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Profound connector tools

8 min

The Profound connector tools in Optimizely Opal let you analyze how AI systems are interacting with your content, providing insights into citations, sentiment, and brand visibility. Complete the following steps to enable them.

Add the Profound Analytics for Opal app in OCP

In the OCP App Directory, complete the following:

Click on Profound Analytics for Opal.

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Click Install App.

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Go to Settings > Profound API Configuration.

Enter your Profound API key. See Profound's documentation on Authentication to learn more.

(Optional) Enter an API Base URL. Entering a URL overrides the Profound API base URL. See Profound's documentation on the Base URL for information.

Click Save API Configuration.

Save API Configuration

Configure default category (optional)

After configuring your Profound API Key, you can select a default Profound category to query when using the Profound tools in Opal. If you have multiple categories, you can set a default here and query others in your Opal prompt, or you can leave this section blank, which may result in Opal asking which category to query.

To configure a default category, complete the following:

Expand the Default Category Configuration section.

Select the Default Category drop-down list.

Select the default category or search to find it.

Click Save Category Configuration.

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Register the Profound connector tool in OCP

After you Add the Profound Analytics for Opal app in OCP and optionally Configure default category, complete the following in OCP:

Click Settings > Add to Opal.

Click Add to Opal for the Opal Account you want to add the Profound connector tools to. Click Remove from Opal to remove the connection.

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You can now use the Profound connector tools within Opal.

Profound connector tools

After you add and register the Profound connector tools, you can call the following tools in Opal.

Click a tool's name to expand it and learn when to use it, its required and optional parameters, and example prompts for calling the tool. If you do not provide a required parameter, Opal prompts you for it.

When to use

To understand overall website traffic – If you want to see the total number of requests to your site over a period.

To analyze user and bot access patterns – If you need to break down traffic by method (for example, GET or POST), status code (for example, 200 or 404), or user agent.

To identify popular pages or resources – If you want to see which paths on your website are most frequently accessed.

To troubleshoot issues – If you need to investigate specific status codes or methods that might indicate problems.

To monitor specific user agents – If you want to track traffic from a particular browser, device, or known bot.

Parameters

domain – Your website domain, for example, www.example.com. Use the Get domains tool if you do not know which domains are available.

start_date – The beginning of the date range for your analysis in YYYY-MM-DD format.

end_date – The end of the date range for your analysis in YYYY-MM-DD format.

metrics – What you want to measure. Currently, only "count" is available.

dimensions – How you want to break down the data. You can choose from the following:

timestamp

method

host

path

status_code

ip

user_agent

referer

bytes_sent

duration_ms

query_params

(Optional) filters – A JSON array of conditions to narrow down your data, for example, [{"field":"method", "operator":"is", "value":"GET"}].

Available fields for filtering includes the following:

path

method

status_code

user_agent

Available operators include the following:

is

not_is

in

not_in

contains

not_contains

contains_case_insensitive

not_contains_case_insensitive

matches

(Optional) limit – The maximum number of records to return. The default is 100.

(Optional) offset – The starting position for pagination. The default is 0.

(Optional) order_by – A JSON object for sorting the results, for example, {"count":"desc"}.

Example prompts

Show me the total number of successful GET requests to www.mywebsite.com last week (October 23rd to October 30th, 2025).

List the top five most accessed paths on example.org in September 2025, along with the number of times each was accessed.

How many requests did blog.company.com receive from mobile user agents in the last 30 days (October 1st to October 30th, 2025), and what were the different status codes returned?

When to use

To identify authoritative sources – If you want to find out which domains or pages are most frequently cited in a specific category.

To understand market share and competitive positioning – If you want to analyze how often your company or specific topics are cited compared to competitors.

To track content influence – If you want to see how AI systems are referencing your content over time.

To analyze citation patterns – If you need to break down citations by region, topic, or AI model.

Parameters

category_id – The ID of the category you want to analyze. Use the get_categories tool to get a list of available categories.

start_date – The beginning of the date range for your analysis in YYYY-MM-DD format.

end_date – The end of the date range for your analysis in YYYY-MM-DD format.

metrics – What you want to measure. Available values are "count" (total number of citations) and "share_of_voice" (your share of citations within the category).

dimensions – How you want to break down the data. Available values include the following:

hostname

path

date

region

topic

model

tag

(Optional) filters – A JSON array of conditions to narrow down your data, for example, [{"field":"hostname", "operator":"is", "value":"example.com"}].

Available fields for filtering include the following:

hostname

path

region

topic

model

tag

Available operators include the following:

is

not_is

in

not_in

contains

not_contains

contains_case_insensitive

not_contains_case_insensitive

matches

(Optional) limit – The maximum number of records to return. The default is 10.

(Optional) offset – The starting position for pagination. The default is 0.

