Quick answer
To benchmark your beauty campaign against competitors, compare engagement rate, views and creator mix against category medians, not averages. Recent India makeup-collab data (5,638 posts, Aug–Nov 2026) shows a median engagement rate of 1.53%, average views of 86.8K, and 65.1% of collabs going to nano and micro creators solid reference points before judging your own results.
Every beauty brand running influencer campaigns eventually asks the same question: is this working, or does it just feel like it's working? To benchmark your beauty campaign against competitors properly, you need a comparison point, not a gut feeling. A 2% engagement rate sounds strong until you learn that mega creators in your category often post lower numbers than nano creators simply because of how reach scales with audience size.
Benchmarking replaces that guesswork with a reference range pulled from campaigns running right now. This matters in beauty more than in most categories, because engagement rate, reach and creator tier all move together in ways that are easy to misread without a baseline. The goal isn't to copy a competitor's exact creator list, but to know what "good" looks like for a given budget, tier and month before committing spend. The sections below cover the metrics worth tracking, current India benchmarks for the category, and a simple method for applying them to your own campaign.
Why Benchmark Your Beauty Campaign Against Competitors
Benchmarking is the practice of comparing your campaign's performance to a defined peer set same category, similar time window, and comparable creator tiers rather than to an internal target picked in isolation. Without a peer set, a brand can misread its own results in either direction: calling an average performing reel a win, or dismissing a strong nano-tier post because it has fewer raw views than a mega-tier one.
The four metrics worth tracking
- Engagement rate (ER%) — (likes + comments) ÷ views per post. This is the clearest indicator of audience response, and should be read as a median across a sample, not a single post.
- Average and median views — views show reach; the gap between average and median views in a dataset reveals whether a few outlier posts are skewing the picture.
- Creator tier mix — the share of collabs going to nano, micro, macro and mega creators. This shapes both cost and the kind of engagement a campaign should expect.
- Repeat rate — the share of brand-creator pairs working together more than once. A rising repeat rate often signals a brand has found creators who convert reliably and is retaining them.
Why medians beat averages here
A single mega-creator post with a very high view count can pull a category's average view figure well above what a typical campaign sees. Medians strip that distortion out, which is why the benchmarks used in this article lead with medians rather than averages.
Current Beauty Influencer Benchmarks in India
Source: MyWall Genie · 5,638 collabs · 2026-08-16 to 2026-11-14
The dataset behind this article covers 5,638 makeup collaboration posts from 2,971 creators across 218 brands, run between 16 August and 14 November 2026. It's a reasonable proxy for beauty more broadly, since makeup collaborations tend to follow similar reach and engagement patterns to skincare and haircare ones. The peak month for collab volume in this window was October 2026, which lines up with festive-season beauty spending.
Engagement rate by creator tier
Median engagement rate by follower tier (Makeup, India)
| Tier | Collabs | Median ER (%) | Avg views | Repeat rate (%) |
|---|---|---|---|---|
| nano | 1,559 | 1.91% | 24,764 | 20.5% |
| micro | 2,109 | 1.45% | 36,957 | 15.2% |
| macro | 1,537 | 1.3% | 101,467 | 24.2% |
| mega | 433 | 1.63% | 500,394 | 33.2% |
Source: MyWall Genie · 5,638 collabs · 2026-08-16 to 2026-11-14
Nano creators post the highest median engagement rate in this sample, while mega creators post the highest average views and the highest repeat rate. This is the pattern most beauty brands should expect: nano and micro accounts for engagement-led objectives, macro and mega for reach and brand recall.
Collab volume across the quarter
Beauty collabs by month, Aug–Nov 2026
Collab volume nearly tripled between August and October before easing in November, suggesting brands front-load beauty campaigns ahead of festive shopping peaks. If a competitor's campaign appears to go quiet in November, that's consistent with category-wide seasonality rather than a pulled budget.
Methodology
Engagement rate = (likes + comments) ÷ views, calculated per collab post. Figures reported are medians, not averages, unless stated otherwise. Creator tiers are based on the creator's follower count. The dataset covers 5,638 makeup collaboration posts from 16 August to 14 November 2026 and was not truncated.
