Pricing

Pay per usage

AI Search Visibility Gap Scorer

Turn imported AI-search, SERP, and AI Overview visibility rows into deterministic visibility gap scores and next actions.

Pricing

Pay per usage

Rating

0.0

(0)

Developer

Wit Nomad

Actor stats

Bookmarked

Total users

Monthly active users

2 days ago

Last modified

Categories

SEO tools

Marketing

You can access the AI Search Visibility Gap Scorer programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = {
9    "mode": "items",
10    "items": [
11        {
12            "query": "best product analytics tools for b2b saas",
13            "engine": "Perplexity manual export",
14            "locale": "US",
15            "answer": "RivalMetrics is frequently recommended for B2B SaaS product analytics. Northstar BI is also mentioned.",
16            "citations": [
17                {
18                    "title": "RivalMetrics customer story",
19                    "url": "https://rivalmetrics.com/customers/b2b-saas",
20                },
21                {
22                    "title": "Product analytics software rankings",
23                    "url": "https://g2.com/categories/product-analytics",
24                },
25            ],
26        },
27        {
28            "prompt": "is acme analytics good for product teams",
29            "platform": "ChatGPT manual audit",
30            "market": "US",
31            "aiAnswer": "Acme Analytics is a possible product analytics option, but buyers often compare it with RivalMetrics.",
32            "sources": [{
33                    "title": "Third-party product analytics roundup",
34                    "url": "https://example-review-site.com/product-analytics",
35                }],
36        },
37        {
38            "keyword": "acme analytics implementation guide",
39            "provider": "Google AI Overview export",
40            "country": "US",
41            "overview": "Acme Analytics provides implementation guidance for product teams, including event tracking and activation reporting.",
42            "organicResults": [
43                {
44                    "title": "Acme Analytics implementation guide",
45                    "url": "https://docs.acmeanalytics.com/implementation",
46                },
47                {
48                    "title": "Acme Analytics product analytics blog",
49                    "url": "https://blog.acmeanalytics.com/product-analytics-guide",
50                },
51            ],
52            "mentionedBrands": ["Acme Analytics"],
53        },
54    ],
55    "brandProfile": {
56        "brandName": "Acme Analytics",
57        "domains": ["acmeanalytics.com"],
58        "competitors": [
59            "RivalMetrics",
60            "Northstar BI",
61        ],
62        "targetMarkets": ["US SaaS"],
63        "targetKeywords": [
64            "product analytics",
65            "AI visibility",
66        ],
67        "priorityTopics": [
68            "B2B SaaS analytics",
69            "implementation guides",
70        ],
71        "ownedSources": [
72            "docs.acmeanalytics.com",
73            "blog.acmeanalytics.com",
74        ],
75        "preferredCitations": [
76            "g2.com",
77            "capterra.com",
78            "docs.acmeanalytics.com",
79        ],
80        "avoidKeywords": ["guaranteed ranking"],
81    },
82    "scrapedAt": "2026-07-08T00:00:00.000Z",
83}
84
85# Run the Actor and wait for it to finish
86run = client.actor("rotvuvo/ai-search-visibility-gap-scorer").call(run_input=run_input)
87
88# Fetch and print Actor results from the run's dataset (if there are any)
89print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
90for item in client.dataset(run["defaultDatasetId"]).iterate_items():
91    print(item)
92
93# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

AI Search Visibility Gap Scorer API in Python

The Apify API client for Python is the official library that allows you to use AI Search Visibility Gap Scorer API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

$pip install apify-client

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