For decades, media planning has been a direct artifact of marketing strategy. Where the rubber meets the road – one page. Channels on the left, budget on the right, assignments mapped out for the year. When the CEO asks where the money is going, you give them a press release. The media system forces rigor. It makes the exchange transparent. Aligns groups.
Ask live teams something similar and you will get crickets.
That’s not a dig at SEO teams. For most of search history, SEO has been a single commodity discipline. You have developed one legacy, your website, for Google. The channel was small, the exterior was clear, and the strategy could live within one group.
That time is over.
The sources that shape how AI models represent your product now extend far beyond your website. Reddit, YouTube, review forums, third party editing, influence spreads; they all contribute to the picture of AI systems building around your product. They also have different dynamics, owners and relationships with your brand. Their relative importance also varies significantly by product, vertical and LLM. And right now, most brands are managing that portfolio without a plan at all.
The problem is that most biological groups are still not organized around that fact. Despite the change, many organic programs still operate with disconnected functions: a content calendar here, a keyword roadmap there, maybe some digital PR that works separately.
Enter the Organic Media Mix.
What is an Organic Media Mix?
The Organic Media Mix (OMM) is a strategic framework for allocating effort, resources, and budget across organic channels based on where AI programs are citing your category, and where you have a realistic opportunity to influence those statistics.
The output is a one-page strategic vision: a document that tells you which organic channels you’re prioritizing this quarter, makes trade-offs transparent, aligns various teams, and gives leadership a clear picture of where organic investments are going and what they’re expected to deliver.
An important thing to understand before building one: no two OMMs look alike, and the differences between them are small. A CPG product mix is much different than a B2B technology company. And within the same product, the picture changes depending on which AI model you’re looking at.
Step 1: Download your quote report
The citations report shows where the AI models found their answers in your section. When a user asks a question related to your product, product question, comparison, recommendation, what sources does the AI cite? Your site? A Reddit thread? A TechCrunch article? A YouTube update?
Most AI visualization platforms (Profound, seoClarity, AirOps and others) can generate this data. The procedure is:
- Define your data set, the questions your customers are likely to ask AI assistants, from informational (“what is X?”) to highly targeted commercial (“what is the best X for a mid-market SaaS group?”).
- Run those guides against the AI models you care about: ChatGPT, Gemini, Perplexity, Claude, and Google AI Overviews.
- Capture which sources are cited in the responses.
- Categorize those sources: affiliate site, YouTube, 3P editorial sites, Reddit, review forums, Wikipedia, influencer content, store listings, and more.
What you get is a map of where the authority sits in your category, not where you want it to be, but where the AI models actually go to answer questions about you and your competitors.
The quote report will surprise you and the surprises are different for every brand
In one category we analyzed, Reddit did not appear in the top 100 citation sources. For one, it represented 21% of all citations and was 3x larger than the second most cited domain. Whether Reddit is important to your brand isn’t a general question, it’s a practical one, and you can’t answer it without data.
Variation across AI models adds another layer. In one product we worked with, Reddit accounted for 23% of citations in ChatGPT responses, but only 3% in AI Overviews. The model you are looking at changes the picture completely. A strategy built on one platform’s data alone will miss out on how a large portion of your customers are searching.
This is why the OMM cannot be a static, one-size-fits-all document. It should be based on your specific quote data, across all models used by your customers.
Step 2: Extract each channel in four ways
The green quote volume tells you what’s going on. It doesn’t tell you where to invest. With that, he rates each channel on four dimensions.
Level of influence. How much control do you have over what appears in this area? Your website lives in the end, you write it, publish it, and update it without asking anyone. Wikipedia sits at one extreme. Reddit, review sites, and digital PR all fall somewhere in between. High-impact channels aren’t always the most important, but all things being equal, you can move them faster.
Difficulty using. Some channels require a single team and content calendar. Others require developer services, agency relationships, legal clearances, or long planning cycles. Difficulty using points helps you track the road in a realistic way.
Approaching trade quickly. Not all quotes have equal weight. Excerpt from “what is protein powder?” soon things are less than one achieved by “what is the best high protein supplement for endurance athletes over 40?” The closer the information is to the purchase decision, the more important the quote is. Get a set of your information accordingly, and the weight quotes from the top buys are very encouraging in your analysis.
Emotions. Mention is not victory if it is negative. Popular quotes, especially from trusted third-party sources, carry far more weight than neutral or critical mentions. Find each quote source for the experience it consistently delivers, and include that in your investment. A forum thread that unfavorably cites your product in a highly cited article is an active liability, not a neutral data point.
Step 3: Build the mix
With a report breakdown of your citations and results for your channel in hand, you can now build an Organic Media Mix.
Here is a hypothetical CPG product. Before doing the citation analysis, the team assumed that your own content did the most work and assigned accordingly. The data told a different story.
Anonymous example: A consumer health brand (illustration)
Finding that the strategy changed: third-party programming was the biggest citation driver, with high commercial affinity and consistently positive sentiment, but the product had almost no planned investment in it. The team treated digital PR as a brand awareness game, not an AI visibility game. OMM rescheduled that discussion and opened an open budget.
Step 4: Assign resources, groups, and owners
OMM is only valuable if it drives decisions. Specifically, it should answer three questions.
Who does what? AI visibility isn’t just an SEO discipline, it’s a marketing team game. Doing OMM requires SEO experts in managed content and technical infrastructure, PR teams and comms for digital PR and editorial input, social and community groups, and potential influencers or collaborators in video and third-party representation. The OMM is a document that forces a multifaceted discussion about ownership.
What is the budget? It’s not about ad dollars, but organic isn’t free. Content production, communications, PR agency retainers, community management tools, and influencer partnerships all have costs, not to mention the precious time and focus of your marketing team. OMM makes those costs transparent and commits to expected citation results, in the same way that a paid media program links exposure spend to targeted conversions.
What is succession? Not everything happens at once. Use difficulty scores and quote gap analysis to track the road: priorities, with lowest difficulty first, with long-term infrastructure investments planned in parallel.
Integrating organic and paid
One of the most underutilized applications of OMM: using it to connect organic intelligence with paid investment decisions.
If your citations report shows a Reddit thread that is highly cited and consistently relevant to your product, that’s not just an organic signal, it’s a paid opportunity. Can your paid social team place a target on that thread or nearby community to grow content?
This same concept goes back. If a paid campaign drives awareness about a specific use case, your organic team should build coverage for the same query quote, so that your product appears in many trusted sources, not just your site.
This is a different type of play that is not visible without data in front of the whole team. Paid and live have historically been managed in silos. OMM creates a shared language that makes integration useful.
Document your CMO is missing
Too many AI visibility strategies are driven by agnostic assertions, which have worked for traditional SEO and vibes. Organic Media Mix is a document that solves that. It starts with data (a report of your quotes in all important AI models), the weighting channels are compared to the criteria that drive real results (influence, difficulty, commercial proximity, emotions), and ends with a systematic framework for the allocation of resources, owners, and priorities.
Your OMM will not look like someone else’s. Channel mix, model variation and emotional image are all specific to your product and category. That’s the point. The general organic strategy is why most brands don’t show up in AI-mediated searches. Clarity is an advantage.
If your CMO can provide the board with a media plan that shows where all the paid dollars are going, they should be able to provide them with an OMM that shows where all the organic dollars are going.
Brainlabs creates Organic Media Mix strategies for companies navigating AI visibility. If you want to understand where your category quotes are coming from and where you should invest get in touch.