How to Set Your Own Benchmark
Step 1: Define a comparable peer set
Pull campaigns from the same brand category, a similar time window, and, where possible, a similar creator tier mix. Comparing a nano-heavy campaign against a competitor that leans mega will make your engagement rate look artificially strong or weak.
Step 2: Compare medians, not single posts
One standout reel is a data point, not a trend. Before concluding a competitor is beating you, look at their typical post, not their best one. Average views for mega creators sit well above median views in this dataset, because a handful of standout reels carry the average.
Step 3: Weight the comparison by objective
If the goal is engagement and community response, benchmark against the nano or micro median engagement rate. If the goal is reach and awareness, benchmark against macro or mega average views instead. Measuring an awareness campaign by engagement rate, or vice versa, produces a benchmark that technically works but answers the wrong question.
Step 4: Track repeat rate as a quality signal
A brand's repeat rate with its creators is a proxy for how well partnerships are actually converting. The category's overall repeat rate in this window sits at 19.9%; brands repeating with creators well above that figure are typically doing something right with their pick-and-retain process.
Reading Real Campaigns as Benchmarks
Looking at how individual posts perform puts the numbers in context. One mega-tier collab in this dataset reached over 15.8 million views, illustrating the upper end of reach a well-placed mega collaboration can generate in this category.
Mega-reach example in a beauty campaign
Reach isn't the only story. A different mega-tier collab in the dataset posted an engagement rate close to 4.7%, well above the mega-tier median of 1.63%, showing that high-reach creators can still post above-benchmark engagement when the content format resonates.
Above-benchmark engagement at scale
At the smaller end, one macro-tier collab posted an engagement rate above 11%, several multiples above the macro median of 1.3%. This is a reminder that tier alone doesn't guarantee performance — content and creator fit still decide the outcome.
Common Benchmarking Mistakes to Avoid
- Comparing one post to a category average. A single data point is noise; use a sample across several weeks before drawing conclusions.
- Ignoring tier mix. A campaign built entirely on mega creators should never be benchmarked against a nano-heavy competitor's engagement rate.
- Benchmarking only on vanity metrics. Views without engagement rate and repeat-partnership context give an incomplete read on whether a campaign is landing with its audience.
- Skipping the time window. Beauty collab volume and engagement both shift with season, so benchmark against the same calendar period as your competitor, not a year-round average.
Working with a specialist influencer marketing agency in India can simplify this process, since category-level benchmarking data of this kind usually sits behind agency reporting tools rather than something a brand team can pull together post by post. For brands building a benchmarking habit from scratch, it's worth reading how beauty brands are currently using influencer marketing and why many are increasing investment in the channel before setting internal targets.
Key Takeaways
- Benchmark against medians, not averages, and never against a single post.
- Nano and micro creators post higher median engagement rates; macro and mega creators post higher reach. Match the benchmark to the campaign objective.
- A category repeat rate (19.9% in this dataset) is a useful quality check on whether creator partnerships are working beyond a single post.
- Match your comparison window to the competitor's: beauty collab volume shifts noticeably by month, especially around festive peaks.
- Different types of influencer campaigns call for different benchmark metrics; decide the objective before picking the number.
Frequently Asked Questions
What is a good engagement rate for a beauty influencer campaign in India?
Based on recent makeup collaboration data, a median engagement rate of around 1.5% is typical overall, with nano creators trending closer to 1.9% and macro creators closer to 1.3%. Treat these as category medians, not universal targets.
How many competitor posts should I review before benchmarking?
Aim for at least 15–20 posts per creator tier over a comparable time window. A single post, even a strong-performing one, isn't a reliable benchmark on its own.
Should I benchmark against views or engagement rate?
It depends on the campaign goal. Use views, including the gap between average and median views, for reach and awareness campaigns, and engagement rate for consideration or community-building campaigns.
Does follower count affect what counts as a good benchmark?
Yes. Engagement rate typically falls as follower count rises, so comparing a mega creator's engagement rate directly against a nano creator's is misleading. Always benchmark within the same tier.
How often should beauty brands update their benchmarks?
Quarterly is a reasonable cadence, since collab volume, engagement rate and creator tier mix in beauty can shift meaningfully between festive and non-festive months.