How to Improve Ad Relevance to Lower Costs

A paid media report lands in the inbox. Click-through rates look fine, conversions are decent, yet costs keep creeping up and the feeling lingers that half the budget is being wasted on people who never should have seen those ads in the first place. That uneasy gap between spend and impact almost always comes down to one thing: relevance.

According to Bain & Company, 40% of consumers say the ads they see are irrelevant to themBain & Company report on ad relevance. That is not just an engagement problem. It is a cost problem. Every irrelevant impression chips away at budgets, drags down quality signals in the ad auction, and makes it more expensive to reach people who actually might buy.

The good news: ad platforms are built to reward relevance. The more useful ads are to a specific person in a specific moment, the more often those ads win auctions, the better they perform, and the less each click or conversion tends to cost over time. That makes relevance one of the fastest levers for lowering costs without simply slashing budgets or squeezing bids until performance breaks.

This article walks through practical ways to make ads more relevant, how that relevance translates directly into lower costs, and how to use AI, data, and smart bidding to keep improving over time. It also lifts the curtain on how we at North Country Consulting approach ad relevance so clients stop paying for noise and start buying meaningful attention instead.

Why Irrelevant Ads Are Burning Through Your Budget

Irrelevant ads are not just mildly annoying to audiences; they are expensive for advertisers. Every time an ad is shown to someone who does not care about the message or the offer, the campaign accrues hidden costs in the form of lower engagement rates, weaker conversion signals, and deteriorating auction performance. These negative signals make platforms less confident that showing your ads is a good user experience.

When 40% of people say the ads they see are not relevant to themBain & Company research on consumer perceptions, that frustration shows up in behavior: less engagement, more ad blindness, and weaker downstream signals for the algorithms that decide which ads win auctions. Platforms care deeply about user experience. If an account consistently serves creatives that people scroll past or bounce from, the system gradually steers impressions and favorable pricing toward competing advertisers whose ads perform better with the same users.

The result is a vicious cycle. Weak relevance leads to weak engagement streams into the auction models; the auction models respond by giving those ads fewer chances and worse pricing; costs rise, performance worsens, and teams feel pressure to “boost” results by raising bids or budgets. Breaking that cycle requires treating relevance as a core performance lever, not a soft branding nice-to-have.

How Relevance Lowers Your Costs Inside the Auction

Every major ad platform uses some version of the same logic: estimate how likely a user is to engage with an ad, factor in the bid, and then decide which advertiser wins the impression and at what price. Relevance is the backbone of those estimates. When an ad reliably earns clicks, video views, or conversions from a particular type of user, the system learns that it is a strong match for similar users in the future.

Higher expected engagement makes platforms more willing to show those ads at lower bids. The system is trying to maximize total value: a slightly lower bid from an advertiser with highly engaging ads can beat a higher bid from one with weak engagement, because the platform expects better user outcomes and long-term revenue from the stronger performer. In effect, relevance acts like an invisible discount.

This is why accounts with sharp targeting, tight message–audience fit, and consistent creative quality often report lower costs per click or per conversion even when their nominal bids do not look aggressive. The auction is quietly doing them a favor. Raising relevance is not just a tactic for “better ads”; it is a way of buying cheaper traffic from the same inventory everyone else is fighting over.

Use Personalization to Make Ads Feel Obviously Meant for Each User

Relevance improves when ads stop talking to “everyone” and start talking to specific people with specific motivations. That is where personalization comes in. Instead of one generic message, high-performing accounts tailor headlines, imagery, and offers to distinct segments based on intent, behavior, and context.

Studies show that personalized ads can outperform generic versions by 50% in engagement ratesMoldStud analysis of personalized vs. generic ads. That kind of lift does not just pad vanity metrics. Higher engagement sends strong positive signals back into the auction, which over time can reduce effective costs per click and per acquisition. The system learns, “When people like this see ads like that, good things happen,” and starts rewarding that pairing.

Aaron Cheris, a partner in Bain & Company’s Retail practice, puts it succinctly: personalization is enabling retailers to turn their intentions into real-time actions. When a brand knows what a user is browsing, abandoning, or buying, it can trigger ads that respond to that behavior instead of pushing the same fixed creative to everyone in the audience. That shift from static messaging to dynamic, behavior-led communication raises the odds that each impression feels timely and useful instead of random or intrusive.

