Turn Creative Chaos into Insight: Use Claude to Lift Ad ROAS
Marketing teams drown in dashboards but still can’t say which creative angles actually drive ROAS. This guide shows how to use Claude to turn raw ad reports into clear creative insights and faster test cycles, and how Reruption can help you implement it in a robust, compliant way.
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The Challenge: Weak Creative Performance Insight
Modern marketing teams run hundreds of ad variations across Meta, Google, TikTok, LinkedIn and more. Yet when performance drops, answering a simple question – which creative elements actually drive clicks, conversions, or ROAS? – becomes almost impossible. Data is scattered across platforms, naming conventions are inconsistent, and weekly performance reports rarely go deeper than “this campaign worked, this one didn’t.”
Traditional analysis methods rely on manual spreadsheet work, gut feeling in creative reviews, and one-off deep dives when something is on fire. Analysts manually tag creatives, export CSVs, build pivot tables, and try to isolate variables like headline, visual style, or call-to-action. By the time patterns emerge, the campaign is often over, budgets have shifted, and the opportunity to iterate quickly has been lost. The result is a constant lag between what happens in the market and how your creative strategy responds.
The business impact is substantial. Without clear creative performance insight, brands over-invest in underperforming angles, miss out on scaling winners early, and waste hours each week on low-value reporting. Cost per acquisition creeps up, experimentation slows down, and marketing teams struggle to justify spend in conversations with finance. Over time, this erodes competitive advantage: faster, more data-driven competitors simply learn quicker which creative stories convert and outbid you in the auction.
This challenge is real, but it is solvable. With the latest generation of AI models like Claude, it’s now possible to ingest messy ad exports and transform them into structured, nuanced insight about what truly drives ROAS. At Reruption, we’ve built AI-powered analysis and decision-support tools inside organizations facing similar complexity. The rest of this page walks through practical ways to use Claude to move from noisy dashboards to clear creative hypotheses – and how to set this up so it actually sticks in your marketing workflow.
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Our Assessment
A strategic assessment of the challenge and high-level tips how to tackle it.
From Reruption’s work building AI-first analytics and decision tools, we’ve seen that the real unlock is not "more data" but better questions and structure. Claude is particularly strong at long-form reasoning over messy inputs – exactly what you need to make sense of raw ad exports, creative briefs, and fragmented dashboards. Used well, Claude can become a creative insight copilot that helps your marketing team see patterns, form hypotheses, and prioritize testing, instead of drowning in spreadsheets.
Think in Creative Hypotheses, Not Just Metrics
Most marketing teams think in terms of surface metrics: CTR, CPC, conversion rate, ROAS. Those are crucial, but they don’t explain why a creative works. To get value from Claude for ad performance optimization, you need to frame the problem as a set of hypotheses: “Is urgency-based messaging outperforming aspirational messaging?” “Do product-centric visuals beat lifestyle shots on retargeting?” Claude is very good at ingesting data and narrative context, then suggesting nuanced hypotheses you can test.
Before you upload any data, write down the 3–5 questions you want Claude to answer about your creatives. Combine quantitative objectives (e.g. lower CPA) with qualitative angles (e.g. emotional tone, problem/solution framing, benefit hierarchy). This mindset shift turns Claude from a glorified reporting tool into a strategic creative insight partner your team can use in ongoing campaign planning.
Design a Minimal but Robust Data Structure
Claude handles unstructured text very well, but for systematic creative performance insight you still need a minimal structure: consistent naming for campaigns, ad sets, and asset variants; clear columns for spend, impressions, clicks, conversions, revenue. Without that, you’ll get interesting narratives but weak, repeatable insight. Reruption often starts projects by defining a pragmatic data schema that your team can actually maintain, instead of a theoretically perfect taxonomy that collapses after two weeks.
Strategically, this also means aligning marketing, analytics, and sometimes finance on what “good performance” means. If your BI team uses contribution margin while your marketers optimize for ROAS, Claude will surface conflicting signals. A shared metric layer – even if simple at first – lets you use Claude to prioritize creative directions in a way the whole organization can trust.
