Facebook is adding conversational controls that let people refine Feed and Reels recommendations.
Facebook is making its recommendation system more conversational. A new feature called Your algorithm lets people tell Facebook, in their own words, which topics they want to see more or less often in Feed and Reels.
For marketers, the change is more than a new settings screen. It introduces explicit natural-language feedback into a ranking system that has traditionally inferred interests from actions such as likes, comments, shares and watch time. Content relevance may become more precise—and generic posts may find it harder to reach people who have clearly defined their preferences.
How “Your algorithm” works
Meta says the feature gives users a dedicated place to add and manage topics they want to see. It is accessible through the three-dot menu on Facebook posts. Users can also select “Interested” or “Not interested” and provide more detail about their preference in freeform text.
The recommendations can update within the same session. Large language models interpret the context and intent in a user’s words, then combine that input with the behavioral signals Facebook already uses. The result is intended to be a ranking system that responds more directly to current interests.
Why this is important for content strategy
Interest-based recommendations have often relied on broad categories. Natural-language input can capture more nuance. A person might not simply ask for “marketing” content; they could request practical analytics tutorials, independent software reviews or advanced paid-media experiments while excluding beginner material.
That added precision raises the standard for publishers. A post with a clear subject, recognizable expertise and a specific audience promise is easier for both people and ranking systems to understand. Vague engagement bait may generate short-term reactions but provide weaker evidence about the durable interest it serves.
This direction also reinforces the value of human editorial judgment. Our coverage of AI-generated content on professional networks reached a similar conclusion: automation works best when it supports a distinctive point of view rather than replacing one.
What marketers should change
- Define the audience need precisely. Write down the problem, experience level and outcome for every content series.
- Use specific language. Headlines and opening lines should make the topic obvious without relying on exaggerated claims.
- Build repeatable themes. Consistent editorial pillars make it easier for audiences to identify what they want more of.
- Measure meaningful signals. Track saves, qualified comments, completion rate and downstream actions—not only reach.
- Study negative feedback. “Not interested” signals can reveal topic fatigue, poor targeting or a mismatch between headline and delivery.
Reels and Feed may require different creative
The same stated interest can appear differently across formats. In Feed, a detailed explanation, chart or link may satisfy the user. In Reels, the content may need a faster demonstration or a concise expert answer. Marketers should preserve the subject and value while adapting the presentation to the format.
Republishing identical assets everywhere can weaken relevance. A better workflow starts with one strong idea, then develops channel-specific executions. The headline, opening seconds, caption and call to action should all support the same clear topic.
What the update does not mean
The announcement does not say that stated interests will replace existing ranking signals. Meta describes freeform feedback as an addition to what Facebook already understands from engagement and viewing behavior. Marketers should therefore avoid treating the feature as a keyword-targeting system for organic posts.
It also does not guarantee distribution. Content still competes on usefulness, quality, originality and audience response. A post that matches a declared topic but disappoints the viewer is unlikely to build durable reach.
Implications for paid social teams
Meta’s announcement focuses on organic Feed and Reels recommendations, not a new advertising targeting option. However, the underlying shift is relevant to paid teams because it reflects improving interest interpretation. Advertisers should watch for future changes to contextual controls, creative diagnostics and recommendation-driven placements.
Teams testing newer inventory can compare this development with our guide to Threads advertising strategy. In both cases, creative that fits the surrounding experience is more useful than a generic asset distributed everywhere.
A practical testing framework
Create three versions of a content idea: a broad introduction, a specialist explanation and a practical checklist. Publish them over several weeks with consistent visual identity. Compare retention, saves, meaningful comments and profile actions. The goal is not to discover a trick for the algorithm; it is to learn which level of specificity attracts the right audience.
Document the words real customers use in comments, support requests and sales conversations. Those phrases can improve future topics and clarify the language used in captions. They should inform original writing, not be copied as artificial testimonials.
Frequently asked questions
What is Facebook’s “Your algorithm” feature?
It is a set of controls that lets people add, manage and describe the topics they want to see in Feed and Reels.
Can users change recommendations with freeform text?
Yes. Meta says users can explain what they want more or less of in their own words, and recommendations can respond in real time.
Does this replace likes and watch time?
No. Meta says natural-language preferences work together with the many behavioral signals already used by its ranking systems.
Does the update change Facebook Ads targeting?
The announcement concerns organic Feed and Reels recommendations. It does not introduce a new advertising targeting control.
Where is the official announcement?
Meta published the details in its Facebook “Your Algorithm” announcement.
Source: Meta Newsroom, October 13, 2026. Original analysis by GoogleDXB.
