filter results by timeframe to see what’s trending now versus what’s been a consistent pain point over time.
In my search for “moisturizer for oily skin,” filtering by “Relevance” shows the closest matches, while “Hot” surfaces the most recently upvoted posts.
Pro tip: Use Google with the search operator site:reddit.com “keyword.” This often works better than Reddit’s native search, especially if you’re looking for niche phrases.
Find the Right Subreddits
While it’s easy to find bigger and popular subreddits, it’s equally important to look for smaller, niche spaces where your audience might hang out.
Remember, the same buyers may express themselves differently depending on the space they’re in.
For instance, a skincare brand could find valuable insights across:
r/SkincareAddiction: Broad, general skincare conversations
r/AsianBeauty: Discussions centered on Asian markets
r/30PlusSkincare: Catering to an older demographic
Each subreddit reflects a different slice of the audience.
Read Posts and Comments Like a Researcher
A good Reddit post will give you context into people’s problems, goals, and lived experiences.
But the comments add more nuance to the original post. This is where people expand on the issue, discuss solutions, and share personal stories.
Here’s a post where the original poster (OP) shares their concerns about using Retinol, an ingredient known for its anti-aging properties.
Other Redditors share their take and advice on this issue, highlighting some alternatives to consider.
For a skincare brand, this post is helpful to understand:
Buyers’ concerns regarding Retinol
Commonly used and recommended solutions
Based on these insights, the brand can create content focusing on the best practices for Retinol use. Another great idea is to make a beginners’ guide for using Retinol and taking care of your skin.
Besides, Reddit also offers something other platforms can’t: clear signals of what not to do.
Upvotes highlight ideas and opinions people love. Downvotes show the perspectives or advice they reject.
Find AMAs (Ask Me Anything)
Ask Me Anything (AMAs) can be a gateway to your audience’s biggest questions or issues they’re curious about.
Any industry expert or influencer with trusted credentials can host an AMA.
Here’s an example from a certified dermatologist.
Questions asked in this thread reveal issues where people need an expert’s guidance.
For example, one Redditor asked for basic skincare regimens while another shared a question about stretch marks.
Pay attention to questions with high upvotes. Those are the ones that most people want advice on.
Check Out YouTube Comments and Videos
YouTube is the second-largest search engine where people go to solve problems, compare options, and learn new skills.
Naturally, it can reveal a lot about your buyers.
An audience intelligence tool like Sparktoro is a good starting point for YouTube research.
When you enter any keyword, it lists the most relevant YouTube channels for this audience.
Visit these channels and extract rich insights based on the steps I explain below.
For example, this video comparing stainless steel pans with cast iron skillets tells you the creator’s subjective take on the topic.
But when you scroll through the comments, you’ll find which option people prefer — and why.
Here’s a quick and easy process to document insights from as many YouTube videos as you want.
Copy comments from every video in one go. Then, paste them into ChatGPT or any LLM tool of your choice.
Share this prompt to extract common pain points and themes:
I have added a collection of YouTube comments below. Please analyze them as if you’re conducting target audience research.
Identify:
→ The most common themes and topics people talk about
→ Motivations, desires, or positive outcomes they want
→ Patterns in language (words/phrases that repeat often)
Present your findings in a structured summary. Create a table highlighting frequent pain points, frustrations, or complaints, and add users’ quotes for each pain point.
Here are the comments:
[Paste comments]
This way, you can turn hundreds of scattered thoughts into a structured list of what your audience actually struggles with in their exact words.
I tried this myself and here’s how it went:
I found a clear breakdown of my audience’s pain points spelled out in their exact words.
Add these to our research tracker — and just like that, I have topics for my next few Instagram reels, like “Health concerns around non-stick pans” and “Why stainless steel pans are better than non-stick.”
Learn From User-Generated Content
Beyond comments, user-generated content (UGC) can also offer a direct line into what your buyers care about.
Think product reviews, unboxing videos, comparisons, or even vlogs where people share how they use a product.
Notice the kind of pros and cons that people highlight in these videos.
For example, this YouTube creator made a video about his decision to stop using Hexclad pans.
He explains:
Why he bought these pans
What went wrong with these products
What alternatives he considered and switched to
Use these insights to understand key buying factors and some pain points worth exploring.
