Real-user data is one of the most valuable data types for creating successful strategies and making informed decisions in digital marketing. Knowing the real intent of your users, how they interact with websites, and what drives their behavior is crucial for improving a business’s digital presence.
However, what kind of real-user data can give insights into user interaction and is suitable for substantial analysis?
Clickstream data emerges as a powerful solution, offering a comprehensive and detailed record of users’ online journeys and interactions.
Additionally, the use of clickstream data is not limited to analyzing user behavior and engagement with a website. Clickstream data is precious for SEO tool developers and data-driven search engine optimization professionals. From refining keyword search volume to analyzing competitors’ performance, this data source provides many actionable insights for multiple purposes.
In this article, we’ll explore the nature of clickstream data, how it is collected, and its applications in digital marketing. Moreover, we will show you how you can access the clickstream data insights in the first place.
Contents:
Clickstream data explained: what is it, and where does it come from?
➤What is clickstream data?
➤How is clickstream data collected?
➤Considerations and limitations of clickstream data
Leveraging clickstream data in marketing
➤Refining keyword metrics for more precise results
➤Optimizing website content through user interaction analysis
➤Analyzing competitor traffic with precise engagement data
Unlocking clickstream data insights with DataForSEO APIs
➤Fetch clickstream keyword data
➤Discover the gender and age distribution of search volume
➤Fetch clickstream search volume for multiple keywords
➤Analyze the traffic volume of your competitors
➤Get the global search volume and its distribution by country
Conclusion
Clickstream data explained: what is it, and where does it come from?
What is clickstream data?
In general, the essence of clickstream data comes directly from its name – a record of a sequence of clicks a user makes while navigating the Internet. However, clickstream data generally encompasses a broad range of user actions in search engines, websites, etc. User interactions, including search queries, page visits, time spent, and website element engagement, are recorded by clickstream data.
To get a better understanding of clickstream data structure, let’s take a look at a sample of a clickstream events log:
This is one of the default examples of how raw clickstream data looks like. Here, you can see a sequence of events that might occur during a session on an e-commerce website. Each row represents a single event in the clickstream dataset. Additionally, you can see an event type and element type for each event, along with a URL where this event occurred.
The most distinguishing feature of clickstream data is that it captures the actions of real users. Thus, the number of clicks, visit duration, and user interaction patterns are not derived from assumptions or estimations – they are accurate, precise data.
In particular, clickstream data can reveal such important information as:
- Search terms and queries used to find your site;
- Initial landing pages and how effectively they engage users;
- Popular content areas and sections that attract the most attention;
- User engagement metrics, including time spent on various pages;
- Interaction patterns with page elements and the sequence of these interactions;
- Navigation paths users follow throughout your site.
Based on these insights, we can categorize clickstream data into three main types:
- Clickstream search data, which provides insights into search terms used to find your website;
- Clickstream interaction data, demonstrating how users interact with your content and website elements;
- Clickstream session data, showing the time users spend on particular pages or your website overall.
Furthermore, clickstream data can be classified as aggregated or unaggregated, each serving different analytical purposes. Aggregated clickstream data displays the total number of user interactions on a website during a specific time period. In contrast, unaggregated data provides more granular information, like customer journeys, click sequences, and visit durations of individual users.
Now that we have figured out what clickstream data is, let’s explore the different ways of collecting clickstreams.
How is clickstream data collected?
There are two methods of obtaining clickstream data. First, you can get such data via first-party sources, which include tools that track clickstream events on your website. Second, you can receive clickstream data from third-party providers, who collect, aggregate, and deliver clickstream datasets. Let’s explore the difference between first-party and third-party clickstream data sources.
1 First-party sources of clickstream encompass a variety of means of tracking and analyzing user interactions on your website:
Tag management systems. Such systems allow you to implement so-called “tags” into your website to track different types of user activities, like clicks, page views, scrolls, and more. Tags are samples of tracking code that allow the detection and collection of information about user actions.
The most common tag management system is Google Tag Manager, which is used in combination with Google Analytics to collect and interpret user actions on your website. Google Tag Manager allows you to create specific tags that can track clicks on multiple website properties, monitor user journeys, and deliver data directly to Google Analytics, where you can analyze it. However, doing clickstream analysis with Google Tag Manager and Google Analytics requires much manual work and deep knowledge of these tools. For instance, to track specific user interactions, you should properly create a tag with custom parameters, set triggers for user action, connect it to Google Analytics, and create a custom report. If you want to track multiple user interactions, the tag creation process may be time-consuming.
Cookies. Website cookies are text files containing small amounts of information downloaded to the user’s device when they visit a website. Cookies are designed to remember things about a user and their browsing preferences. Cookies are usually implemented manually into a website with the help of special code snippets, as shown in the example below:
// Set a cookie
document.cookie = "username=John Doe; expires=Thu, 18 Dec 2025 12:00:00 UTC; path=/";
// Read a cookie
function getCookie(name) {
const value = `; ${document.cookie}`;
const parts = value.split(`; ${name}=`);
if (parts.length === 2) return parts.pop().split(';').shift();
}
let user = getCookie("username");
Cookies can track various types of information, including login status, shopping cart contents, etc. Although cookies can assist you with collecting user data, there are various considerations regarding their use. For example, cookies must adhere to personal data regulations like GDPR, which require consent. Due to that, users can block or delete cookies, potentially affecting tracking functionality. In addition, cookies can’t store large amounts of data and are very complex to manage, especially for larger websites.
Custom tracking and analysis tools. Some companies offer all-in-one solutions to collect and interpret clickstream data from your website. Such solutions include special plugins or software kits connected to a custom analytic platform to assess the clickstream data almost immediately. Moreover, some of these tools can be installed hassle-free and have dedicated documentation.
For example, Hotjar offers a comprehensive user interaction tracking system to detect user clicks, session duration, and website navigation journeys. This system can be easily connected to a website by implementing a tracking code snippet, and the tracking tool itself is compatible with various content management systems.
Besides, Hotjar gives users access to an analytics dashboard to see and analyze clickstream events on graphs tables and view the website’s heatmap.
(Image source: Hotjar)
Hotjar is one example of a custom tracking tool that collects clickstreams and other data from your website. Other tools may differ in terms of clickstream data interpretation, additional functions, and so on.
2 Third-party data sources are indispensable for large-scale clickstream analysis beyond your website. Solutions based on first-party clickstream data are usually focused on monitoring and analyzing users’ interactions with your website. They don’t offer options to track and analyze how users interact with your competitors’ websites or assess the traffic to these websites.
In contrast, with third-party clickstream data, you can analyze search terms people use to reach competitors’ websites and estimate website traffic. Besides, you can access site-wide competitor engagement data like website visit duration, bounce rate, and so on.
Third-party vendors collect clickstreams across numerous websites, store clickstream data in extensive databases, and sell the data to customers. With the help of vendors, you can access large datasets of clickstream data quickly, which is vital for extensive research or fueling your own marketing tools with actual information.
For instance, well-known enterprises like SimilarWeb or Nielsen collect vast amounts of clickstream data. Solutions like AWS Data Exchange or Snowflake can also give access to various datasets, including clickstream data. Finally, you can search for clickstream datasets or data vendors at data marketplaces like Datarade.
Getting clickstream data from third parties comes with a variety of considerations. First, third-party data is usually very expensive. Integrating even one source of clickstream data can cost a company a significant amount, not to mention the additional expenses of needing multiple sources for stable access to comprehensive insights. The reliability of clickstream data providers is also crucial. Ensuring that you receive accurate and timely data and that the vendor adheres to legal data regulations is essential.
Along with considerations regarding methods of getting clickstream data, it is also essential to take into account its limitations.
Considerations and limitations of clickstream data
➤ The accuracy of clickstream data strongly depends on the data pool’s size, robustness, and quality. A larger and more diverse sample size generally leads to more reliable insights. However, if the data pool is limited or biased, it may not accurately represent the broader population’s online behavior. This can result in skewed conclusions and potentially misleading insights. Therefore, it’s crucial to assess the characteristics and limitations of the data source before drawing conclusions.
➤ It’s important to note that clickstream data cannot be the sole source for estimating search volume or other online metrics. While it provides valuable information about user behavior, it should be used in combination with other data sources to get a complete picture of online performance and user engagement.
➤ Privacy concerns have led to the anonymization and aggregation of clickstream data. While this is necessary to protect user privacy, it can limit the granularity of insights derived from the data. Anonymization may remove specific demographic or personal identifiers, making it unreliable for any targeted analysis.
Clickstream data vendors’ reliability and ethical practices are also among the crucial factors to consider, as breaches of trust can have far-reaching consequences. For example, you may have heard about the Jumpshot controversy. Jumpshot, a subsidiary of the antivirus company Avast, was collecting user browsing data and selling it to various companies. This practice raised significant privacy concerns when it was revealed that Jumshot’s data could be easily traced back to individual users despite claims of anonymization. The backlash was substantial, leading to Jumpshot’s shutdown in early 2020.
After exploring clickstream data, its collection methods, and key considerations, it’s time to move forward and discover various applications of this data in online marketing.
Leveraging clickstream data in online marketing
Clickstream data has numerous applications in online marketing, starting from user interaction analysis to data-driven competitor traffic research. Let’s examine various ways to incorporate clickstream data into marketing solutions.
Refining keyword metrics for more precise results
For SEO tool creators, clickstream data emerges as a powerful source for refining keyword metrics. Clickstream data on search queries and SERP interactions enables the estimation of metrics like search volume and traffic.
For instance, here is how clickstream data can be used to refine search volume. First, the clickstream dataset is filtered, systematized, and merged with information from other sources like Google Keyword Planner or Google Analytics. Then, using machine learning algorithms, this data is multiplied by special coefficients that can be derived from numerous factors like the correlations between the number of devices and users. After that, the refined search volume data is integrated into the SEO tool.
