Instagram started hiding like counts from public view in several markets in 2019. This change sparked debate about whether engagement would drop, rise, or stay the same.
The evidence shows that hiding likes had minimal impact on overall engagement rates. However, it changed how marketers measure performance and make decisions.
Most brands and creators saw no significant shift in comments, shares, or saves when like counts disappeared from feeds.
The real issue isn't whether likes went up or down. Likes were never a reliable signal of genuine engagement.
They're easy to inflate, don't reflect reach or conversion, and reveal little about audience quality. When Instagram removed public like counts, it highlighted how many campaigns relied on weak metrics.20
Brands often used like counts to evaluate influencers, justify budgets, and report results. This approach created blind spots.
This article explains what changed after Instagram hid likes, why engagement metrics need better context, and which signals matter more for marketing performance.
Key Takeaways
- Hiding like counts caused little change to actual engagement behaviour on Instagram
- Likes alone are a poor measure of campaign performance or audience quality
- Marketers should prioritise reach, saves, shares, and conversion data for better decisions
Platform and Marketing Shifts Following Hidden Like Counts
Instagram began testing hidden like counts in 2019 and rolled out optional visibility controls in 2021. These changes affected how users assessed content performance and how marketers reported campaign results.
Changes for Users and Marketers
Instagram's decision to hide like counts altered the platform's interface, not its mechanics. Users could still see their own like counts but couldn't view totals on other people's posts.
For marketers, this created a reporting gap. Clients and stakeholders expected to see like counts as proof of campaign success.
When those numbers disappeared from public view, agencies had to request screenshots from account owners or shift focus to other metrics. The change also affected influencer vetting.
Brands could no longer quickly scan an influencer's posts to gauge popularity. They needed direct access to analytics or had to rely on self-reported data.
Key shifts included:
- Loss of public like counts as a credibility signal
- Increased reliance on reach and impression data
- Greater emphasis on comments and shares
- Need for screenshot-based reporting in Social Media Marketing
Why the Impact Was Widely Misunderstood
Many articles claimed hidden likes would reduce engagement or fundamentally change user behaviour. The data didn't support this.
Engagement rates remained relatively stable across most account types. The confusion came from conflating visibility with value.
Hiding like counts changed what viewers could see, not what the algorithm prioritised. Instagram's ranking systems still heavily weighted likes when determining content distribution.
Likes still mattered for reach. Marketers simply needed account access to view them.
The real impact was practical. Reporting became more cumbersome, and competitive analysis required new tools.
The core dynamics of Instagram engagement did not transform as dramatically as many predicted.
Limitations of Like Counts as an Engagement Signal
Like counts provide incomplete data about content performance. They can lead businesses to misread audience behaviour.
Public metrics often prioritise surface-level validation over meaningful commercial outcomes.
Visibility Does Not Equal Influence
A high like count does not guarantee that a post drove conversions, changed opinions, or strengthened brand perception. Some posts with thousands of likes generate zero enquiries, while others with modest engagement produce qualified leads.
Likes measure one action: a tap. They don't capture saves, shares to close contacts, or off-platform conversations.
A user might like a post out of habit or politeness without reading the caption or remembering the brand. This becomes critical when evaluating influencer partnerships.
An account with 50,000 likes per post might reach a disengaged audience that scrolls passively. Another creator with 3,000 likes could maintain an active community that trusts recommendations and takes action.
Likes also fail to distinguish between audience types:
- Existing customers showing support
- Competitors monitoring your content
- Bots or inactive accounts
- Users who never purchase in your category
Without segmentation, like counts flatten all interactions into a single number. This number doesn't reflect commercial value.
How Public Likes Can Distort Campaign Decisions
Visible like counts often push brands to optimise for the wrong outcomes. Teams chase vanity metrics instead of testing what drives revenue, signups, or retention.
Some marketing departments select influencers based solely on average likes rather than audience demographics or conversion history. This leads to misallocated budgets and partnerships that look impressive in reports but deliver poor return on investment.
