Instagram customizable algorithm: what changes for brands

The news in summary: Instagram redesigns the user-feed relationship

On June 27, 2026, TechCrunch reported that Instagram is testing new features within the section Your Algorithm. The stated goal is to offer users more granular control over the content displayed in their feed. However, the impact of this move extends well beyond the individual consumer's experience.

In practice, users could soon indicate explicit preferences for content types, creators, and topics. Consequently, the distribution algorithm will adapt to declared signals, not just implicit behaviors like likes, saves, and watch time. This represents a structural shift in how Instagram balances content supply and demand.

Why does this change the rules for content marketers

Until today, brands have built their organic strategies on Instagram based on aggregated behavioral signals. Therefore, formats like Reels have dominated distribution because they were favored by the algorithm across the board. With the introduction of declared preferences, this advantage may be reduced.

Indeed, if a user explicitly states a preference for informative content over entertainment, the feed will adapt selectively. Similarly, a brand that produces educational content could benefit from a more qualified reach towards predisposed audience segments. Conversely, those focusing solely on viral formats might see a decrease in organic distribution to misaligned targets.

In addition to this, algorithmic personalization drives a more refined audience segmentation. For this reason, strategies digital marketing They will have to integrate a more careful reading of the stated preferences of the target audience.

The immediate impact on organic metrics

In the short term, marketing teams may observe fluctuations in reach and impression metrics. Therefore, it's important not to interpret any dips as permanent negative signals. Instead, this is a period of realignment between produced content and user preferences.

In particular, the metrics to monitor with greater attention in the coming months include the save rate, video completion rate, and the ratio of organic reach to active followers. Furthermore, it will be useful to observe the trend of impressions across different content formats to identify any algorithmic reallocations.

According to the analysis of McKinsey on Personalization, systems that integrate explicit user signals generate a significant increase in qualified engagement. Therefore, this evolution of Instagram is not isolated: it fits into a platform trend towards declared personalization.

Three operational areas to act on immediately

First of all, it's worth reviewing the current content mix. If the strategy is focused on a single format, now is the right time to diversify. In fact, a balanced distribution between Reels, carousels, and static content offers greater resilience against algorithmic changes.

Subsequently, it is appropriate to analyze the available audience data in Instagram Insights. In particular, the most active follower segments and the content types with the highest save rate provide valuable insights into what the audience already prefers. This data becomes even more relevant in a context of declared personalization.

Finally, it's time to structure systematic A/B tests on different editorial formats and angles. By doing so, you accumulate a portfolio of proprietary data that allows for rapid adaptation as soon as new features Your Algorithm will be released more broadly. The activities of Strategic copywriting and of SEO They can also support this process in terms of textual content.

The perspective of an agency working in the field

We at SHM Studio observe this evolution with analytical interest, not alarm. Social platforms have always modified their algorithms. However, the shift from implicit signals to declared preferences is a relevant qualitative leap. Therefore, it requires conscious adaptation, not a panicked reaction.

In concrete terms, brands that have invested in a Consistent content strategy those oriented towards user value are better positioned to benefit from this transition. Conversely, those who have built their Instagram presence solely on volume dynamics—frequent posting without a defined editorial strategy—will need to rethink their approach.

Incidentally, this dynamic aligns with what Harvard Business Review has documented on the value of a qualitative customer relationship compared to simple volume acquisition. Algorithmic personalization rewards relevance, not frequency.

Connections with paid advertising strategy

It's important not to isolate the organic aspect from the paid aspect. In fact, user preferences will also influence the quality of the context in which ads appear. Therefore, whoever manages Google Ads campaigns and paid activities on Meta will have to take into account how user behavior changes even outside the platform.

Analogously, the LinkedIn campaign For B2B, they can offer interesting methodological insights: on that platform, segmentation by declared interest is already a consolidated practice. Therefore, teams that have already developed expertise in this area can transfer part of that know-how to managing Instagram.

In summary, the convergence between organic personalization and paid targeting requires an integrated vision. This is precisely the type of approach we propose in our activities. digital marketing and in strategic consulting for clients.

Prospects: Where is Instagram Heading in the Next 12-18 Months?

The current test is likely the first step in a longer journey. Therefore, it is reasonable to expect Meta to progressively expand algorithmic controls, partly in response to European regulatory pressure for algorithmic transparency. Digital Services Act already requires large platform operators to offer alternative recommendation systems.

Furthermore, the direction Instagram is taking aligns with what's happening on other platforms. TikTok has introduced similar features in recent months. YouTube has long allowed users to explicitly state content preferences. Therefore, we are looking at an industry trend, not an isolated choice by Meta.

For Italian marketing managers, the operational recommendation is clear: start now to build an editorial strategy based on relevance for defined audience segments. By doing so, you'll be ready when new customization features are available for all accounts. To delve deeper into these topics, you can Contact the SHM Studio team to consult available resources in our blog. The activities AI applied to marketing They can also support predictive analysis of audience preferences in this new algorithmic context.