Various SEO tools already leverage clickstream data to provide refined keyword search volume. Moreover, certain tools display clickstream-based search volume alongside Google search volume to demonstrate the actual popularity of search queries. One example of such a tool is seoClarity. This platform features a special metric called “True Demand™” that displays estimates of search volume rate based on clickstream.
(Image source: seoClarity)
As seoClarity explains, “True Demand™” displays search volume values based on proprietary clickstream data and gives access to granular search volume data for singular, plural, and trending queries. With this feature, you can easily compare Google and clickstream search volume values and observe a search volume trend.
Optimizing website content through the user interaction analysis
Utilizing clickstream insights is vital for website owners who want to understand how users interact with their website, identify potential bottlenecks in the customer journey, and optimize website content to drive more conversions.
The recent Google leak emphasized the importance of real user interaction data, confirming that Google uses click-based metrics to adjust website rankings. Here are examples of Google metrics disclosed in the leak:
- ClicksGood – quantity of clicks representing a positive experience;
- ClicksBad – quantity of clicks representing a negative experience;
- Dwells – time users spend on a page after clicking on a search result;
- PositiveReactionBoostScore – final ranking score based on positive interactions;
- NegativeReactionBoostScore – final ranking score based on negative interactions.
Internal Google algorithms calculate these metrics and use clickstream data directly from Google Chrome users. Thus, Google pays special attention to the quantity and quality of user interactions with a website.
Complying with these new Google metrics requires paying extra attention to user experience on your website. With the help of clickstream insights, it is now possible to do that in a data-driven way. For instance, you can start with tools provided by Google, such as Google Analytics and Google Search Console.
Google Analytics offers insights into engagement metrics such as bounce rate, page views, and average session duration. By integrating Google Tag Manager with Google Analytics, you can create tags that analyze specific user actions, including clicks on particular website buttons and video replays. Google Search Console provides visibility into your website’s impressions, the search queries that drive traffic to your site, and your overall click-through rate.
Additionally, you can use custom first-party tracking tools to track user interactions and identify customer journey problems. One great example is Microsoft Clarity – a comprehensive and free-to-use website analytics tool. Microsoft Clarity allows you to create various types of heatmaps that show the density of user clicks and scrolls, helping you visualize which parts of a page attract the most attention.
(Image source: Microsoft Clarity)
Moreover, in Microsoft Clarity, you can replay user sessions to see how users navigate your site and where they bounce back or drop out of your funnel.
(Image source: Microsoft Clarity)
You can quickly identify areas of your website that cause frustration and damage to user experience. With this information, you can improve page content with pinpoint accuracy.
Analyzing competitor traffic with precise engagement data
With access to third-party clickstream data, businesses can accurately analyze competitor traffic. Third-party clickstreams offer a variety of applications in competitor analysis:
- Analyze clickstream traffic driven by specific keywords to a competitor’s website and compare it with your website’s keyword performance.
- Obtain estimates of overall website traffic volume based on all ranking keywords.
- Gain insights into the demographic composition of a competitor’s audience, including gender and age distribution.
- Compare key performance indicators such as website visit duration, bounce rate, and other session-related metrics between your site and your competitors.
The opportunities for competitor analysis with clickstream data can go far beyond it, and various marketing tool providers are already trying to maximize the benefits of clickstreams in their solutions.
For instance, SimilarWeb relies on clickstream to give customers detailed information on site-wide competitor engagement metrics and compare multiple websites simultaneously.
(Image source: SimilarWeb)
This tool lets you analyze and compare engagement metrics across multiple websites.
Clickstream data proves to be a true gem in online marketing, reshaping approaches to digital strategy, user experience optimization, and competitive analysis. At DataForSEO, we consistently stay ahead of online marketing trends and have developed various solutions to help you easily harness the power of clickstream data. Let’s explore how you can access these valuable clickstream insights using the DataForSEO toolkit.
Unlocking clickstream data insights with the DataForSEO APIs
In DataForSEO, we introduced various solutions that leverage clickstream data to enhance your online marketing analytics. First, our Keyword Data API now features new clickstream-based endpoints – Bulk Clickstream Search Volume and Global Search Volume.
Bulk Clickstream Search Volume provides search volume data for up to 1,000 keywords in a single request and monthly search trends over the past 12 months. To calculate this clickstream-based search volume, we analyze and refine collected clickstream data, creating a dataset of clickstream events. These events are then multiplied by specific coefficients to estimate the number of monthly searches made for a particular keyword. These coefficients are derived from various factors, the primary factor being the ratio between the number of devices and the overall number of internet users.
With the Global Search Volume, you can get the total number of times a specific keyword or phrase is searched globally and a breakdown of search volume distribution by country. Like the Bulk Clickstream Search Volume, this endpoint uses clickstream data, aggregating search volume values across different countries to calculate the global total.
Moreover, we integrated clickstream-based metrics into several endpoints of DataForSEO Labs API, providing valuable insights to enhance your online marketing analytics. This API now offers clickstream-derived keyword search volume, gender and age distribution of search volume, and estimated traffic volume to domains or specific pages. The following endpoints of DataForSEO Labs API now feature clickstream metrics:
- Categories For Domain
- Domain Intersection
- Keyword Ideas
- Keywords For Site
- Keywords For Categories
- Keyword Suggestions
- Related Keywords
- Historical Search Volume
- Top Searches
- Ranked Keywords
- Page Intersection
- Subdomains
- Relevant Pages
- Competitors Domain
- Historical Rank Overview
In these endpoints, you will encounter the following clickstream-based metrics:
clickstream_keyword_infoobject that provides clickstream data on the related keyword. In particular, it contains the clickstream search volume and its distribution by gender and age.clickstream_etvmetric that displays the approximate number of monthly visits that specific keywords can bring to a target website.clickstream_gender_distributionandclickstream_age_distributionrepresent the distribution of the clickstream traffic by gender and age.
To calculate these metrics, we leverage third-party clickstream data from reliable providers, refine it, and combine this data with a special multiplier derived from numerous factors. Using our sophisticated approach to calculate clickstream-based metrics, we assure you that you will always have the most accurate data available.
You can learn more about how we calculate clickstream-based metrics in our dedicated Help Center article.
Now, let’s move on to examples of using clickstream insights with DataForSEO Labs API endpoints.
Fetch clickstream keyword data
Let’s assume you are conducting keyword research and want to expand your keyword list with relevant search queries. Additionally, you want to access the clickstream search volume of new keywords. For this purpose, you can use the Keyword Suggestions endpoint of DataForSEO Labs API, which provides search queries that include the specified seed keyword.
You can quickly learn how to use DataForSEO APIs in this blog post.
First, make a call to the Keyword Suggestions endpoint:
POST https://api.dataforseo.com/v3/dataforseo_labs/google/keyword_suggestions/live
In the request, specify the seed keyword, location, and language, and don’t forget to set the parameter include_clickstream_data to true. To get keywords with clickstream search volume above 200 and difficulty level below 50, apply filters: ["clickstream_keyword_info.search_volume",">",200], “and”, ["keyword_properties.keyword_difficulty"," in the filters array. Then, add “order_by” field with ["clickstream_keyword_info.search_volume,desc"] filter to get keywords with the highest clickstream search volume. Finally, with the limit parameter, you can specify the number of returned keyword suggestions in the API response.
The request should be structured like this:
[
{
"keyword": "seo tool",
"location_code": 2840,
"language_code": "en",
"include_serp_info": true,
"include_clickstream_data": true,
"filters": [
[
"clickstream_keyword_info.search_volume",
">",
200
],
"and",
[
"keyword_properties.keyword_difficulty",
"
The result will return as follows:
{
"version": "0.1.20240626",
"status_code": 20000,
"status_message": "Ok.",
"time": "0.1433 sec.",
"cost": 0.0205,
"tasks_count": 1,
"tasks_error": 0,
"tasks": [
{
"id": "07301521-1535-0399-0000-03a7b93f8ee1",
"status_code": 20000,
"status_message": "Ok.",
"time": "0.0890 sec.",
"cost": 0.0205,
"result_count": 1,
"path": [
"v3",
"dataforseo_labs",
"google",
"keyword_suggestions",
"live"
],
"data": {
"api": "dataforseo_labs",
"function": "keyword_suggestions",
"se_type": "google",
"keyword": "seo tool",
"location_code": 2840,
"language_code": "en",
"include_serp_info": true,
"include_clickstream_data": true,
"filters": [
[
"clickstream_keyword_info.search_volume",
">",
200
],
"and",
[
"keyword_properties.keyword_difficulty",
"
In the items array, you can find the clickstream_keyword_info object that contains the keyword's search volume, gender_distribution, and age_distribution of the clickstream search volume, as well as monthly_searches of the keyword.
Discover the gender and age distribution of search volume
Suppose you’re searching for new keywords for your online makeup shop. However, you want to get search terms that are popular among the female audience within the age range of 25-34. You can use the Keyword Ideas endpoint of DataForSEO Labs API to find them.