Prepare Your Team for an AI-Augmented Workflow
Introducing Claude into creative performance analysis is not just a tooling change; it’s a workflow and culture shift. Creative, performance marketing, and analytics teams need to understand where AI-driven insights fit into existing rituals like weekly performance calls, creative reviews, and sprint planning. If Claude’s recommendations live in a parallel universe, they’ll be ignored after the initial novelty wears off.
We recommend defining explicit touchpoints: for example, “Every Monday, Claude summarizes last week’s performance and proposes 3 new creative hypotheses,” or “Before new campaigns go live, Claude reviews the brief against past performance patterns.” This makes the AI visible and useful, rather than a side experiment only one analyst cares about.
Mitigate Risk with Guardrails and Human Oversight
Claude is powerful but not infallible. It can misinterpret spurious correlations or overfit to a limited sample of campaigns. Strategically, you need clear guardrails: Claude should suggest patterns and hypotheses, not autonomously switch off your top-performing campaigns or reallocate budgets without human review. Pair its qualitative pattern recognition with your existing quantitative checks in tools like Google Ads, Meta Ads Manager, or your BI stack.
At Reruption, we design workflows where Claude’s output feeds into a human decision step. For example, Claude might propose that “short benefit-led headlines with product imagery” outperform others. A performance marketer then validates this against native platform reports, sanity-checks the sample size, and turns the insight into a structured A/B test plan. This keeps risk low while still accelerating learning.
Start with a Focused Pilot Before Scaling Across Channels
It’s tempting to throw all your Meta, Google, TikTok, and programmatic data at Claude from day one. In practice, this leads to confusion and over-engineering. A better strategic path is to pick one channel and one core objective – e.g. Meta prospecting for new customer acquisition – and pilot Claude as your “creative insights analyst” there. Once the workflow is proven and your team trusts the output, expand step by step.
This pilot-first approach aligns with Reruption’s AI PoC philosophy: validate that AI-driven creative analysis delivers real lift (e.g. lower CPA, higher ROAS, faster creative iteration) in a contained environment. Then, invest in automation, integrations, and process changes to scale it. You de-risk the initiative while still moving faster than traditional consulting or BI projects.
Used with the right structure and mindset, Claude can transform weak creative performance insight into a repeatable advantage: clearer patterns, sharper hypotheses, and faster creative iteration that shows up in ROAS. Reruption combines this tool with deep engineering and workflow design experience to embed AI-driven creative analysis directly into your marketing routines, not just in a slide deck. If you want to explore a focused pilot or turn your existing exports into actionable insight, we’re happy to discuss how our AI PoC and Co-Preneur approach could fit your specific setup.
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Real-World Case Studies
From Payments to Energy: Learn how companies successfully use Claude.
Best Practices
Successful implementations follow proven patterns. Have a look at our tactical advice to get started.
Standardize Your Ad Export and Brief Format for Claude
Claude delivers the best insights when it sees consistent, well-labeled data. Before every analysis session, export your ad performance data (from Meta, Google, etc.) into a structured CSV or Excel and make sure key columns are present: campaign, ad set, ad name, creative text, image/video description or ALT text, spend, impressions, clicks, conversions, revenue/ROAS.
In parallel, align your creative briefs in a standard template (objective, target audience, main message, emotional tone, key benefits, offer). When you share both the export and the brief with Claude, it can connect the intent of the creative with its actual performance, producing deeper insights than metrics-only analysis.
Example prompt to Claude:
You are an AI marketing analyst helping us understand which ad creatives drive ROAS.
Inputs:
1) Ad performance export (CSV pasted below)
2) Creative brief template and a few real examples
Tasks:
- Identify performance patterns across headlines, body copy, visual descriptions, and CTAs.
- Highlight 3–5 creative angles that consistently outperform others.
- Highlight 3–5 angles that consistently underperform.
- Propose 5 concrete hypotheses we should test next week.
