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Trends
Last updated: October 9, 2025
Last updated: October 9, 2025
Industry categories
To obtain a list of all domains within specific industry categories from the Industry Categories report, select the relevant category values from the list and specify them in the request parameters:
| Value | Market Overview business category |
|---|---|
| accounting_and_auditing | Accounting & Auditing |
| adult | Adult |
| advertising_and_marketing | Advertising & Marketing |
| aerospace_and_defense | Aerospace & Defense |
| agriculture | Agriculture |
| airlines | Airlines |
| apparel_and_fashion | Apparel & Fashion |
| architecture | Architecture |
| automotive | Automotive |
| banking | Banking |
| beauty_and_cosmetics | Beauty & Cosmetics |
| biotech | Biotech |
| ceramics_and_pottery | Ceramics & Pottery |
| chemicals | Chemicals |
| civil_engineering | Civil Engineering |
| comics_and_animation | Comics & Animation |
| computer_and_video_games | Computer & Video Games |
| computer_hardware | Computer Hardware |
| computer_software_and_development | Computer Software & Development |
| computers_and_electronics | Computers & Electronics |
| construction_and_maintenance | Construction & Maintenance |
| consulting | Consulting |
| consumer_electronics | Consumer Electronics |
| crafts | Crafts |
| customer_services | Customer Services |
| design | Design |
| distance_learning | Distance Learning |
| ecology_and_environment | Ecology & Environment |
| education | Education |
| entertainment | Entertainment |
| equipment_and_supplies | Equipment & Supplies |
| events_services | Events Services |
| facilities_services | Facilities Services |
| farms_and_ranches | Farms & Ranches |
| finance | Finance |
| fishery | Fishery |
| food_and_beverages | Food & Beverages |
| foreign_language | Foreign Language |
| furniture | Furniture |
| gambling | Gambling |
| government | Government |
| graphic_design | Graphic Design |
| healthcare | Healthcare |
| hospitality | Hospitality |
| human_resources | Human Resources |
| import_and_export | Import & Export |
| information_technology | Information Technology |
| insurance | Insurance |
| investment | Investment |
| jewelry_and_luxury_products | Jewelry & Luxury Products |
| legal | Legal |
| libraries | Libraries |
| machinery | Machinery |
| mail_and_package_delivery | Mail & Package Delivery |
| manufacturing | Manufacturing |
| maritime | Maritime |
| market_research | Market Research |
| mass_media | Mass Media |
| medical_devices_and_equipment | Medical Devices & Equipment |
| mental_health | Mental Health |
| metals_and_mining | Metals & Mining |
| military | Military |
| museums | Museums |
| music | Music |
| nanotechnology | Nanotechnology |
| newspapers | Newspapers |
| nonprofit_organizations | Nonprofit Organizations |
| oil_and_gas | Oil & Gas |
| online_services | Online Services |
| outsourcing | Outsourcing |
| packaging_and_containers | Packaging & Containers |
| performing_arts | Performing Arts |
| pharmaceuticals | Pharmaceuticals |
| photography | Photography |
| plastics_and_polymers | Plastics & Polymers |
| political_organizations | Political Organizations |
| printing | Printing |
| public_policy | Public Policy |
| public_relations | Public Relations |
| public_safety | Public Safety |
| public_utility | Public Utility |
| publishing | Publishing |
| real_estate | Real Estate |
| recreational_facilities | Recreational Facilities |
| recruitment_and_staffing | Recruitment & Staffing |
| reference | Reference |
| religion_and_belief | Religion & Belief |
| renewable_energy | Renewable Energy |
| restaurants | Restaurants |
| retail | Retail |
| science | Science |
| security_products_and_services | Security Products & Services |
| social_and_charitable_organizations | Social & Charitable Organizations |
| sporting_goods | Sporting Goods |
| sports | Sports |
| telecom | Telecom |
| textiles_and_nonwovens | Textiles & Nonwovens |
| tobacco | Tobacco |
| training_and_certification | Training & Certification |
| transportation_and_logistics | Transportation & Logistics |
| travel_and_tourism | Travel & Tourism |
| tv_and_movies | Tv & Movies |
| venture_capital | Venture Capital |
| veterinary | Veterinary |
| visual_art | Visual Art |
| warehousing | Warehousing |
| wellness | Wellness |
| wholesalers_and_liquidators | Wholesalers & Liquidators |
| wine_and_spirits | Wine & Spirits |
| writing_and_editing_services | Writing & Editing Services |
Show all
Columns
Each Trends API method supports a set of output columns that determine the data returned in the CSV response.
