TL;DR: Cold audiences are people who have never heard of you. Interest stacking combines 3--5 related interests into a single ad set to create an audience of 1--5 million people that Meta's algorithm can optimize. This guide gives you three proven audience blueprints for coaching and consulting businesses, plus the rules for testing and scaling.

Your lead magnet funnel is built. Your tracking is set up. Your email sequence is ready. Now you need strangers to see it.

Cold audiences are how you reach people who have never visited your website, joined your list, or heard your name. They are the top of your growth funnel. Get this right, and you have a predictable, scalable source of leads. Get it wrong, and you burn through your ad budget showing ads to people who will never convert.

The biggest mistake I see with cold targeting is going too narrow ("AI consultants in Austin who also like Elon Musk") or too broad ("all entrepreneurs in the US"). Interest stacking finds the sweet spot.

Interest stacking means combining multiple related interests into a single ad set. Instead of targeting one narrow interest, you layer 3--5 interests together using Meta's Detailed Targeting OR logic.

When you add multiple interests in the same targeting field, Meta shows your ad to anyone who matches any of the selected interests. This expands your audience while keeping it relevant.

Example:

Combined with US targeting and age 25--55, this creates an audience of roughly 2--4 million people. Large enough for the algorithm to optimize, focused enough to be relevant.

Here are three proven cold audience stacks for technology consulting and coaching businesses. Test all three simultaneously with identical ad creative to find your winner.

Who these are: Business owners actively working on their business growth.

<style>.cf-tbl-1{width:100%;border-collapse:separate;border-spacing:0;border-radius:12px;overflow:hidden;box-shadow:0 4px 15px rgba(0,0,0,0.08);font-family:system-ui,-apple-system,sans-serif;margin:2rem 0}.cf-tbl-1 thead tr{background:#1a1a2e}.cf-tbl-1 thead th{color:#fff;text-transform:uppercase;font-size:0.75rem;letter-spacing:0.05em;padding:14px 18px;text-align:left;font-weight:600}.cf-tbl-1 tbody tr{transition:background 0.15s}.cf-tbl-1 tbody tr:hover{background:#f8f9fa}.cf-tbl-1 tbody td{padding:12px 18px;border-bottom:1px solid #e9ecef;font-size:0.92rem}.cf-tbl-1 tbody tr:last-child td{border-bottom:none}.cf-tbl-1 tbody tr:nth-child(6n+1) td:first-child{border-left:3px solid #6366f1}.cf-tbl-1 tbody tr:nth-child(6n+2) td:first-child{border-left:3px solid #f59e0b}.cf-tbl-1 tbody tr:nth-child(6n+3) td:first-child{border-left:3px solid #10b981}.cf-tbl-1 tbody tr:nth-child(6n+4) td:first-child{border-left:3px solid #ec4899}.cf-tbl-1 tbody tr:nth-child(6n+5) td:first-child{border-left:3px solid #8b5cf6}.cf-tbl-1 tbody tr:nth-child(6n+6) td:first-child{border-left:3px solid #06b6d4}@media(max-width:540px){.cf-tbl-1,.cf-tbl-1 thead,.cf-tbl-1 tbody,.cf-tbl-1 tr,.cf-tbl-1 td,.cf-tbl-1 th{display:block}.cf-tbl-1 thead tr{position:absolute;top:-9999px;left:-9999px}.cf-tbl-1 tbody td{padding-left:50%;position:relative;border-bottom:1px solid #eee}.cf-tbl-1 tbody td:before{content:attr(data-label);position:absolute;left:18px;font-weight:600;text-transform:uppercase;font-size:0.7rem;color:#666}}</style><table class="cf-tbl-1"><thead><tr><th>Setting</th><th>Value</th></tr></thead><tbody><tr><td data-label="Setting">Location</td><td data-label="Value">United States</td></tr><tr><td data-label="Setting">Age</td><td data-label="Value">28--55</td></tr><tr><td data-label="Setting">Gender</td><td data-label="Value">All</td></tr><tr><td data-label="Setting">Interest 1</td><td data-label="Value">Entrepreneurship</td></tr><tr><td data-label="Setting">Interest 2</td><td data-label="Value">Small business owners</td></tr><tr><td data-label="Setting">Interest 3</td><td data-label="Value">Business coaching</td></tr><tr><td data-label="Setting">Interest 4</td><td data-label="Value">Startup company</td></tr><tr><td data-label="Setting">Interest 5</td><td data-label="Value">Business strategy</td></tr><tr><td data-label="Setting">Estimated size</td><td data-label="Value">2--5 million</td></tr></tbody></table>

Why it works: These people self-identify as business builders. They follow business pages, engage with entrepreneurship content, and are actively looking for ways to grow.

Who these are: People already investing in marketing who need better tools and strategy.

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Why it works: These people already understand funnels and marketing. They are likely paying for tools but struggling to get results. Your expertise in making those tools work is exactly what they need.

Who these are: Business owners curious about AI and technology adoption.

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Why it works: These are the people asking "How do I use AI in my business?" -- the exact question your content answers.

Critical rule: Do NOT use the Narrow Audience button. Narrowing requires users to match ALL interests (AND logic), which shrinks your audience too much for the algorithm to optimize.

Run all three audiences simultaneously with the same ad creative. This tells you which audience responds best to your message.

Test setup:

After 7 days, evaluate:

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The winner is not always the cheapest CPL. It is the audience that produces leads who open your emails, click your links, and book calls. A $7 lead who books a call is worth more than a $3 lead who never opens an email.

Always exclude these audiences to avoid wasting budget:

How to add exclusions:

Once you have a winning audience (consistent CPL below your target for 7+ days):

Once your pixel has 100+ Lead events, create a Lookalike Audience:

Lookalikes typically outperform interest-based audiences because they are modeled on people who actually converted, not just people with matching interests.

A cold audience consists of people who have never interacted with your brand -- no website visits, no email list, no social media engagement. You reach them through interest-based targeting, broad targeting, or lookalike audiences.

3--5 interests per ad set. Fewer than 3 creates too narrow an audience for the algorithm. More than 5 dilutes the focus and makes it harder to identify which interests drive results.

For cold prospecting, target 1--5 million people. Below 500K, the algorithm lacks data to optimize. Above 10M, you are paying for too many irrelevant impressions. In between gives Meta enough room to find your ideal customers.

For your first campaigns, use manual interest stacking so you learn which audiences work. Once you have strong pixel data (100+ conversions), test Advantage+ Audience -- it uses Meta's AI to find converters, sometimes outperforming manual targeting.

Minimum 7 days. The algorithm needs 3--5 days to exit the learning phase, and you need 2+ days of post-learning data to evaluate real performance. Do not judge or change anything before day 5.

Carlos Vargas is the founder of Bezalel Digital, a technology consulting firm that helps entrepreneurs and small business owners implement AI, funnels, and automation to scale their businesses. Need help building your ad targeting strategy? [Book a free strategy call](https://www.carlosvargas.com/strategy-call).

Disclaimer: Ad performance varies based on offer, creative quality, audience composition, and market conditions. The audience blueprints in this article are starting points based on typical results for coaching and consulting businesses. Your results may differ.