How to get historical mentions data with the LLM Mentions API
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A single snapshot of current LLM mentions data doesn’t provide a full picture of a website’s AI visibility. Without historical context, you can’t determine whether the result is normal, an outlier, or a trend, and thus measure the impact of the optimization effort. That makes access to historical LLM mention insights vital for effective GEO. Even developers of AI optimization tools can benefit from historical data, as it can be used to instantly display past AI visibility trends for a new user’s website.
At DataForSEO, we answered the demand for LLM historical data with three purpose-built endpoints of the LLM Mentions API: Historical, Timeseries Delta, and Timeseries New and Lost. Each answers a different question about how a target’s AI visibility has changed over time. This guide walks through all three, with practical use cases for each.
LLM Mentions API historical data endpoints: overview & use cases
1LLM Mentions Historical
The LLM Mentions Historical endpoint gives a broad overview of historical mention metrics for the target domain or keyword. It returns the monthly mentions count and AI search volume for the specified target, starting from August 2025.
The task setting process for this endpoint is overall similar to that of other LLM Mentions endpoints. Here is how to set a task step-by-step:
1. Call the LLM Mentions Historical endpoint:
POST https://api.dataforseo.com/v3/ai_optimization/llm_mentions/historical/live
2. Select the platform to get the historical data from. You can choose between google and chat_gpt.
3. Specify the location parameters with location_name or location_code. Note that for the ChatGPT platform, the only supported location is the United States.
4. Specify a language with language_name or language_code to narrow down the historical dataset to a specific language. For the ChatGPT platform, the only supported language is English.
5. In the target array, specify the target domain or target keyword entity with the target domain or keyword, respectively, and set additional entity parameters, if necessary. You can learn more about how to define targets and apply additional parameters in this Help Center article.
The complete request should look like this:
[
{
"target": [
{
"keyword": "bmw",
"search_scope": [
"answer"
],
"search_filter": "include"
}
],
"platform": "chat_gpt",
"language_code": "en",
"location_code": 2840
}
]
The result returns as follows:
{
"version": "0.1.20260610",
"status_code": 20000,
"status_message": "Ok.",
"time": "0.8998 sec.",
"cost": 0.101,
"tasks_count": 1,
"tasks_error": 0,
"tasks": [
{
"id": "06181510-1535-0662-0000-ef3c05d6ae6e",
"status_code": 20000,
"status_message": "Ok.",
"time": "0.8033 sec.",
"cost": 0.101,
"result_count": 1,
"path": [
"v3",
"ai_optimization",
"llm_mentions",
"historical",
"live"
],
"data": {
"api": "ai_optimization",
"function": "historical",
"target": [
{
"keyword": "bmw",
"search_scope": [
"answer"
],
"search_filter": "include"
}
],
"platform": "chat_gpt",
"language_code": "en",
"location_code": 2840
},
"result": [
{
"items_count": 12,
"items": [
{
"year": 2026,
"month": 6,
"metrics": {
"mentions": 19832,
"ai_search_volume": 1011382
}
},
{
"year": 2026,
"month": 5,
"metrics": {
"mentions": 8883,
"ai_search_volume": 339166
}
},
{
"year": 2026,
"month": 4,
"metrics": {
"mentions": 14980,
"ai_search_volume": 799538
}
},
{
"year": 2026,
"month": 3,
"metrics": {
"mentions": 12723,
"ai_search_volume": 455304
}
},
{
"year": 2026,
"month": 2,
"metrics": {
"mentions": 9780,
"ai_search_volume": 436170
}
},
{
"year": 2026,
"month": 1,
"metrics": {
"mentions": 15342,
"ai_search_volume": 580039
}
},
{
"year": 2025,
"month": 12,
"metrics": {
"mentions": 4567,
"ai_search_volume": 171667
}
},
{
"year": 2025,
"month": 11,
"metrics": {
"mentions": 14779,
"ai_search_volume": 363741
}
},
{
"year": 2025,
"month": 10,
"metrics": {
"mentions": 8535,
"ai_search_volume": 247514
}
},
{
"year": 2025,
"month": 9,
"metrics": {
"mentions": 2672,
"ai_search_volume": 101129
}
},
{
"year": 2025,
"month": 8,
"metrics": {
"mentions": 24487,
"ai_search_volume": 833760
}
},
{
"year": 2025,
"month": 7,
"metrics": {
"mentions": 356,
"ai_search_volume": 190070
}
}
]
}
]
}
]
}
In the response, locate the items array. This array contains objects with historical mention metrics for the specified target, grouped by month. In each object, you’ll get the total mentions count and the ai_search_volume rate for a particular month.
That’s it, just in a single request, you get a one-year snapshot of AI visibility for a target domain or keyword. With these insights, you can do the following:
- Establish a 12-month baseline before launching a GEO campaign for a customer’s website. That will allow you to measure the campaign’s impact in the future by comparing it with the initial historical data.
