Share one strategy that helped you reduce your ad cost on Meta or Google Ads.

For me, the biggest cost of running Meta ads often comes down to two things: the high cost of producing ad creatives, and the money wasted on creatives that don't convert. To increase my chances of success, I always start by researching what works for competitors using tools like the Meta Ad Library. If certain angles or formats are performing well for them, there's a good chance we can either learn from it or create something even better. To avoid wasting budget on low-performing ads, I set up dedicated test campaigns with around 10 percent of the total budget. I use those to test different hooks and creatives. Only the best-performing ones get promoted to the main campaign. That way, I reduce guesswork, improve creative performance, and spend more of the budget on what actually works.

One strategy that significantly reduced ad costs on Meta was leaning into content that felt native to the platform. So instead of polished, highly produced ads, I started using simple iPhone videos. Just talking directly to the camera with no fancy edits or scripts. The more it looked like something a friend might post, the better it performed. CPMs dropped, click-through rates went up, and the algorithm seemed to prefer this kind of content because people actually engaged with it. Another shift was moving away from interest-based targeting. Broad targeting gave the algorithm more room to find the right people. Especially once the creative had enough data behind it. Strong creative did most of the heavy lifting. Because when the message landed, it found the audience. When it didn’t, results dropped fast. So it became easier to cut underperforming campaigns early. Instead of building complex funnels with multiple retargeting layers, most of the budget went straight to cold traffic. Because when the offer was strong and the creative hit, extra steps weren’t needed. Each ad was treated like its own landing page. With a clear headline, strong hook, one main message, and a reason to act now. If any part of it didn’t land, it was better to rebuild than tweak endlessly. The biggest cost savings came from being quick to pause slow-moving campaigns. Even if something looked profitable on paper. Because if it took too long to scale or deliver consistent results, it tied up budget that could be testing something better. Fast feedback and fast decisions kept CAC low and performance strong.

One strategy that consistently reduces ad costs on Meta and Google Ads is tightening audience intent with high-signal actions. For example, we ran retargeting only to users who viewed key pages (like pricing or product demos) and excluded low-intent visitors. Pairing that with creative tailored to their last action (e.g. Still considering "product"?) cut our cost per lead by 30% while improving lead quality.

Instead of just running ads like everyone else, I take care of comments. I ask my friends, customers to leave comments under ads with the most spend. We've cut ad costs by 30-50% overnight on multiple campaigns by increasing quality social proof under ads.

Don't just increase Meta ad budgets. Watch first-time impression share like a hawk. If it drops below 30%, your audience is fatigued. No amount of spend will fix that. Fresh creative and broader reach win scale, not bigger budgets alone.

One strategy that really helped reduce ad cost on Meta was narrowing the audience with value-based lookalikes instead of broad targeting Instead of targeting general interests or demographics I uploaded a custom list of high-value customers who had made repeat purchases Then I created a 1 to 2 percent lookalike audience based on that list and combined it with engaged users from our Instagram and Facebook pages This made the audience much more qualified and reduced wasted impressions As a result the cost per purchase dropped by 38 percent and the ROAS nearly doubled because we were reaching people more likely to convert instead of casting a wide net Tight targeting plus high-quality creatives that spoke directly to those users made all the difference

Our strategy for reducing ad cost on Meta and Google Ads is to use negative keywords and exclusion lists relentlessly. It's a simple but powerful way to ensure your money is only spent on reaching the most relevant audience. For Google Ads, we carefully analyze the search terms report to find and add keywords that are irrelevant to our business, such as "free," "DIY," or "tutorial" when we're promoting a paid product. This prevents our ads from showing up in front of people who have no intention of buying, which saves us a significant amount of money on wasted clicks. By doing this, we also improve our Quality Score, which Google rewards with a lower cost per click and better ad positions. The result is a much more efficient use of our budget. On Meta, the principle is the same even though the feature is a bit different. We use custom audience exclusion lists to keep our ads from being shown to people who have already converted or who have engaged with our brand in a way that suggests they are unlikely to become a new customer. For example, we might exclude existing customers from our acquisition campaigns or people who have already downloaded a specific resource. This prevents us from wasting ad spend on an audience that is no longer relevant to our campaign's objective. By continually refining who we are targeting and, more importantly, who we are excluding, we get better results for less money and we keep our ad relevance high.