First, call the Keyword Ideas endpoint:
POST https://api.dataforseo.com/v3/dataforseo_labs/google/keyword_ideas/live
After specifying the seed keyword, location, and language, add the following filters in the filters array to target search terms with a search volume above 200 and popular among women within the age range of 25-34:
["clickstream_keyword_info.search_volume", ">", 200],
"and",
["clickstream_keyword_info.gender_distribution.female", ">", 60],
"and",
["clickstream_keyword_info.age_distribution.25-34", ">", 60]
Then, order keywords by clickstream search volume using "order_by":["clickstream_keyword_info.search_volume,desc"]
Request example:
[
{
"keywords": [
"makeup"
],
"location_code": 2840,
"language_code": "en",
"include_serp_info": true,
"include_clickstream_data": true,
"filters": [
[
"clickstream_keyword_info.search_volume",
">",
200
],
"and",
[
"clickstream_keyword_info.gender_distribution.female",
">",
60
],
"and",
[
"clickstream_keyword_info.age_distribution.25-34",
">",
60
]
],
"order_by": [
"clickstream_keyword_info.search_volume,desc"
],
"limit": 10
}
]
The result will return as follows:
{
"version": "0.1.20240626",
"status_code": 20000,
"status_message": "Ok.",
"time": "0.2113 sec.",
"cost": 0.021,
"tasks_count": 1,
"tasks_error": 0,
"tasks": [
{
"id": "07301524-1535-0400-0000-039bca9e3000",
"status_code": 20000,
"status_message": "Ok.",
"time": "0.1550 sec.",
"cost": 0.021,
"result_count": 1,
"path": [
"v3",
"dataforseo_labs",
"google",
"keyword_ideas",
"live"
],
"data": {
"api": "dataforseo_labs",
"function": "keyword_ideas",
"se_type": "google",
"keywords": [
"makeup"
],
"location_code": 2840,
"language_code": "en",
"include_serp_info": true,
"include_clickstream_data": true,
"filters": [
[
"clickstream_keyword_info.search_volume",
">",
200
],
"and",
[
"clickstream_keyword_info.gender_distribution.female",
">",
60
],
"and",
[
"clickstream_keyword_info.age_distribution.25-34",
">",
60
]
],
"order_by": [
"clickstream_keyword_info.search_volume,desc"
],
"limit": 10
},
"result": [
{
"se_type": "google",
"seed_keywords": [
"makeup"
],
"location_code": 2840,
"language_code": "en",
"total_count": 204,
"items_count": 10,
"offset": 0,
"offset_token": "eyJDdXJyZW50T2Zmc2V0IjoxMCwiUmVxdWVzdERhdGEiOnsia2V5d29yZHMiOlsibWFrZXVwIl0sImxvY2F0aW9uIjoyODQwLCJsYW5ndWFnZSI6ImVuIiwiY2xvc2VseV92YXJpYW50cyI6ZmFsc2UsIm5ld2VzdCI6ZmFsc2UsImV4dGVuZGVkIjpmYWxzZSwibG9hZF9zZXJwX2luZm8iOnRydWUsImF1dG9jb3JyZWN0Ijp0cnVlLCJJc09sZCI6ZmFsc2UsInNlYXJjaF9hZnRlcl90b2tlbiI6bnVsbCwiaWdub3JlX3N5bm9ueW1zIjpmYWxzZSwic2VhcmNoX2VuZ2luZSI6Imdvb2dsZSIsInVzZV9uZXdfY2F0ZWdvcmllcyI6dHJ1ZSwib3JkZXJfYnkiOnsib3JkZXJfZmllbGQiOiJjbGlja3N0cmVhbV9rZXl3b3JkX2luZm8uc2VhcmNoX3ZvbHVtZSIsIm9yZGVyX3R5cGUiOiJEZXNjIiwibmV4dCI6bnVsbH0sImxpbWl0IjoxMCwib2Zmc2V0IjowLCJhaWQiOjE1MzV9LCJSYXdRdWVyeSI6eyJ0eXBlIjoiYW5kIiwibGVmdCI6eyJmaWVsZCI6ImNsaWNrc3RyZWFtX2tleXdvcmRfaW5mby5zZWFyY2hfdm9sdW1lIiwidHlwZSI6Imd0IiwidmFsdWUiOjIwMH0sInJpZ2h0Ijp7InR5cGUiOiJhbmQiLCJsZWZ0Ijp7ImZpZWxkIjoiY2xpY2tzdHJlYW1fa2V5d29yZF9pbmZvLmdlbmRlcl9kaXN0cmlidXRpb24uZiIsInR5cGUiOiJndCIsInZhbHVlIjo2MH0sInJpZ2h0Ijp7ImZpZWxkIjoiY2xpY2tzdHJlYW1fa2V5d29yZF9pbmZvLmFnZV9kaXN0cmlidXRpb24uMjUtMzQiLCJ0eXBlIjoiZ3QiLCJ2YWx1ZSI6NjB9fX0sIklkIjoiNDUxNGE3NmUtNjVhOS00NzJhLWFmZjUtYzgwZjBhYzc0MmJlIiwiU2VhcmNoQWZ0ZXJEYXRhIjpbODc5LCI5NGE2MzZjOS0xY2E5LWE4ZTAtMTdlMi02MDYyY2VhMTczZDQiXX0=",
"items": [
{
"se_type": "google",
"keyword": "em cosmetics",
"location_code": 2840,
"language_code": "en",
"keyword_info": {
"se_type": "google",
"last_updated_time": "2024-07-12 12:32:56 +00:00",
"competition": 1,
"competition_level": "HIGH",
"cpc": 0.38,
"search_volume": 12100,
"low_top_of_page_bid": 1.78,
"high_top_of_page_bid": 55.29,
"categories": [
10005,
10054,
10324,
10331,
11420
],
"monthly_searches": [
{
"year": 2024,
"month": 6,
"search_volume": 9900
},
{
"year": 2024,
"month": 5,
"search_volume": 9900
},
{
"year": 2024,
"month": 4,
"search_volume": 9900
},
{
"year": 2024,
"month": 3,
"search_volume": 12100
},
{
"year": 2024,
"month": 2,
"search_volume": 12100
},
{
"year": 2024,
"month": 1,
"search_volume": 14800
},
{
"year": 2023,
"month": 12,
"search_volume": 12100
},
{
"year": 2023,
"month": 11,
"search_volume": 22200
},
{
"year": 2023,
"month": 10,
"search_volume": 12100
},
{
"year": 2023,
"month": 9,
"search_volume": 9900
},
{
"year": 2023,
"month": 8,
"search_volume": 12100
},
{
"year": 2023,
"month": 7,
"search_volume": 9900
}
]
},
"clickstream_keyword_info": {
"search_volume": 3809,
"last_updated_time": "2024-07-04 10:00:55 +00:00",
"gender_distribution": {
"female": 61,
"male": 39
},
"age_distribution": {
"18-24": 57,
"25-34": 92,
"35-44": 8,
"45-54": 26,
"55-64": null
},
"monthly_searches": [
{
"year": 2024,
"month": 6,
"search_volume": 3810
},
{
"year": 2024,
"month": 5,
"search_volume": 3940
},
{
"year": 2024,
"month": 4,
"search_volume": 3510
},
{
"year": 2024,
"month": 3,
"search_volume": 7530
},
{
"year": 2024,
"month": 2,
"search_volume": 5050
},
{
"year": 2024,
"month": 1,
"search_volume": 4890
},
{
"year": 2023,
"month": 12,
"search_volume": 3890
},
{
"year": 2023,
"month": 11,
"search_volume": 9340
},
{
"year": 2023,
"month": 10,
"search_volume": 5050
},
{
"year": 2023,
"month": 9,
"search_volume": 3540
},
{
"year": 2023,
"month": 8,
"search_volume": 5940
},
{
"year": 2023,
"month": 7,
"search_volume": 4500
}
]
},
"keyword_properties": {
"se_type": "google",
"core_keyword": null,
"synonym_clustering_algorithm": "text_processing",
"keyword_difficulty": 21,
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"daily_impressions_max": 37.02,
"daily_impressions_average": 33.65,
"daily_clicks_min": 0.85,
"daily_clicks_max": 1.04,
"daily_clicks_average": 0.94,
"daily_cost_min": 417.67,
"daily_cost_max": 510.48,
"daily_cost_average": 464.07
},
"serp_info": {
"se_type": "google",
"check_url": "https://www.google.com/search?q=estee%20lauder%20brands&num=100&hl=en&gl=US&gws_rd=cr&ie=UTF-8&oe=UTF-8&glp=1&uule=w+CAIQIFISCQs2MuSEtepUEUK33kOSuTsc",
"serp_item_types": [
"found_on_web",
"organic",
"people_also_ask",
"featured_snippet",
"images",
"related_searches",
"knowledge_graph"
],
"se_results_count": 25700000,
"last_updated_time": "2024-06-23 13:46:12 +00:00",
"previous_updated_time": "2024-05-13 11:08:03 +00:00"
},
"avg_backlinks_info": {
"se_type": "google",
"backlinks": 931.5,
"dofollow": 648.7,
"referring_pages": 780.1,
"referring_domains": 196.8,
"referring_main_domains": 165.6,
"rank": 171.6,
"main_domain_rank": 569.9,
"last_updated_time": "2024-06-23 13:48:08 +00:00"
},
"search_intent_info": {
"se_type": "google",
"main_intent": "transactional",
"foreign_intent": null,
"last_updated_time": "2023-03-03 19:04:52 +00:00"
}
}
]
}
]
}
]
}
You can find the values in the gender distribution and age distribution objects within the clickstream_keyword_info object.
Fetch clickstream search volume for multiple keywords
If you want to get precise search volume data for multiple keywords simultaneously, the Bulk Clickstream Search Volume endpoint of Keyword Data API is the best solution. This endpoint is particularly useful for analyzing the search volume of numerous keywords in extensive keyword lists. With the capacity of up to 1000 keywords in one API request, you can quickly get search volume data for the most complex keyword sets.
To get the clickstream search volume, make a call to the endpoint first:
POST: https://api.dataforseo.com/v3/keywords_data/clickstream_data/bulk_search_volume/live
Then, specify up to 1000 keywords in the keywords array. Don’t forget to set the location parameters with location_name or location_code.