Explore Social Media Platforms Your Buyers Use
Social media works best as an audience research method when you know where your buyers actually spend their time.
Tools like Similarweb make this easier by showing you which channels your audience prefers.
Add your website and a few key competitors to get started, like this example with TechCrunch, Wired, and other competitors.
Here’s how the tool breaks down each brand’s audience share on different social media platforms:
The takeaway: Identify the platforms that matter most to your buyers and dig deep into those spaces.
LinkedIn
On LinkedIn, start by identifying people who fit your Ideal Customer Profile (ICP).
Pay close attention to the posts they share — their wins, failures, roadblocks, and processes.
These real-world updates reveal where your product or service can make a meaningful impact.
For example, if your ICP includes customer success teams, this LinkedIn post shows how leaders are experimenting with AI tools.
It highlights both opportunities and gaps you could address — like growing interest in a trend (opportunity) or frequent complaints (gap).
To scale your research, use LinkedIn Sales Navigator to apply filters and zero in on the right people within your ICP.
For example, you can filter results by industry, keywords, location, seniority, language, and more of these filters.
Instagram
Instagram hashtags are a great way to discover audience interests.
Start with broad themes like #mealprepideas to see what’s trending.
Each hashtag (like a keyword) surfaces a collection of posts tagged with this term.
Look for posts with high engagement because they signal what truly resonates.
For instance, this post earned over 393k likes because it offered clear, visual recipe ideas that people found useful.
Like LinkedIn, you can also follow influencers or niche creators in your space to get closer to your audience.
Their posts (and especially the comments) often pinpoint the questions, frustrations, and goals your buyers are struggling with.
TikTok
To use TikTok as an audience research method, create a fresh account dedicated to your niche.
Interact only with videos specific to your space, and TikTok’s algorithm will start curating a feed of trending content.
Once you see relevant videos, dive into the comments to spot recurring themes and pain points.
For example, the comments on this meal prep video include many questions about the containers and the recipe.
You can also search for your keywords and toggle between “Top,” “Users,” “Videos,” and “LIVE” content to explore different kinds of content on the app.
X
X has powerful tools for audience research if you know where to look.
Use the advanced search function to filter posts by keyword, engagement, account, or time frame.
Another underrated feature for target audience research: “Lists.”
It lets you build a curated feed of accounts you want to hear more from, like potential customers, influencers, or industry voices.
You can either follow existing lists or create a new one.
For instance, searching for “vibe coding” lists shows ready-made feeds you can tap into for insights.
Compare Platforms with Semrush Social Tracker
Semrush’s Social Tracker helps you zoom out and learn more about your audience from multiple channels at once.
It pulls data from Instagram, Facebook, LinkedIn, X, YouTube, Pinterest, and TikTok, so you can see how your audience interacts with different channels.
With this report, you can identify which platforms generate the strongest engagement from your target audience.
And it’s easier to spot popular post formats (Reels, carousels, videos, etc.) and hashtags that drive interaction.
To get started, connect your social accounts and add competitor profiles in Social Tracker.
Use the “Overview” tab to compare follower growth, posting activity, and engagement side by side.
Then, jump to platform-specific tabs to get in-depth reports for each platform.
Mine Customer Reviews
A single customer review may just be one person’s opinion.
But when you analyze these reviews at scale, clear patterns start to emerge.
For starters, look for factors that led people to buy a product. Or, notice the cons people mention in low-rated reviews.
Both indicate pain points you can target.
For example, this customer calls out weak product durability and a disappointing warranty process.
You also want to find what success looks like for your potential customers. Is it saving time, cutting costs, improving quality, or something else?
Document the features they call out as good or bad.
This insight can shape your messaging and even suggest improvements for your offering.
See if reviews pinpoint any competitors that people considered. Note why they chose or didn’t choose a specific brand over others.
Similar to the exercise I suggested for YouTube, collect product reviews from different platforms.
Ask any LLM tool to analyze these reviews and prepare a list of pain points.
Here are the review platforms you should check out based on your business type:
The more you know about your buyers, the stronger results your marketing efforts can produce.
What’s even better, your audience is already leaving signals about what they want.