- Detect seasonal popularity of a specific brand or product in AI searches.
- Compare year-over-year AI visibility for the same target.
- Enable an AI optimization tool to display the previous mentions and AI search volume trends for a new user’s website.
2 LLM Mentions Timeseries Delta
The LLM Mentions Timeseries Delta endpoint returns the period-over-period change in mentions and AI search volume for the target. Instead of absolute monthly values, the endpoint displays how the target gained or lost compared to the previous period. The period length is controlled by the group_range parameter, which accepts day, week, month, or year values. The historical data is available from August 2025.
The task setting process follows similar steps as in the LLM Mentions Historical endpoint, with the addition of date and grouping parameters:
1. Call the LLM Mentions Timeseries Delta endpoint:
POST https://api.dataforseo.com/v3/ai_optimization/llm_mentions/timeseries_delta/live
2. Specify the target platform.
3. Set the location_name or location_coordinate.
4. Specify a language with language_name or language_code.
5. In the target array, specify the target domain or keyword entity and (optionally) additional parameters.
6. Set the date_from and date_to parameters to bound the analysis range. Both use the UTC format (yyyy-mm-dd).
7. Set the group_range parameter to choose the period granularity. The available values are day, week, month, and year.
Request example:
[
{
"target": [
{
"keyword": "bmw",
"search_scope": [
"answer"
],
"search_filter": "include"
}
],
"platform": "chat_gpt",
"language_code": "en",
"location_code": 2840,
"date_from": "2025-08-01",
"date_to": "2025-12-01",
"group_range": "day"
}
]
Response example:
{
"version": "0.1.20260610",
"status_code": 20000,
"status_message": "Ok.",
"time": "0.8006 sec.",
"cost": 0.223,
"tasks_count": 1,
"tasks_error": 0,
"tasks": [
{
"id": "06181513-1535-0663-0000-a106fa521aa5",
"status_code": 20000,
"status_message": "Ok.",
"time": "0.7203 sec.",
"cost": 0.223,
"result_count": 1,
"path": [
"v3",
"ai_optimization",
"llm_mentions",
"timeseries_delta",
"live"
],
"data": {
"api": "ai_optimization",
"function": "timeseries_delta",
"target": [
{
"keyword": "bmw",
"search_scope": [
"answer"
],
"search_filter": "include"
}
],
"platform": "chat_gpt",
"language_code": "en",
"location_code": 2840,
"date_from": "2025-08-01",
"date_to": "2025-12-01",
"group_range": "day"
},
"result": [
{
"items_count": 123,
"items": [
{
"date": "2025-08-01",
"delta_mentions": -193,
"delta_ai_search_volume": -149007
},
{
"date": "2025-08-02",
"delta_mentions": 59,
"delta_ai_search_volume": 1908
},
{
"date": "2025-08-03",
"delta_mentions": -1,
"delta_ai_search_volume": -3867
},
{
"date": "2025-08-04",
"delta_mentions": 392,
"delta_ai_search_volume": 37806
},
{
"date": "2025-08-05",
"delta_mentions": 944,
"delta_ai_search_volume": 49287
},
{
"date": "2025-08-06",
"delta_mentions": 494,
"delta_ai_search_volume": -10732
},
{
"date": "2025-08-07",
"delta_mentions": -142,
"delta_ai_search_volume": -33755
},
{
"date": "2025-08-08",
"delta_mentions": 9,
"delta_ai_search_volume": -12599
},
{
"date": "2025-08-09",
"delta_mentions": -140,
"delta_ai_search_volume": -13977
},
{
"date": "2025-08-10",
"delta_mentions": -62,
"delta_ai_search_volume": -5986
},
{
"date": "2025-08-11",
"delta_mentions": -424,
"delta_ai_search_volume": -13127
},
{
"date": "2025-08-12",
"delta_mentions": -1111,
"delta_ai_search_volume": -24411
},
{
"date": "2025-08-13",
"delta_mentions": 13,
"delta_ai_search_volume": 513
},
{
"date": "2025-08-14",
"delta_mentions": -9,
"delta_ai_search_volume": -604
},
{
"date": "2025-08-15",
"delta_mentions": -12,
"delta_ai_search_volume": -554
},
{
"date": "2025-08-16",
"delta_mentions": -13,
"delta_ai_search_volume": -39
},
{
"date": "2025-08-17",
"delta_mentions": 50,
"delta_ai_search_volume": 676
},
{
"date": "2025-08-18",
"delta_mentions": -34,
"delta_ai_search_volume": 4911
},
{
"date": "2025-08-19",
"delta_mentions": 928,
"delta_ai_search_volume": 12271
},
{
"date": "2025-08-20",
"delta_mentions": 110,
"delta_ai_search_volume": 358
},
{
"date": "2025-08-21",
"delta_mentions": -201,
"delta_ai_search_volume": -3816
},
{
"date": "2025-08-22",
"delta_mentions": -70,
"delta_ai_search_volume": -1803
},
{
"date": "2025-08-23",
"delta_mentions": -775,
"delta_ai_search_volume": -13105
},
{
"date": "2025-08-24",