Public visibility also creates pressure to replicate high-performing formats without understanding why they worked. A viral post might succeed due to timing, external trends, or algorithmic luck rather than repeatable strategy.
Like-focused decisions often ignore:
- Cost per acquisition
- Customer lifetime value from social channels
- Engagement rate relative to reach
- Sentiment in comments and direct messages
Hiding like counts encourages teams to examine deeper metrics. However, many still request screenshots or third-party data that reintroduce the same bias.
Analysing the Effects on Engagement Metrics
Changes to like visibility don't happen in isolation. The data we collect rarely tells a simple story.
Multiple variables shift at once, making it difficult to isolate what actually drove a change in performance.
Why Simple Before-and-After Claims Can Be Misleading
Many reports claim that hiding likes increased engagement by 20% or 30%. These figures almost never account for what else changed during the same period.
Instagram's algorithm updates constantly. A brand might test hidden likes in November and see a spike in comments, but that same month could coincide with a feed ranking change that boosted reach for certain content types.
Seasonal patterns matter too. Engagement often rises during holidays, product launches, or industry events.
If you compare October to December without controlling for these factors, you're measuring timing as much as like visibility. Sample size creates another problem.
A single account testing hidden likes for two weeks doesn't generate enough data to draw reliable conclusions. Reliable results require data across multiple accounts, content types, and time periods.
Other Factors Influencing Engagement
Content quality remains the strongest driver of engagement, regardless of whether likes are visible. A poorly targeted post won't perform better simply because the like count is hidden.
Audience composition shifts over time. New followers might engage differently than long-term ones.
If you gained 5,000 followers from a viral post during your test period, that influx will affect your engagement rate independently of like visibility. Posting frequency and timing influence results.
Caption length, hashtag strategy, and whether you use Reels versus static posts also play a role. External factors matter as well.
Competitor activity, news cycles, and platform-wide trends all affect how users interact with content. Engagement changes rarely stem from a single variable.
Alternative Metrics for Assessing Performance
Likes are only one signal among many, and often not the most valuable. Tracking saves, shares, comments, clicks, and conversions provides a more complete picture of how content drives business outcomes.
Saves, Shares, Comments, Clicks, and Conversions
Saves indicate that someone found your content valuable enough to revisit. Instagram's algorithm treats saves as a strong engagement signal, often stronger than likes.
A high save rate typically means your content offers practical information, inspiration, or reference value. Shares extend your reach beyond your existing audience.
When someone shares your post to their story or sends it via direct message, they're endorsing your content to their network. This is particularly valuable for brand awareness and trust-building.
Comments reveal deeper engagement than passive likes. They show that someone took time to respond, ask questions, or start a conversation.
I look at comment quality and sentiment, not just volume. Clicks and conversions tie Instagram activity to business results.
Link clicks in stories, profile visits, and website traffic from Instagram connect content to revenue. Tracking these through analytics and data analysis tools helps measure return on investment.
Engagement Quality Versus Visible Engagement Totals
A post with 500 likes and no other action is less valuable than one with 100 likes, 50 saves, and 20 meaningful comments. Quality engagement drives business outcomes, while high like counts may simply reflect follower size or posting time.
I focus on engagement rate relative to reach, not just follower count. A small, engaged audience often converts better than a large, passive one.
Accounts with many followers but low saves, shares, or clicks typically underperform on actual business metrics. Measuring engagement quality means tracking who engages, not just how many.
Engagement from your target audience—potential customers, industry peers, or relevant influencers—matters more than generic attention. This requires segmenting your audience data and analysing which content resonates with high-value followers.
Evolving Influencer Marketing Evaluation Criteria
Brands now use more sophisticated metrics to evaluate influencer partnerships, moving beyond follower counts. They focus on audience authenticity, backend performance data, and the challenge of identifying manufactured engagement.
Increased Focus on Audience Quality
Brands no longer select influencers based only on follower numbers. They care more about who those followers are and how authentically they engage.
Audience demographics now outweigh vanity metrics. Brands check age ranges, locations, and interests to match their target customers.