When you listen closely and capture these insights, you can create content and launch campaigns that hit closer to home.
Download our Audience Research Tracker to easily document this data and turn these insights into content opportunities.
Next up: Wondering how to tie all your audience-centric content ideas together? Check out our guide on building a customer-focused content strategy to put this research to work.
Their answers often cite Reddit as one of the sources.
And this isn’t just anecdotal.
A Detailed.com study shows Reddit dominates product-related search terms in Google’s new “Discussions and forums” feature.
Semrush research backs this up, saying Reddit is the most-cited domain in AI answers.
In short:
Reddit now sits at the heart of your customers’ decision-making.
From the first flicker of curiosity to the final purchase, chances are good they’ll hit Reddit along the way.
Reddit Influences Buyer Trust
People trust Reddit more than your polished marketing.
The open grievances and the unfiltered praise make Reddit feel real in a way your ad copy never can.
Be honest:
How often do you tack “reddit” onto a Google search? I do it all the time. And Semrush data proves I’m not alone.
That’s Reddit becoming the internet’s social proof engine.
As Rob Gaige, Reddit’s Global Head of Insights, says:
“91% of people who discover a product on another platform are passing through Reddit to validate the claims they’re finding elsewhere.”
In other words, buyers don’t just take your word for it. They take Reddit’s.
Reddit Gives You an Edge Competitors Can’t Easily Copy
There’s no copy-paste trick when it comes to Reddit marketing.
Like you, your competitors have to put in the time to learn the culture and earn their keep.
That’s why the earlier you start, the stronger your position becomes. Every month you engage, you’re stacking credibility that shortcuts can’t match.
Yes, some try to game the system. And that might work briefly.
But eventually, Reddit’s algorithms, volunteer moderators, and the community’s BS detector flush them out.
(And with spam on the rise, the rules are only getting stricter.)
The Reddit Marketing System to Build Karma & Cred
Forget Reddit SEO “hacks,” like slipping links past moderators.
That’s short-sighted thinking.
Here’s the thing:
Reddit’s power isn’t clicks. It’s credibility and influence.
Earn it inside Reddit, AND it reverberates into search results and AI answers.
You don’t earn that trust with Reddit marketing tricks.
You earn it by contributing and becoming part of the community.
Here’s how.
(Shoutout to Ken Savage of Launch Club AI, a Reddit marketing agency, for sharing his insights from the trenches.)
Step 1: Build a Profile That Says “Redditor,” Not “Marketer”
The best way to optimize your Reddit profile? Do nothing.
A shiny, over-engineered profile from a Reddit newborn is a dead giveaway: You’re here to take, not give.
Sure, change your avatar if you like. But, resist the urge to polish.
Instead, keep it plain:
Leave the bio blank
Don’t link to your site or socials
Forget the “curated” look
Let your engagement history do the talking
Take ItsWahl, a plumber’s profile. You don’t see business links or calls-to-action. But scroll through his comments and post history, and you instantly know what he does.
That’s the beauty of Reddit. Reputation builds itself.
The profile follows.
Username tip: Just pick something forgettable. Maybe it’s an old gaming handle, a random word combination, or your pet’s name plus some numbers. The more unremarkable, the better.
Step 2: Get Fluent in Reddit Before You Speak
In your first week (or two) of Reddit marketing, don’t post. Just watch.
Study the culture and pay attention to tone and the little quirks of how people interact.
Why?
Because that look-at-me energy that Instagram and LinkedIn reward is exactly what gets you mocked or banned on Reddit.
It’s the platform’s general code of conduct, which includes:
Remembering the human behind the screen
Using proper grammar and spelling
Assuming good intent until proven otherwise
Formatting posts and comments clearly
But here’s the twist:
Reddit isn’t one community.
It’s thousands of communities, called subreddits (subs), with their own rules and expectations.
What gets you praise in one can get you flagged in another.
For example, in r/Entrepreneur, you need 10 comment karma (Reddit points from helpful comments), and self-promotion is banned.
But in r/Pen_Swap, buying, selling, and trading is the whole point.
Think of it as two layers: global expectations and local rules.
Break either, and the community will remind you. Sometimes, not too gently.
