A segment of users actively researching or considering a purchase in a specific product or service category.
01What it is and how it works
In-market audiences are defined by signals that indicate purchase intent, such as recent search queries, website visits, and engagement with product pages. Google Ads, for example, builds these audiences from users who have shown interest in a category within a recent time window. In the context of AI search, these signals influence how a language model generates responses. When a user with in-market intent asks a question, the AI may prioritize brands that are commonly associated with that intent in its training data. The mechanism is not transparent, but factors like brand authority, content relevance, and structured data markup play a role. For instance, a user searching 'best running shoes for marathon' might receive an AI answer that includes brands like Nike or Asics because those brands have strong online presence and are frequently mentioned in authoritative sources.
In-market audiences are people who are ready to buy and searching for information. When they ask AI assistants questions, the brands that appear in the answers get their attention. This entry explains how to track and improve your brand's presence for these users.
02What to do about it
Start by identifying the key in-market queries for your product category. Use keyword research tools to find question-based and long-tail queries that signal purchase intent. Then, create content that directly answers those questions. Ensure your product pages include Product schema markup to help AI understand your offerings. Build authority through backlinks and expert citations. Monitor AI search results for your brand using tools that simulate queries. Adjust your strategy based on which brands appear. Also, consider running Google Ads campaigns targeting in-market audiences to complement organic visibility.
03How it is measured or noticed
Measure your brand's share of voice in AI answers for a set of in-market queries. Track the number of times your brand appears in AI-generated responses compared to competitors. Use analytics to see referral traffic from AI search sources. Monitor click-through rates from AI answers to your site. Also, track changes in brand search volume after AI visibility improves. Tools like our product provide dashboards that show these metrics over time.
04Common mistakes
- Ignoring conversational, long-tail queries that in-market users actually ask.
- Assuming AI search behaves exactly like traditional search engines.
- Not optimizing for featured snippets or structured data, which AI models often use.
- Focusing only on head terms and neglecting the long tail of purchase intent.
- Failing to monitor AI search results regularly, as models update frequently.
05Limits
In-market audience targeting is less effective for very niche or emerging categories where training data is sparse. AI models may not have enough context to surface brands accurately. Also, in-market audiences are often confused with 'target audiences' (demographic-based) or 'lookalike audiences' (similar to existing customers). In-market is specifically about recent purchase intent, not general interest. Additionally, AI search results can be inconsistent; a brand may appear one day and not the next due to model updates.
06Worked example
A user asks an AI assistant: 'What are the best noise-canceling headphones under $200?' The AI responds with a list that includes Brand A, Brand B, and Brand C. Brand A has optimized its product page with structured data and has a high authority score, so it appears first. This visibility to an in-market audience leads to a 20% increase in referral traffic from AI search. The brand then uses our product to track this share of voice and adjusts its content strategy to maintain presence.
Frequently asked questions
How is an in-market audience different from a lookalike audience?
In-market audiences are based on current purchase intent signals like recent searches and site visits, while lookalike audiences are modeled from existing customer data to find similar users. In-market audiences reflect real-time intent; lookalikes reflect demographic or behavioral similarity.
Should we target in-market audiences for a new product launch?
It depends on the category maturity. For established categories with sufficient search data, yes. For niche or emerging categories where training data is sparse, in-market audience targeting is less effective.
How do we identify in-market queries for our brand?
Use keyword research tools and analyze search trends for terms indicating purchase intent, such as "buy", "best", "reviews", and "compare". Then monitor AI answers for those queries to see where your brand appears.
Does in-market audience targeting still work if AI search results change frequently?
Yes, but it requires continuous monitoring. AI answers can shift as models update, so regular measurement of share of voice is necessary to maintain accuracy and capture high-intent users.
What happens if we ignore in-market audiences in AI search?
Competitors may capture high-intent users by appearing in AI answers, leading to lost sales opportunities. You would notice a decline in organic traffic from purchase-intent queries.
How long does it take to see results from optimizing for in-market audiences?
It varies by category and content freshness. Typically, you may see changes within weeks as AI models recrawl and reindex, but consistent optimization is needed for sustained impact.
Asked out loud
spoken, not typedThe same term in the words somebody uses speaking to an assistant rather than typing into a box — written from the situation, which is why each one carries the situation it came from.
You're describing an in-market audience. Focus on measuring your share of voice for high-intent queries to demonstrate the gap and justify optimization efforts.
Yes, you need to monitor in-market audiences. Use a tool that tracks brand mentions in AI answers for purchase-intent queries to see where you stand.
You're likely missing in-market audiences. Shift focus to queries with purchase intent and measure your brand's presence there to capture ready-to-buy users.