"delta_mentions": 20,
"delta_ai_search_volume": 556
},
{
"date": "2025-08-25",
"delta_mentions": -12,
"delta_ai_search_volume": -524
},
{
"date": "2025-08-26",
"delta_mentions": 890,
"delta_ai_search_volume": 13005
},
{
"date": "2025-08-27",
"delta_mentions": 410,
"delta_ai_search_volume": 5832
},
{
"date": "2025-08-28",
"delta_mentions": 132,
"delta_ai_search_volume": 792
},
{
"date": "2025-08-29",
"delta_mentions": -651,
"delta_ai_search_volume": -9388
},
{
"date": "2025-08-30",
"delta_mentions": -952,
"delta_ai_search_volume": -12882
},
{
"date": "2025-08-31",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-01",
"delta_mentions": 311,
"delta_ai_search_volume": 16156
},
{
"date": "2025-09-02",
"delta_mentions": 35,
"delta_ai_search_volume": -4404
},
{
"date": "2025-09-03",
"delta_mentions": 86,
"delta_ai_search_volume": 6138
},
{
"date": "2025-09-04",
"delta_mentions": -285,
"delta_ai_search_volume": -12920
},
{
"date": "2025-09-05",
"delta_mentions": -147,
"delta_ai_search_volume": -4970
},
{
"date": "2025-09-06",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-07",
"delta_mentions": 158,
"delta_ai_search_volume": 5372
},
{
"date": "2025-09-08",
"delta_mentions": 12,
"delta_ai_search_volume": 133
},
{
"date": "2025-09-09",
"delta_mentions": 18,
"delta_ai_search_volume": 1541
},
{
"date": "2025-09-10",
"delta_mentions": 265,
"delta_ai_search_volume": 9201
},
{
"date": "2025-09-11",
"delta_mentions": -187,
"delta_ai_search_volume": -7884
},
{
"date": "2025-09-12",
"delta_mentions": -94,
"delta_ai_search_volume": -2274
},
{
"date": "2025-09-13",
"delta_mentions": -143,
"delta_ai_search_volume": -4350
},
{
"date": "2025-09-14",
"delta_mentions": -29,
"delta_ai_search_volume": -1739
},
{
"date": "2025-09-15",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-16",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-17",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-18",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-19",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-20",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-21",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-22",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-23",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-24",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-25",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-26",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-27",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-28",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-29",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-09-30",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-10-01",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-10-02",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-10-03",
"delta_mentions": 14,
"delta_ai_search_volume": 925
},
{
"date": "2025-10-04",
"delta_mentions": -14,
"delta_ai_search_volume": -925
},
{
"date": "2025-10-05",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-10-06",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-10-07",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-10-08",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-10-09",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-10-10",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-10-11",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-10-12",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-10-13",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-10-14",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-10-15",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-10-16",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-10-17",
"delta_mentions": 106,
"delta_ai_search_volume": 2369
},
{
"date": "2025-10-18",
"delta_mentions": 17,
"delta_ai_search_volume": 988
},
{
"date": "2025-10-19",
"delta_mentions": -89,
"delta_ai_search_volume": -1652
},
{
"date": "2025-10-20",
"delta_mentions": 19,
"delta_ai_search_volume": -84
},
{
"date": "2025-10-21",
"delta_mentions": -5,
"delta_ai_search_volume": -322
},
{
"date": "2025-10-22",
"delta_mentions": -12,
"delta_ai_search_volume": -591
},
{
"date": "2025-10-23",
"delta_mentions": 6,
"delta_ai_search_volume": 424
},
{
"date": "2025-10-24",
"delta_mentions": 0,
"delta_ai_search_volume": 916
},
{
"date": "2025-10-25",
"delta_mentions": 865,
"delta_ai_search_volume": 38890