So, before you comment or post, always check the subreddit’s rules. They’re pinned at the top or listed in the sidebar.
The Reddit Moderators (aka Mods) and Their Power
Moderators are the gatekeepers of subreddits.
They control how the community runs within Reddit’s sitewide rules.
You can see who moderates any subreddit by checking the sidebar and clicking “Moderators.”
And yes, they have powers. They can:
Remove posts or comments
Issue warnings
Ban users
Your mileage with mods will vary.
Most are fair and invested in building solid communities.
Others, less so.
As one Redditor put it, “picky and easily angered.”
What most people miss about moderators is this:
Many of them run communities with tens of thousands, sometimes millions, of members. Managing these subreddits takes an enormous amount of unpaid time and effort.
It’s really in your interest to make their jobs easier by:
Reading and following the rules
Contributing genuine value
Respecting their authority
Do that, and you’ll stay on their good side.
Ignore it, and you’ll learn just how much power they really have.
Reddit Language
Reddit speak is conversational and BS-free. Humor, sarcasm, and the occasional bit of self-deprecation are all part of the mix.
It’s also full of shorthand and in-jokes that longtime users expect you to know.
You don’t need to memorize them all, but it’s worth knowing the basics if you want your Reddit marketing to have legs.
Here are a few common ones.
OP: Original poster
ELI5: Explain like I’m 5
TL;DR: Too long didn’t read
TIL: Today I learned
OC: Original content
NSFW: Not safe for work
IIRC: If I recall correctly
FTFY: Fixed that for you
AMA: Ask me anything
Most of these you’ll pick up through context.
But it’s worth bookmarking the full list for reference.
Karma & Voting
Karma is Reddit’s point system.
(Or, as Reddit’s “welcome” guide calls it: fake internet points.)
You’ll see your karma score in your profile sidebar, split into post karma and comment karma.
Here’s why these “fake” points matter:
Karma is the closest thing Reddit has to a reputation score. It affects where you can post and how you’re perceived.
You earn it through upvotes. If people find your post or comment useful, they tap the arrow pointing up.
But there’s a flip side to this democracy.
The down arrow — the downvote — takes karma away.
It’s the community’s way of saying “this doesn’t add value.”
The most-upvoted posts and comments rise to the top. Which means more people see them and more people engage.
(And the cycle reinforces itself.)
Those top comments also tend to spread beyond Reddit through shares or even showing up in search results.
Side note: Karma isn’t a clean one-upvote, one-point system. Reddit muddies the math to stop spam. Your goal is to earn more upvotes than downvotes and stay out of the red.
Step 3: Choose Subreddits Strategically
The subreddits you join will decide how quickly (or how slowly) you earn Karma.
Aim for a mix of niche communities tied to your expertise, plus a sprinkling of subreddits on topics you genuinely enjoy.
The rookie mistake is jumping straight into the biggest subs, hoping for easy upvotes.
But big subs move very fast. Their rules are stricter, and mods are hyper-vigilant.
Take r/AskReddit, for example, which has over 57 million members.
To stand out in your Reddit marketing, you need perfect timing, luck, and genuinely compelling content.
Otherwise, your post just disappears.
So, it’s better to start with smaller subreddits. They move at a manageable pace and are often more forgiving while you learn the ropes.
Side note: You can join as many subs as you want. Once you’ve built experience and have more time to contribute, you can always branch out to bigger subs.
How to Find Subreddits
My go-to method to find new communities is the Reddit search bar.
From the front page, type in your niche.
In the results, click “Communities,” and check two numbers:
Total members and currently online.
That ratio tells you how active a subreddit is.
For example, when I type “SEO” I see r/SEO with 421k members and 64 online, while r/seogrowth has 31k members with 16 online.
Even though r/SEO is bigger, I’d definitely consider also joining r/seogrowth as it’s more “alive.”
When you’re starting out, join 10–15 subreddits.
That’s enough range to test where you get traction. Over time, you’ll naturally narrow to 3–5 subs where you’re most active and recognized.
Getting the Lay of the Land
For your first 1–2 weeks, resist the urge to post. Just observe and absorb (aka lurking).
See which questions people ask repeatedly.
