Quantitative Analysis in Influencer Campaigns

I've spent over $250,000 paying influencers to post for brands. What metrics are the most helpful in predicting if an influencer partnership will be ROI positive for you? There is no one predictive KPI that predicts this with 100% accuracy. You have to analyze an array of datapoints and use those to essentially make a gut decision. Here are all of the factors I analyze, from most important to least important: 1. Geo distribution - the biggest thing you need to ensure is that you're not out of the race before it even starts. Does the influencer have an audience predominately in your target country? If you're paying for a post by a creator with 1mil followers, but 80% are in Germany and you only ship to the US, then you're paying a 1mil price tag for 200k results. 2. iOS breakdown - device usage by the influencer's audience is always a fantastic proxy for quality. It's a hard fact that historically, android users convert at a far lower rate for most ecommerce products than iOS users, as they generally skew less affluent. If an influencer's audience has an iOS device usage rate less than 75%, I almost NEVER work with them. 3. View consistency - this is a huge one. When you partner with an influencer, you are pulling a slot machine handle and praying that the video they post featuring your brand will get a view rate and engagement rate similar to their historical performance. The more an influencer's historical view counts fluctuate up and down, the less likely you are to get lucky and see the level of engagement that you actually paid for. This is far more important than "average view count". 4. Audience engagement rate - look at the comment:view ratio, the like:view ratio, and the completion rate of the creator's videos as proxies for audience quality, similar to the iOS breakdown. I ran a study on 6 figures of influencer spend and saw that conversion rate from the video, far more than CTR from the video or even CPM (meaning how affordable the influencer was for their size), had the highest correlation to an affordable CAC. There are no exact benchmarks for these metrics as they vary by platform, but you should only go with influencers in the top quartile of the profiles you analyze. How do you analyze these metrics? There are several ways. The screenshots in this post were pulled from Upfluence's influencer analysis chrome extension, which is completely free and allows you to view analytics on any IG or YouTube account, along with TikTok's native Creator Marketplace analytics which are also completely free.

Indian influencer marketing is evolving into a full-blown performance engine. In 2024, the industry crossed ₹3,600 crore, and it’s expected to grow another 25% in 2025. But the real story is in the mindset shift. Indian brands are no longer using influencer campaigns for vague brand awareness or chasing viral reels. They’re using them for trackable ROI, conversion, customer acquisition, and brand trust. Most brands have moved on from one-off influencer shoutouts. Today, 72% of them prefer long-term collaborations. It’s about building ongoing relationships that feel authentic to the audience and credible to the customer. What’s even more interesting is the role of micro and nano-influencers. A nano-influencer might only have 5,000 followers, but with engagement rates between 4–6% on Instagram, they often outperform creators 20 times their size. For brands that want depth instead of just breadth, these small creators are ROI gold. And then there’s regional content. Whether it’s Chennai Mobiles running vernacular campaigns or Levista Coffee leveraging local language storytelling, India’s most successful influencer campaigns today aren’t PAN India, they’re hyperlocal. Creators speaking to their communities in their own dialects are driving both emotional resonance and sales lift. But all of this only works because brands are finally treating influencer marketing like performance marketing. They’re tracking CPE, CAC, ROAS, and even sentiment data. They’re using UTM links, affiliate codes, custom landing pages, and creator-specific funnels. They’re building dashboards, running A/B tests, and in some cases, even calculating Earned Media Value to understand the true reach and monetary worth of a campaign. Take Dorco, for example. The brand worked with 105 influencers to launch in India. They didn’t just get views, they got over 3,000 link clicks per influencer, 250K impressions per post, and a massive boost in brand awareness without spending on traditional ads. Flipkart did a winterwear campaign with 32 male creators and saw a 20% spike in category sales. SUGAR Cosmetics went from industry-average engagement to 4–5%, and in just two years, attributed 3X sales growth to creator-led campaigns. Mamaearth spent ₹182 crore on influencers in FY23 and it worked, because their focus wasn’t just on going viral, but on going credible. The biggest shift is that brands now factor in more than just short-term sales. They’re looking at repeat purchases, brand lift, earned media, and overall LTV. The smartest ones know that influencer marketing isn’t just a line item in the marketing budget, it’s a core part of their business engine. Influencers have become distribution. They are brand trust. And they are revenue drivers, if you’re tracking them right.