- Present results in a structured table with columns: Angle, Evidence, Channels, Suggested Next Test.Expected outcome: Claude produces an insight report that your performance marketer can quickly review and turn into a prioritized test plan, cutting manual analysis time by several hours per week.
Tag and Decompose Creatives into Testable Elements
To move beyond “this ad works” toward actionable creative insight, you need to break each ad into components: value proposition, emotional tone, offer type, format, CTA style, and visual concept. You can either do this manually or let Claude propose tags based on your raw ad text and descriptions.
Start by asking Claude to generate a tagging scheme and automatically assign tags to each ad row from your export. Then, in a second step, ask it to analyze performance by tag combination.
Example prompt to Claude:
You are a creative performance analyst.
1) Define a concise tagging scheme for our ads, including:
- Value proposition (e.g. price, quality, convenience, social proof)
- Emotional tone (e.g. urgent, aspirational, reassuring, playful)
- Offer type (e.g. discount, free trial, bundle, new launch)
- Visual concept (based on descriptions in the data)
2) Apply tags to each ad row in the dataset below.
3) Then, analyze performance by tag and tag combination, focusing on ROAS and CPA.
4) Output two tables:
- Table 1: Tags ranked by performance
- Table 2: Best-performing tag combinations and their evidence.Expected outcome: a clear view of which creative themes and combinations actually move your KPIs, enabling more focused ideation and scaling decisions.
Use Claude to Draft Data-Backed Creative Briefs
Once you know which angles perform, close the loop by letting Claude assist with new briefs. Instead of starting from a blank page, you can have Claude produce a data-backed brief that summarizes winning themes, audience insights, and example messages tailored to each channel.
Feed Claude your past performance analysis and ask it to generate a concise brief for the next sprint, aligned with your growth targets and budgets.
Example prompt to Claude:
You are a senior performance creative strategist.
Based on the analysis below (paste Claude's previous insight output), create a creative brief for our next campaign.
Brief should include:
- Objective and primary KPI
- Target audiences and key pain points
- 3–4 winning creative angles with supporting evidence
- Do's and don'ts for copy and visuals, based on past performance
- 5 concrete ad concepts per channel (Meta, Google Display, TikTok) with sample headlines and body copy.Expected outcome: your creative team receives a structured, insight-based brief that translates past performance into future concepts, reducing back-and-forth and time-to-first-draft.
Automate Weekly Creative Performance Summaries
Instead of manually compiling weekly decks, you can give Claude a recurring task: ingest the latest exports and generate a standardized insight summary for your team. This doesn’t require deep integration at first – even a simple workflow where an analyst exports CSVs and pastes them into Claude on Monday morning can dramatically speed up reporting.
Define a fixed summary format that matches how your leadership and creative teams like to consume insight.
Example prompt to Claude:
You are our weekly creative insights assistant.
Using the ad performance data from last week (pasted below):
- Summarize overall performance vs. the previous 4 weeks.
- Identify top 10 winning creatives and explain WHY they worked.
- Identify top 10 underperformers and likely reasons.
- Suggest 5 concrete optimization actions for this week.
- Produce an email-ready summary with bullet points for leadership
and a more detailed section for the performance/creative team.Expected outcome: consistent, high-quality weekly insights in 10–15 minutes instead of hours, freeing your senior marketers to focus on decisions, not deck-building.
Turn Insights into Structured Test Plans and Naming Conventions
Insight only matters if it changes what you test next. Use Claude to convert qualitative findings into a structured A/B testing roadmap and harmonized naming conventions that make future analysis easier. This creates a virtuous cycle: better naming → better data → better insights.
Ask Claude to propose a testing backlog prioritized by expected impact and ease of implementation, plus a naming scheme that encodes key creative variables, so next month’s exports are easier to analyze.
Example prompt to Claude:
You are an experimentation lead.
Given the creative insight report below, create:
1) A prioritized test plan for the next 4 weeks, including:
- Test name
- Hypothesis
- Variants to create
- Primary KPI and guardrail metrics
2) A simple, scalable naming convention for campaigns/ad sets/ads
that encodes: audience, offer, angle, format, and CTA.