Go hang out in the comment sections. That’s where you’ll get a real feel for the community’s personality. You’ll pick up on how people joke, offer support, or tear bad ideas apart.
And above all: Read the rules.
They’re listed in the sidebar of every subreddit, and they can vary wildly.
For example, r/nutrition has a long list of guidelines to keep discussions science-based, while r/machinedpens has only three rules.
This is also the perfect time to gauge buyer sentiment about your brand or products.
I’ve used Reddit this way for years. And it’s helped me improve product page conversions, get better returns on Meta ads, and even given sales teams a clearer picture of buyer objections.
Take a hair supplement brand I worked with.
Their Meta ads had gone flat.
So, I spent hours in subreddits like r/haircare, r/hair, and r/hairloss scanning threads for brand sentiment and figuring out the deeper psychology behind purchase decisions.
Those insights fueled a creative refresh with new campaign angles, helping turn their Meta campaigns around.
Step 4: Join Conversations Without Being Annoying (The E.A.R.S. Reddit Marketing Framework)
Three hours a week of Reddit marketing is enough to make steady progress.
Here’s how to spend it using the E.A.R.S framework:
Explore: 5-10 minutes/day discovering threads
Add insight: 10–20 minutes/day reading, upvoting, and commenting
Respond: One 30-minute session/week writing and publishing
Share: 5-10 minutes/day amplifying your posts and comments
And no, your weekends aren’t part of the deal.
Side note: Three hours is a benchmark. In practice, it’s between 2-4 hours a week. Some weeks you’ll breeze through, others will take more. The good news is that the longer you do this, the quicker and easier it gets.
Explore: Find the Right Threads (5–10 Minutes/Day)
“Explore” is your foundation for quality and time control.
Your goal is to find 4-7 threads worth engaging in every day.
Get disciplined. This shouldn’t take more than 10 minutes.
Pro tip: Set a timer. Without one, it’s easy to slip into “just five more minutes” and somehow end up deep in r/oddlysatisfying watching hedgehogs take baths. (We’ve all been there.)
Here’s what to do:
Open a few of the subreddits you joined in the previous step.
Then, filter the threads by “Rising.”
This shows new posts starting to gain traction.
Get in early, and your comment is more likely to get noticed while the thread is still developing.
Next, cross-check with “Hot” to show the top posts.
As you scan both “Rising” and “Hot,” focus on threads where you can genuinely add value.
That means:
Answering a question with your knowledge
Filling in missing context
Clearing up a common misconception
Sharing a story from experience
Offering practical help to a “how-to” question
Top tip: Adjust your picks by subreddit size and activity. In large subs (over 1M members or 100+ posts/day), look for posts with 50+ upvotes and 15+ comments. In smaller subs, 5+ upvotes and a handful of comments are enough.
Add Insight: Write Comments That Get Upvotes (15–20 Minutes/Day)
“Add Insight” is the engine of your Reddit SEO strategy.
It’s your daily commenting session to build trust and visibility.
(And get those karma points climbing.)
Your goal is to leave 4-7 high-value comments a day. That’s it.
To leave comments, you have two options:
You can reply directly to the main post by clicking “Join the conversation.”
Or you can reply within a thread by clicking “Reply” under someone else’s comment.
The catch is:
What you say is only half the battle. How you format your comment decides whether people will give it the time of day.
(Because even the smartest insight dies as a wall of text.)
So, formatting matters. If you want eyes (and upvotes):
Break paragraphs early and often (but don’t go full broetry — that one sentence per line LinkedIn thing)
Use spacing to guide the eye
Bold key ideas when the subreddit allows it
Like this:
You can do all this using Reddit’s built-in comment editor.
Click the “Aa” icon in the comment box, and it will expand to show formatting options similar to Google Docs.
Now, comment with a purpose.
You want upvotes, and Reddit doesn’t give those willy-nilly. You get them by making the conversation better.
There are a few ways to do that.
The Explainer Comment
This is perfect when answering direct questions like “How do I…?” or “What’s the best way to…?”
Just give a direct answer with a bit of reasoning and extra info to support your answer.
The Gap Filler Comment
Use this when replies are missing something important.
Acknowledge what’s already been said, then add the missing piece.
The Shared Experience Comment
When the question overlaps with something you’ve been through, comment by sharing what you tried, what happened, and the key lesson.