You can customize your request using the export_columns parameter to include only the fields relevant to your analysis.
The following table indicates:
- Parameter (the
export_columnsparameter value same as the column name in the CSV report) - Description of what each column represents
- Possible values to help interpret the results (if applicable)
- API methods where the columns are used
| Parameter | Description | API methods |
|---|---|---|
| accuracy | Accuracy of the data. Possible values: 1, 2, 3, where 3 indicates high accuracy. | Data Accuracy, Traffic Summary |
| age | User age group, such as 18-24 or 25-34. | Age and Sex Distribution |
| age_18_24 | Users aged between 18 and 24 years. | Industry Categories |
| age_25_34 | Users aged between 25 and 34 years. | Industry Categories |
| age_35_44 | Users aged between 35 and 44 years. | Industry Categories |
| age_45_54 | Users aged between 45 and 54 years. | Industry Categories |
| age_55_64 | Users aged between 55 and 64 years. | Industry Categories |
| age_65_plus | Users aged 65 years and older. | Industry Categories |
| ai_assistants | Traffic from AI assistant platforms. For example, chat-based assistants like ChatGPT. | Daily Traffic, Subfolders, Top Pages, Traffic Summary, Weekly Traffic |
| ai_assistants_traffic | Traffic from AI assistant platforms. | Industry Categories |
| ai_search | Traffic from AI-powered search engines. | Daily Traffic, Subfolders, Top Pages, Traffic Summary, Weekly Traffic |
| ai_search_traffic | Traffic from AI-powered search engines. | Industry Categories |
| avg_visit_duration | Average amount of time spent viewing an analyzed competitor. | Top Pages |
| bounce_rate | Percentage of single-page sessions. | Daily Traffic, Industry Categories, Subfolders, Traffic Rank, Traffic Summary, Weekly Traffic |
| bounced_visits | Number of single-page sessions. | Industry Categories |
| categories | Industry categories related to the site. Can include several categories, for example: online_services;retail. | Audience Insights, Geo Distribution, Traffic Destinations, Traffic Sources, Traffic Summary |
| category | Industry category related to the site. | Audience Interests |
| channel | Channel type. Possible values: direct, referral, search, social, mail, display_ad, ai_assistants, ai_search. | Traffic Sources |
| conversion | Percentage of sessions that ended with a purchase, identified by visits to a unique "thank you" page confirming a completed order or transaction. | Purchase Conversion |
| conversion_rate | Estimated percentage of sessions that ended with a checkout. | Industry Categories |
| country | Standardized 2-letter code representing the country. If the parameter isn't specified, global data is shown by default. | Age and Sex Distribution, Audience Interests, Daily Traffic, Data Accuracy, Education Distribution, Geo Distribution, Household Distribution, Income Distribution, Occupation Distribution, Purchase Conversion, Social Media, Subdomains, Top Pages, Traffic Destinations, Traffic Rank, Traffic Sources, Traffic Summary, Weekly Traffic |
| country_code | Standardized 2-letter code representing the country. | Industry Categories |
| desktop_share | Proportion of total traffic that came from desktops. | Daily Traffic, Weekly Traffic, Geo Distribution, Subdomains, Top Pages, Traffic Rank |
| device_type | Type of device used by the user, such as desktop or mobile. | Age and Sex Distribution, Audience Interests, Daily Traffic, Data Accuracy, Education Distribution, Geo Distribution, Household Distribution, Income Distribution, Occupation Distribution, Purchase Conversion, Social Media, Subdomains, Top Pages, Traffic Destinations, Traffic Rank, Traffic Sources, Traffic Summary, Weekly Traffic |
| direct | Traffic from users typing in the URL or using bookmarks. | Daily Traffic, Subfolders, Top Pages, Traffic Summary, Weekly Traffic |
| direct_traffic | Traffic from users typing in the URL or using bookmarks. | Industry Categories |
| display_ad | Traffic from banner or display advertising. | Daily Traffic, Subfolders, Top Pages, Traffic Summary, Weekly Traffic |
| display_ad_traffic | Traffic from banner or display advertising. | Industry Categories |
| display_date | Date for which the data is shown. | Age and Sex Distribution, Audience Interests, Daily Traffic, Data Accuracy, Education Distribution, Geo Distribution, Household Distribution, Income Distribution, Occupation Distribution, Purchase Conversion, Social Media, Subdomains, Subfolders, Top Pages, Traffic Destinations, Traffic Rank, Traffic Sources, Traffic Summary, Weekly Traffic |
