Instagram customizable algorithm: what changes for brands

News in brief: Instagram redesigns the relationship between user and feed

On June 27, 2026, TechCrunch has 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 far beyond the individual consumer's experience.

Basically, users could soon state explicit preferences on content types, creators, and topics. As a result, the distribution algorithm will adapt to declared signals, not just implicit behaviors like likes, saves, and watch time. This represents a structural change in how Instagram balances content supply and demand.

Why this changes 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 could diminish.

Indeed, if a user explicitly states they prefer informative content over entertainment, the feed will adapt selectively. Similarly, a brand producing educational content could benefit from a more qualified reach towards already predisposed audience segments. Conversely, those who exclusively focus on viral formats might see a decrease in organic distribution to non-aligned targets.

In addition to this, algorithmic personalization pushes towards a more refined segmentation of the audience. For this reason, strategies of Digital marketing will need 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 might notice fluctuations in reach and impression metrics. Therefore, it's important not to interpret any drops as permanent negative signals. Instead, this is a phase of realignment between produced content and user preferences.

Specifically, the metrics to monitor most closely in the coming months include the save rate, video completion rate, and the ratio of organic reach to active followers. Additionally, it will be useful to observe the trend of impressions on content of different formats to identify any algorithmic redistributions.

According to the analyses of McKinsey on personalization systems that integrate explicit user signals generate a significant increase in qualified engagement. So, this evolution of Instagram isn't isolated: it's part of a platform trend towards declared personalization.

Three action areas to focus on right away

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.

Next, it's worth analyzing the audience data available 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 build a wealth 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 can support this process also on the textual content side.

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 significant qualitative leap. Therefore, it requires conscious adaptation, not a panicked reaction.

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

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

Connections with paid advertising strategy

It's important not to isolate the organic issue from the paid one. In fact, user preferences will also influence the quality of the context in which ads appear. Therefore, those managing google ads campaigns and paid activities on Meta will have to take into account how user behavior is changing even outside the platform.

Similarly, the LinkedIn campaigns for B2B can offer interesting methodological insights: on that platform, segmentation by declared interest is already a consolidated practice. Therefore, teams that have already developed skills in this area can transfer some of that know-how to managing Instagram.

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

Outlook: where Instagram is heading in the next 12-18 months

The current test is likely the first step in a longer journey. Therefore, it's reasonable to expect that Meta will progressively extend algorithmic controls, partly in response to European regulatory pressure on algorithmic transparency. The Digital Services Act already requires major 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 allowed users to declare explicit content preferences for some time now. Therefore, we are facing an industry trend, not an isolated choice by Meta.

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