},
{
"date": "2025-10-26",
"delta_mentions": -91,
"delta_ai_search_volume": -26279
},
{
"date": "2025-10-27",
"delta_mentions": 189,
"delta_ai_search_volume": 14169
},
{
"date": "2025-10-28",
"delta_mentions": 421,
"delta_ai_search_volume": 5308
},
{
"date": "2025-10-29",
"delta_mentions": -194,
"delta_ai_search_volume": 7181
},
{
"date": "2025-10-30",
"delta_mentions": 12,
"delta_ai_search_volume": -18605
},
{
"date": "2025-10-31",
"delta_mentions": 170,
"delta_ai_search_volume": 27048
},
{
"date": "2025-11-01",
"delta_mentions": -266,
"delta_ai_search_volume": -20672
},
{
"date": "2025-11-02",
"delta_mentions": 358,
"delta_ai_search_volume": 10722
},
{
"date": "2025-11-03",
"delta_mentions": -216,
"delta_ai_search_volume": -86
},
{
"date": "2025-11-04",
"delta_mentions": 67,
"delta_ai_search_volume": -16407
},
{
"date": "2025-11-05",
"delta_mentions": -60,
"delta_ai_search_volume": 24142
},
{
"date": "2025-11-06",
"delta_mentions": -165,
"delta_ai_search_volume": -31872
},
{
"date": "2025-11-07",
"delta_mentions": 270,
"delta_ai_search_volume": 29227
},
{
"date": "2025-11-08",
"delta_mentions": -502,
"delta_ai_search_volume": -34685
},
{
"date": "2025-11-09",
"delta_mentions": -742,
"delta_ai_search_volume": -6545
},
{
"date": "2025-11-10",
"delta_mentions": -63,
"delta_ai_search_volume": -1385
},
{
"date": "2025-11-11",
"delta_mentions": 35,
"delta_ai_search_volume": 274
},
{
"date": "2025-11-12",
"delta_mentions": 85,
"delta_ai_search_volume": 2707
},
{
"date": "2025-11-13",
"delta_mentions": 6,
"delta_ai_search_volume": -1078
},
{
"date": "2025-11-14",
"delta_mentions": -13,
"delta_ai_search_volume": 2437
},
{
"date": "2025-11-15",
"delta_mentions": -24,
"delta_ai_search_volume": -2468
},
{
"date": "2025-11-16",
"delta_mentions": -20,
"delta_ai_search_volume": -1086
},
{
"date": "2025-11-17",
"delta_mentions": -77,
"delta_ai_search_volume": -2019
},
{
"date": "2025-11-18",
"delta_mentions": -87,
"delta_ai_search_volume": -966
},
{
"date": "2025-11-19",
"delta_mentions": 0,
"delta_ai_search_volume": 0
},
{
"date": "2025-11-20",
"delta_mentions": 194,
"delta_ai_search_volume": 5428
},
{
"date": "2025-11-21",
"delta_mentions": 8,
"delta_ai_search_volume": -1541
},
{
"date": "2025-11-22",
"delta_mentions": 5,
"delta_ai_search_volume": 2946
},
{
"date": "2025-11-23",
"delta_mentions": -62,
"delta_ai_search_volume": -4046
},
{
"date": "2025-11-24",
"delta_mentions": 20,
"delta_ai_search_volume": 478
},
{
"date": "2025-11-25",
"delta_mentions": 28,
"delta_ai_search_volume": 655
},
{
"date": "2025-11-26",
"delta_mentions": -25,
"delta_ai_search_volume": 536
},
{
"date": "2025-11-27",
"delta_mentions": -35,
"delta_ai_search_volume": -1391
},
{
"date": "2025-11-28",
"delta_mentions": 139,
"delta_ai_search_volume": 4499
},
{
"date": "2025-11-29",
"delta_mentions": 1334,
"delta_ai_search_volume": 32945
},
{
"date": "2025-11-30",
"delta_mentions": -1606,
"delta_ai_search_volume": -40509
},
{
"date": "2025-12-01",
"delta_mentions": 29,
"delta_ai_search_volume": 13862
}
]
}
]
}
]
}
In the items array of the response, you will find objects that contain timeseries delta metrics for the specified date range. Each object represents one period in the requested range and contains the date, the delta_mentions, and the delta_ai_search_volume. Deltas can be negative when mentions or AI search volume decline relative to the previous period.
With period-over-period change visible at a glance, you can do the following:
- Quantify the impact of a content launch or AI optimization campaign overall on a customer’s AI visibility.
- Spot volatility in a website’s AI visibility before it becomes a long-term trend.
- Compare two competitors’ delta patterns over the same range to see which one is gaining ground in AI searches.
- Add a feature to an AI optimization that displays gain and loss trends across specific timeframes for any tracked target.
3LLM Mentions Timeseries New and Lost
The LLM Mentions Timeseries New and Lost endpoint goes one level deeper than Timeseries Delta. The endpoint displays which mentions are new in each period (the target appeared in answers it didn’t appear in before) and which are lost (the target appeared in those answers in the previous period but no longer does). The same applies to AI search volume rate. Similar to other historical data endpoints, the data is available from August 2025.