| domain | The domain being analyzed, such as example.com. | Subdomains, Traffic Rank |
| domain_name | The domain being analyzed, such as example.com. | Industry Categories |
| edu_level_compulsory_school | Users with compulsory school education. | Industry Categories |
| edu_level_none_completed | Users without any completed formal education. | Industry Categories |
| edu_level_post_graduate_education | Users with postgraduate-level education. | Industry Categories |
| edu_level_university | Users with a university-level education. | Industry Categories |
| email_traffic | Traffic from email campaigns. | Industry Categories |
| entrance_traffic | Traffic entering through a specific page. | Top Pages |
| entrances | Number of times users entered through a specific page. | Subfolders |
| exits | Number of times users exited from a specific page. | Subfolders, Top Pages |
| facebook_traffic | Traffic coming from Facebook. | Industry Categories |
| female | Share of female users in the total number of users. | Industry Categories |
| female_18_24 | Female users aged 18–24. | Industry Categories |
| female_25_34 | Female users aged 25–34. | Industry Categories |
| female_35_44 | Female users aged 35–44. | Industry Categories |
| female_45_54 | Female users aged 45–54. | Industry Categories |
| female_55_64 | Female users aged 55–64. | Industry Categories |
| female_65_plus | Female users aged 65+. | Industry Categories |
| female_share | Percentage share of female users. | Age and Sex Distribution |
| female_users | Total number of female users. | Age and Sex Distribution |
| from_target | The target where users came from before landing on the domain. | Traffic Sources |
| high_income | Users classified as high-income. | Industry Categories |
| hits | Total number of pageviews on the target—domain, subdomain, subfolder, or specific page. | Daily Traffic, Industry Categories, Weekly Traffic |
| household_size_1 | Users in a 1-person household. | Industry Categories |
| household_size_10plus | Users in households with 10 or more people. | Industry Categories |
| household_size_2 | Users in a 2-person household. | Industry Categories |
| household_size_3 | Users in a 3-person household. | Industry Categories |
| household_size_4 | Users in a 4-person household. | Industry Categories |
| household_size_5 | Users in a 5-person household. | Industry Categories |
| household_size_6 | Users in a 6-person household. | Industry Categories |
| household_size_7 | Users in a 7-person household. | Industry Categories |
| household_size_8 | Users in a 8-person household. | Industry Categories |
| household_size_9 | Users in a 9-person household. | Industry Categories |
| income_type | Income classification for the user: high, middle, or low. | Income Distribution |
| instagram_traffic | Traffic from Instagram. | Industry Categories |
| is_adult | Indicates whether adult content sites are displayed in the results. Possible values: true, false. | Audience Insights |
| is_forecasted | Indicates if the data is forecated. Possible values: true, false. | Daily Traffic, Weekly Traffic |
| linkedin_traffic | Traffic coming from LinkedIn. | Industry Categories |
| low_income | Users classified as low-income. | Industry Categories |
| Traffic from email campaigns. | Daily Traffic, Subfolders, Top Pages, Traffic Summary, Weekly Traffic | |
| male | Share of male users in the total number of users. | Industry Categories |
| male_18_24 | Male users aged 18–24. | Industry Categories |
| male_25_34 | Male users aged 25–34. | Industry Categories |
| male_35_44 | Male users aged 35–44. | Industry Categories |
| male_45_54 | Male users aged 45–54. | Industry Categories |
| male_55_64 | Male users aged 55–64. | Industry Categories |
| male_65_plus | Male users aged 65+. | Industry Categories |
| male_share | Percentage share of male users. | Age and Sex Distribution |
| male_users | Total number of male users. | Age and Sex Distribution |
| middle_income | Users classified as middle-income. | Industry Categories |
| mobile_bounce_rate | Bounce rate specific to users on mobile devices. | Traffic Summary |
| mobile_hits | Number of tracked interactions or pageviews from mobile devices. | Traffic Summary |
| mobile_pages_per_visit | Number of pages viewed during a single session from mobile devices. | Traffic Summary |