An influencer with 50,000 relevant followers often outperforms one with 500,000 disengaged accounts.
Key audience quality indicators include:
- Comment sentiment and conversation depth
- Follower-to-engagement ratios within specific niches
- Audience overlap with the brand's customer base
- Account activity patterns and posting consistency
The prevalence of fake followers and inauthentic engagement makes this scrutiny necessary.
Greater Importance on Private Performance Data
Brands now ask for access to influencer analytics dashboards instead of relying on public metrics. These backend insights reveal patterns that public data misses.
Instagram Insights breaks down reach, impressions, story completion, and profile visits. Saves and shares often show stronger audience connection than likes. Exit rates and watch times highlight content quality beyond public engagement.
Critical private metrics now include:
- Story retention and tap-forward rates
- Profile activity after posts (visits, website clicks)
- Audience growth sources (organic vs. paid)
- Peak engagement times and follower activity patterns
This data shows if an influencer's audience cares about the content or just scrolls past it.
Challenges in Detecting Fake Engagement
Fraudulent engagement has grown more sophisticated, making detection harder without specialised tools. Bot accounts now mimic human behaviour, leaving generic but plausible comments and varying their activity.
Engagement pods and comment groups artificially inflate metrics. Members agree to like and comment on each other's posts, creating numbers that look real but lack genuine interest.
Warning signs of manufactured engagement:
- Sudden engagement spikes that don't match follower growth
- Comments lacking specificity or relevance
- High engagement rates from accounts with few followers
- Disproportionate likes compared to saves, shares, or meaningful comments
Analysing engagement velocity and interaction ratios helps spot fake patterns. Genuine audiences respond in varied ways, while fake engagement follows predictable trends.
Brand Perspectives on the Value of Likes
Brands track likes for reporting, but the real value appears when likes influence customer purchasing decisions through visible social proof.
Vanity Metrics and Internal Reporting
Most marketing teams include like counts in their monthly reports. The metric is easy to track and explain to stakeholders unfamiliar with social media.
Likes alone reveal little about business performance. A post with 500 likes might drive no website visits, while another with 200 likes could generate 50 conversions.
Internal teams often judge campaigns by like counts because the metric is visible and comparable. It allows for month-over-month tracking and competitive benchmarking.
What likes actually measure:
- Initial content appeal
- Audience size
- Posting time and algorithm effects
Likes do not measure purchase intent, brand recall, or customer lifetime value. Using likes for evaluation measures audience reaction, not business results.
When Visible Social Proof Influences Decisions
Like counts matter when customers can see them. A post with 2,000 likes signals popularity to someone new to the brand.
Visible engagement affects consumer trust. New customers often check social proof before buying. High like counts suggest others have validated the brand.
Instagram's 2019 test to hide like counts removed a key trust signal from the customer journey. Brands couldn't use social proof in the same way.
However, the business impact was limited. Customers still saw follower counts, comments, and shares. Purchase decisions rely on multiple factors besides like counts.
Contemporary Best Practices for Assessing Engagement
Modern engagement assessment goes beyond surface-level counts. It focuses on metrics that reflect genuine audience interest and commercial outcomes.
Moving Beyond Public Metrics
Track engagement metrics that Instagram provides to account holders, even if public like counts are hidden. Saves, shares, and comment depth reveal more about content resonance than likes.
Reach and impressions from non-followers show how content performs algorithmically. Profile visits indicate whether engagement leads to genuine interest.
Monitor the percentage of followers who engage with each post, not just raw numbers.
Instagram's professional dashboard offers data on audience demographics, active hours, and top-performing content types. These insights matter more than public validation metrics.
Private metrics reveal patterns public counts cannot. A post with 200 likes and 50 saves may be more valuable than one with 500 likes and no saves.
Comparing Consistency Across Posts
Analyse engagement patterns across multiple posts rather than focusing on individual performance. One viral post does not indicate healthy engagement if later content underperforms.
Calculate average engagement rates across 10-20 recent posts to set a baseline. This shows if an account maintains audience interest or relies on occasional spikes.
