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Cross-Competitor Field Name Map

Legend:
  • HIGH = full schema verified from public API docs
  • MED = partial, from marketing docs or search snippets
  • LOW = unconfirmed, from feature pages only
  • (n/a) = not documented or not offered

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Follower / Subscriber Count

ConceptCreatorDB (YT)CreatorDB (IG)HypeAuditor (HIGH)Modash (MED)Phyllo (MED)Influencers.club (HIGH)
Follower/subscriber counttotalSubscriberstotalFollowersfollowers_count / subscribers_countfollowersfollower_count / subscriber_countfollower_count (IG) / subscriber_count (YT)
Following count(n/a)totalFollowingfollowings_count(n/a)following_count(n/a)
Pattern: All competitors use platform-specific terms (followers vs. subscribers). HypeAuditor, Phyllo, and Influencers.club append _count suffix. Modash uses bare followers. CreatorDB uses total prefix instead of _count suffix. 4 of 4 competitors with data use snake_case.

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Display Name

ConceptCreatorDB (YT)CreatorDB (IG)HypeAuditor (HIGH)Modash (MED)Phyllo (MED)Influencers.club (HIGH)
Display namedisplayNameusernamefull_name(n/a)full_namefirst_name (top-level) / title (YT)
Pattern: Industry favors full_name (2 of 3 with data). Influencers.club uses first_name at top level and title for YouTube channel name. CreatorDB YouTube uses displayName while Instagram uses username — an internal inconsistency. displayName is more self-documenting than username for this concept.

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Handle / Username

ConceptCreatorDB (YT)CreatorDB (IG)HypeAuditor (HIGH)Modash (MED)Phyllo (MED)Influencers.club (HIGH)
Platform handleuniqueIduserIdusernameuserIdplatform_usernameusername (inside platform object)
Pattern: username is the most common term for handle (HypeAuditor, Influencers.club — 2 of 4). Phyllo uses platform_username. Modash uses userId. CreatorDB uses uniqueId (YT) and userId (IG).

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Engagement Rate

ConceptCreatorDB (YT)CreatorDB (IG)HypeAuditor (HIGH)Modash (MED)Phyllo (MED)Influencers.club (HIGH)
Per-content ERengagementRateengagementRate(n/a at content level)(n/a)(n/a)(n/a)
Creator aggregate ERavgEngagementRateavgEngagementRateer / er.avgengagementRateengagement_rateengagement_percent
Pattern: No consensus on naming. HypeAuditor abbreviates to er. Influencers.club uses engagement_percent and returns a percentage (e.g., 1.34) not a ratio. CreatorDB’s distinction between per-content and aggregate is more precise but unique in the market.
ConceptCreatorDBHypeAuditor (HIGH)Influencers.club (HIGH)
Has sponsored contenthasSponsorsadvertising_data (object with counts)has_brand_deals
Sponsor mentionssponsorList[]advertising_data.brand_mentions[](n/a)
Pattern: Influencers.club uses has_brand_deals, HypeAuditor uses an advertising_data object. CreatorDB’s hasSponsors is unique but clear.

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Niche / Category Classification

ConceptCreatorDBHypeAuditor (HIGH)Influencers.club (HIGH)
CategorymainCategory (search) / categoryBreakdown (profile)blogger_categories(n/a)
Nicheniches(n/a)niche_class
Sub-niche(n/a)(n/a)niche_sub_class (YT only)
Pattern: Influencers.club has a two-level niche system (niche_class + niche_sub_class). CreatorDB has niches + topics. HypeAuditor uses a taxonomy ID system.

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Average Likes / Comments / Views

ConceptCreatorDB (YT)CreatorDB (IG)HypeAuditor (HIGH)Modash (MED)Phyllo (MED)
Avg likesvideosPerformanceRecent.likes.avgimagesPerformance.likes.avgavg_likesavgLikes(n/a)
Avg commentsvideosPerformanceRecent.comments.avgimagesPerformance.comments.avgavg_comments(n/a)(n/a)
Avg viewsvideosPerformanceRecent.views.avgreelsPerformance.views.avg(n/a)(n/a)(n/a)
Pattern: HypeAuditor and Modash use flat field names (avg_likes, avgLikes). CreatorDB nests inside content-type-specific performance objects, which provides more granularity (videos vs. shorts, recent vs. all) at the cost of deeper paths.

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Audience Location

ConceptCreatorDB (YT)CreatorDB (IG)HypeAuditor (HIGH)Modash (MED)Phyllo (MED)
Location arrayaudienceLocations[]audienceLocations[]audience_geography.countries[]audienceGeo(n/a)
Country codeaudienceLocations[].countryaudienceLocations[].countryaudience_geography.countries[].code(n/a)(n/a)
Share/proportionaudienceLocations[].shareaudienceLocations[].shareaudience_geography.countries[].value(n/a)(n/a)
Pattern: HypeAuditor uses audience_geography with deep nesting. Modash uses flat audienceGeo. CreatorDB’s audienceLocations is a reasonable middle ground. HypeAuditor uses value for proportions while CreatorDB uses share — CreatorDB’s choice is more descriptive.

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Audience Gender

ConceptCreatorDB (YT)CreatorDB (IG)HypeAuditor (HIGH)Modash (MED)Phyllo (MED)
Gender objectaudienceGenderaudienceGenderdemography[]genders(n/a)
Male ratioaudienceGender.maleRatioaudienceGender.maleRatiodemography[].gender="M" + .value(n/a)(n/a)
Female ratioaudienceGender.femaleRatioaudienceGender.femaleRatiodemography[].gender="F" + .value(n/a)(n/a)
Pattern: HypeAuditor uses an array with gender as a key. CreatorDB uses an object with named ratio fields. Both are valid; CreatorDB’s approach is simpler for consumers who just want male/female splits.