| mobile_share | Proportion of total traffic that came from mobile devices. | Daily Traffic, Subdomains, Top Pages, Traffic Rank, Traffic Summary, Weekly Traffic |
| mobile_users | Number of unique users accessing via mobile devices. | Subdomains, Traffic Summary |
| mobile_visits | Total number of sessions initiated from mobile devices. | Subdomains, Traffic Rank, Traffic Summary |
| occupation | General occupation or employment category of users. | Occupation Distribution |
| occupation_fulltimework | Users employed in full-time positions. | Industry Categories |
| occupation_homemaker | Users whose primary occupation is homemaking. | Industry Categories |
| occupation_leaveofabsence | Users temporarily out of work due to health or family leave. | Industry Categories |
| occupation_ownbusiness | Users running their own businesses. | Industry Categories |
| occupation_parentalleave | Users on maternity or paternity leave. | Industry Categories |
| occupation_parttimework | Users working part-time jobs. | Industry Categories |
| occupation_retired | Users who are retired from the workforce. | Industry Categories |
| occupation_studies | Users currently studying. | Industry Categories |
| occupation_unemployed | Users who are currently unemployed. | Industry Categories |
| overlap_score | Score indicating the level of audience overlap between the domains. | Audience Insights |
| overlap_users | Number of unique visitors to both the listed and analyzed domains. | Audience Insights |
| page | Analyzed page. | Top Pages |
| pages_per_visit | Number of pages viewed during a single session. | Daily Traffic, Subfolders, Traffic Rank, Traffic Summary, Weekly Traffic |
| paid | Traffic from all paid sources, including ads. | Subfolders, Top Pages, Traffic Summary |
| pinterest_traffic | Traffic originating from Pinterest. | Industry Categories |
| prev_traffic | Traffic from the previous month for comparison. | Geo Distribution, Traffic Destinations, Traffic Sources |
| rank | Ranking of the target based on traffic volume, where 1 indicates the highest traffic. | Daily Traffic, Traffic Rank, Traffic Summary, Weekly Traffic |
| reddit_traffic | Traffic coming from Reddit. | Industry Categories |
| referral | Refferal traffic. | Daily Traffic, Subfolders, Top Pages, Traffic Summary, Weekly Traffic |
| referral_traffic | Refferal traffic. | Industry Categories |
| report_date | Report date. | Industry Categories |
| search | Total search engine traffic (organic and paid). | Subfolders, Top Pages, Traffic Summary |
| search_organic | Traffic from unpaid search results. | Daily Traffic, Subfolders, Top Pages, Traffic Summary, Weekly Traffic |
| search_organic_traffic | Traffic from unpaid search results. | Industry Categories |
| search_paid | Traffic from paid search ads. | Daily Traffic, Subfolders, Top Pages, Traffic Summary, Weekly Traffic |
| search_paid_traffic | Traffic from paid search ads. | Industry Categories |
| similarity_score | Percentage of audience overlap between the domains and the selected domains. | Audience Insights |
| size | Household size. Possible values: 1-10+, where 1 is a 1-person household and 10+ is households with 10 or more people. | Household Distribution |
| social | Traffic from all social media sources. | Subfolders, Top Pages, Traffic Summary |
| social_domain | Domain of the social platform, such as facebook.com. | Social Media |
| social_name | Name of the social platform, such as Facebook or Twitter) | Social Media |
| social_organic | Unpaid traffic from social platforms. | Daily Traffic, Subfolders, Top Pages, Traffic Summary, Weekly Traffic |
| social_organic_traffic | Unpaid traffic from social platforms. | Industry Categories |
| social_paid | Paid traffic from social media advertising. | Daily Traffic, Subfolders, Top Pages, Traffic Summary, Weekly Traffic |
| social_paid_traffic | Paid traffic from social media advertising. | Industry Categories |
| subdomain | Subdomain of the target site. For example: blog.example.com. | Subdomains, Subfolders |
| subfolder | Specific path or folder within a site. For example: /products/shoes. | Subfolders |
| sum_time_on_site | Total time users spent on the site. | Industry Categories |
| target | The domain being analyzed. | Age and Sex Distribution, Audience Insights, Audience Interests, Daily Traffic, Data Accuracy, Education Distribution, Geo Distribution, Household Distribution, Income Distribution, Occupation Distribution, Purchase Conversion, Social Media, Top Pages, Traffic Destinations, Traffic Sources, Traffic Summary, Weekly Traffic |
