Fix Inefficient Audience Targeting with Gemini-Powered Ad Optimization
Most marketing teams still target audiences with rough segments and intuition, wasting budget on people who will never convert. This guide shows how to use Gemini with your Google marketing data to sharpen audience targeting, cut wasted spend, and systematically improve ROAS. You’ll get both strategic guidance and concrete workflows you can apply immediately.
Inhalt
The Challenge: Inefficient Audience Targeting
Marketing teams are under pressure to deliver growth, but many still aim campaigns at broad, imprecise audiences. You group users by high-level demographics or generic interests, then hope your message hits the right people. The result: budgets leak on impressions and clicks from users who were unlikely to convert from the start.
Traditional approaches to audience targeting rely heavily on manual analysis, platform presets, and marketer intuition. You pull segments in Google Ads, Meta, or your DSP, try to interpret search terms and audience insights, then update targeting rules by hand. This process is slow, biased by personal experience, and almost impossible to keep consistent across channels and markets. As user behavior fragments and privacy rules change, guesswork simply can’t keep up.
The cost of not solving this is significant. Wasted spend on mismatched audiences inflates customer acquisition costs and pushes ROAS down. Sales teams receive low-quality leads. Valuable micro-segments that could convert at high rates remain hidden in your data. Meanwhile, competitors that use AI to refine their audiences can outbid you efficiently, dominate the best inventory, and set new performance benchmarks your manual setup can’t match.
The good news: this problem is highly solvable with the right use of AI. By combining your existing Google marketing data with Gemini, you can move from intuition-based targeting to data-driven audience design at scale. At Reruption, we’ve helped organisations build AI-first workflows that turn raw signals into actionable segments and negative audiences. Below, we’ll walk through a practical, non-theoretical approach you can use to systematically improve your audience targeting and ad performance.
Need a sparring partner for this challenge?
Let's have a no-obligation chat and brainstorm together.
Innovators at these companies trust us:
Our Assessment
A strategic assessment of the challenge and high-level tips how to tackle it.
From Reruption’s hands-on work building AI-first marketing workflows, we see a clear pattern: companies already sit on rich Google Ads and Analytics data, but struggle to turn it into precise audiences. Gemini is particularly strong here because it natively understands Google’s ecosystem and can interpret search terms, queries, and funnel performance into concrete audience targeting strategies that marketers can actually use.
Anchor Gemini in a Clear Audience Strategy, Not Just "Better Keywords"
Many teams try AI as a quick fix for keyword lists or ad copy, but ignore the underlying audience strategy. Before plugging Gemini into your marketing workflows, define what “good” targeting means for your business: which customer profiles are truly profitable, which intents matter, and which segments you actively want to exclude. This strategic clarity gives Gemini a frame to generate meaningful audience segment frameworks instead of generic ideas.
Use your existing LTV, margin, and sales feedback to describe your best and worst-fit customers in business terms. Then instruct Gemini to translate those profiles into search behavior, content consumption patterns, and likely channel touchpoints. That way, the AI operates as a strategic partner in sharpening your targeting, not just as a keyword expansion tool.
Treat Gemini as an Analyst for Cross-Channel Audience Signals
Marketing organisations are often structured by channel: search, social, display, affiliate. Audience insights get trapped in silos, and each team reinvents the wheel. A smarter approach is to use Gemini as a cross-channel analyst that can read exported reports from multiple platforms and identify patterns you’d miss manually.
Strategically, this means setting up a recurring workflow where audience performance data from Google Ads, Analytics, and potentially CRM exports are summarised and interpreted by Gemini. The goal is not to replace your channel experts, but to give them a shared, AI-generated perspective on which intents, creative angles, and demographic traits consistently drive profitable responses across channels.
Prepare Your Team for AI-Augmented Decision-Making
Even the best AI insights are wasted if the marketing team lacks the mindset or processes to act on them. Before scaling Gemini-based targeting, align your marketing, data, and performance teams on how AI-driven audience recommendations will be used. Clarify roles: who validates new segments, who owns negative audience decisions, and who is allowed to adjust bids or budgets based on Gemini’s suggestions.