Your request should be structured as in the following example:
[
{
"location_code": 2840,
"keywords": [
"iphone 15",
"iphone 15 pro",
"iphone 15 pro max",
"macbook air m3",
"ipad pro"
]
}
]
The result will return as follows:
{
"version": "0.1.20240801",
"status_code": 20000,
"status_message": "Ok.",
"time": "0.2771 sec.",
"cost": 0.0105,
"tasks_count": 1,
"tasks_error": 0,
"tasks": [
{
"id": "08221738-1535-0591-0000-f085b41749f6",
"status_code": 20000,
"status_message": "Ok.",
"time": "0.2175 sec.",
"cost": 0.0105,
"result_count": 1,
"path": [
"v3",
"keywords_data",
"clickstream_data",
"bulk_search_volume",
"live"
],
"data": {
"api": "keywords_data",
"function": "bulk_search_volume",
"se": "clickstream_data",
"location_code": 2840,
"keywords": [
"iphone 15",
"iphone 15 pro",
"iphone 15 pro max",
"macbook air m3",
"ipad pro"
]
},
"result": [
{
"location_code": 2840,
"items_count": 5,
"items": [
{
"keyword": "iphone 15",
"search_volume": 971481,
"monthly_searches": [
{
"year": 2024,
"month": 7,
"search_volume": 971481
},
{
"year": 2024,
"month": 6,
"search_volume": 1031124
},
{
"year": 2024,
"month": 5,
"search_volume": 1031975
},
{
"year": 2024,
"month": 4,
"search_volume": 1024573
},
{
"year": 2024,
"month": 3,
"search_volume": 1010790
},
{
"year": 2024,
"month": 2,
"search_volume": 1010364
},
{
"year": 2024,
"month": 1,
"search_volume": 999984
},
{
"year": 2023,
"month": 12,
"search_volume": 966801
},
{
"year": 2023,
"month": 11,
"search_volume": 982684
},
{
"year": 2023,
"month": 10,
"search_volume": 984742
},
{
"year": 2023,
"month": 9,
"search_volume": 972377
},
{
"year": 2023,
"month": 8,
"search_volume": 562905
}
]
},
{
"keyword": "iphone 15 pro max",
"search_volume": 406017,
"monthly_searches": [
{
"year": 2024,
"month": 7,
"search_volume": 406017
},
{
"year": 2024,
"month": 6,
"search_volume": 402784
},
{
"year": 2024,
"month": 5,
"search_volume": 373686
},
{
"year": 2024,
"month": 4,
"search_volume": 351224
},
{
"year": 2024,
"month": 3,
"search_volume": 328676
},
{
"year": 2024,
"month": 2,
"search_volume": 314127
},
{
"year": 2024,
"month": 1,
"search_volume": 296430
},
{
"year": 2023,
"month": 12,
"search_volume": 269373
},
{
"year": 2023,
"month": 11,
"search_volume": 255203
},
{
"year": 2023,
"month": 10,
"search_volume": 234942
},
{
"year": 2023,
"month": 9,
"search_volume": 193168
},
{
"year": 2023,
"month": 8,
"search_volume": 53455
}
]
},
{
"keyword": "iphone 15 pro",
"search_volume": 309022,
"monthly_searches": [
{
"year": 2024,
"month": 7,
"search_volume": 309022
},
{
"year": 2024,
"month": 6,
"search_volume": 309533
},
{
"year": 2024,
"month": 5,
"search_volume": 287922
},
{
"year": 2024,
"month": 4,
"search_volume": 271160
},
{
"year": 2024,
"month": 3,
"search_volume": 250910
},
{
"year": 2024,
"month": 2,
"search_volume": 238914
},
{
"year": 2024,
"month": 1,
"search_volume": 223599
},
{
"year": 2023,
"month": 12,
"search_volume": 201987
},
{
"year": 2023,
"month": 11,
"search_volume": 191196
},
{
"year": 2023,
"month": 10,
"search_volume": 173365
},
{
"year": 2023,
"month": 9,
"search_volume": 147108
},
{
"year": 2023,
"month": 8,
"search_volume": 41082
}
]
},
{
"keyword": "ipad pro",
"search_volume": 238658,
"monthly_searches": [
{
"year": 2024,
"month": 7,
"search_volume": 238658
},
{
"year": 2024,
"month": 6,
"search_volume": 250145
},
{
"year": 2024,
"month": 5,
"search_volume": 244954
},
{
"year": 2024,
"month": 4,
"search_volume": 219174
},
{
"year": 2024,
"month": 3,
"search_volume": 216707
},
{
"year": 2024,
"month": 2,
"search_volume": 217643
},
{
"year": 2024,
"month": 1,
"search_volume": 221216
},
{
"year": 2023,
"month": 12,
"search_volume": 218494
},
{
"year": 2023,
"month": 11,
"search_volume": 214330
},
{
"year": 2023,
"month": 10,
"search_volume": 205093
},
{
"year": 2023,
"month": 9,
"search_volume": 203186
},
{
"year": 2023,
"month": 8,
"search_volume": 194482
}
]
},
{
"keyword": "macbook air m3",
"search_volume": 46795,
"monthly_searches": [
{
"year": 2024,
"month": 7,
"search_volume": 46795
},
{
"year": 2024,
"month": 6,
"search_volume": 44583
},
{
"year": 2024,
"month": 5,
"search_volume": 38798
},
{
"year": 2024,
"month": 4,
"search_volume": 34458
},
{
"year": 2024,
"month": 3,
"search_volume": 27567
},
{
"year": 2024,
"month": 2,
"search_volume": 19654
},
{
"year": 2024,
"month": 1,
"search_volume": 16591
},
{
"year": 2023,
"month": 12,
"search_volume": 12252
},
{
"year": 2023,
"month": 11,
"search_volume": 10698
},
{
"year": 2023,
"month": 10,
"search_volume": 8401
},
{
"year": 2023,
"month": 9,
"search_volume": 5444
},
{
"year": 2023,
"month": 8,
"search_volume": 5285
}
]
}
]
}
]
}
]
}
The items array in the response contains objects with the clickstream search volume for each keyword. The search_volume field indicates the current search volume based on clickstream data for a specific keyword. Additionally, the monthly_searches array within the same object presents the keyword's monthly clickstream search volumes for the past 12 months.
Analyze the clickstream traffic volume of your competitors
Let’s say you want to conduct an in-depth traffic analysis of the competitor domains from organic and paid search. In addition to that, you want to know the amount of clickstream traffic competitors' domains get. With the Competitors Domain endpoint of DataForSEO Labs API, you can assess the clickstream estimated traffic volume of your competitors' websites.
To do that, call the Competitors Domain endpoint.
POST https://api.dataforseo.com/v3/dataforseo_labs/google/competitors_domain/live
In the request, specify your website’s domain and write down competitors’ domains in the intersecting_domains field. Remember to specify the include_clickstream_data parameter.
Request example:
[
{
"target": "newmouth.com",
"intersecting_domains": [
"dentaly.org",
"health.com",
"trysnow.com"
],
"language_name": "English",
"location_code": 2840,
"include_clickstream_data": true,
"limit": 3
}
]
Response example:
{
"version": "0.1.20240626",
"status_code": 20000,
"status_message": "Ok.",
"time": "2.9098 sec.",
"cost": 0.0203,
"tasks_count": 1,
"tasks_error": 0,
"tasks": [
{
"id": "07301522-1535-0386-0000-6bc79bcc39a8",
"status_code": 20000,
"status_message": "Ok.",
"time": "2.8520 sec.",
"cost": 0.0203,
"result_count": 1,
"path": [
"v3",
"dataforseo_labs",
"google",
"competitors_domain",
"live"
],
"data": {
"api": "dataforseo_labs",
"function": "competitors_domain",
"se_type": "google",
"target": "newmouth.com",
"intersecting_domains": [
"dentaly.org",
"health.com",
"trysnow.com"
],
"language_name": "English",
"location_code": 2840,
"include_clickstream_data": true,
"limit": 3
},
"result": [
{
"se_type": "google",
"target": "newmouth.com",
"location_code": 2840,
"language_code": "en",
"total_count": 1833,
"items_count": 3,
"items": [
{
"se_type": "google",
"domain": "dentaly.org",
"avg_position": 64.66666666666667,
"sum_position": 10282,
"intersections": 159,
"full_domain_metrics": {
"organic": {
"pos_1": 0,
"pos_2_3": 8,
"pos_4_10": 39,
"pos_11_20": 391,
"pos_21_30": 835,
"pos_31_40": 1002,
"pos_41_50": 992,
"pos_51_60": 1148,
"pos_61_70": 1234,
"pos_71_80": 1289,
"pos_81_90": 1320,
"pos_91_100": 1125,
"etv": 12058.740109547973,
"impressions_etv": 1468.0760931707919,
"count": 9383,
"estimated_paid_traffic_cost": 64451.99886273214,
"is_new": 2524,
"is_up": 2278,
"is_down": 4363,
"is_lost": 7528,
"clickstream_etv": 225.74081000000004,
"clickstream_gender_distribution": {
"female": 49,
"male": 49
},
"clickstream_age_distribution": {
"18-24": 42,
"25-34": 10,
"35-44": 17,
"45-54": 29,
"55-64": 0
}
},
"paid": {
"pos_1": 0,
"pos_2_3": 0,
"pos_4_10": 0,
"pos_11_20": 0,
"pos_21_30": 0,
"pos_31_40": 0,
"pos_41_50": 0,
"pos_51_60": 0,
"pos_61_70": 0,
"pos_71_80": 0,
"pos_81_90": 0,
"pos_91_100": 0,
"etv": 0,
"impressions_etv": 0,
"count": 0,
"estimated_paid_traffic_cost": 0,