The task-setting process is identical to that of the LLM Mentions Timeseries Delta endpoint. Here is how to set a task step-by-step:
1. Call the LLM Mentions Timeseries New and Lost endpoint:
POST https://api.dataforseo.com/v3/ai_optimization/llm_mentions/timeseries_new_lost/live
2. Set the target platform.
3. Specify the location_name or location_code.
4. Set the target language with language_name or language_code.
5. In the target array, specify the target domain or keyword entity and set additional parameters, if necessary.
6. Set the date_from and date_to parameters to bound the analysis range. Both use the UTC format (yyyy-mm-dd).
7. Set the group_range parameter to choose the period granularity. The available values are day, week, month, and year.
Request example:
[
{
"target": [
{
"keyword": "bmw",
"search_scope": [
"answer"
],
"search_filter": "include"
}
],
"platform": "chat_gpt",
"language_code": "en",
"location_code": 2840,
"date_from": "2025-08-01",
"date_to": "2025-12-01",
"group_range": "day"
}
]
Response example:
{
"version": "0.1.20260610",
"status_code": 20000,
"status_message": "Ok.",
"time": "1.1240 sec.",
"cost": 0.223,
"tasks_count": 1,
"tasks_error": 0,
"tasks": [
{
"id": "06181514-1535-0664-0000-7aa0fa7576dd",
"status_code": 20000,
"status_message": "Ok.",
"time": "1.0636 sec.",
"cost": 0.223,
"result_count": 1,
"path": [
"v3",
"ai_optimization",
"llm_mentions",
"timeseries_new_lost",
"live"
],
"data": {
"api": "ai_optimization",
"function": "timeseries_new_lost",
"target": [
{
"keyword": "bmw",
"search_scope": [
"answer"
],
"search_filter": "include"
}
],
"platform": "chat_gpt",
"language_code": "en",
"location_code": 2840,
"date_from": "2025-08-01",
"date_to": "2025-12-01",
"group_range": "day"
},
"result": [
{
"items_count": 123,
"items": [
{
"date": "2025-08-01",
"new_mentions": 158,
"lost_mentions": 351,
"new_ai_search_volume": 33254,
"lost_ai_search_volume": 182261
},
{
"date": "2025-08-02",
"new_mentions": 217,
"lost_mentions": 158,
"new_ai_search_volume": 35162,
"lost_ai_search_volume": 33254
},
{
"date": "2025-08-03",
"new_mentions": 216,
"lost_mentions": 217,
"new_ai_search_volume": 31295,
"lost_ai_search_volume": 35162
},
{
"date": "2025-08-04",
"new_mentions": 608,
"lost_mentions": 216,
"new_ai_search_volume": 69101,
"lost_ai_search_volume": 31295
},
{
"date": "2025-08-05",
"new_mentions": 1552,
"lost_mentions": 608,
"new_ai_search_volume": 118388,
"lost_ai_search_volume": 69101
},
{
"date": "2025-08-06",
"new_mentions": 2046,
"lost_mentions": 1552,
"new_ai_search_volume": 107656,
"lost_ai_search_volume": 118388
},
{
"date": "2025-08-07",
"new_mentions": 1904,
"lost_mentions": 2046,
"new_ai_search_volume": 73901,
"lost_ai_search_volume": 107656
},
{
"date": "2025-08-08",
"new_mentions": 1913,
"lost_mentions": 1904,
"new_ai_search_volume": 61302,
"lost_ai_search_volume": 73901
},
{
"date": "2025-08-09",
"new_mentions": 1773,
"lost_mentions": 1913,
"new_ai_search_volume": 47325,
"lost_ai_search_volume": 61302
},
{
"date": "2025-08-10",
"new_mentions": 1711,
"lost_mentions": 1773,
"new_ai_search_volume": 41339,
"lost_ai_search_volume": 47325
},
{
"date": "2025-08-11",
"new_mentions": 1287,
"lost_mentions": 1711,
"new_ai_search_volume": 28212,
"lost_ai_search_volume": 41339
},
{
"date": "2025-08-12",
"new_mentions": 176,
"lost_mentions": 1287,
"new_ai_search_volume": 3801,
"lost_ai_search_volume": 28212
},
{
"date": "2025-08-13",
"new_mentions": 189,
"lost_mentions": 176,
"new_ai_search_volume": 4314,
"lost_ai_search_volume": 3801
},
{
"date": "2025-08-14",
"new_mentions": 180,
"lost_mentions": 189,
"new_ai_search_volume": 3710,
"lost_ai_search_volume": 4314
},
{
"date": "2025-08-15",
"new_mentions": 168,
"lost_mentions": 180,
"new_ai_search_volume": 3156,
"lost_ai_search_volume": 3710
},
{
"date": "2025-08-16",
"new_mentions": 155,
"lost_mentions": 168,
"new_ai_search_volume": 3117,
"lost_ai_search_volume": 3156
},
{
"date": "2025-08-17",
"new_mentions": 205,
"lost_mentions": 155,
"new_ai_search_volume": 3793,
"lost_ai_search_volume": 3117
},
{
"date": "2025-08-18",
"new_mentions": 171,
"lost_mentions": 205,
"new_ai_search_volume": 8704,
"lost_ai_search_volume": 3793
},
{
"date": "2025-08-19",
"new_mentions": 1099,
"lost_mentions": 171,
"new_ai_search_volume": 20975,
"lost_ai_search_volume": 8704
},
{
"date": "2025-08-20",
"new_mentions": 1209,
"lost_mentions": 1099,
"new_ai_search_volume": 21333,
"lost_ai_search_volume": 20975
},
{
"date": "2025-08-21",
"new_mentions": 1008,
"lost_mentions": 1209,
"new_ai_search_volume": 17517,