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Audience Age

ConceptCreatorDB (YT)CreatorDB (IG)HypeAuditor (HIGH)Modash (MED)Phyllo (MED)
Age breakdownaudienceAgeBreakdown[]audienceAgeBreakdown[]demography_by_age[].by_age_group[]ages(n/a)
Age range labelaudienceAgeBreakdown[].ageRangeaudienceAgeBreakdown[].ageRange.group(n/a)(n/a)
ShareaudienceAgeBreakdown[].shareaudienceAgeBreakdown[].share.value(n/a)(n/a)
Pattern: HypeAuditor nests age within gender (cross-tabulated). CreatorDB separates them. CreatorDB’s audienceAgeBreakdown is verbose but self-documenting. HypeAuditor’s demography_by_age is similarly verbose.

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Content Count

ConceptCreatorDB (YT)CreatorDB (IG)HypeAuditor (HIGH)Modash (MED)Phyllo (MED)
Total content counttotalContentstotalContentsposts_count / media_count(n/a)(n/a)
Content frequencycontentCountByDays.{7d,30d,90d}contentCountByDays.{7d,30d,90d}media_per_week(n/a)(n/a)
Pattern: HypeAuditor uses posts_count (action-oriented) and media_count (media-oriented). CreatorDB uses totalContents (platform-neutral). HypeAuditor tracks frequency as media_per_week; CreatorDB uses day-bucketed counts.

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Growth Metrics

ConceptCreatorDB (YT)CreatorDB (IG)HypeAuditor (HIGH)Modash (MED)Phyllo (MED)
Subscriber/follower growthsubscriberGrowth.{g7,g30,g90}followerGrowthIn30dsubscribers_growth_prc.performance.{7d,30d,90d,180d,365d}.value(n/a)(n/a)
Content performance growthrecentVideosGrowth.{g7,g30,g90}.avgViews(n/a)(n/a)(n/a)(n/a)
Pattern: HypeAuditor uses explicit day labels (7d, 30d). CreatorDB uses abbreviated keys (g7, g30). HypeAuditor offers more time windows (up to 365d). The g7/g30 abbreviation is an established CreatorDB convention.

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Avatar / Profile Image

ConceptCreatorDB (YT)CreatorDB (IG)HypeAuditor (HIGH)Modash (MED)Phyllo (MED)
Profile picture URLavatarUrlavatarUrlphoto_url(n/a)(n/a)
Pattern: HypeAuditor uses photo_url. CreatorDB uses avatarUrl. Both are clear. CreatorDB is consistent across platforms.

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Bio / Description

ConceptCreatorDB (YT)CreatorDB (IG)HypeAuditor (HIGH)Modash (MED)Phyllo (MED)
Profile biobiobioabout(n/a)(n/a)
Pattern: HypeAuditor uses about. CreatorDB uses bio. Both are clear and short.

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Verified Status

ConceptCreatorDB (YT)CreatorDB (IG)HypeAuditor (HIGH)Modash (MED)Phyllo (MED)
Verified badgeisVerifiedisVerifiedis_verified(n/a)(n/a)
Pattern: Universal agreement on the concept name is_verified / isVerified. Only casing differs.
ConceptCreatorDB (YT)CreatorDB (IG)HypeAuditor (HIGH)Modash (MED)Phyllo (MED)
Sponsor listsponsoredContent[] (pricing ref) / sponsorList[] (IG)sponsorList[]advertising_data.brand_mentions[](n/a)(n/a)
Brand namesponsoredContent[].brandNamesponsorList[].brandNameadvertising_data.brand_mentions[].username(n/a)(n/a)
Sponsored ERsponsoredVideosPerformance.engagement.avgEngagementRatesponsoredImagesPerformance.engagement.avgEngagementRateadvertising_data.avg_ad_er(n/a)(n/a)
Has sponsors flaghasSponsorshasSponsors(n/a)(n/a)(n/a)
Pattern: HypeAuditor frames this as “advertising data” with “brand mentions.” CreatorDB currently has an internal inconsistency: YouTube pricing ref uses sponsoredContent[] while Instagram uses sponsorList[]. Neither matches HypeAuditor’s terminology. The concept of grouping by brand is consistent.

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Contact Information

ConceptCreatorDB (YT)CreatorDB (IG)HypeAuditor (HIGH)Modash (MED)Phyllo (MED)
Email addressesemailsemailscontact_details.emails[](n/a)(n/a)
Phone numbers(n/a)(n/a)contact_details.phones[](n/a)(n/a)
Pattern: HypeAuditor nests under contact_details. CreatorDB uses flat emails. Both are reasonable for the current scope.

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Rankings / Scores

ConceptCreatorDB (YT)CreatorDB (IG)HypeAuditor (HIGH)Modash (MED)Phyllo (MED)
Ranking objectranking.totalSubscribers.{global,country,language}ranking.totalFollowers.{global,country,language}blogger_rankings.worldwide.rank(n/a)(n/a)
Audience quality(n/a)(n/a)audience_type.real + brand_safety.scoreaudienceCredibilityreputation
Pattern: HypeAuditor uses absolute rank positions; CreatorDB uses percentile scores (0-1). These are different metrics. CreatorDB does not currently expose audience authenticity or brand safety scores — this is a feature gap relative to HypeAuditor and Modash.
Last modified on March 25, 2026