This organisational readiness matters more than another dashboard. Encourage a test-and-learn culture where Gemini’s recommendations are treated as hypotheses to be validated via controlled experiments, not as unquestionable truths. This keeps risk under control while building trust in AI-assisted targeting.
Design Guardrails to Mitigate Risk and Bias
AI-generated segments can sometimes drift into sensitive or non-compliant territory (e.g. proxies for protected characteristics, or segments that violate your brand’s guidelines). At a strategic level, you need clear guardrails for how Gemini is allowed to refine audiences. This includes defining forbidden targeting criteria, safe negative audiences, and compliance considerations with your legal and data protection teams.
Embed those constraints into your prompts and workflows from the start. For example, explicitly instruct Gemini to avoid using health, political, or other sensitive attributes when suggesting new audience ideas. This reduces risk and prevents uncomfortable surprises when ideas move from analysis to live campaigns.
Start with Focused Pilots in High-Impact Funnels
Trying to “AI everything” at once is a recipe for chaos. Instead, strategically select 1–2 high-impact funnels—such as branded and non-branded search for your top product line—and use Gemini-powered audience refinement there first. These funnels usually have enough volume to generate statistically valid results and enough business relevance to showcase impact.
Define clear success metrics (e.g. % reduction in cost per acquisition, improvement in conversion rate from new segments, or decrease in wasted spend from negative audiences) and a fixed test period. Once the pilot shows stable improvements, you can roll out the approach to additional campaigns, channels, and markets with more confidence.
Used deliberately, Gemini can transform inefficient audience targeting from a guessing game into a systematic, data-backed process that continuously improves ROAS. The key is to combine your business understanding with Gemini’s analytical power and to embed it into the way your team makes targeting decisions. At Reruption, we specialise in turning these concepts into working AI tools and workflows inside your organisation, not just slideware—if you want to explore a focused proof of concept or a production-ready setup, our team is ready to help you design and implement it.
Need help implementing these ideas?
Feel free to reach out to us with no obligation.
Real-World Case Studies
From EdTech to Manufacturing: Learn how companies successfully use Gemini.
Best Practices
Successful implementations follow proven patterns. Have a look at our tactical advice to get started.
Use Gemini to Mine Search Term Reports into Actionable Audience Intents
Start by exporting your Google Ads search term reports for the last 30–90 days, including impressions, clicks, conversions, and cost. Combine this with performance columns so Gemini can see which terms drive value versus waste. Your goal is not just more keywords, but a richer map of user intent that informs which audiences to target or exclude.
Feed these exports into Gemini (chunked if necessary) and ask it to cluster queries into intent groups, then map them to audience characteristics and potential segment names. Include business context: products, pricing, and your definition of a qualified lead or high-value customer. This allows Gemini to distinguish between research intent, price shoppers, and high-intent buyers.
Example prompt for Gemini:
You are a performance marketing analyst.
You receive a Google Ads search term report with columns:
- search_term
- impressions
- clicks
- conversions
- cost
- conversion_value
Tasks:
1. Cluster search_term values into intent groups.
2. For each intent group, describe:
- Typical user problem or need
- Likely stage in the funnel (awareness, consideration, purchase)
- Whether this group is likely high, medium, or low value, based on metrics.
3. Suggest audience segment ideas and negative audience ideas based on these groups.
4. Output in a concise table-like structure I can translate into new campaigns.
Expected outcome: a set of 8–20 intent-based audience groups and a short list of negative intents you can use to refine your targeting and exclusions.
Generate Positive and Negative Audience Frameworks from CRM and Funnel Data
Export anonymised CRM or conversion data from Google Analytics/GA4 (e.g. medium, campaign, landing page, basic demographics if available, and outcome such as LTV band or qualification status). The goal is to show Gemini which combinations of attributes tend to produce high-value versus low-value outcomes.
