AI Search Performance: How Should I Use My 2,500 AI Response Credits?

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You’ve just unlocked AI Search Performance ↗️ and have 2,500 AI Response Credits—your starting point for understanding your brand’s visibility in the new era of AI search. But with so many configuration options available, it can be challenging to know where to begin. This guide will walk you through three popular, thoughtful strategies to help you choose a configuration that aligns directly with your business goals.

Before selecting a strategy, it’s important to decide which AI engine to monitor. We find that most customers want to start by tracking ChatGPT (Auto). There are two key reasons for this:

Market Share: ChatGPT is the most widely used AI chat application, meaning its responses are what the largest segment of your audience is actually seeing.
Authenticity: The “Auto” mode is the default setting for most users. It dynamically switches between models to deliver the best response, giving you the most authentic view of the typical user experience.

While other engines can provide valuable insights, ChatGPT (Auto) offers the best all-around foundation for your initial tracking. If your primary goal, however, is to monitor the maximum number of prompts possible, you might consider more credit-efficient engines like Perplexity or Google AI Mode. We’ll cover that in our third strategy. Cadence is the second lever — but the goal is matching frequency to business need, not minimizing cost. Weekly is the recommended starting point for most topics because it produces the trend data you need to make decisions. Monthly is the right fit for broad strategic topics where a monthly pulse is genuinely sufficient. For a starter package of 2,500 credits, leaning toward Weekly + Monthly (and holding off on Daily) gives you meaningful signal across more topics without burning your budget in the first few weeks.

Your initial credits can be used for a short-term deep dive to prove value, a year-long baseline to monitor trends, or a broad-coverage model to maximize the number of prompts you track.

This approach is designed to be a “proof of concept” sprint. It’s the perfect strategy if your main goal is to gather a large, compelling dataset in a short period to build a business case for a larger investment in AI search tracking. 💡 Choose this strategy if you want to:

Analyze a wide range of your brand’s topics in a short sprint.
Showcase the depth of insights available in this report to your leadership.
Quickly determine which topics and prompts warrant long-term tracking.

🛠️ Configuration Example:

Goal: Track 5 of your core topics.
Prompts: Track 50 prompts per topic (250 prompts total).
AI Engine: ChatGPT (Auto) (1 credit per response).

🧮 The Calculation:

250 prompts x 1 credit = 250 credits per week.
2,500 total credits / 250 weekly credits = 10 weeks of tracking.

This setup provides a rich dataset across five key areas of your business in just over two months, delivering powerful insights you can act on quickly.

This strategy is for teams who want to make their credits last for the entire year while keeping a consistent pulse on their performance in the most popular AI engine. 💡 Choose this strategy if you want to:

Establish a consistent performance baseline for your most critical brand topic.
Track performance fluctuations and trends across a full 12 months.
Use your initial credits for long-term monitoring without needing a larger budget.

🛠️ Configuration Example:

Goal: Monitor 1 “crown jewel” topic for a full year (52 weeks).
AI Engine: ChatGPT (Auto) (1 credit per response).

🧮 The Calculation:

2,500 total credits / 52 weeks = ~48 credits available per week.
With ChatGPT (Auto) at 1 credit per prompt, you can consistently track approximately 48 prompts for your most important topic, every single week, for the entire year.

What if your primary goal is to track the absolute maximum number of prompts for a full year? For this, you’ll leverage the most credit-efficient AI engines. 💡 Choose this strategy if you:

Are less concerned with tracking ChatGPT specifically and more interested in broad coverage.
Want to monitor the widest possible range of audience questions.
Prioritize the quantity of data gathered over a full year.

🛠️ Configuration Example:

Goal: Maximize prompt tracking over 52 weeks with a budget of ~48 credits per week.
AI Engines: Perplexity (0.2 credits), Google AI Mode (0.01 credits) or Google AIO (0.01 credits).

🧮 The Calculation:

Using Perplexity: 48 weekly credits / 0.2 credits per prompt = 240 prompts per week.
Using Google AI Mode or Google AIO: 48 weekly credits / 0.01 credits per prompt = 4,800 prompts per week.

This strategy allows you to track a massive volume of prompts, offering incredible coverage if you want to cast the widest net possible with your initial credits.

This strategy mixes cadences to give you reliable weekly signal on your most important topics and broad monthly coverage everywhere else — making your starter credits go further without sacrificing the data quality that makes Weekly tracking valuable. 💡 Choose this strategy if you want to:

Monitor a handful of priority topics at full weekly resolution while maintaining coverage across a larger set of broader categories.

🛠️ Configuration Example:

Weekly: 5 strategic topics × 50 prompts × ChatGPT (Auto) = 250 credits/week
Monthly: 12 broad topics × 50 prompts × ChatGPT (Auto) = 600 credits/month ≈ 138 credits/week-equivalent

🧮 The Calculation:

~388 credits/week-equivalent. 2,500 ÷ 388 ≈ 6.4 weeks of headroom on initial credits — enough for a clean 4–6 week proof-of-concept with genuine weekly trend data on your priority topics.

Note on Daily tracking: Daily cadence multiplies credit consumption significantly and is best suited for accounts with larger credit allocations. For a 2,500-credit starter, Weekly gives you the actionable trend data you need without the overhead.

Once you’ve selected the strategy that best fits your goals, implementing it is simple and transparent.

Navigate to Settings > Topics and Prompts in your Conductor account.
Launch the Configuration Wizard to begin your setup.
Use Custom Instructions to focus the generator on your chosen strategy. If you’re running the “Proof of Concept” sprint, instructions like “Only generate prompts that reflect mid-funnel Comparison and Recommendation intents” will keep every credit pointed at decision-stage queries. For the “Year-Long Baseline,” instructions like “Emphasize evergreen queries; avoid time-sensitive or seasonal topics” keep the dataset comparable week over week.
As you select your engine(s), topics, and the number of prompts, pay close attention to the Credit Usage Forecast tool.
This tool updates in real-time, showing your projected weekly credit usage and, most importantly, an estimate of how long your 2,500 credits will last.
Adjust your inputs until the forecast aligns with your chosen strategy—whether it’s 10 weeks, 52 weeks, or something in between. You have full control to model your plan before you commit.

See this AI Search Setup article for further configuration support, and use our AI Response Credits Estimator (scroll down to “How do I calculate my AI Response Credit usage?”) to project your credit usage per week and per year across various tracking scenarios. By aligning your configuration with a clear goal, you can ensure every one of your initial AI Response Credits delivers maximum value for your business.