"is_new": 0,
"is_up": 0,
"is_down": 0,
"is_lost": 0,
"clickstream_etv": 0,
"clickstream_gender_distribution": {
"female": 0,
"male": 0
},
"clickstream_age_distribution": {
"18-24": 0,
"25-34": 0,
"35-44": 0,
"45-54": 0,
"55-64": 0
}
},
"local_pack": null,
"featured_snippet": null
},
"metrics": {
"organic": {
"pos_1": 0,
"pos_2_3": 0,
"pos_4_10": 1,
"pos_11_20": 17,
"pos_21_30": 18,
"pos_31_40": 13,
"pos_41_50": 21,
"pos_51_60": 21,
"pos_61_70": 22,
"pos_71_80": 19,
"pos_81_90": 10,
"pos_91_100": 17,
"etv": 121.01634098216891,
"impressions_etv": 32.34618016052991,
"count": 159,
"estimated_paid_traffic_cost": 829.2403031568974,
"is_new": 31,
"is_up": 54,
"is_down": 69,
"is_lost": 0,
"clickstream_etv": 1.05,
"clickstream_gender_distribution": {
"female": 0,
"male": 200
},
"clickstream_age_distribution": {
"18-24": 0,
"25-34": 100,
"35-44": 100,
"45-54": 0,
"55-64": 0
}
},
"paid": {
"pos_1": 0,
"pos_2_3": 0,
"pos_4_10": 0,
"pos_11_20": 0,
"pos_21_30": 0,
"pos_31_40": 0,
"pos_41_50": 0,
"pos_51_60": 0,
"pos_61_70": 0,
"pos_71_80": 0,
"pos_81_90": 0,
"pos_91_100": 0,
"etv": 0,
"impressions_etv": 0,
"count": 0,
"estimated_paid_traffic_cost": 0,
"is_new": 0,
"is_up": 0,
"is_down": 0,
"is_lost": 0,
"clickstream_etv": 0,
"clickstream_gender_distribution": {
"female": 0,
"male": 0
},
"clickstream_age_distribution": {
"18-24": 0,
"25-34": 0,
"35-44": 0,
"45-54": 0,
"55-64": 0
}
},
"local_pack": null,
"featured_snippet": null
},
"competitor_metrics": {
"organic": {
"pos_1": 0,
"pos_2_3": 0,
"pos_4_10": 2,
"pos_11_20": 5,
"pos_21_30": 20,
"pos_31_40": 7,
"pos_41_50": 9,
"pos_51_60": 20,
"pos_61_70": 22,
"pos_71_80": 18,
"pos_81_90": 29,
"pos_91_100": 27,
"etv": 118.25062108412385,
"impressions_etv": 31.48173012305051,
"count": 159,
"estimated_paid_traffic_cost": 822.5941328573972,
"is_new": 50,
"is_up": 25,
"is_down": 79,
"is_lost": 0,
"clickstream_etv": 1.0499999523162842,
"clickstream_gender_distribution": {
"female": 0,
"male": 200
},
"clickstream_age_distribution": {
"18-24": 0,
"25-34": 100,
"35-44": 100,
"45-54": 0,
"55-64": 0
}
},
"paid": {
"pos_1": 0,
"pos_2_3": 0,
"pos_4_10": 0,
"pos_11_20": 0,
"pos_21_30": 0,
"pos_31_40": 0,
"pos_41_50": 0,
"pos_51_60": 0,
"pos_61_70": 0,
"pos_71_80": 0,
"pos_81_90": 0,
"pos_91_100": 0,
"etv": 0,
"impressions_etv": 0,
"count": 0,
"estimated_paid_traffic_cost": 0,
"is_new": 0,
"is_up": 0,
"is_down": 0,
"is_lost": 0,
"clickstream_etv": 0,
"clickstream_gender_distribution": {
"female": 0,
"male": 0
},
"clickstream_age_distribution": {
"18-24": 0,
"25-34": 0,
"35-44": 0,
"45-54": 0,
"55-64": 0
}
},
"local_pack": null,
"featured_snippet": null
}
},
{
"se_type": "google",
"domain": "newmouth.com",
"avg_position": 53.9496855345912,
"sum_position": 8578,
"intersections": 159,
"full_domain_metrics": {
"organic": {
"pos_1": 2,
"pos_2_3": 5,
"pos_4_10": 97,
"pos_11_20": 646,
"pos_21_30": 1555,
"pos_31_40": 2452,
"pos_41_50": 3704,
"pos_51_60": 4945,
"pos_61_70": 5581,
"pos_71_80": 5678,
"pos_81_90": 5771,
"pos_91_100": 4242,
"etv": 36440.212248019874,
"impressions_etv": 1911.7211238220334,
"count": 34678,
"estimated_paid_traffic_cost": 192639.0719879492,
"is_new": 9077,
"is_up": 10150,
"is_down": 14361,
"is_lost": 16467,
"clickstream_etv": 409.87649999999996,
"clickstream_gender_distribution": {
"female": 43,
"male": 56
},
"clickstream_age_distribution": {
"18-24": 35,
"25-34": 8,
"35-44": 12,
"45-54": 26,
"55-64": 16
}
},
"paid": {
"pos_1": 0,
"pos_2_3": 3,
"pos_4_10": 0,
"pos_11_20": 0,
"pos_21_30": 0,
"pos_31_40": 0,
"pos_41_50": 0,
"pos_51_60": 0,
"pos_61_70": 0,
"pos_71_80": 0,
"pos_81_90": 0,
"pos_91_100": 0,
"etv": 119.40000009536743,
"impressions_etv": 6.119999885559082,
"count": 3,
"estimated_paid_traffic_cost": 517.7909965515137,
"is_new": 3,
"is_up": 0,
"is_down": 0,
"is_lost": 0,
"clickstream_etv": 0,
"clickstream_gender_distribution": {
"female": 0,
"male": 0
},
"clickstream_age_distribution": {
"18-24": 0,
"25-34": 0,
"35-44": 0,
"45-54": 0,
"55-64": 0
}
},
"local_pack": null,
"featured_snippet": null
},
"metrics": {
"organic": {
"pos_1": 0,
"pos_2_3": 0,
"pos_4_10": 1,
"pos_11_20": 17,
"pos_21_30": 18,
"pos_31_40": 13,
"pos_41_50": 21,
"pos_51_60": 21,
"pos_61_70": 22,
"pos_71_80": 19,
"pos_81_90": 10,
"pos_91_100": 17,
"etv": 121.01634098216891,
"impressions_etv": 32.34618016052991,
"count": 159,
"estimated_paid_traffic_cost": 829.2403031568974,
"is_new": 31,
"is_up": 54,
"is_down": 69,
"is_lost": 0,
"clickstream_etv": 1.05,
"clickstream_gender_distribution": {
"female": 0,
"male": 200
},
"clickstream_age_distribution": {
"18-24": 0,
"25-34": 100,
"35-44": 100,
"45-54": 0,
"55-64": 0
}
},
"paid": {
"pos_1": 0,
"pos_2_3": 0,
"pos_4_10": 0,
"pos_11_20": 0,
"pos_21_30": 0,
"pos_31_40": 0,
"pos_41_50": 0,
"pos_51_60": 0,
"pos_61_70": 0,
"pos_71_80": 0,
"pos_81_90": 0,
"pos_91_100": 0,
"etv": 0,
"impressions_etv": 0,
"count": 0,
"estimated_paid_traffic_cost": 0,
"is_new": 0,
"is_up": 0,
"is_down": 0,
"is_lost": 0,
"clickstream_etv": 0,
"clickstream_gender_distribution": {
"female": 0,
"male": 0
},
"clickstream_age_distribution": {
"18-24": 0,
"25-34": 0,
"35-44": 0,
"45-54": 0,
"55-64": 0
}
},
"local_pack": null,
"featured_snippet": null
},
"competitor_metrics": {
"organic": {
"pos_1": 0,
"pos_2_3": 0,
"pos_4_10": 1,
"pos_11_20": 17,
"pos_21_30": 18,
"pos_31_40": 13,
"pos_41_50": 21,
"pos_51_60": 21,
"pos_61_70": 22,
"pos_71_80": 19,
"pos_81_90": 10,
"pos_91_100": 17,
"etv": 121.01634098216891,
"impressions_etv": 32.34618016052991,
"count": 159,
"estimated_paid_traffic_cost": 829.2403031568974,
"is_new": 31,
"is_up": 54,
"is_down": 69,
"is_lost": 0,
"clickstream_etv": 1.0499999523162842,
"clickstream_gender_distribution": {
"female": 0,
"male": 200
},
"clickstream_age_distribution": {
"18-24": 0,
"25-34": 100,
"35-44": 100,
"45-54": 0,
"55-64": 0
}
},
"paid": {
"pos_1": 0,
"pos_2_3": 0,
"pos_4_10": 0,
"pos_11_20": 0,
"pos_21_30": 0,
"pos_31_40": 0,
"pos_41_50": 0,
"pos_51_60": 0,
"pos_61_70": 0,
"pos_71_80": 0,
"pos_81_90": 0,
"pos_91_100": 0,
"etv": 0,
"impressions_etv": 0,
"count": 0,
"estimated_paid_traffic_cost": 0,
"is_new": 0,
"is_up": 0,
"is_down": 0,
"is_lost": 0,
"clickstream_etv": 0,
"clickstream_gender_distribution": {
"female": 0,
"male": 0
},
"clickstream_age_distribution": {
"18-24": 0,
"25-34": 0,
"35-44": 0,
"45-54": 0,
"55-64": 0
}
},
"local_pack": null,
"featured_snippet": null
}
},
{
"se_type": "google",
"domain": "health.com",
"avg_position": 39.503144654088054,
"sum_position": 6281,
"intersections": 159,
"full_domain_metrics": {
"organic": {
"pos_1": 26775,
"pos_2_3": 81332,
"pos_4_10": 343117,
"pos_11_20": 423391,
"pos_21_30": 311803,
"pos_31_40": 340417,
"pos_41_50": 306924,
"pos_51_60": 276116,
"pos_61_70": 254073,
"pos_71_80": 232255,
"pos_81_90": 212110,
"pos_91_100": 154517,
"etv": 66899733.02550565,
"impressions_etv": 2263241.271597644,
"count": 2962839,
"estimated_paid_traffic_cost": 76323304.81425516,
"is_new": 842717,
"is_up": 978337,
"is_down": 955427,
"is_lost": 587684,
"clickstream_etv": 624076.5407002005,
"clickstream_gender_distribution": {
"female": 44,
"male": 55
},
"clickstream_age_distribution": {
"18-24": 33,
"25-34": 12,
"35-44": 13,
"45-54": 27,
"55-64": 12
}
},
"paid": {
"pos_1": 25,
"pos_2_3": 28,
"pos_4_10": 10,
"pos_11_20": 0,
"pos_21_30": 0,
"pos_31_40": 0,
"pos_41_50": 0,
"pos_51_60": 0,
"pos_61_70": 0,
"pos_71_80": 0,
"pos_81_90": 0,
"pos_91_100": 0,
"etv": 408.55499970912933,
"impressions_etv": 324.7427608370781,
"count": 63,
"estimated_paid_traffic_cost": 686.7624353319407,
"is_new": 63,
"is_up": 0,
"is_down": 0,
"is_lost": 107,
"clickstream_etv": 32.65,
"clickstream_gender_distribution": {
"female": 25,
"male": 75
},
"clickstream_age_distribution": {
"18-24": 0,
"25-34": 25,
"35-44": 75,
"45-54": 0,
"55-64": 0
}
},
"local_pack": null,
"featured_snippet": null
},
"metrics": {
"organic": {
"pos_1": 0,