Practical Ways to Personalize Without Getting Creepy

Effective personalization does not require showing people every detail known about them. The goal is to make the ad obviously relevant while still feeling respectful and brand-safe. That balance starts with segmenting based on intent signals-search queries, content consumed, past purchases, or product categories browsed-rather than overly narrow demographic guesses.

For example, new visitors who searched for a specific product benefit from ads emphasizing availability, benefits, and social proof for that exact item or category. Warm audiences who abandoned a cart may respond better to reminders, urgency, or value props that address common hesitations. Long-term customers might see cross-sell or loyalty-focused messaging. Each of these flows from a different point in the journey, which means the same budget can work harder by speaking to where people actually are.

From a cost standpoint, this segmentation means ad spend is weighted toward users whose recent behavior suggests higher conversion likelihood. Platforms learn to associate stronger outcomes with particular audience signals, so bids can stretch further instead of being wasted on broad, uninterested traffic.

Let AI and Programmatic Do the Heavy Lifting (Without Losing Control)

Ad auctions today are dominated by AI-powered programmatic systems. Industry reports estimate that AI-driven programmatic advertising accounts for nearly 85% of digital display ad spendWiFi Talents report on AI in digital advertising. For advertisers, that is both a challenge and an opportunity. Competing effectively means learning how to collaborate with these systems, not fight them.

On the opportunity side, AI is exceptionally good at spotting subtle patterns in who engages, who converts, and which combinations of creative and placement work best. Retailers experimenting with AI-powered targeted campaigns have reported 10% to 25% increases in return on ad spend, even against rising media costs, by letting models adapt bids and creative combinations in real time instead of relying entirely on static, human-set strategies.

AI also makes it easier to test relevance at scale. Rather than manually rotating a few ad variations, marketers can feed platforms a broader set of headlines, descriptions, and images, then allow algorithms to learn which pairings resonate with each micro-audience. That approach does not remove human strategy-it amplifies it. Strategy decides what messages and offers to test; AI decides which ones to serve where, and when.

Where AI Helps Most With Lowering Costs

The biggest cost savings from AI typically show up in three areas: audience discovery, bid optimization, and creative matching. Audience discovery means surfacing lookalike pockets of users whose behavior mirrors that of converters, then testing into those pockets without vast amounts of manual segmentation. Bid optimization means letting the system adjust bids according to predicted value of each impression or click, which smooths out overbidding on weak traffic and underbidding on strong traffic.

Creative matching is where relevance and cost efficiencies often compound. When the system can dynamically pair a specific creative angle with a specific user profile or intent signal, it can squeeze more engagement out of the same impressions. Higher engagement then feeds back as a positive relevancy signal, nudging effective prices down compared with less relevant competitors chasing the same users.

Bid and Budget Smarter: Pay Less for the Same Attention

Even with strong relevance and smart AI assistance, how bids are structured affects how much is actually paid for each impression or click. One of the most interesting developments here is bid shading in programmatic auctions. Bid shading techniques aim to reduce the price paid for an impression compared with what a straightforward second-price auction might suggest.

Research on bid shading has found that these methods can reduce price per impression to about 55% of the unshaded cost on averageacademic study on bid shading and impression pricing. That is a powerful reminder that there is often room to pay less for the same inventory if bidding strategies are tuned correctly. Platforms and demand-side partners increasingly bake these techniques into their algorithms, seeking that sweet spot between winning enough auctions and overpaying.

For advertisers, the takeaway is not to obsess over every penny in a bid, but to combine good relevance with a bidding approach that reflects true business value. Campaigns should be structured around the actual outcomes that matter: leads, purchases, qualified calls, or downstream revenue, not just cheap clicks. When the system learns which auctions lead to those outcomes, it can shade bids down on low-value impressions and stay competitive only where it really counts.

Aligning Budget With High-Relevance Moments

Budget allocation should follow the same logic. Instead of spreading spend thinly across all hours, devices, and placements, direct more budget toward contexts where relevance is naturally higher. That might mean heavier investment in certain keywords, top-performing audiences, or remarketing pools where intent is strong and messaging can be laser-focused.