Ask Gemini to describe patterns in the data and to propose a framework of positive audiences (who you want more of) and negative audiences (who you want fewer impressions from). Include clear instructions about privacy and compliance so Gemini avoids suggesting sensitive attributes.
Example prompt for Gemini:
You are helping refine advertising audiences.
Here is sample data of past leads and customers with columns like:
- source / medium
- campaign
- device category
- country
- basic demographic buckets (if available)
- final_status (e.g. Won, Lost, Unqualified)
- LTV_band (e.g. <100, 100-500, >500)
1. Identify patterns that distinguish high LTV or Won customers from Unqualified/Low LTV.
2. Propose 5–10 positive audience segment definitions using only non-sensitive attributes.
3. Propose 5–10 negative audience or exclusion ideas to reduce wasted spend.
4. For each segment, explain why it should perform better or worse.
Expected outcome: a prioritised list of concrete audience rules and exclusion ideas you can translate into Google Ads audiences or custom segments in GA4.
Ask Gemini to Draft Audience-Specific Creatives and Message Variants
Once you have intent-based segments, use Gemini to generate creative variants aligned to each audience. Export your top-performing headlines, descriptions, and landing page copy from Google Ads and your website. Share these with Gemini as examples of brand voice and what has worked historically.
Then ask Gemini to produce 3–5 ad copy variants per audience segment that address the specific problem, language, and objections of that group. Include your brand and legal guidelines in the prompt so outputs are usable with minimal edits.
Example prompt for Gemini:
You are a performance copywriter for [Brand].
Here are examples of high-performing search ads and our brand guidelines: <paste>.
Here is an audience description:
"SMB owners searching for 'fast implementation marketing software' who value speed over price."
Tasks:
1. Write 5 Google search ad headlines (max 30 chars) and 4 descriptions (max 90 chars)
tailored to this audience.
2. Emphasise implementation speed and ease, while staying within our brand voice.
3. Avoid mentioning discounts or pricing.
Expected outcome: a library of audience-tailored creatives you can plug into responsive search ads or A/B tests, reducing manual copywriting time and improving relevance.
Build a Recurring Gemini-Based Targeting Review Ritual
To keep your targeting sharp, establish a weekly or bi-weekly ritual where Gemini reviews updated performance data. Export fresh campaign and audience performance from Google Ads/GA4, then use a standard prompt to have Gemini summarise what’s working, what’s wasting spend, and which segments should be scaled or cut.
Document this as a repeatable process: where data is pulled from, how it’s prepped, which prompts are used, and how decisions are logged. Over time, you can semi-automate this with scripts or simple internal tools that feed data into Gemini and present recommendations in a structured format for your team to approve.
Example prompt for Gemini:
You are my weekly performance marketing analyst.
I will paste updated performance exports for:
- Campaign level
- Audience/segment level (if available)
- Search term level
Tasks:
1. Highlight 5–10 audiences or queries that are clearly underperforming.
2. Suggest specific negative audience or keyword exclusions to reduce wasted spend.
3. Highlight 5–10 high-performing patterns and recommend how to scale them
(e.g. new segments, bid adjustments, new campaigns).
4. Summarise in a short, actionable report with priorities A/B/C.
Expected outcome: a consistent cadence of AI-assisted targeting improvements, with clear decisions each cycle rather than ad-hoc, reactive tweaks.
Use Gemini to Translate Business Strategy into Campaign Structures
When marketing receives a new strategic directive—entering a new market segment, launching a product, or targeting a specific industry—Gemini can help bridge the gap between abstract strategy and concrete campaign structures. Provide Gemini with your strategic brief, ICP descriptions, and historical performance insights, then ask it to propose campaign, ad group, and audience structures that reflect the strategy.
This is especially useful for teams that need to roll out consistent structures across markets or brands. Use Gemini’s output as a blueprint, then refine with your channel experts before implementation.
Example prompt for Gemini:
You are a senior performance marketing strategist.