"pos_2_3": 0,
"pos_4_10": 1,
"pos_11_20": 17,
"pos_21_30": 18,
"pos_31_40": 13,
"pos_41_50": 21,
"pos_51_60": 21,
"pos_61_70": 22,
"pos_71_80": 19,
"pos_81_90": 10,
"pos_91_100": 17,
"etv": 121.01634098216891,
"impressions_etv": 32.34618016052991,
"count": 159,
"estimated_paid_traffic_cost": 829.2403031568974,
"is_new": 31,
"is_up": 54,
"is_down": 69,
"is_lost": 0,
"clickstream_etv": 1.05,
"clickstream_gender_distribution": {
"female": 0,
"male": 200
},
"clickstream_age_distribution": {
"18-24": 0,
"25-34": 100,
"35-44": 100,
"45-54": 0,
"55-64": 0
}
},
"paid": {
"pos_1": 0,
"pos_2_3": 0,
"pos_4_10": 0,
"pos_11_20": 0,
"pos_21_30": 0,
"pos_31_40": 0,
"pos_41_50": 0,
"pos_51_60": 0,
"pos_61_70": 0,
"pos_71_80": 0,
"pos_81_90": 0,
"pos_91_100": 0,
"etv": 0,
"impressions_etv": 0,
"count": 0,
"estimated_paid_traffic_cost": 0,
"is_new": 0,
"is_up": 0,
"is_down": 0,
"is_lost": 0,
"clickstream_etv": 0,
"clickstream_gender_distribution": {
"female": 0,
"male": 0
},
"clickstream_age_distribution": {
"18-24": 0,
"25-34": 0,
"35-44": 0,
"45-54": 0,
"55-64": 0
}
},
"local_pack": null,
"featured_snippet": null
},
"competitor_metrics": {
"organic": {
"pos_1": 1,
"pos_2_3": 2,
"pos_4_10": 13,
"pos_11_20": 27,
"pos_21_30": 26,
"pos_31_40": 25,
"pos_41_50": 18,
"pos_51_60": 13,
"pos_61_70": 9,
"pos_71_80": 10,
"pos_81_90": 8,
"pos_91_100": 7,
"etv": 201.5090589635074,
"impressions_etv": 36.23634017445147,
"count": 159,
"estimated_paid_traffic_cost": 996.3282509827986,
"is_new": 37,
"is_up": 67,
"is_down": 48,
"is_lost": 0,
"clickstream_etv": 1.0499999523162842,
"clickstream_gender_distribution": {
"female": 0,
"male": 200
},
"clickstream_age_distribution": {
"18-24": 0,
"25-34": 100,
"35-44": 100,
"45-54": 0,
"55-64": 0
}
},
"paid": {
"pos_1": 0,
"pos_2_3": 0,
"pos_4_10": 0,
"pos_11_20": 0,
"pos_21_30": 0,
"pos_31_40": 0,
"pos_41_50": 0,
"pos_51_60": 0,
"pos_61_70": 0,
"pos_71_80": 0,
"pos_81_90": 0,
"pos_91_100": 0,
"etv": 0,
"impressions_etv": 0,
"count": 0,
"estimated_paid_traffic_cost": 0,
"is_new": 0,
"is_up": 0,
"is_down": 0,
"is_lost": 0,
"clickstream_etv": 0,
"clickstream_gender_distribution": {
"female": 0,
"male": 0
},
"clickstream_age_distribution": {
"18-24": 0,
"25-34": 0,
"35-44": 0,
"45-54": 0,
"55-64": 0
}
},
"local_pack": null,
"featured_snippet": null
}
}
]
}
]
}
]
}
In the full_domain_metrics object, you can find the clickstream_etv field with the clickstream estimated traffic value. Additionally, you can find clickstream_gender_distribution and clickstream_age_distribution objects that show the breakdown of clickstream estimated traffic volume by gender and age.
Get the global search volume and its distribution by country
Suppose you want to adjust your SEO or content strategy for different markets and find new opportunities in specific regions. To do that, you plan to get the worldwide search volume of targeted keywords and the distribution of search volume by various countries. The Global Search Volume of Keyword Data API makes this task feasible and easy.
First, call the Global Search Volume endpoint:
POST: https://api.dataforseo.com/v3/keywords_data/clickstream_data/global_search_volume/live
Then, specify your keywords in the keywords array. You can specify up to 1000 keywords in a single request.
Request example:
[
{
"keywords": [
"seo tool",
"keyword tool",
"seo guide",
"marketing campaign"
]
}
]
Response example:
{
"version": "0.1.20240801",
"status_code": 20000,
"status_message": "Ok.",
"time": "0.2121 sec.",
"cost": 0.15,
"tasks_count": 1,
"tasks_error": 0,
"tasks": [
{
"id": "08221739-1535-0592-0000-f82a9c738917",
"status_code": 20000,
"status_message": "Ok.",
"time": "0.1407 sec.",
"cost": 0.15,
"result_count": 1,
"path": [
"v3",
"keywords_data",
"clickstream_data",
"global_search_volume",
"live"
],
"data": {
"api": "keywords_data",
"function": "global_search_volume",
"se": "clickstream_data",
"keywords": [
"seo tool",
"keyword tool",
"seo guide",
"marketing campaign"
]
},
"result": [
{
"items_count": 4,
"items": [
{
"keyword": "keyword tool",
"search_volume": 300262,
"country_distribution": [
{
"country_iso_code": "IN",
"search_volume": 47973,
"percentage": 15.97716
},
{
"country_iso_code": "TR",
"search_volume": 29685,
"percentage": 9.88662
},
{
"country_iso_code": "DE",
"search_volume": 29610,
"percentage": 9.86139
},
{
"country_iso_code": "US",
"search_volume": 24981,
"percentage": 8.31973
},
{
"country_iso_code": "ID",
"search_volume": 20160,
"percentage": 6.71414
},
{
"country_iso_code": "VN",
"search_volume": 19031,
"percentage": 6.33824
},
{
"country_iso_code": "PK",
"search_volume": 15600,
"percentage": 5.19546
},
{
"country_iso_code": "BD",
"search_volume": 12666,
"percentage": 4.21854
},
{
"country_iso_code": "MA",
"search_volume": 8163,
"percentage": 2.71868
},
{
"country_iso_code": "BR",
"search_volume": 7646,
"percentage": 2.5465
},
{
"country_iso_code": "EG",
"search_volume": 6866,
"percentage": 2.28689
},
{
"country_iso_code": "MX",
"search_volume": 6549,
"percentage": 2.18112
},
{
"country_iso_code": "GB",
"search_volume": 5890,
"percentage": 1.9617
},
{
"country_iso_code": "ES",
"search_volume": 5477,
"percentage": 1.82418
},
{
"country_iso_code": "IT",
"search_volume": 3862,
"percentage": 1.28652
},
{
"country_iso_code": "TH",
"search_volume": 3644,
"percentage": 1.21372
},
{
"country_iso_code": "FR",
"search_volume": 3438,
"percentage": 1.14519
},
{
"country_iso_code": "NL",
"search_volume": 2808,
"percentage": 0.93529
},
{
"country_iso_code": "JP",
"search_volume": 2800,
"percentage": 0.93252
},
{
"country_iso_code": "PH",
"search_volume": 2075,
"percentage": 0.69123
},
{
"country_iso_code": "AE",
"search_volume": 2072,
"percentage": 0.69012
},
{
"country_iso_code": "UA",
"search_volume": 1825,
"percentage": 0.608
},
{
"country_iso_code": "CN",
"search_volume": 1800,
"percentage": 0.59948
},
{
"country_iso_code": "AZ",
"search_volume": 1706,
"percentage": 0.56839
},
{
"country_iso_code": "CO",
"search_volume": 1576,
"percentage": 0.52496
},
{
"country_iso_code": "CA",
"search_volume": 1563,
"percentage": 0.5206
},
{
"country_iso_code": "DZ",
"search_volume": 1493,
"percentage": 0.4974
},
{
"country_iso_code": "PL",
"search_volume": 1355,
"percentage": 0.45133
},
{
"country_iso_code": "IR",
"search_volume": 1333,
"percentage": 0.44406
},
{
"country_iso_code": "AU",
"search_volume": 1330,
"percentage": 0.44322
},
{
"country_iso_code": "RU",
"search_volume": 1303,
"percentage": 0.43426
},
{
"country_iso_code": "NG",
"search_volume": 1120,
"percentage": 0.37301
},
{
"country_iso_code": "SA",
"search_volume": 1060,
"percentage": 0.35325
},
{
"country_iso_code": "ZA",
"search_volume": 1058,
"percentage": 0.35253
},
{
"country_iso_code": "KH",
"search_volume": 924,
"percentage": 0.30801
},
{
"country_iso_code": "MY",
"search_volume": 912,
"percentage": 0.30401
},
{
"country_iso_code": "TW",
"search_volume": 831,
"percentage": 0.27704
},
{
"country_iso_code": "FI",
"search_volume": 797,
"percentage": 0.26574
},
{
"country_iso_code": "PT",
"search_volume": 781,
"percentage": 0.26019
},
{
"country_iso_code": "LK",
"search_volume": 777,
"percentage": 0.25886
},
{
"country_iso_code": "AR",
"search_volume": 763,
"percentage": 0.25425
},
{
"country_iso_code": "KE",
"search_volume": 741,
"percentage": 0.24687
},
{
"country_iso_code": "RS",
"search_volume": 727,
"percentage": 0.24232
},
{
"country_iso_code": "IE",
"search_volume": 706,
"percentage": 0.23513
},
{
"country_iso_code": "CH",
"search_volume": 627,
"percentage": 0.2091
},
{
"country_iso_code": "BE",
"search_volume": 620,
"percentage": 0.20671
},
{
"country_iso_code": "PE",
"search_volume": 575,
"percentage": 0.19169
},
{
"country_iso_code": "NP",
"search_volume": 533,
"percentage": 0.17762
},
{
"country_iso_code": "HU",
"search_volume": 446,
"percentage": 0.14868
},
{
"country_iso_code": "TN",