"lost_ai_search_volume": 21333
},
{
"date": "2025-08-22",
"new_mentions": 938,
"lost_mentions": 1008,
"new_ai_search_volume": 15714,
"lost_ai_search_volume": 17517
},
{
"date": "2025-08-23",
"new_mentions": 163,
"lost_mentions": 938,
"new_ai_search_volume": 2609,
"lost_ai_search_volume": 15714
},
{
"date": "2025-08-24",
"new_mentions": 183,
"lost_mentions": 163,
"new_ai_search_volume": 3165,
"lost_ai_search_volume": 2609
},
{
"date": "2025-08-25",
"new_mentions": 171,
"lost_mentions": 183,
"new_ai_search_volume": 2641,
"lost_ai_search_volume": 3165
},
{
"date": "2025-08-26",
"new_mentions": 1061,
"lost_mentions": 171,
"new_ai_search_volume": 15646,
"lost_ai_search_volume": 2641
},
{
"date": "2025-08-27",
"new_mentions": 1471,
"lost_mentions": 1061,
"new_ai_search_volume": 21478,
"lost_ai_search_volume": 15646
},
{
"date": "2025-08-28",
"new_mentions": 1603,
"lost_mentions": 1471,
"new_ai_search_volume": 22270,
"lost_ai_search_volume": 21478
},
{
"date": "2025-08-29",
"new_mentions": 952,
"lost_mentions": 1603,
"new_ai_search_volume": 12882,
"lost_ai_search_volume": 22270
},
{
"date": "2025-08-30",
"new_mentions": 0,
"lost_mentions": 952,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 12882
},
{
"date": "2025-08-31",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-01",
"new_mentions": 311,
"lost_mentions": 0,
"new_ai_search_volume": 16156,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-02",
"new_mentions": 346,
"lost_mentions": 311,
"new_ai_search_volume": 11752,
"lost_ai_search_volume": 16156
},
{
"date": "2025-09-03",
"new_mentions": 432,
"lost_mentions": 346,
"new_ai_search_volume": 17890,
"lost_ai_search_volume": 11752
},
{
"date": "2025-09-04",
"new_mentions": 147,
"lost_mentions": 432,
"new_ai_search_volume": 4970,
"lost_ai_search_volume": 17890
},
{
"date": "2025-09-05",
"new_mentions": 0,
"lost_mentions": 147,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 4970
},
{
"date": "2025-09-06",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-07",
"new_mentions": 158,
"lost_mentions": 0,
"new_ai_search_volume": 5372,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-08",
"new_mentions": 170,
"lost_mentions": 158,
"new_ai_search_volume": 5505,
"lost_ai_search_volume": 5372
},
{
"date": "2025-09-09",
"new_mentions": 188,
"lost_mentions": 170,
"new_ai_search_volume": 7046,
"lost_ai_search_volume": 5505
},
{
"date": "2025-09-10",
"new_mentions": 453,
"lost_mentions": 188,
"new_ai_search_volume": 16247,
"lost_ai_search_volume": 7046
},
{
"date": "2025-09-11",
"new_mentions": 266,
"lost_mentions": 453,
"new_ai_search_volume": 8363,
"lost_ai_search_volume": 16247
},
{
"date": "2025-09-12",
"new_mentions": 172,
"lost_mentions": 266,
"new_ai_search_volume": 6089,
"lost_ai_search_volume": 8363
},
{
"date": "2025-09-13",
"new_mentions": 29,
"lost_mentions": 172,
"new_ai_search_volume": 1739,
"lost_ai_search_volume": 6089
},
{
"date": "2025-09-14",
"new_mentions": 0,
"lost_mentions": 29,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 1739
},
{
"date": "2025-09-15",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-16",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-17",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-18",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-19",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-20",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-21",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-22",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-23",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-24",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-25",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-26",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-27",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-28",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-29",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-09-30",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-10-01",
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"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-10-02",
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"new_ai_search_volume": 0,
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},
{
"date": "2025-10-03",
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"lost_ai_search_volume": 0
},
{
"date": "2025-10-04",
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},
{
"date": "2025-10-05",
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"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-10-06",