(Optional) order_by – A JSON object for sorting the results, for example, {"count":"desc"}.

Example prompts

For the 'Technology' category (ID: tech_123), show me the top 5 hostnames with the most citations in the last month (October 2025).

I want to see the share of voice for different topics within the 'Digital Marketing' category (ID: digital_marketing_456) for the last quarter (July 1st to September 30th, 2025). Please exclude any citations from 'spamdomain.com'.

Can you give me a daily count of citations for my website mycompany.com in the 'Ecommerce' category (ID: ecommerce_789) for the first two weeks of November 2025?

When to use

To understand company reputation – If you want to identify companies with the most positive or negative sentiment.

To analyze sentiment across themes – If you need to see which topics generate positive or negative sentiment for your company or competitors.

To track sentiment over time – If you want to monitor changes in sentiment for specific entities or topics over various date intervals.

To identify areas for improvement – If you need to pinpoint specific areas that are causing negative sentiment.

Parameters

category_id – The ID of the category you want to analyze. Use the get_categories tool to get a list of available categories.

start_date – The beginning of the date range for your analysis in YYYY-MM-DD format.

end_date – The end of the date range for your analysis in YYYY-MM-DD format.

metrics – What you want to measure. Available values are include the following:

positive

negative

neutral

total_mentions

dimensions – How you want to break down the data. Available values are include the following:

hostname

path

date

region

topic

model

tag

asset_name

theme

(Optional) date_interval – How to group the dates – day, week, month. The default is day.

(Optional) filters – A JSON array of filters, for example, [{"field":"hostname", "operator":"is", "value":"example.com"}].

Available fields for filtering include the following:

hostname

path

region

topic

model

tag

asset_name

theme

Available operators include the following:

is

not_is

in

not_in

contains

not_contains

contains_case_insensitive

not_contains_case_insensitive

matches

(Optional) limit – The number of records to return. The default is 10.

(Optional) offset – The starting position for pagination. The default is 0.

(Optional) order_by – A JSON object for sorting the results, for example, {"positive":"desc"}.

Example prompts

For the 'Financial Services' category (ID: financial_123), show me the top 5 companies with the most positive sentiment last quarter (July 1st to September 30th, 2025).

I want to analyze the sentiment across different topics for 'MyCompany' in the 'Retail' category (ID: retail_456) for the month of October 2025. Show me the topics with the highest positive sentiment.

What was the daily negative sentiment trend for 'Product X' in the 'Consumer Goods' category (ID: consumer_789) during the first two weeks of November 2025?

When to use

To identify market leaders – If you want to see which companies have the highest visibility scores in a particular category.

To benchmark against competitors – If you need to compare your company's visibility performance against top performers.

To monitor daily performance changes – If you want to track how your visibility score changes over time with daily, weekly, or monthly granularity.

To analyze visibility by topic or region – If you need to understand how your visibility varies across different topics or geographic regions.

To identify content gaps – If you want to see which of your assets are contributing most to your visibility, and where there might be opportunities to improve.

Parameters

category_id – The ID of the category you want to analyze. Use the get_categories tool to get a list of available categories.

start_date – The beginning of the date range for your analysis in YYYY-MM-DD format.

end_date – The end of the date range for your analysis in YYYY-MM-DD format.

metrics – What you want to measure. Available values are count (total mentions) and share_of_voice (your share of mentions within the category).

dimensions – How you want to break down the data. Available values include the following:

hostname

path

date

region

topic

model

tag

asset_name

(Optional) date_interval – How to group the dates. date_interval is only used with the date dimension. The default is day. Available options include the following:

day

week

month

year

(Optional) filters – A JSON array of filters, for example, [{"field":"hostname", "operator":"is", "value":"example.com"}].

Available fields for filtering include the following:

hostname

path

region

topic

model

tag

asset_name

Available operators include the following:

is

not_is

in

not_in

contains

not_contains

contains_case_insensitive

not_contains_case_insensitive

matches

(Optional) limit – The number of records to return. The default is 10.

(Optional) offset – The starting position for pagination. The default is 0.

(Optional) order_by – A JSON object for sorting the results, for example, {"count":"desc"}.

Example prompts

For the 'Software' category (ID: software_123), show me the top five companies with the highest visibility scores between January 1st and January 31st, 2024.

Track the daily visibility performance for 'MyCompany' in the 'Cloud Computing' category (ID: cloud_456) for the month of October 2025.

What is the share of voice for different regions in the 'Fintech' category (ID: fintech_789) for the last quarter (July 1st to September 30th, 2025)?

Note

If you use Opti ID, administrators can turn off generative AI in the Opti ID Admin Center. See Turn generative AI off across Optimizely applicationsTurn generative AI off across Optimizely applications.

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