"search_volume": 439,
"percentage": 0.14634
},
{
"country_iso_code": "SE",
"search_volume": 433,
"percentage": 0.14448
},
{
"country_iso_code": "DK",
"search_volume": 386,
"percentage": 0.12869
},
{
"country_iso_code": "AT",
"search_volume": 373,
"percentage": 0.12428
},
{
"country_iso_code": "SG",
"search_volume": 360,
"percentage": 0.1202
},
{
"country_iso_code": "JO",
"search_volume": 343,
"percentage": 0.11423
},
{
"country_iso_code": "GR",
"search_volume": 339,
"percentage": 0.1131
},
{
"country_iso_code": "BG",
"search_volume": 301,
"percentage": 0.10041
},
{
"country_iso_code": "CZ",
"search_volume": 296,
"percentage": 0.09869
},
{
"country_iso_code": "KR",
"search_volume": 295,
"percentage": 0.09839
},
{
"country_iso_code": "RO",
"search_volume": 295,
"percentage": 0.09855
},
{
"country_iso_code": "NO",
"search_volume": 282,
"percentage": 0.09392
},
{
"country_iso_code": "CL",
"search_volume": 270,
"percentage": 0.09014
},
{
"country_iso_code": "IQ",
"search_volume": 266,
"percentage": 0.08881
},
{
"country_iso_code": "YE",
"search_volume": 266,
"percentage": 0.08881
},
{
"country_iso_code": "VE",
"search_volume": 264,
"percentage": 0.08801
},
{
"country_iso_code": "LY",
"search_volume": 238,
"percentage": 0.07954
},
{
"country_iso_code": "HR",
"search_volume": 224,
"percentage": 0.07466
},
{
"country_iso_code": "HK",
"search_volume": 220,
"percentage": 0.07327
},
{
"country_iso_code": "EC",
"search_volume": 217,
"percentage": 0.07246
},
{
"country_iso_code": "BO",
"search_volume": 210,
"percentage": 0.07002
},
{
"country_iso_code": "SV",
"search_volume": 183,
"percentage": 0.06103
},
{
"country_iso_code": "LT",
"search_volume": 177,
"percentage": 0.059
},
{
"country_iso_code": "NZ",
"search_volume": 174,
"percentage": 0.05795
},
{
"country_iso_code": "IL",
"search_volume": 146,
"percentage": 0.04885
},
{
"country_iso_code": "DO",
"search_volume": 142,
"percentage": 0.04735
},
{
"country_iso_code": null,
"search_volume": 136,
"percentage": 0.04557
},
{
"country_iso_code": "LB",
"search_volume": 133,
"percentage": 0.04441
},
{
"country_iso_code": "CM",
"search_volume": 133,
"percentage": 0.04441
},
{
"country_iso_code": "ET",
"search_volume": 133,
"percentage": 0.04441
},
{
"country_iso_code": "TZ",
"search_volume": 133,
"percentage": 0.04441
},
{
"country_iso_code": "OM",
"search_volume": 130,
"percentage": 0.04341
},
{
"country_iso_code": "LV",
"search_volume": 124,
"percentage": 0.04133
},
{
"country_iso_code": "PR",
"search_volume": 109,
"percentage": 0.03652
},
{
"country_iso_code": "CY",
"search_volume": 106,
"percentage": 0.03552
},
{
"country_iso_code": "SN",
"search_volume": 100,
"percentage": 0.0333
},
{
"country_iso_code": "EE",
"search_volume": 99,
"percentage": 0.03325
},
{
"country_iso_code": "QA",
"search_volume": 90,
"percentage": 0.03025
},
{
"country_iso_code": "BY",
"search_volume": 82,
"percentage": 0.02761
},
{
"country_iso_code": "NI",
"search_volume": 78,
"percentage": 0.02623
},
{
"country_iso_code": "MM",
"search_volume": 66,
"percentage": 0.0222
},
{
"country_iso_code": "BJ",
"search_volume": 66,
"percentage": 0.0222
},
{
"country_iso_code": "AF",
"search_volume": 66,
"percentage": 0.0222
},
{
"country_iso_code": "PS",
"search_volume": 66,
"percentage": 0.0222
},
{
"country_iso_code": "SY",
"search_volume": 66,
"percentage": 0.0222
},
{
"country_iso_code": "UG",
"search_volume": 66,
"percentage": 0.0222
},
{
"country_iso_code": "CD",
"search_volume": 66,
"percentage": 0.0222
},
{
"country_iso_code": "ZM",
"search_volume": 66,
"percentage": 0.0222
},
{
"country_iso_code": "UZ",
"search_volume": 66,
"percentage": 0.0222
},
{
"country_iso_code": "MD",
"search_volume": 65,
"percentage": 0.02179
},
{
"country_iso_code": "GT",
"search_volume": 64,
"percentage": 0.02156
},
{
"country_iso_code": "TG",
"search_volume": 56,
"percentage": 0.01896
},
{
"country_iso_code": "UY",
"search_volume": 53,
"percentage": 0.01768
},
{
"country_iso_code": "GE",
"search_volume": 49,
"percentage": 0.01649
},
{
"country_iso_code": "MO",
"search_volume": 49,
"percentage": 0.01635
},
{
"country_iso_code": "AL",
"search_volume": 45,
"percentage": 0.01501
},
{
"country_iso_code": "BH",
"search_volume": 42,
"percentage": 0.01399
},
{
"country_iso_code": "MK",
"search_volume": 41,
"percentage": 0.0139
},
{
"country_iso_code": "MN",
"search_volume": 36,
"percentage": 0.0121
},
{
"country_iso_code": "CR",
"search_volume": 34,
"percentage": 0.01132
},
{
"country_iso_code": "JM",
"search_volume": 31,
"percentage": 0.01046
},
{
"country_iso_code": "TT",
"search_volume": 26,
"percentage": 0.00869
},
{
"country_iso_code": "LU",
"search_volume": 25,
"percentage": 0.00844
},
{
"country_iso_code": "NR",
"search_volume": 0,
"percentage": 0
}
]
},
{
"keyword": "marketing campaign",
"search_volume": 17745,
"country_distribution": [
{
"country_iso_code": "US",
"search_volume": 4373,
"percentage": 24.64779
},
{
"country_iso_code": "GB",
"search_volume": 1723,
"percentage": 9.71494
},
{
"country_iso_code": "IN",
"search_volume": 1586,
"percentage": 8.94149
},
{
"country_iso_code": "ID",
"search_volume": 1280,
"percentage": 7.2133
},
{
"country_iso_code": "TH",
"search_volume": 780,
"percentage": 4.40077
},
{
"country_iso_code": "CA",
"search_volume": 750,
"percentage": 4.22842
},
{
"country_iso_code": "VN",
"search_volume": 613,
"percentage": 3.45919
},
{
"country_iso_code": "PH",
"search_volume": 518,
"percentage": 2.92383
},
{
"country_iso_code": "JP",
"search_volume": 466,
"percentage": 2.62985
},
{
"country_iso_code": "AU",
"search_volume": 462,
"percentage": 2.60825
},
{
"country_iso_code": "HK",
"search_volume": 440,
"percentage": 2.48004
},
{
"country_iso_code": "ES",
"search_volume": 402,
"percentage": 2.26965
},
{
"country_iso_code": "SA",
"search_volume": 385,
"percentage": 2.17338
},
{
"country_iso_code": "FI",
"search_volume": 319,
"percentage": 1.79863
},
{
"country_iso_code": "FR",
"search_volume": 312,
"percentage": 1.76153
},
{
"country_iso_code": "SE",
"search_volume": 289,
"percentage": 1.62957
},
{
"country_iso_code": "PK",
"search_volume": 266,
"percentage": 1.50277
},
{
"country_iso_code": "BD",
"search_volume": 200,
"percentage": 1.12708
},
{
"country_iso_code": "AE",
"search_volume": 194,
"percentage": 1.09467
},
{
"country_iso_code": "MX",
"search_volume": 165,
"percentage": 0.93407
},
{
"country_iso_code": "TR",
"search_volume": 153,
"percentage": 0.86644
},
{
"country_iso_code": "CN",
"search_volume": 133,
"percentage": 0.75139
},
{
"country_iso_code": "EG",
"search_volume": 133,
"percentage": 0.75139
},
{
"country_iso_code": "PL",
"search_volume": 123,
"percentage": 0.69409
},
{
"country_iso_code": "IE",
"search_volume": 117,
"percentage": 0.6631
},
{
"country_iso_code": "IT",
"search_volume": 113,
"percentage": 0.64009
},
{
"country_iso_code": "MY",
"search_volume": 101,
"percentage": 0.57152
},
{
"country_iso_code": "NL",
"search_volume": 96,
"percentage": 0.54569
},
{
"country_iso_code": "NO",
"search_volume": 94,
"percentage": 0.52973
},
{
"country_iso_code": "ZA",
"search_volume": 88,
"percentage": 0.49685
},
{
"country_iso_code": "RS",
"search_volume": 80,
"percentage": 0.45553
},
{
"country_iso_code": "BE",
"search_volume": 77,
"percentage": 0.43721
},
{
"country_iso_code": "AM",
"search_volume": 72,
"percentage": 0.40622
},
{
"country_iso_code": "TW",
"search_volume": 69,
"percentage": 0.39025
},
{
"country_iso_code": "KH",
"search_volume": 66,
"percentage": 0.37194
},
{
"country_iso_code": "OM",
"search_volume": 65,
"percentage": 0.36724
},
{
"country_iso_code": "LV",
"search_volume": 62,
"percentage": 0.34939
},
{
"country_iso_code": "RO",
"search_volume": 59,
"percentage": 0.33343
},
{
"country_iso_code": "NZ",
"search_volume": 58,
"percentage": 0.32685
},
{
"country_iso_code": "JO",
"search_volume": 57,
"percentage": 0.32216
},
{
"country_iso_code": "TN",
"search_volume": 54,