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"lost_mentions": 0,
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"lost_ai_search_volume": 0
},
{
"date": "2025-10-07",
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"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-10-08",
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"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-10-09",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-10-10",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-10-11",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-10-12",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-10-13",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-10-14",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-10-15",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-10-16",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-10-17",
"new_mentions": 106,
"lost_mentions": 0,
"new_ai_search_volume": 2369,
"lost_ai_search_volume": 0
},
{
"date": "2025-10-18",
"new_mentions": 123,
"lost_mentions": 106,
"new_ai_search_volume": 3357,
"lost_ai_search_volume": 2369
},
{
"date": "2025-10-19",
"new_mentions": 34,
"lost_mentions": 123,
"new_ai_search_volume": 1705,
"lost_ai_search_volume": 3357
},
{
"date": "2025-10-20",
"new_mentions": 53,
"lost_mentions": 34,
"new_ai_search_volume": 1621,
"lost_ai_search_volume": 1705
},
{
"date": "2025-10-21",
"new_mentions": 48,
"lost_mentions": 53,
"new_ai_search_volume": 1299,
"lost_ai_search_volume": 1621
},
{
"date": "2025-10-22",
"new_mentions": 36,
"lost_mentions": 48,
"new_ai_search_volume": 708,
"lost_ai_search_volume": 1299
},
{
"date": "2025-10-23",
"new_mentions": 42,
"lost_mentions": 36,
"new_ai_search_volume": 1132,
"lost_ai_search_volume": 708
},
{
"date": "2025-10-24",
"new_mentions": 42,
"lost_mentions": 42,
"new_ai_search_volume": 2048,
"lost_ai_search_volume": 1132
},
{
"date": "2025-10-25",
"new_mentions": 907,
"lost_mentions": 42,
"new_ai_search_volume": 40938,
"lost_ai_search_volume": 2048
},
{
"date": "2025-10-26",
"new_mentions": 816,
"lost_mentions": 907,
"new_ai_search_volume": 14659,
"lost_ai_search_volume": 40938
},
{
"date": "2025-10-27",
"new_mentions": 1005,
"lost_mentions": 816,
"new_ai_search_volume": 28828,
"lost_ai_search_volume": 14659
},
{
"date": "2025-10-28",
"new_mentions": 1426,
"lost_mentions": 1005,
"new_ai_search_volume": 34136,
"lost_ai_search_volume": 28828
},
{
"date": "2025-10-29",
"new_mentions": 1232,
"lost_mentions": 1426,
"new_ai_search_volume": 41317,
"lost_ai_search_volume": 34136
},
{
"date": "2025-10-30",
"new_mentions": 1244,
"lost_mentions": 1232,
"new_ai_search_volume": 22712,
"lost_ai_search_volume": 41317
},
{
"date": "2025-10-31",
"new_mentions": 1414,
"lost_mentions": 1244,
"new_ai_search_volume": 49760,
"lost_ai_search_volume": 22712
},
{
"date": "2025-11-01",
"new_mentions": 1148,
"lost_mentions": 1414,
"new_ai_search_volume": 29088,
"lost_ai_search_volume": 49760
},
{
"date": "2025-11-02",
"new_mentions": 1506,
"lost_mentions": 1148,
"new_ai_search_volume": 39810,
"lost_ai_search_volume": 29088
},
{
"date": "2025-11-03",
"new_mentions": 1290,
"lost_mentions": 1506,
"new_ai_search_volume": 39724,
"lost_ai_search_volume": 39810
},
{
"date": "2025-11-04",
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"lost_mentions": 1290,
"new_ai_search_volume": 23317,
"lost_ai_search_volume": 39724
},
{
"date": "2025-11-05",
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"lost_mentions": 1357,
"new_ai_search_volume": 47459,
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},
{
"date": "2025-11-06",
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"lost_mentions": 1297,
"new_ai_search_volume": 15587,
"lost_ai_search_volume": 47459
},
{
"date": "2025-11-07",
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"lost_mentions": 1132,
"new_ai_search_volume": 44814,
"lost_ai_search_volume": 15587
},
{
"date": "2025-11-08",
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"lost_mentions": 1402,
"new_ai_search_volume": 10129,
"lost_ai_search_volume": 44814
},
{
"date": "2025-11-09",
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"lost_mentions": 900,
"new_ai_search_volume": 3584,
"lost_ai_search_volume": 10129
},
{
"date": "2025-11-10",
"new_mentions": 95,
"lost_mentions": 158,
"new_ai_search_volume": 2199,
"lost_ai_search_volume": 3584
},
{
"date": "2025-11-11",
"new_mentions": 130,
"lost_mentions": 95,
"new_ai_search_volume": 2473,
"lost_ai_search_volume": 2199
},
{
"date": "2025-11-12",