By pruning low-relevance segments-those with weak engagement and poor conversion efficiency-accounts free up budget that can be reinvested into high-performing combinations. The practical effect is paying less per meaningful interaction, because money is no longer wasted on impressions that never had a realistic chance of converting in the first place.

Measure and Optimize Relevance Like a Pro

Relevance can feel slippery as a concept, but it becomes manageable once it is translated into concrete metrics and workflows. The key is to separate vanity metrics from the signals that platforms and businesses actually care about. Click-through rates, engagement rates, and quality scores are useful leading indicators, but only when connected to cost per acquisition, return on ad spend, and downstream customer value.

Retailers that have invested in AI-powered targeted campaigns have seen return on ad spend improve by 10% to 25%, showing that more precise targeting and messaging can deliver real financial results rather than just prettier dashboardsBain & Company findings on AI-powered campaigns. That kind of lift rarely comes from tinkering with bids alone. It comes from ongoing measurement of which audience–creative–offer combinations generate the best outcomes at the best prices, then doubling down on those while retiring weaker variants.

Many businesses also report a meaningful increase in actionable insights when they use AI-generated reporting and analysis instead of manual spreadsheet work. When data is synthesized quickly and patterns are surfaced clearly, it is easier to spot where relevance is spiking or fading and adjust campaigns accordingly. Less time wrangling data means more time refining strategy and creative.

Metrics That Actually Reflect Relevance

Certain metrics deserve special attention when the goal is to improve relevance and lower costs. Engagement rates help show whether messages resonate with the right people, while conversion rates reveal whether that resonance carries through to outcomes. Segment-level performance-by audience, keyword theme, creative angle, or landing page-highlights where message–market fit is strongest.

From there, analysts can calculate cost per engaged user, cost per qualified lead, or cost per sale for each segment. Segments with both high relevance and efficient costs get more budget and creative support; underperforming segments are either fixed with better targeting and messaging or phased out. Over time, this process shifts the entire spend portfolio toward the pockets of inventory where relevance is naturally highest and costs per desired action are lowest.

How We at North Country Consulting Improve Relevance and Lower Costs

At North Country Consulting, we look at every paid media account through the lens of relevance first. We do not start by asking how to squeeze bids down a few cents; we start by asking how to make each impression more meaningful to the person seeing it. That shift in perspective consistently leads to lower costs per conversion and healthier return on ad spend for our clients.

Our process begins with a deep dive into audience behavior and search or browsing intent. We map out who the high-value segments really are, what they care about, and where existing campaigns are missing the mark. Then we rebuild or refine campaign structures so that each major audience group sees messaging tailored to its needs and stage in the journey, instead of lumping everyone into a single “catch-all” strategy.

Creative and landing page alignment is the next pillar. We work closely with clients to ensure that ad copy, imagery, and on-site experiences speak the same language. When someone clicks because a message promises a particular outcome or benefit, the landing page needs to reinforce that promise immediately. That kind of message match strengthens trust, improves conversion rates, and signals to ad platforms that our clients’ ads are delivering a satisfying experience-helping win better auction placements at lower effective costs.

Combining Human Strategy With Smart Automation

We also embrace automation where it adds value. We set clear performance goals, define guardrails that reflect real business economics, and then let platform algorithms optimize within those bounds. Smart bidding, dynamic creative, and programmatic audience expansion are all tools we use-carefully-to find more high-relevance impressions at sustainable prices.

Most importantly, we do not treat campaigns as “set and forget” machines. We run structured tests, monitor performance across segments, and make ongoing adjustments to targets, creative assets, and budgets. When a particular combination of audience and message proves especially effective, we scale it. When something underperforms, we dig in to understand whether the problem is targeting, creative, or the offer itself. That constant tuning keeps relevance trending upward, which in turn helps costs trend downward.

If you want to stop paying for impressions that do not move the needle and build a paid media engine that gets more results out of every dollar, this is exactly the kind of work we love to do at North Country Consulting.