One of the most effective ways we reduced ad cost on Google Ads was by tightening our negative keyword list early in the campaign. In one case, we saw nearly 20 percent of the budget going to irrelevant clicks from loosely related terms. By reviewing the search term reports weekly and blocking out low-converting or misleading queries, we immediately improved our cost per lead and overall ad relevance. This strategy works because it filters out the noise and ensures your budget is spent only on people who are actually looking for what you offer. It's simple, repeatable, and one of the easiest wins for any paid search campaign.

One smart way to cut ad costs on Meta or Google Ads is to focus on audience segmentation. Instead of throwing a wide net, break your audience into smaller groups based on behavior, interests, or past interactions. This way, your ads speak directly to each group's needs. It's like serving the right dish to the right guest at a party, everyone's happier, and you waste less food. Also, keep an eye on negative keywords and exclude irrelevant traffic. This stops your budget from draining on clicks that don't convert. Think of it as closing doors to unwanted guests. Finally, test your ads often. Small tweaks in copy or visuals can drastically improve performance. Don't set it and forget it, be ready to pivot quickly. Ads aren't set in stone; they're more like a garden that needs regular watering and pruning to bloom.

One effective strategy to reduce ad cost on both Meta and Google Ads is to narrow audience targeting and use exclusion lists. By refining your audience to focus only on high-intent or relevant segments and actively excluding groups unlikely to convert, you reduce wasted impressions and clicks. This leads to higher relevance scores on Meta or Quality Scores on Google, which in turn lowers your cost per click or impression. Regularly reviewing performance data and updating your exclusions based on non-converting demographics, interests, or search terms keeps your targeting efficient and your ad spend focused on the most valuable prospects.

One strategy that consistently helped me lower ad costs on Meta was dialing in on creative that speaks directly to a specific segment of our audience. I used to run broad hooks that sounded clever but didn't resonate deeply. Then I shifted to what I call creative targeting, where the ad copy and visuals clearly call out the person we want. For example, instead of saying "tired of slow results," we used "busy moms over 40 who struggle with bloating," and suddenly our CTR went up and cost per lead dropped by 30 percent. Meta rewards relevance, and when the right people stop scrolling, your cost naturally drops.

One strategy that significantly reduced my ad cost on Meta was refining my audience segmentation. Instead of broad targeting, I created multiple custom audiences based on detailed user behaviour and engagement data. I used Meta Pixel to track specific actions on my website, then built lookalike audiences from those who completed valuable actions like purchases or sign-ups. This helped ensure my ads reached users more likely to convert, not just click. I also tested different ad creatives for each segment to improve relevance and engagement. Over time, I used A/B testing to eliminate underperforming ads and focus budget on the top performers. This approach steadily lowered my cost per acquisition while maintaining conversion rates. I regularly reviewed performance metrics and adjusted placements and bidding strategies to keep costs in check. By staying focused on quality and relevance, I achieved better returns without needing to increase ad spend.

In affiliate marketing, we effectively reduced ad costs on Meta and Google Ads by implementing advanced audience segmentation and dynamic creative optimization. By segmenting our audience based on demographics, interests, behaviors, and past purchases, we tailored our marketing messages for better engagement. This targeted approach led to improved conversion rates and lower advertising costs, maximizing overall campaign efficiency.

One strategy that really helped us reduce ad costs on Meta for Olivia Croft was tightening our audience targeting using first-party data - specifically, creating high-intent custom audiences from people who had already engaged with our brand (like email subscribers, website visitors who viewed product pages, or those who abandoned carts). Instead of broad cold targeting, we focused on these warm segments and layered in lookalike audiences based on our best customers. That shift dramatically improved our click-through and conversion rates, which in turn lowered our cost per result. We also simplified our creative: instead of polished brand ads, we tested more natural, story-driven video content - often shot on a phone. It felt more native to the platform and performed better. The key was relevance over reach. By focusing on people who already showed interest and speaking directly to them, we saw our Meta ROAS climb and our ad spend stretch further.