Facebook is making its recommendation system more conversational. A new feature called Your algorithm lets people tell Facebook, in their own words, which topics they want to see more or less often in Feed and Reels.
For marketers, the change is more than a new settings screen. It introduces explicit natural-language feedback into a ranking system that has traditionally inferred interests from actions such as likes, comments, shares and watch time. Content relevance may become more precise—and generic posts may find it harder to reach people who have clearly defined their preferences.
How “Your algorithm” works
Meta says the feature gives users a dedicated place to add and manage topics they want to see. It is accessible through the three-dot menu on Facebook posts. Users can also select “Interested” or “Not interested” and provide more detail about their preference in freeform text.
The recommendations can update within the same session. Large language models interpret the context and intent in a user’s words, then combine that input with the behavioral signals Facebook already uses. The result is intended to be a ranking system that responds more directly to current interests.
Why this is important for content strategy
Interest-based recommendations have often relied on broad categories. Natural-language input can capture more nuance. A person might not simply ask for “marketing” content; they could request practical analytics tutorials, independent software reviews or advanced paid-media experiments while excluding beginner material.
That added precision raises the standard for publishers. A post with a clear subject, recognizable expertise and a specific audience promise is easier for both people and ranking systems to understand. Vague engagement bait may generate short-term reactions but provide weaker evidence about the durable interest it serves.
This direction also reinforces the value of human editorial judgment. Our coverage of AI-generated content on professional networks reached a similar conclusion: automation works best when it supports a distinctive point of view rather than replacing one.
What marketers should change
- Define the audience need precisely. Write down the problem, experience level and outcome for every content series.
- Use specific language. Headlines and opening lines should make the topic obvious without relying on exaggerated claims.
- Build repeatable themes. Consistent editorial pillars make it easier for audiences to identify what they want more of.
- Measure meaningful signals. Track saves, qualified comments, completion rate and downstream actions—not only reach.
- Study negative feedback. “Not interested” signals can reveal topic fatigue, poor targeting or a mismatch between headline and delivery.
Reels and Feed may require different creative
The same stated interest can appear differently across formats. In Feed, a detailed explanation, chart or link may satisfy the user. In Reels, the content may need a faster demonstration or a concise expert answer. Marketers should preserve the subject and value while adapting the presentation to the format.
Republishing identical assets everywhere can weaken relevance. A better workflow starts with one strong idea, then develops channel-specific executions. The headline, opening seconds, caption and call to action should all support the same clear topic.
What the update does not mean
The announcement does not say that stated interests will replace existing ranking signals. Meta describes freeform feedback as an addition to what Facebook already understands from engagement and viewing behavior. Marketers should therefore avoid treating the feature as a keyword-targeting system for organic posts.
It also does not guarantee distribution. Content still competes on usefulness, quality, originality and audience response. A post that matches a declared topic but disappoints the viewer is unlikely to build durable reach.
Implications for paid social teams
Meta’s announcement focuses on organic Feed and Reels recommendations, not a new advertising targeting option. However, the underlying shift is relevant to paid teams because it reflects improving interest interpretation. Advertisers should watch for future changes to contextual controls, creative diagnostics and recommendation-driven placements.
Teams testing newer inventory can compare this development with our guide to Threads advertising strategy. In both cases, creative that fits the surrounding experience is more useful than a generic asset distributed everywhere.
A practical testing framework
Create three versions of a content idea: a broad introduction, a specialist explanation and a practical checklist. Publish them over several weeks with consistent visual identity. Compare retention, saves, meaningful comments and profile actions. The goal is not to discover a trick for the algorithm; it is to learn which level of specificity attracts the right audience.
Document the words real customers use in comments, support requests and sales conversations. Those phrases can improve future topics and clarify the language used in captions. They should inform original writing, not be copied as artificial testimonials.
Frequently asked questions
What is Facebook’s “Your algorithm” feature?
It is a set of controls that lets people add, manage and describe the topics they want to see in Feed and Reels.
Can users change recommendations with freeform text?
Yes. Meta says users can explain what they want more or less of in their own words, and recommendations can respond in real time.
Does this replace likes and watch time?
No. Meta says natural-language preferences work together with the many behavioral signals already used by its ranking systems.
Does the update change Facebook Ads targeting?
The announcement concerns organic Feed and Reels recommendations. It does not introduce a new advertising targeting control.
Where is the official announcement?
Meta published the details in its Facebook “Your Algorithm” announcement.
Source: Meta Newsroom, October 13, 2026. Original analysis by GoogleDXB.