Here is our new go-to-market strategy and ICP description: <paste>.
Here is a summary of our past campaign structures and what has worked: <paste>.
Design a Google Ads account plan that includes:
1. Recommended campaign structure (search, Performance Max, etc.).
2. Suggested audience segments and exclusions per campaign.
3. Example ad messaging angles for each audience.
4. Notes on risks and what to monitor in the first 4 weeks.
Expected outcome: faster, more consistent translation of strategy into execution, with better upfront targeting assumptions and fewer rounds of trial-and-error.
Track Impact with Clear KPIs and Reasonable Expectations
To prove value and avoid overpromising, define clear before/after metrics for your Gemini-driven targeting improvements. Focus on KPIs tied directly to audience quality, such as cost per qualified lead, conversion rate by audience, wasted spend percentage (spend without conversions), and ROAS per segment.
In many cases, teams can realistically target 10–25% reduction in wasted spend on low-intent or misaligned audiences within 8–12 weeks, alongside incremental gains in conversion rate for refined segments. The exact numbers will depend on your baseline, but the key is to measure at the segment level, not just at the overall account level, so you can see where Gemini has made a real difference.
Need implementation expertise now?
Let's talk about your ideas!
Frequently Asked Questions
Gemini can analyse your existing Google Ads, Analytics, and CRM exports to uncover patterns that are hard to see manually. It clusters search terms and performance data into intent-based groups, proposes positive and negative audience segments, and generates audience-specific creative ideas.
Instead of guessing which users to target, you can use Gemini’s analysis to focus spend on high-intent, high-value segments while systematically excluding low-quality traffic. Over time, this shifts your campaigns from broad, inefficient targeting towards precise segments that convert at a higher rate.
You don’t need a full data science team to benefit from Gemini, but you do need basic performance marketing and data-handling skills. Typically, a performance marketer or marketing operations person can export Google Ads/GA4 reports, anonymise data if needed, and work with Gemini via prompts.
For more advanced setups—like automating recurring analyses or integrating Gemini into internal tools—you’ll benefit from light engineering support (e.g. for scripting, APIs, or dashboards). Reruption often bridges this gap by pairing marketing teams with our engineers so the workflows become sustainable instead of one-off experiments.
For most organisations, you can see early impact on audience quality and wasted spend within 4–8 weeks. In the first 1–2 weeks, you’ll focus on setting up data exports, running initial analyses in Gemini, and implementing new segments and negative audiences in your campaigns.
The following weeks are about collecting enough data to validate the changes and iterating based on performance. Sustainable improvements—like a 10–25% reduction in wasted spend or a noticeable lift in conversion rate for key segments—typically become visible after one to two optimisation cycles.
The direct usage cost of Gemini for analysis and content generation is typically minor compared to your media budget. The main investment is internal time (marketing, ops, potentially engineering) and any support from external partners like Reruption.
From an ROI perspective, the benchmark is your current level of inefficiency: if even 10–15% of your spend goes to low-intent or misaligned audiences, reducing that waste with Gemini pays back quickly. Additional upside comes from better-performing segments and creatives, which can lift ROAS and lower cost per acquisition without increasing budget.
Reruption works as a Co-Preneur inside your organisation: we don’t just recommend tools, we build and ship working AI workflows with you. For Gemini-based audience optimization, we can start with our AI PoC offering (9,900€) to prove technical feasibility and demonstrate impact on a concrete funnel—using your real Google Ads, Analytics, and CRM data.
From there, our team helps you design prompts, data pipelines, and simple internal tools so marketers can use Gemini reliably without becoming prompt engineers. We embed with your performance team, challenge assumptions, and move fast—from first prototype to a production-ready audience optimization workflow that fits your compliance and reporting standards.
Contact Us!
Contact Directly
Philipp M. W. Hoffmann
Founder & Partner
Address
Reruption GmbH
Falkertstraße 2
70176 Stuttgart
Contact
Phone