"percentage": 0.30948
},
{
"country_iso_code": "DO",
"search_volume": 47,
"percentage": 0.26674
},
{
"country_iso_code": "LK",
"search_volume": 45,
"percentage": 0.25735
},
{
"country_iso_code": "AL",
"search_volume": 45,
"percentage": 0.25406
},
{
"country_iso_code": "SG",
"search_volume": 45,
"percentage": 0.25406
},
{
"country_iso_code": "BH",
"search_volume": 42,
"percentage": 0.23669
},
{
"country_iso_code": "MT",
"search_volume": 40,
"percentage": 0.22776
},
{
"country_iso_code": "AR",
"search_volume": 34,
"percentage": 0.19536
},
{
"country_iso_code": "JM",
"search_volume": 31,
"percentage": 0.17705
},
{
"country_iso_code": null,
"search_volume": 2,
"percentage": 0.01174
}
]
},
{
"keyword": "seo tool",
"search_volume": 13733,
"country_distribution": [
{
"country_iso_code": "IN",
"search_volume": 2893,
"percentage": 21.06834
},
{
"country_iso_code": "US",
"search_volume": 1429,
"percentage": 10.4116
},
{
"country_iso_code": "DE",
"search_volume": 1410,
"percentage": 10.26718
},
{
"country_iso_code": "PK",
"search_volume": 1000,
"percentage": 7.28169
},
{
"country_iso_code": "GB",
"search_volume": 574,
"percentage": 4.18394
},
{
"country_iso_code": "IT",
"search_volume": 568,
"percentage": 4.1366
},
{
"country_iso_code": "VN",
"search_volume": 526,
"percentage": 3.83138
},
{
"country_iso_code": "BD",
"search_volume": 466,
"percentage": 3.39812
},
{
"country_iso_code": "TR",
"search_volume": 461,
"percentage": 3.35989
},
{
"country_iso_code": "KE",
"search_volume": 370,
"percentage": 2.69847
},
{
"country_iso_code": "AE",
"search_volume": 323,
"percentage": 2.35745
},
{
"country_iso_code": "FR",
"search_volume": 312,
"percentage": 2.27613
},
{
"country_iso_code": "PH",
"search_volume": 296,
"percentage": 2.15902
},
{
"country_iso_code": "EG",
"search_volume": 266,
"percentage": 1.94178
},
{
"country_iso_code": "CA",
"search_volume": 187,
"percentage": 1.36592
},
{
"country_iso_code": "ZA",
"search_volume": 176,
"percentage": 1.28461
},
{
"country_iso_code": "AU",
"search_volume": 173,
"percentage": 1.26398
},
{
"country_iso_code": "RS",
"search_volume": 161,
"percentage": 1.17721
},
{
"country_iso_code": "TW",
"search_volume": 138,
"percentage": 1.00912
},
{
"country_iso_code": "TH",
"search_volume": 130,
"percentage": 0.94723
},
{
"country_iso_code": "AT",
"search_volume": 124,
"percentage": 0.90536
},
{
"country_iso_code": "PL",
"search_volume": 123,
"percentage": 0.89686
},
{
"country_iso_code": "HK",
"search_volume": 110,
"percentage": 0.80099
},
{
"country_iso_code": "ID",
"search_volume": 106,
"percentage": 0.77671
},
{
"country_iso_code": "CH",
"search_volume": 104,
"percentage": 0.76154
},
{
"country_iso_code": "MY",
"search_volume": 101,
"percentage": 0.73848
},
{
"country_iso_code": "GE",
"search_volume": 99,
"percentage": 0.72149
},
{
"country_iso_code": "DK",
"search_volume": 96,
"percentage": 0.70329
},
{
"country_iso_code": "NL",
"search_volume": 96,
"percentage": 0.70511
},
{
"country_iso_code": "LK",
"search_volume": 91,
"percentage": 0.66567
},
{
"country_iso_code": "MX",
"search_volume": 82,
"percentage": 0.60317
},
{
"country_iso_code": "ES",
"search_volume": 80,
"percentage": 0.58618
},
{
"country_iso_code": "IL",
"search_volume": 73,
"percentage": 0.53399
},
{
"country_iso_code": "PT",
"search_volume": 71,
"percentage": 0.517
},
{
"country_iso_code": "NP",
"search_volume": 66,
"percentage": 0.48545
},
{
"country_iso_code": "CN",
"search_volume": 66,
"percentage": 0.48545
},
{
"country_iso_code": "IQ",
"search_volume": 66,
"percentage": 0.48545
},
{
"country_iso_code": "SI",
"search_volume": 63,
"percentage": 0.46421
},
{
"country_iso_code": "LT",
"search_volume": 59,
"percentage": 0.42962
},
{
"country_iso_code": "CO",
"search_volume": 46,
"percentage": 0.33738
},
{
"country_iso_code": "AL",
"search_volume": 45,
"percentage": 0.32828
},
{
"country_iso_code": "PA",
"search_volume": 43,
"percentage": 0.31857
},
{
"country_iso_code": "AR",
"search_volume": 34,
"percentage": 0.25243
},
{
"country_iso_code": null,
"search_volume": 10,
"percentage": 0.07767
}
]
},
{
"keyword": "seo guide",
"search_volume": 3114,
"country_distribution": [
{
"country_iso_code": "GB",
"search_volume": 574,
"percentage": 18.44668
},
{
"country_iso_code": "US",
"search_volume": 504,
"percentage": 16.20204
},
{
"country_iso_code": "IN",
"search_volume": 280,
"percentage": 8.98925
},
{
"country_iso_code": "MY",
"search_volume": 202,
"percentage": 6.51185
},
{
"country_iso_code": "KE",
"search_volume": 185,
"percentage": 5.94735
},
{
"country_iso_code": "DE",
"search_volume": 176,
"percentage": 5.65841
},
{
"country_iso_code": "SE",
"search_volume": 144,
"percentage": 4.64177
},
{
"country_iso_code": "PK",
"search_volume": 133,
"percentage": 4.28059
},
{
"country_iso_code": "CA",
"search_volume": 125,
"percentage": 4.01306
},
{
"country_iso_code": "AU",
"search_volume": 115,
"percentage": 3.71341
},
{
"country_iso_code": "FR",
"search_volume": 104,
"percentage": 3.34421
},
{
"country_iso_code": "BG",
"search_volume": 100,
"percentage": 3.2265
},
{
"country_iso_code": "NL",
"search_volume": 96,
"percentage": 3.10878
},
{
"country_iso_code": "VN",
"search_volume": 87,
"percentage": 2.81449
},
{
"country_iso_code": "BR",
"search_volume": 86,
"percentage": 2.78774
},
{
"country_iso_code": "MX",
"search_volume": 82,
"percentage": 2.65932
},
{
"country_iso_code": "EG",
"search_volume": 66,
"percentage": 2.1403
},
{
"country_iso_code": "SG",
"search_volume": 45,
"percentage": 1.44738
},
{
"country_iso_code": null,
"search_volume": 2,
"percentage": 0.06688
}
]
}
]
}
]
}
]
}
The items array includes objects that display the global search volume and the distribution of this volume across different countries for each keyword. The search_volume field holds the global search volume figure.
Inside the country_distribution array, you'll find objects with the following fields:
country_iso_code: the ISO code representing the specific country;search_volume: the search volume for a keyword within that country;percentage: the proportion of the search volume relative to the keyword's global search volume.
As you can see, with DataForSEO APIs, you can easily access valuable clickstream insights. Moreover, we plan to introduce even more clickstream-based metrics in our endpoints to provide you with more granular insights.
Conclusion
Clickstream data is undoubtedly a powerful source of data-driven insights for online marketers seeking to improve business visibility on the Internet. For marketing technology developers, clickstreams are also important because they help refine keyword metrics and enhance the accuracy of search volume estimates. By integrating clickstream data into website performance tools, developers can offer more comprehensive analytics, providing users with deeper insights into user behavior, traffic patterns, and engagement metrics.
Nevertheless, acquiring precious clickstream data and leveraging it in solutions comes with various challenges. Data privacy concerns and compliance with regulations like GDPR pose significant hurdles for companies collecting and using this information. The sheer volume of clickstream data requires sophisticated processing capabilities, demanding substantial computational resources. Ensuring data accuracy and reliability is another major challenge, as clickstream data can be affected by bot traffic or sampling biases, potentially skewing results.
In DataForSEO, we understand the importance of clickstream data in online marketing and its challenging nature. Therefore, we offer hassle-free access to clickstream insights using the Bulk Clickstream Search Volume and Global Search Volume endpoints of Keyword Data API and DataForSEO Labs endpoints enriched with clickstream-based metrics.
Try our APIs now and fuel your marketing solutions with clickstream insights!