A 30-Day Action Plan to Raise Relevance and Cut Waste

Improving ad relevance does not have to be a multi-year transformation. Meaningful progress can be made in a single month with a focused plan. The key is to prioritize actions that quickly align targeting, creative, and offers with the audiences most likely to convert, while removing obvious sources of waste.

The following 30-day roadmap is designed for practical execution. It assumes existing campaigns are running and aims to make them sharper, not to rebuild everything from scratch. Each week has a clear focus, with tasks that directly support better relevance and lower effective costs.

Week 1: Audit and Identify the Biggest Relevance Gaps

Start by reviewing current campaigns at a segment level. Look at performance broken down by audience, keyword themes, placement types, and devices. The goal is to spot where engagement and conversion rates are weakest relative to spend and to identify segments where results are surprisingly strong despite modest investment.

From that analysis, create a shortlist of clear misalignments: ads that promise one thing while landing pages focus on another, audiences that are too broad for the budget, or creatives that speak generically when user intent is specific. These are the first areas where improvements in relevance are most likely to yield immediate cost benefits.

Week 2: Restructure Campaigns Around Real Intent and Segments

Next, refine or rebuild core campaign and ad group structures so they more accurately reflect user intent and behavioral segments. Group keywords or audiences by themes that match different problems, needs, or stages in the buying journey rather than by internal product categories alone.

Then adjust targeting settings to narrow in on the most promising segments identified in Week 1. That might mean excluding low-value demographics, trimming out irrelevant placements, or refocusing budgets on search terms and audiences that show strong commercial intent. This structural work lays the foundation for more personalized and relevant messaging in the next phases.

Week 3: Refresh Creative and Landing Pages for Stronger Message Match

With cleaner structures in place, develop new ad variations that speak directly to each segment’s needs. Write headlines that echo the language people actually use in queries or on-page behavior. Highlight benefits that matter most for each group, supported by social proof or proof points where appropriate.

On the landing page side, make sure the first screen reinforces the promises made in the ads. If an ad emphasizes fast shipping, pricing, or a specific use case, the landing page should acknowledge that right away. Even small changes-like adjusting hero copy, adding relevant testimonials, or clarifying key benefits-can significantly improve perceived relevance and conversion rates.

Week 4: Layer in Smart Bidding, Test, and Reallocate Budget

In the final week, turn attention to optimization and scaling. Where there is enough conversion data, consider enabling automated bidding strategies that align with business goals, such as target cost per acquisition or target return on ad spend. These strategies can help the system adjust bids in real time based on predicted value of each impression or click.

Run controlled tests of new creatives and bids, watching how engagement and conversion metrics shift across segments. As clearer winners emerge, reallocate budget away from underperforming segments and toward those where relevance is highest and costs per desired action are lowest. By the end of 30 days, the account should be leaning harder into its strengths and wasting less on traffic unlikely to convert.

The Bottom Line: Relevance Is the New Discount

Competition and automation are only increasing in digital advertising. The global AI advertising market alone is projected to reach $27.4 billion by 2028, growing at a compound annual rate above 30%WiFi Talents forecast for AI advertising growth. As more spend flows through AI-driven auctions, platforms will keep favoring ads that deliver strong user experiences over those that simply bid higher.

For advertisers, that reality turns relevance into a structural advantage. Brands that invest in understanding their audiences, tailoring messages, aligning creative with real intent, and letting AI optimize within well-defined parameters will keep finding ways to pay less per meaningful interaction than competitors who treat paid media as a blunt instrument. Relevance becomes a permanent discount in the auction, compounding over time.

For teams tired of paying premium prices for lukewarm results, the path forward is clear: stop trying to outbid everyone and focus on out-relevancing them instead. And if you want a partner that lives and breathes that philosophy, we at North Country Consulting are ready to help build campaigns that feel right to your customers and look great to your finance team.

Ready to transform your Google Ads performance and stop wasting budget on low-impact impressions? At North Country Consulting, our expertise is deeply rooted in creating highly relevant and cost-effective ad campaigns that resonate with your audience. With a founder who has an extensive background at Google and leading revenue teams at Stripe and Apollo.io, we bring unparalleled insights to your digital marketing and revops strategies. Book a free consultation with us today, and let's elevate your ad relevance to unlock the true potential of your advertising spend.