TL;DR - Track fewer prompts without sacrificing AI search coverage. - Identify which prompts deliver unique value and cut the ones that don’t to reduce cost, noise, and redundancy. - Customize your strategy with flexible configurations and see the impact with data-backed visualizations.
We built a feature that might shrink your bill—and that’s the point. Most AI search platforms (including us) price by prompt, which can nudge teams toward over-tracking. More prompts don’t always mean better insight; they often mean overlapping results, higher costs, and noisier signals. Topic Prompt Optimizations is designed to right-size your monitoring so every prompt pulls its weight.
With Topic Prompt Optimizations, Scrunch helps you: - Identify which prompts contribute unique value and which are redundant. - Develop the optimal set of prompts to monitor for each key topic. - Tune your strategy to your KPIs and risk tolerance—with transparent, data-backed recommendations.
1) Open Topic Prompt Optimizations - Go to the Insights tab in Scrunch and select Topic Prompt Optimizations. Choose a topic (we surface options from your AI Context) and the AI platforms to analyze. By default, Scrunch evaluates the past 14 days across all active models.
2) Run the optimization - Click Run optimization. Scrunch analyzes your prompts for that topic and returns: - The full list of tracked prompts mapped to the topic - Which prompts to keep vs. cut - Anticipated impact on coverage, resilience, brand presence, answer position, and sentiment
3) Review the rationale - Recommendations balance two core signals: - Coverage: the percentage of unique URLs cited by at least one prompt - Resilience: the percentage of URLs cited by two or more prompts - If new prompts introduce new URLs, you’re expanding visibility. If they return the same URLs, you’re paying for overlap.
4) Act with confidence - Archive suggested prompts directly from results. Drill into any prompt for personas, tags, and funnel-stage context. Export a CSV with: - Keep vs. cut recommendations - Closest replacement prompts for any removals - The configuration used to generate your results - If your setup is already efficient, you’ll see “Pruning not recommended.” That’s a good outcome—no changes needed.
Under the hood, recommendations are generated via a Pareto frontier: the set of optimal prompt combinations where you can’t improve coverage without hurting resilience (and vice versa).
The coverage floor is set to 95% by default. Below that threshold, we’ve observed that core metrics (brand presence rate, citation share, sentiment, etc.) tend to fluctuate meaningfully.
Full configurability
Open Advanced Configuration to adjust constraints, change the coverage floor, or apply different pruning strategies. Click Apply changes to update results instantly.
Visual proof
Start with more prompts than you think you need. More initial data makes optimization more accurate, and trimming is easy.
Let data accrue
Run prompts for at least two weeks before pruning. You need enough signal to separate high-value prompts from redundant ones.
Watch the coverage curve
A flattening coverage curve means new prompts are no longer discovering new URLs—strong signal it’s time to prune. Avoid aggressive pruning if every prompt still adds unique URLs.
Reallocate budget to blind spots
If you’re evaluating for an enterprise: free trials are limited to a single brand and don’t include certain Enterprise features (SSO, enterprise data API, etc.). If you need a broader evaluation, book a demo with our team.
Ready to right-size your monitoring and boost ROI? Request access to Topic Prompt Optimizations via support or your CSM, start your 7-day free trial, or book a demo to see it in action.