The Source Comment
This is great for when a thread is full of assumptions, but you’ve got credible info.
Share the source and summarize in everyday language.
And if you’re the source, by all means join in the conversation.
The Case Study/Lived Experience Comment
Best for when you have real-world results to share: yours or someone else’s. Great for “does this actually work” questions.
Simply outline the situation, what you did, and the outcome.
The Checklist Comment
Sometimes, a checklist is all you need to be helpful.
This can be a step-by-step guide, tips, or just a few boxes to tick.
The Brand Comment
If your brand comes up in a thread, that’s a perfect opportunity to be visible in conversations about your brand.
Identify yourself and answer plainly.
Keep it useful, not salesy. Show that you’re listening and willing to help.
This works great when multiple people share similar problems. Tag them with u/ and put in the username after the slash
You can say “u/username above had the same issue. Worth comparing notes.”
Acknowledge + Build
Highlight a good point from someone else, then add your own idea. It builds goodwill while boosting your credibility.
Say something like:
“Great point, I hadn’t considered that angle. For anyone reading, here’s why it matters:“
Think Before You Reply
Not every reply deserves your energy.
Here’s a quick response matrix to help you decide what’s worth engaging and what to ignore.
If the reply…
Action
Example Response
Adds useful detail or perspective
Thank + expand
“Good point, thanks. I’d also add [extra detail]”
Corrects your point respectfully
Acknowledge + clarify
“Fair call. You’re right in general. I was thinking of [specific angle/context]”
Comes with mild sarcasm
Likely ignore
No need to reply. Better to save your energy than get pulled into a spiral
Is hostile or trolling
Ignore, downvote, report
(No response)
Share: Publish a Strategic Post (30 Minutes to 1 Hour/Week)
At some point, you’ll want to go beyond commenting and start your own threads.
There’s no magic karma number that unlocks this.
Each subreddit sets its own bar. Some require account age or karma, others don’t care at all.
The real question isn’t “Can I post?,” but “Should I?”
That depends on softer factors:
How well you know the community
How much you understand its culture
How much you’ve already contributed in comments
For context, I’ve posted with less than 50 karma when I had a genuine question.
That’s different from posting to build visibility or reputation, where the bar is much higher.
Ken Savage recommends getting a karma score of 500 before posting anything that mentions your brand:
“I’ve never been removed for anything above 500 karma. You can usually get that in two to four weeks of 20 minutes per day, five days a week, commenting. The core principle is to be authentic and provide detailed, thorough answers to people’s questions, as if you were getting paid for it.”
Once you’re ready, focus on posts with weight.
That means content that has a real shot at earning upvotes and visibility. These topics often come from:
Your top-performing comments
Recurring questions people ask you
Threads where the same issues keep surfacing
Once you’ve got a promising topic, package it in a format Reddit loves.
Here are some of the best.
Case Studies
Great for credibility-building. Walk readers through a real experience: yours, your customers’, or someone else’s.
Set up the problem or situation, explain step by step what you did, and share the outcome. Close with a clear takeaway.
Lessons Learned & Common Mistakes
This format works when your goal is to teach.
These posts show where you went wrong and how you fixed it: the “what I wish I knew” or “what I learned” stories.
To make this work, frame the mistake or lesson clearly, share the story behind it, and then give a practical fix.
Keep it simple.
One mistake per point makes it more relatable and easier to apply.
For example, if you’re a financial advisor, your topic could be “the budgeting mistakes I see most in new families and quick fixes that help.”
Discussion Prompt
Discussion prompts flip the spotlight back to the community and get people talking.
(Exactly what you want to happen in your Reddit marketing playbook.)
They work best when you give people a chance to share their stories.
Keep the question short and specific, and follow up in the comments to keep the thread going.
Some examples include:
Teachers: What’s one low-cost classroom supply you can’t live without?
What’s the best cleaning hack you’ve found for fur all over the house?
What’s the most surprising product you’ve found through ecommerce AI search?
Checklists & Step-by-Step Tips
Checklists help people self-diagnose and improve.
They work best when Redditors in the community are often worried they’re “doing it wrong” and want a quick way to check.