Engagement rate fluctuations identify which content types, times, and formats work best. Track whether certain topics generate saves while others drive comments.
Compare engagement rates between feed posts, stories, and reels. An account might excel in reels but have weak feed engagement, highlighting audience behaviour that affects planning.
Aligning Engagement with Campaign Goals
Match engagement metrics to campaign objectives. Brand awareness campaigns need reach and impressions. Conversion campaigns need link clicks and enquiry messages.
Comments matter for community-building. Saves indicate intent for educational content. Shares extend reach for advocacy campaigns. Choose primary metrics based on campaign goals.
Set benchmarks using industry standards and account history. B2B consultancies should not expect the same engagement rates as fashion brands.
Consider follower count, as larger accounts typically see lower percentage engagement. Different products and services require different engagement thresholds for success.
Prioritise qualified enquiries over high like counts from irrelevant audiences.
Assessing Commercial Relevance Over Activity
Focus on engagement from accounts that match target customer profiles, not just total volume. Ten comments from decision-makers matter more than 100 from casual browsers.
Review comment quality, not just quantity. Generic emoji responses suggest passive scrolling. Questions and detailed feedback show real interest.
Track how many engaged users convert to leads or customers. Profile visits, website clicks, and direct messages provide clearer paths to commercial outcomes than likes or comments.
Monitor whether engagement comes from target markets and demographics. High engagement from outside target markets inflates metrics without supporting business goals.
Implications for Businesses, Creators, and Agencies
Access to like counts changes how marketing teams evaluate performance, select partners, and justify campaign spending.
Enhancing Reporting Decisions
Like counts offer a quick reference when building reports or assessing performance. They help spot patterns in what resonates with audiences without deep dives into analytics for every post.
Like counts allow more consistent creator comparisons. When like counts were hidden, I relied on reach and saves, but those don't always show if content connected with viewers. Likes give immediate feedback on audience response.
Key reporting improvements:
- Faster performance comparisons across posts
- Easier identification of top-performing content formats
- More complete data for month-over-month analysis
Metrics like conversion rate and click-through rate remain priorities for commercial outcomes. Likes help identify engagement trends before audiences take action. They're useful for early-stage content testing and experimentation.
Improving Creator Selection
Like counts help filter potential creator partnerships more efficiently. I check like-to-follower ratios to spot creators with engaged audiences versus inflated follower numbers.
A creator with 50,000 followers and 500 likes per post signals different engagement quality than one with 10,000 followers and 800 likes. I use this data with comment quality and profile growth rates to assess partnership value.
I don't rely solely on like counts. Some niches generate fewer likes but higher conversion rates. B2B content often gets more saves than likes because audiences reference it later.
Evaluation checklist:
- Like-to-follower ratio consistency
- Engagement rate trends over three months
- Comment authenticity and depth
- Audience demographics alignment
Strengthening Campaign Evaluation
I measure campaign success through sales and leads first. Like counts help me evaluate content resonance during the campaign by showing whether messaging landed with the target audience.
When I run awareness campaigns without direct conversion tracking, likes provide a measurable signal of content reception. I combine them with reach data to calculate engagement rates that guide future creative direction.
I track like counts against benchmarks specific to each industry and content type. For example, a product carousel might average 2-4% engagement, while educational content hits 5-7%.
These benchmarks help me set realistic targets and identify underperforming content faster.
Final Verdict
Instagram hiding like counts did not fundamentally change engagement. What it really changed was visibility. Likes became harder to use as a quick public reference point, but they were never strong enough on their own to judge campaign quality, audience interest, or business performance.
For marketers, the bigger lesson is simple: public likes are a weak decision-making tool. Reach, saves, shares, comments, clicks, profile activity, and conversion data give a far better picture of whether content is actually working.
That does not mean likes are useless. They still offer a basic signal of initial content appeal and can help with trend spotting. But they should sit inside a wider measurement framework, not act as the headline metric that drives strategy, reporting, or influencer selection.
If you want better Instagram decisions, focus less on visible social proof and more on audience quality, engagement depth, and commercially relevant outcomes. That is where the real value sits.
