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Understanding Archive Radar

Learn how Archive Radar detects your brand in posts without tags or mentions.

Kylie Decipeda avatar
Written by Kylie Decipeda
Updated today

Archive Radar automatically finds content featuring your brand, even when creators don't tag or mention you. This means you can discover valuable content that would otherwise stay hidden from your social listening feeds.


What Archive Radar Does

Archive Radar detects your brand's logos and products in images and videos from influencer content across social platforms. It works by analyzing visual content that lacks text mentions or hashtags, then surfaces these posts alongside your other social listening content.

This solves a common problem for brands: some of your best user-generated content never shows up in traditional social listening because creators simply post photos or videos of your products without tagging your brand or using relevant hashtags.


How It Works

Archive Radar runs automatically in the background. When Archive scans influencer content, posts that already have mentions or hashtags are captured through our standard systems. The remaining content gets analyzed by Archive Radar to detect whether your brand appears visually.

Once your brand is detected in a post, Archive validates the content for quality before adding it to your workspace. This quality check ensures you only see relevant, high-value content.


Accessing Your Radar Content

You can find content detected by Archive Radar in several places:

  1. Social Listening Page: Radar posts appear alongside your other posts. Filter specifically for Radar content by going to Filter β†’ Source β†’ "Archive Radar: @mentiontag".

  2. Individual Posts: When you open a post that was detected by Radar, you'll see "Archive Radar" listed as its source.

  3. Dedicated Views: Archive automatically creates dedicated views for Radar content in both Social Listening and Reports, making it easy to access without manual filtering.


When Radar Works Best

Archive Radar performs exceptionally well for brands with distinctive, recognizable visual elements. Think clear logos like Carhartt, or unique product designs like Crocs. These brands benefit most from Radar's ability to spot their products in images and videos.

The feature scales automatically with your brand's reach. Bigger brands naturally generate more detected content, and the system handles high volumes without any issues.


Real-World Impact

Archive Radar has proven its value by catching content that generates millions of views. For instance, it can detect posts like celebrities or influencers casually wearing your products in their content, even when they don't mention your brand. These organic moments represent high-value content you can leverage for marketing and social proof.

In recent months, Archive Radar has detected millions of untagged mentions across brands using the feature.


Combining Radar with Sentiment Analysis

When you use Archive Radar alongside sentiment analysis, you get even more insight. You can see not just where your products appear, but understand whether that content carries positive or negative sentiment. This helps you identify great brand moments to amplify and potential issues that need attention.


Important Things to Know

  • Content Limits: Archive Radar content does count toward your UGC limits. However, because Archive validates content for quality before adding it to your workspace, you receive high-value posts rather than noise.

  • Turning It Off: If you need to disable Archive Radar, contact our support team. That said, most brands find the feature valuable because of the quality validation that happens before content appears.

  • Detection Quality: Archive Radar works best when brands have easily recognizable visual elements. If your brand uses subtle or generic designs without visible logos, detection may be limited.


Providing Feedback

If you see content that doesn't match your brand or appears incorrectly detected, use the feedback option in the interface. Your feedback helps us continuously improve detection accuracy over time.

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