Your next co-marketing campaign has two discovery problems to solve: how to earn visibility in search, and how to show up when buyers turn to AI for recommendations.
The most effective approach to co-marketing SEO is to build one strong asset that generates useful search and AI signals across the channels your buyers already trust.
We spoke with Tye DeGrange, founder and CEO of B2B partner marketing agency Round Barn Labs, who has more than 20 years of performance marketing experience, about building partner campaigns around the audiences partners already understand.
In this piece, we share:
- How to design co-marketing campaigns for search and AI visibility
- How to turn one source asset into links, mentions and citations across relevant surfaces
- How to measure both outcomes without mistaking AI visibility for business impact
One campaign, two paths to discovery
A strong co-marketing asset can bring in search traffic and give LLMs a credible source to reference when buyers ask related questions.
But the two discovery paths produce different signals.
In traditional search, for example, partner content might include an analysis of your benchmark report and link to the original research. That link can send referral traffic and contribute to the signals search engines use to assess the page.
AI search takes a different route. An AI engine can cite the original report, use a partner's analysis as a source or mention one of the brands behind the research. A citation and a brand mention are different signals.
In a June 2026 study with growth advisor Kevin Indig, Semrush analyzed 3,981 domain appearances across four AI platforms (ChatGPT, Google AI Overviews, Gemini and Google AI Mode) and found that 61.7 per cent were “ghost citations”: the source was cited, but the brand wasn't mentioned in the answer. Only 13.2 per cent were both cited and mentioned. Results also varied by engine. When a brand appeared, ChatGPT cited it 87 per cent of the time but named it only 20.7 per cent of the time, while Gemini did roughly the reverse.
This implies that you should not treat every AI appearance as a win. The prompt, context and business outcome all matter, so don't lump every appearance into one number. Track these signals separately:
- SEO backlinks: A partner links to your original asset, creating a path for referral traffic and search visibility.
- LLM citations: An AI system references your page or domain as a source in its answer.
- Brand mentions: An AI answer names your company, whether or not it links to your site.
The good news is that the rules of engagement in answer engine optimization for SaaS work in your favor right now. You can leverage your partners to create the type of content that LLMs cite and B2B buyers trust.
Your partners already know the audiences you're trying to reach. As DeGrange explains: “This is what my audience needs. This is what my audience is looking for. They know their community really, really well.”
You might also like: Answer engine optimization: The ultimate 2026 guide for B2B SaaS teams.
How to build a co-marketing campaign for search and AI visibility
Once you understand how search engines and LLMs discover and surface your co-branded content, the next step is to build those SEO and AI search signals into the campaign from the start.
Here’s how to create campaigns that earn both:
Use the source-signal-surface model
A strong co-marketing campaign starts with one authoritative source, then builds relevant signals around it and distributes them across the surfaces your buyers trust.
Here's what the system looks like:
- Source: The definitive asset partners can reference. For example, a crawlable integration page with setup instructions, use cases and supporting evidence.
- Signal: The links, quotations, evidence and brand or topic associations that extend from the source. Examples include a partner tutorial linking to the integration page, a customer explaining the integration or an expert discussing a use case.
- Surface: Where those contributions appear. For instance, partner blogs, creator YouTube channels, newsletters and webinars.
Start by planning the source, signals and surfaces as one system. This gives your co-marketing strategy a clear foundation before anyone starts creating content. Choose the canonical source first, decide what each partner can add that is genuinely useful to its audience and assign the right surface to each contribution.
Build co-marketing assets worth referencing
Give partners something useful to carry forward. Start with an asset that solves a real problem for your shared audience and set up partner enablement resources for each partner to build on.
The strongest formats create original value and multiple angles for content distribution:
- Joint research and benchmarks: Combine data, expertise or audience access to produce findings each partner can interpret for its own audience. Original data is also hard for competitors or AI tools to replicate, which gives buyers a reason to seek out the source.
- Tools and templates: Give buyers something practical to use and partners something useful to demonstrate, recommend or reference.
- Integration guides: Show how two products work together, with workflows and use cases partners can point customers to.
- Expert roundtables: Bring practitioners together around a specific problem, then turn the discussion into articles, newsletters, videos or transcripts.
- Comparison resources: Answer the questions buyers ask when evaluating solutions, with clear criteria and honest trade-offs. Comparison content also tends to earn brand mentions: in the same Semrush study, comparative queries (such as “best,” “vs” and “recommend”) produced 2.4 times more brand mentions than informational ones.
Design the SEO and AI visibility layers before production starts
The next step is to decide how buyers should discover the asset before production starts. This planning makes up your SEO and AI visibility strategy.
For every co-marketing asset, document the following. Here’s what it might look like for a joint partner benchmark report:
- Asset owner: The company that hosts and maintains the canonical version (for example, PartnerStack)
- Canonical URL: The single page partners link to (for example, /research/b2b-partner-benchmark)
- Partner angle: What each partner adds for its audience (for example, what the benchmark means for RevOps leaders)
- Target keyword: For example, “B2B partnership benchmarks”
- Target prompts: For example, “What is a good partner-sourced revenue benchmark?”