Frequently Asked Questions
Instagram's like count settings, engagement calculations, and performance benchmarks often create confusion for marketers who need accurate reporting and reliable decision-making frameworks.
Does Instagram still display the number of likes on posts, and how can you toggle this setting?
Instagram allows users to hide like counts on their own posts or on content they view from others. The platform introduced this option in 2021 after testing it in several markets.
To hide likes on your own posts, go to Settings, then Privacy, then Posts. You'll find an option to hide like and view counts.
You can also hide likes on individual posts before publishing by accessing Advanced Settings during the creation process.
To hide likes on posts from other accounts you view, navigate to Settings, then Privacy, then Posts, and enable “Hide Like and View Counts.” This affects only what you see, not what others see on your content.
How do you calculate an Instagram engagement rate accurately, and which formula should you use?
I calculate engagement rate by dividing total engagements by total followers, then multiplying by 100 to get a percentage. Total engagements include likes, comments, saves, and shares on a post.
The formula is: (Likes + Comments + Saves + Shares) ÷ Followers × 100.
Some marketers use reach instead of followers. This method divides total engagements by the number of accounts who saw the post.
Reach-based calculations show how content performs with people who actually see it. Follower-based rates remain the industry standard for comparisons.
What is considered a good engagement rate for an Instagram account in 2026
A good engagement rate ranges between 1% and 5% for most business accounts in 2026. Accounts with fewer than 10,000 followers often see higher rates, sometimes between 3% and 6%.
Larger accounts with over 100,000 followers often see rates below 2%. Audience size and engagement usually have an inverse relationship.
Niche matters. Fashion and beauty accounts typically achieve higher engagement than business-to-business accounts.
I always compare performance within the same industry category rather than across all account types.
With 1,000 followers, how many likes per post is typical across different niches?
An account with 1,000 followers typically receives between 30 and 60 likes per post. This represents a 3% to 6% engagement rate.
Lifestyle and personal brand accounts often perform at the higher end. Professional services and business accounts usually sit at the lower end.
These figures assume the account has genuine followers and posts consistently. Accounts with sudden follower growth or purchased followers see significantly lower like counts.
Influencer marketing statistics and benchmarks show that authentic audience building produces more predictable engagement patterns.
Do hidden like totals affect reach, distribution, or performance insights on Instagram?
Hidden like counts do not affect how Instagram distributes your content. The algorithm tracks all engagement signals whether likes are visible or not.
Your Insights panel shows complete engagement data regardless of your like visibility settings. You retain access to likes, saves, shares, comments, and reach metrics.
Hiding likes may reduce social proof for new viewers. Some marketers report that visible like counts encourage more engagement from hesitant followers.
Instagram's internal systems continue measuring all interactions normally.
What is the 5-3-1 rule on Instagram, and how is it used to improve interaction?
The 5-3-1 rule is a daily engagement strategy. You engage with five posts in your niche, leave three genuine comments on target accounts, and post one piece of your own content.
This approach increases visibility through regular interaction. Commenting on other posts puts your username in front of their followers and can drive profile visits.
This rule often helps smaller accounts build initial traction. Larger accounts usually need more advanced engagement strategies tailored to their audience and business goals.
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Hi, I’m Stuart Kerr Spindlow; the publisher behind StuartKerrs.com.
I review and evaluate digital marketing software used by businesses, marketers, and website owners; including hosting platforms, website builders, email marketing tools, SEO software, analytics, and automation systems.
I hold a degree in Computer Science from The Open University and began my career working in financial technology, developing and supporting production software systems, banking intranets, and web platforms. Over the past 20+ years, I’ve tested, implemented, and analysed a wide range of digital tools across real-world business environments.
Today, this site focuses on independent, experience-led software reviews. Tools are assessed based on usability, performance, pricing transparency, long-term value, and suitability for real businesses; not vendor claims or sponsorships.
I don’t run an agency and I don’t sell services through this site. The goal is simple: publish honest, practical software reviews that help people choose the right tools with confidence.
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