One strategy that helped reduce ad costs was focusing on optimizing my bidding strategy based on campaign stages. In the awareness phase, I allocated more budget to Meta Ads, where reach and impressions were more affordable, and the audience was broad. Once we moved to the conversion stage, I shifted more budget toward Google Ads, targeting high-intent users who were actively searching for solutions. By separating the stages like this, I avoided wasting money on broad targeting during the conversion phase, while maximizing cost-efficiency by capturing high-intent leads. This method helped us lower the cost per acquisition (CPA) by 20%, as the ads were more aligned with the user's journey. It's a simple shift, but it ensures each dollar spent is more impactful.

One strategy that significantly helped us reduce ad costs on Meta was shifting from broad targeting to intent-driven content paired with lookalike audiences built on high-quality conversion events. Early on, we were casting a wide net—targeting interests, behaviors, and demographics based on assumptions. The CPMs were high, and while traffic came in, conversions weren't where we needed them to be. So we flipped the model. Instead of paying to interrupt people, we focused on creating highly relevant, native-feeling content—short-form video testimonials, problem-solution reels, and value-first carousels that matched the experience users expected on Meta platforms. Then we fed Meta's algorithm with stronger signals. We built custom audiences from people who completed our most meaningful events—not just site visitors, but those who stayed on-page for over 45 seconds, viewed pricing, or initiated checkouts. From those, we created lookalikes that were far more aligned with our actual buyers. The result? Our relevance score shot up, and our CPMs dropped by nearly 30%. More importantly, our cost-per-lead fell significantly because we weren't just buying impressions—we were reaching people who actually wanted what we offered. The big takeaway: instead of obsessing over squeezing costs at the ad set level, invest in content that speaks directly to your ideal user's intent, and let the platform optimize from clean, high-value data. That's where the real efficiency comes from.

I rebuild our creative around specific blog pain points. Instead of running broad "why pest control matters" ads, we took insights from our top-performing articles—like "how to tell if you have termite swarmers"—and built ad copy and visuals that mirrored those exact concerns. We'd even retarget visitors who had read the article with a follow-up offer. That tighter message match lowered our CPC and boosted conversion rates because the ad felt like a continuation of a conversation the user had already started. It worked because we didn't treat the ad as its own campaign—we treated it as a sequel to content. When the ad speaks directly to what someone's been Googling at 11 p.m., you don't need to shout to get their attention. You just need to show them you understand the problem and are ready with a fix. That alignment between the content funnel and the ad funnel is where we saw costs drop and ROI climb.

One way I managed to lower our Google Ads costs was by improving the quality score of our ads. The quality score is how Google rates how relevant and helpful your ads are to people. To boost this score, I created ad copy that was very specific to the keywords we were targeting. I also made sure our landing pages matched the ads and offered a good experience for visitors. By making our ads more relevant and user-friendly, Google rewarded us with lower costs per click and better ad placements. I kept an eye on the data to spot keywords that weren't performing well and either paused or adjusted them. This strategy helped us cut overall ad expenses while still maintaining or even increasing the number of conversions. Focusing on making our ads better rather than just bidding more made our campaigns more efficient and affordable over time.

One strategy that significantly reduced our ad costs on Meta was building custom audiences from engaged video viewers and retargeting them with offers. We first ran a video ad showcasing our resort's drone footage, amenities, and guest testimonials — not pushing a booking, just storytelling. Then we created a custom audience of users who watched at least 50% of that video. Those people were already familiar with our brand and much more likely to convert. When we retargeted that warmed-up audience with a specific booking offer (like a seasonal discount or long-term stay promo), our cost per lead dropped by over 60% compared to cold targeting. It also improved ROAS and reduced wasted spend on unqualified clicks.

Our most effective strategy for reducing Meta ad costs was to shift our budget from broad interest targeting to hyper-specific "Life Event" targeting. Previously, we were competing in expensive auctions, targeting general interests like "Luxury Goods" or "Engagement Rings." The cost per click was high and the conversion rates were inconsistent. The change was simple: we now focus the majority of our budget on ad sets targeting users with an immediate reason to buy. Our most profitable campaigns are laser-focused on Meta audiences like "Anniversary within 30 days," "Friends of people with an upcoming birthday," and for our engagement pieces, users whose status recently changed to "Newly engaged." This works because we stopped targeting people who simply like jewelry and started targeting people who have an urgent, emotionally-driven need for it. Our ad relevance scores skyrocketed, which dramatically lowered our CPM and CPC. We're no longer wasting money trying to create demand; we're capturing it at the perfect moment.