> For the complete documentation index, see [llms.txt](https://help.bizmachine.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.bizmachine.com/en/ai-prioritization/ai-prioritization-tips.md).

# How to write a use case for AI Prioritization

Tips on how to describe your product and your ideal customer so that the AI agent evaluates companies more accurately.

*Updated: 1 October 2026*

How you write your use case has a direct effect on how accurate the prioritization is. The better you describe your product and your ideal customer, the more useful the results.

When you run AI Prioritization, you choose a saved use case under **Select Use Case**. You describe the use case itself in the **Value Proposition** field.

### The 3 parts of a good use case

#### 1. What you sell and which problem it solves

Describe your product or service. Focus on what makes it different and which problem it solves for your customers.

> *"We offer software for customer support across several channels. It lets you handle customer cases from one place: by phone, web chat and social media."*

#### 2. Who your ideal customer is

State the company size, industry, region and any other conditions your ideal customer should meet.

> *"A mid-sized Czech company in an energy-intensive industry, with several production sites across the country."*

#### 3. Who is not a good candidate

List the industries or types of companies where you know you will not succeed. The agent then gives a lower value to companies where it makes no sense to try.

> *"We don't want the public sector or foreign-owned companies."*

![Run AI Prioritization dialog with a saved use case selected and its menu open with Edit Use Case and Remove Use Case](https://247275268-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYkl7SJ14Nk0vzhVx7upl%2Fuploads%2Fgit-blob-3355c80c1fad880da233d413b4cec308287f30ee%2Fai-prioritization-tips-editace-nabidky.png?alt=media)

### Example use cases

#### Sensors for heat monitoring

> *"I offer sensors that monitor heat loss in production halls. They are most useful for companies where a stable operating temperature matters. A mid-sized Czech company in an energy-intensive industry with several production sites. I don't want the public sector or foreign-owned companies."*

#### Customer support software

> *"We supply software for customer support across several channels. It works best in companies that have hundreds to thousands of customer cases a month and need routing between several support agents. Typically B2C or an open B2B market. Their products are complex, for example software, electronics, financial or insurance services."*

#### Sales intelligence platform

> *"We offer a sales intelligence platform for B2B sales teams that work in a large, changing market with thousands of potential customers. Typically companies that do not work in fixed supply chains, but need to split the market into segments and set priorities."*

### Test on a small sample first

Start with a small sample: under **Options**, choose **First Results**, or **Custom Count** with a number up to 10. Read the reasons for each one and check whether the agent takes into account what matters to you.

If the results do not match your expectations yet:

1. **Make the product description more specific.** Add concrete details that set your product apart from its general category.
2. **Make the customer description more precise.** Add the conditions a company must meet (size, industry, technology).
3. **Extend the exclusions.** Add the industries or types of companies where you know you will not succeed.

When you are happy with the results on the small sample, run the prioritization on the whole segment.

{% hint style="info" %}
You can come back to your use case at any time and change it: open the menu next to the use case and choose **Edit Use Case**. A changed use case does not update the values of companies that were already evaluated. You need to run the prioritization again.
{% endhint %}

### Frequently asked questions

#### How often is the value updated?

The value does not update automatically. Run AI Prioritization again when your use case changes, or when you want to work with more recent data. Run it again especially if your prioritization depends on data that changes quickly (job positions, technologies, signals, management changes).

#### Why do all companies have a similar value?

Your use case is probably too general. When the agent does not get specific conditions, it cannot tell the companies apart. Make the product description more concrete, make the profile of your ideal customer more precise, and add exclusions.

#### How is AI Prioritization different from filtering?

Filtering and AI Prioritization work together. First use filters to narrow the list of companies down to a well-defined segment (industry, region, size, financial results). Then run AI Prioritization on that segment. On a smaller, more precisely defined segment you get better results, and it is easier to improve your use case.

#### What are the limits?

AI Prioritization has its own monthly credit limit. Each evaluated company uses one credit, and the limit renews on the 1st day of every calendar month *(as of October 2026)*. This is one more reason to test on a small sample first. The dialog you use to start a prioritization shows how many credits you have used. To get a higher limit, ask your sales representative. For details, see [How credits and limits work in Prospector](/en/lists-and-export/credits-and-limits.md).

#### Can my colleagues see the AI Prioritization results?

That depends on the visibility of the use case. The default is **Only me**: only you can see the use case and its results. If you want to share the use case with your whole team, switch the **Visibility** to the option for everyone in your organization when you create or edit the use case.

#### Can I export the results?

Yes. Click **Export** above the results table and choose **Export AI prioritization**. For what the file contains, see [AI Prioritization: overview of features and options](/en/ai-prioritization/ai-prioritization-overview.md#export-to-excel).

### Related articles

* [AI Prioritization: overview of features and options](/en/ai-prioritization/ai-prioritization-overview.md)
* [How credits and limits work in Prospector](/en/lists-and-export/credits-and-limits.md)