| target_type | Type of the analyzed target. Possible values: domain, subdomain. | Subdomains |
| target_users | Total number of users for the target domain. | Audience Insights |
| time_on_site | Average time spent on the site per session. | Daily Traffic, Traffic Rank, Traffic Summary, Weekly Traffic |
| time_on_subfolder | Average time spent within a specific subfolder. | Subfolders |
| to_target | The target where users go after visiting the domain. | Geo Distribution, Traffic Destinations |
| total_traffic | Combined traffic from all sources. | Industry Categories |
| total_users | Combined count of all unique users. | Subdomains |
| total_visits | Total number of visits. | Subdomains |
| traffic | Total amount of traffic. | Geo Distribution, Top Pages, Traffic Destinations, Traffic Sources |
| traffic_diff | Change in traffic compared to a previous time period. | Traffic Sources |
| traffic_share | Percentage of total traffic coming to the site compared to competitors. | Geo Distribution, Subdomains, Subfolders, Top Pages, Traffic Destinations, Traffic Sources |
| traffic_type | Traffic type. Possible values: organic, paid. | Traffic Sources |
| twitter_traffic | Traffic coming from Twitter. | Industry Categories |
| unique_pageviews | Number of distinct pageviews by unique users. | Subfolders |
| unique_visitors | Number of distinct users visiting the site. | Industry Categories |
| unknown_channel | Traffic for which the source channel could not be determined or classified. | Traffic Summary |
| users | Total number of users. | Audience Interests, Daily Traffic, Education Distribution, Household Distribution, Income Distribution, Occupation Distribution, Social Media, Subfolders, Traffic Rank, Traffic Summary, Weekly Traffic |
| users_by_target | Number of users visiting or associated with a specific target. | Top Pages |
| users_captured | Users successfully identified and tracked—for example, via login, cookies, or CRM. | Industry Categories |
| users_score | Score representing user value or relevance for targeting or analysis. | Audience Interests, Social Media |
| users_share | Share of users with a specific occupational category. | Education Distribution, Household Distribution, Income Distribution, Occupation Distribution |
| vk_traffic | Traffic from VK. | Industry Categories |
| youtube_traffic | Traffic from YouTube. | Industry Categories |
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Tips and tricks
- Column names can't be changed
- The order of columns can be changed
- The number of columns can be increased
- Semrush will only remove old columns after notifying users
Geo type codes
In the Geo Distribution report, the geo_type parameter determines how geographical data is segmented. If the value of geo_type is set to either continent or subcontinent, the geo column will be populated with the corresponding region codes:
| Geo name | Geo type | Code |
|---|---|---|
| SouthAmerica | Subcontinent | 005 |
| WesternAfrica | Subcontinent | 011 |
| CentralAmerica | Subcontinent | 013 |
| EasternAfrica | Subcontinent | 014 |
| NorthernAfrica | Subcontinent | 015 |
| MiddleAfrica | Subcontinent | 017 |
| SouthernAfrica | Subcontinent | 018 |
| NorthernAmerica | Subcontinent | 021 |
| Caribbean | Subcontinent | 029 |
| EasternAsia | Subcontinent | 030 |
| SouthernAsia | Subcontinent | 034 |
| SouthEasternAsia | Subcontinent | 035 |
| SouthernEurope | Subcontinent | 039 |
| AustraliaAndNewZealand | Subcontinent | 053 |
| Melanesia | Subcontinent | 054 |
| Micronesia | Subcontinent | 057 |
| Polynesia | Subcontinent | 061 |
| CentralAsia | Subcontinent | 143 |
| WesternAsia | Subcontinent | 145 |
| EasternEurope | Subcontinent | 151 |
| NorthernEurope | Subcontinent | 154 |
| WesternEurope | Subcontinent | 155 |
| Africa | Continent | 002 |
| SubSaharanAfrica | Continent | 202 |
| LatinAmericaAndTheCaribbean | Continent | 419 |
| Americas | Continent | 019 |
| Asia | Continent | 142 |
| Europe | Continent | 150 |
| Oceania | Continent | 009 |
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Errors
If you send a wrong request, you will receive a 400 HTTP code. You will also get an error message that explains the problem and how to fix it.
For a list of possible error messages, refer to Error messages.