- Distribution surfaces: Partner blog, webinar, newsletter and YouTube
- SEO KPIs: Referring domains, rankings and qualified organic traffic
- AI visibility KPIs: Citations, mentions, prompt coverage and message accuracy
Before you lock a keyword or target prompt, validate the demand: who is searching, what they want and whether your product has a credible role in that journey.
The same principle applies to AI search. In a recent newsletter, Product-Led SEO author Eli Schwartz argues that being cited only drives revenue when it gives buyers a reason to click or search further: “Without a reason to click, the visibility is just vanity.” Choose target prompts tied to a real buyer need, and plan how you’ll prove a placement drove incremental results, not just that it appeared.
Assign the source asset a clear search intent, canonical page, target keyword and internal links. Partners should then create distinct supporting content rather than publishing copies of the source.
For example, the canonical report might target “B2B partnership benchmarks,” while a partner creates an analysis specifically for RevOps leaders and links readers back to the original research.
This gives the source a defined role in search while giving each partner content with its own reason to rank.
See more: AEO for partnerships: How to rank in answer engines.
Structure information for discovery and attribution
Start by making your source asset easy to understand and retrieve. Use descriptive headings, keep related information together and answer specific questions directly instead of burying the key point in a long narrative.
A 2026 AirOps study conducted with Indig analyzed 16,851 ChatGPT queries and found that headings closely matching the user’s query were the strongest on-page factor associated with citations, and pages that answered queries more precisely performed better.
As Indig put it when sharing the research, “The pages that win consistently in ChatGPT are highly focused.”
In other words, structure the page around the questions you want it to answer. Give each important finding, product capability or expert insight enough context to stand on its own when an AI system retrieves it. Name the brands behind the asset clearly, both on the page and in partner content. A citation alone doesn’t guarantee a brand mention.
Turn one launch into a distributed evidence network
Once the source asset is live, give each partner a clear way to extend it through the channels and formats that make sense for its audience. The goal is to build multiple useful pieces of content around the same underlying evidence, rather than asking every partner to repeat the original asset.
Brief partners deliberately, too. Share the positioning, use cases and category language you want reflected, so their content reinforces how buyers and AI systems understand your brand.
A single co-marketing asset could become:
- A partner article that explores one finding or use case in more depth
- A newsletter that highlights an insight relevant to that audience
- A webinar where experts discuss the topic and add new perspectives
- A video or podcast that brings practitioner commentary to the research
- A transcript or recap that puts those insights into a crawlable web format
Each contribution should add something new while reinforcing the same source. That gives search engines and AI systems multiple pieces of relevant evidence to discover, connect and reference across the partner ecosystem.
Finally, keep the source current. When your data, positioning or product changes, update the canonical asset and let partners know so they can refresh their contributions.
Measure the two returns separately
SEO and AI visibility answer different questions, so give each its own scorecard.
SEO scorecard: SEO measures whether the campaign is strengthening search visibility and qualified organic demand. Track:
- Referring domains: New partner links pointing to the source asset
- Keyword rankings: Movement for target searches
- Organic traffic: Qualified visitors reaching the source
- Conversions: Leads, sign-ups or other meaningful actions
AI visibility scorecard: AI visibility measures whether your brand and source are appearing in the answers buyers see. Track:
- Prompt coverage: Priority buyer questions where your brand appears
- Citation share: How often your source is cited for those prompts
- Brand mentions: How often AI answers name your brand
- Source attribution: Which pages and partner surfaces AI systems reference
- Message accuracy: Whether AI systems describe your brand correctly
Pro tip: Track the same prompt set over time, with a focus on high-intent questions rather than generic visibility. The goal should be to become visible and stay top of mind with your target audience, so they come back to your brand whatever the channel.
The co-marketing mistakes that weaken both outcomes
Even a strong co-marketing strategy can lose value in execution, especially when partners create weak versions of the same asset instead of extending the original source. Common mistakes include:
- Republishing the same article across every partner site: Duplicate copies can compete with the source for the same searches, and they give AI systems no new evidence to reference.
- Adding logos without meaningful partner contributions: If the partner adds nothing new, its audience has little reason to engage, share or link.
- Distributing content across irrelevant or low-authority surfaces: Placements that don’t reach your buyers, or that buyers don’t trust, add volume without adding credible signals.
- Measuring only the initial launch instead of the long-term return: Links, citations and mentions build over time.
Make every co-marketing campaign compound
You don’t need to create more content to win in search and AI. You need to make each campaign produce more useful signals from the same source.
Start with one strong source, give partners a reason to contribute and distribute those contributions across the surfaces your buyers trust. Then measure the SEO and AI returns separately.
The payoff compounds over time. As DeGrange puts it, “The exciting thing to me is that long-term is sort of baked into this.”
Hear more from DeGrange on PartnerStack’s Get It, Together podcast: How to crack modern affiliate strategy in B2B SaaS.
PartnerStack gives you the infrastructure to manage those partner relationships at scale, from recruitment and activation to tracking the contribution each partner makes. And with PartnerStack’s Content Marketplace, you can find the publishers and creators already influencing AI answers in your category.
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