For example, if you’re in the beauty niche, you can post a topic on “a 4-step test to see if your skincare routine is helping or hurting.”
Then, break the process into 3–7 simple checks and explain why each one matters.
Here’s a Redditor who nails this format.
Myth-Busting
Myth-busting posts are always welcome on Reddit, especially in spaces where misinformation spreads fast.
Lead with the myth people believe and then refute it with proof or experience.
For example, a good topic in personal finance could be “the 3 biggest myths about credit scores and what actually improves them.”
Behind-the-Scenes
These posts pull back the curtain and show how things work.
They get a lot of upvotes because people love insider knowledge, especially when it reveals details they wouldn’t otherwise see.
Set the context, share the surprising or little-known details, and close with why it matters.
If you’re launching a new product, for example, you could show how it’s made and the trade-offs you wrestled with.
Free Resource
Offer something the community can actually use.
Spreadsheets, calculators, templates, swipe files, SEO checklists, mini-guides, code snippets.
Basically, the stuff people would normally charge for, but you’re cool enough to give away.
A few things to keep in mind:
Experiment with timing to find the best time to post. Generally, early weekday mornings and early evenings outperform weekends, but test for your specific communities.
Stick around after you post. Reply to comments and amplify good responses to help the thread grow.
Repurpose smartly. If a post lands, adapt it for 2–3 related subreddits. Tweak the angle and tone for each community. Plus, space them a few days apart to avoid looking spammy. Also, always check the subreddit rules. Some subs ban cross-posting or set timing restrictions.
Reddit Best Practices: How to Talk About Your Brand Without Getting Banned
Big caveat up front:
Don’t even think about promoting your brand until you’ve built karma and credibility.
Jumping in too early is the fastest way to get downvoted.
Once you’ve established trust, here are three ways to bring your brand into the conversation.
The Profile Discovery Method
This method keeps your brand mentions off your comments and lets your profile do the “selling.”
Your comments are focused on helping, and you let curious readers click through if they want to know more.
Pro tip: Once you’ve built some credibility, you can add a short professional bio or link your site/socials in the designated profile fields. Established Redditors do this on their profile.
The Expertise Sharing Method
This approach uses your role or business as context for why your perspective matters.
It signals credibility without sounding like a sales pitch.
Important: Don’t force it. If your comment works just as well without the brand mention, cut it. If not, Redditors might call that self-serving. No bueno for your karma.
The Direct Mention Method (Use Sparingly)
This Reddit marketing method involves naming your brand or product in comments. It’s a risky approach. So, make sure it adds to the conversation.
The key is balance:
Don’t make it an ad, and don’t act like your product is the only solution.
Ways You Can Lose Karma (& Trust)
Now, let’s talk about the fastest ways to torpedo your reputation and send your karma into free fall.
In short, things not to do.
Posting Like You’re on LinkedIn
Polished “thought leadership” and humblebrags are vomit-inducing on Reddit.
What’s modus operandi on LinkedIn reads as braggy here.
Keep it casual, conversational, and other-focused. Always.
Karma Farming
Yes, you can farm karma with memes and throwaway comments.
But that’s empty calories. It might get you numbers, but it won’t get you credibility.
And if you’re not building relationships and contributing to the community, you’re missing the whole point.
Link-Dumping for Quick Clicks
Dropping bare links or thinly disguised self-promo is Reddit’s oldest sin.
If your post exists just to drive clicks, expect downvotes.
Side note: Even if you play by the rules, downvotes happen. Bots filter posts. Mods nuke comments for reasons you’ll never know. That’s just Reddit being Reddit. Let it go and move on. You’ve only got three hours a week to spend here.
Stop Marketing, Start Belonging
This Reddit marketing strategy isn’t about farming karma.
Sure, you’ll earn enough to look legit and stop tripping newbie filters.
But the real win is this: You’ll start thinking like a Redditor.
And you’ll shed the marketing reflexes that get you downvoted and booted off threads.
With that, you become a trusted Reddit local.
And that’s when the ripple effect kicks in. You get seen more on Google. And through LLM seeding — where AI models pull from sources they trust — you also influence AI answers.
Bottom line: Play Reddit right and you etch your brand in a positive light into the internet’s DNA.