3) A checklist for our team to follow when setting up each new test.Expected outcome: a clear roadmap for experimentation and a consistent naming convention that makes each future Claude analysis faster and more reliable.
Expected Outcomes and Realistic Benchmarks
When implemented as part of your workflow, Claude-powered creative insight typically aims at three realistic outcomes in the first 8–12 weeks: (1) 30–50% reduction in manual analysis and reporting time for performance marketers, (2) consistently faster creative iteration cycles (e.g. from monthly to bi-weekly or weekly), and (3) measurable improvements in ROAS or CPA on key campaigns driven by better scaling of winning angles and earlier pruning of weak ones. Exact numbers will depend on your spend levels, test volume, and how tightly you integrate Claude’s recommendations into decision-making, but the pattern is clear: more learning per euro spent.
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Frequently Asked Questions
Claude can ingest your raw ad exports, creative text, and even high-level briefs, then decompose each ad into themes and elements such as value proposition, emotional tone, offer type, and visual concept. It then cross-references these elements with performance metrics like CTR, CPA, and ROAS to surface patterns you would struggle to see manually.
Instead of just telling you which ads worked, Claude helps explain why they worked, proposing clear hypotheses like “social proof + reassurance tone performs best on retargeting” or “short, benefit-led headlines outperform feature lists on prospecting.” This lets your team focus new creative work and budget on the angles that empirically move the needle.
You don’t need a large data science team to benefit from Claude-based creative analysis. In most organizations, the core requirements are:
- A performance marketer or analyst who can export data from your ad platforms and understands your core KPIs.
- Someone who can maintain basic consistency in naming conventions and brief templates.
- Clear ownership of the workflow (e.g. “performance lead runs the weekly Claude analysis and shares insights”).
Claude handles the heavy lifting of reading raw tables, interpreting text, and suggesting patterns. Reruption can help you define the right prompts, data structure, and routines so your existing team can run this without hiring new specialists.
Time-to-impact depends on your spend level and test velocity, but many teams see qualitative improvements in clarity within the first 1–2 weeks: clearer weekly summaries, better hypotheses, and more focused briefs. Quantitative impact on ROAS and CPA usually appears over a few test cycles, typically in the 4–12 week range, as you start to scale proven angles and stop funding weak ones earlier.
The key is to treat Claude as part of your experimentation loop: analyze → hypothesize → test → analyze again. If your team is already running frequent creative tests, Claude can accelerate learning quickly. If your testing culture is still maturing, the first benefit will be structure and speed in how you prioritize what to test.
The direct cost of using Claude is relatively low compared to typical media budgets or agency retainers. The main investment is in setting up the right workflows, prompts, and data structure. ROI comes from three areas:
- Reduced analysis time: performance teams spend fewer hours in spreadsheets and reporting.
- Smarter budget allocation: faster identification and scaling of winning angles, and earlier pruning of losers.
- Higher creative hit rate: briefs and concepts are guided by actual performance patterns, not just intuition.
In practice, even a small percentage improvement in ROAS on your main channels often exceeds the implementation and usage cost of Claude by a wide margin. Reruption’s AI PoC approach is designed to validate this quickly in your real environment before you commit to broader rollout.
Reruption supports you end-to-end, from idea to working solution. With our AI PoC offering (9,900€), we first define and scope a concrete use case such as “weekly Claude-powered creative insight for Meta and Google campaigns,” then build a functioning prototype in days: data ingestion, prompt design, and example outputs tailored to your setup.
Beyond the PoC, our Co-Preneur approach means we embed with your marketing and analytics teams, operate inside your P&L, and help you ship real internal tools and workflows – not just slides. We bring the engineering depth to connect Claude into your existing tools where needed, design guardrails for security and compliance, and coach your team on running AI-augmented creative reviews and test planning. The goal is simple: a sustainable, AI-first way of learning which creatives actually drive ROAS in your organization.
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