In-Market Audiences

In-Market Audiences are predefined audience segments in Google Ads consisting of users who Google has determined are actively researching or intending to purchase products or services in a specific category. Google identifies these users based on recent search activity, website visits, and content consumption patterns.

Key Takeaways

• In-Market users are actively shopping — they show high purchase intent right now
• Google defines and maintains these segments based on real-time behavioral signals
• Available across Search, Display, YouTube, and Performance Max campaigns
• Typically produce higher conversion rates than broad targeting due to purchase intent
• Best used in observation mode first, then with bid adjustments based on performance data

What Are In-Market Audiences

In-Market Audiences represent users at the bottom of the purchase funnel. Unlike Affinity Audiences (which reflect long-term interests), in-market segments capture users who are demonstrating active buying signals right now.

Google classifies a user as “in-market” when their behavior across Google properties indicates purchase research:

Signal	Example
Search queries	Repeated searches for “best CRM software 2026”
Website visits	Browsing pricing pages on multiple CRM vendor sites
Content consumption	Reading comparison articles and reviews
Click patterns	Clicking on product ads in the same category
YouTube activity	Watching product demo and review videos

Google maintains hundreds of in-market categories organized in a hierarchy. Examples include:

• Business Services > Business Technology > CRM Software
• Vehicles > Motor Vehicles > New Cars
• Real Estate > Residential Properties > Homes for Sale
• Software > Business Software > Project Management Software

How It Works

In-Market Audiences are applied to campaigns in the Audience Segments section of Google Ads:

1. Select your campaign or ad group in the Google Ads interface
2. Navigate to Audiences and click to add segments
3. Browse or search the “In-Market” category for relevant segments
4. Choose application mode — Observation (recommended initially) or Targeting
5. Set bid adjustments based on performance data after an observation period

In observation mode, your ads still show to all users, but you can see how in-market users perform compared to your baseline. After collecting statistically significant data (typically 2-4 weeks), you can apply bid adjustments to increase spend on high-performing segments.

In targeting mode, your ads only show to users who belong to the selected in-market segment. This dramatically narrows reach but maximizes intent alignment.

Practical Example

A B2B accounting software company runs Search campaigns targeting keywords like “small business accounting software.” They add three in-market segments in observation mode:

In-Market Segment	Impressions	Clicks	Conv. Rate	CPA
All traffic (no segment)	12,000	840	3.2%	$145
In-Market: Accounting Software	2,800	224	6.8%	$68
In-Market: Business Financial Services	1,400	98	4.5%	$103
In-Market: Tax Preparation Services	900	54	1.8%	$257

Analysis:

• Accounting Software segment converts at 2.1x the baseline — apply a +50% bid adjustment
• Business Financial Services converts 40% better — apply a +20% bid adjustment
• Tax Preparation Services converts below baseline — apply a -30% bid adjustment

After applying these adjustments for 30 days:

• Overall CPA decreases from $145 to $112 (23% improvement)
• Budget shifts toward the highest-converting user profiles automatically
• Total conversions increase by 15% at the same budget level

Why It Matters

In-Market Audiences let you prioritize users who are ready to act. Two people can search the same keyword but be in very different stages of the buying journey. One might be casually browsing while the other has a budget approved and is comparing final options. In-market signals help you identify and bid more aggressively for the latter.

This is particularly valuable in competitive markets where CPCs are high. Paying a premium for a user who is 2-3x more likely to convert is mathematically sound. The key is starting with observation mode to validate which segments actually perform in your specific account before committing budget through targeting or aggressive bid adjustments.