"new_mentions": 215,
"lost_mentions": 130,
"new_ai_search_volume": 5180,
"lost_ai_search_volume": 2473
},
{
"date": "2025-11-13",
"new_mentions": 221,
"lost_mentions": 215,
"new_ai_search_volume": 4102,
"lost_ai_search_volume": 5180
},
{
"date": "2025-11-14",
"new_mentions": 208,
"lost_mentions": 221,
"new_ai_search_volume": 6539,
"lost_ai_search_volume": 4102
},
{
"date": "2025-11-15",
"new_mentions": 184,
"lost_mentions": 208,
"new_ai_search_volume": 4071,
"lost_ai_search_volume": 6539
},
{
"date": "2025-11-16",
"new_mentions": 164,
"lost_mentions": 184,
"new_ai_search_volume": 2985,
"lost_ai_search_volume": 4071
},
{
"date": "2025-11-17",
"new_mentions": 87,
"lost_mentions": 164,
"new_ai_search_volume": 966,
"lost_ai_search_volume": 2985
},
{
"date": "2025-11-18",
"new_mentions": 0,
"lost_mentions": 87,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 966
},
{
"date": "2025-11-19",
"new_mentions": 0,
"lost_mentions": 0,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 0
},
{
"date": "2025-11-20",
"new_mentions": 194,
"lost_mentions": 0,
"new_ai_search_volume": 5428,
"lost_ai_search_volume": 0
},
{
"date": "2025-11-21",
"new_mentions": 202,
"lost_mentions": 194,
"new_ai_search_volume": 3887,
"lost_ai_search_volume": 5428
},
{
"date": "2025-11-22",
"new_mentions": 207,
"lost_mentions": 202,
"new_ai_search_volume": 6833,
"lost_ai_search_volume": 3887
},
{
"date": "2025-11-23",
"new_mentions": 145,
"lost_mentions": 207,
"new_ai_search_volume": 2787,
"lost_ai_search_volume": 6833
},
{
"date": "2025-11-24",
"new_mentions": 165,
"lost_mentions": 145,
"new_ai_search_volume": 3265,
"lost_ai_search_volume": 2787
},
{
"date": "2025-11-25",
"new_mentions": 193,
"lost_mentions": 165,
"new_ai_search_volume": 3920,
"lost_ai_search_volume": 3265
},
{
"date": "2025-11-26",
"new_mentions": 168,
"lost_mentions": 193,
"new_ai_search_volume": 4456,
"lost_ai_search_volume": 3920
},
{
"date": "2025-11-27",
"new_mentions": 133,
"lost_mentions": 168,
"new_ai_search_volume": 3065,
"lost_ai_search_volume": 4456
},
{
"date": "2025-11-28",
"new_mentions": 272,
"lost_mentions": 133,
"new_ai_search_volume": 7564,
"lost_ai_search_volume": 3065
},
{
"date": "2025-11-29",
"new_mentions": 1606,
"lost_mentions": 272,
"new_ai_search_volume": 40509,
"lost_ai_search_volume": 7564
},
{
"date": "2025-11-30",
"new_mentions": 0,
"lost_mentions": 1606,
"new_ai_search_volume": 0,
"lost_ai_search_volume": 40509
},
{
"date": "2025-12-01",
"new_mentions": 29,
"lost_mentions": 0,
"new_ai_search_volume": 13862,
"lost_ai_search_volume": 0
}
]
}
]
}
]
}
In the items array of the response, each object represents one period and contains four metrics: new_mentions, lost_mentions, new_ai_search_volume, and lost_ai_search_volume. Together, they decompose the period-over-period change into its underlying components. This way, you can see whether a gain came from new mentions in LLM answers, or whether a loss came from the target dropping out of answers that previously included it.
With new and lost data mentions data per period, you can do the following:
- Analyze whether a website’s or a brand’s AI visibility growth comes from new content or from churn through the same answers.
- Identify which responses a website stopped appearing in and investigate why.
- Measure the effectiveness of a GEO campaign by checking whether the
new_mentionsgained in one period are present in the following. - Enable an AI optimization tool to show users not just whether their visibility changed, but exactly how it changed.
However, there is an important note on both Timeseries endpoints to take into account. For the same target and period, delta_mentions from Timeseries Delta equals new_mentions minus lost_mentions from Timeseries New and Lost. However, delta_ai_search_volume does not equal new_ai_search_volume minus lost_ai_search_volume. The two endpoints use different calculation logic for AI search volume, so treat them as complementary angles on the same underlying movement, not as identities.
Wrap up
The three new endpoints of the LLM Mentions API – Historical, Timeseries Delta, and Timeseries New and Lost – provide a solid historical data foundation for more precise, data-driven AI visibility analysis. With these endpoints combined, you can build a complete historical view of any domain’s or keyword’s AI visibility: from assessing absolute mentions and AI search volume metrics, to exploring period-over-period changes.
See the LLM mentions docs for all the details, and if you run into any problem, contact our 24/7 customer support.