We track 1M+ data points to predict influencer success. There's ONE key trait that really matters 👇 — Not many people know this, but I actually have two degrees in environmental engineering. When I entered influencer marketing, I saw an industry operating largely on gut feel and surface metrics. This creates a significant problem: Brands often invest heavily in creators without reliable ways to predict performance. Here's how we solved it (with a bit of home-brewed engineering): First, we built a data warehouse that normalizes creator performance across price points. Whether you're selling a $2000 laptop or a $20 t-shirt, we can compare creator effectiveness using percentile rankings. We use it to track: • Traffic and time on site • Purchase volume and revenue • Customer lifetime value • Platform-specific engagement • Creator responsiveness and reliability This creates an internal rating system where only 0.2% of creators earn our highest rating. But the real value isn't in the ratings – it's in how we use them. For every brand campaign, creators move through two phases: test budget and performance budget. Strong performers graduate to recurring partnerships. Each success or failure makes our predictions more accurate. This helps us get: • More accurate creator selection • Higher conversion rates • Lower customer acquisition costs • Fewer failed campaigns Honestly, our data & engineering is one of the things I’m most proud of. I really enjoy the “aha” moment our clients get when they see the rigor we bring to it; it brings me joy. — Here's the ONE thing that really matters: An audience's propensity to take ACTION. Creator success isn't about follower count or engagement rates. It's their audience's bias toward action. We found that: Bias for action can be measured, analyzed, and predicted. Ten years ago, people called this the "Wild West" of marketing. Today, we're turning it into a science. Not because we love data (though we do), but because it delivers better results for everyone. #marketing #data #influencermarketing #analytics

Plot twist: Your influencer campaigns could be performing 10x better than you think 📊 Most brands are massively underestimating their influencer ROI because they're only looking at discount codes. Real example from our agency:  → Client thought cost per customer: $1,000 (based on discount codes) → Actual cost per customer: $82 (based on pixel data) → That's 92% of customers going untracked! 🤯 The attribution reality: Even our most sophisticated clients with seamless tracking see a minimum 40% "halo effect" of unattributed sales. For luxury/considered purchases? We're talking 100%+ unattributed impact. Why this happens: → People screenshot products and buy later → They share with friends who purchase → They search your brand name directly → They purchase but don't use the code. What to track instead:  ✅ Pixel data and site behavior analysis ✅ Brand lift surveys ✅ Search traffic spikes ✅ Overall sales velocity during campaign periods ✅ Customer journey mapping The takeaway: If you're only measuring discount code redemptions, you're probably missing the majority of your influencer marketing impact. Time to dig deeper into your data. Your CFO will thank you. How are you measuring the true impact of your influencer campaigns? #InfluencerMarketing #MarketingAnalytics #Attribution #ROI #Data #performancemarketing

Most Influencer campaigns are measured incorrectly. Despite the continued growth of influencer marketing, a majority of brands continue undervalue and incorrectly measure influencer impact. Depending on the research you use, either 60% of brands measure influencer campaigns on growth of followers, or 70% measure success on click attributed sales.  Either way most research seems to agree that a majority of brands find the 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 𝗶𝗻 𝗶𝗻𝗳𝗹𝘂𝗲𝗻𝗰𝗲𝗿 𝗺𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝗶𝘀 𝗺𝗲𝗮𝘀𝘂𝗿𝗶𝗻𝗴 𝘀𝘂𝗰𝗰𝗲𝘀𝘀. Over the next three weeks I will be sharing our benchmarks on how influencers actually impact brand performance. 𝗠𝗲𝗮𝘀𝘂𝗿𝗲𝗱 𝗮𝗴𝗮𝗶𝗻𝘀𝘁 𝗿𝗲𝘃𝗲𝗻𝘂𝗲 𝗶𝗺𝗽𝗮𝗰𝘁. Not likes. Not EMV. Not reach. We measure every influencer campaign through MMM, to understand the revenue impact of every single campaign. This helps us to see the direct and indirect impact of influencer activity. This puts these campaigns head to head against other marketing efforts to compare the revenue they drive. (to be clear, every measurement method has strengths and weaknesses. MMM is not perfect, but it is good at providing a consistent full funnel measure across campaign types.) We start week 1 with looking at how influencers drive value. Comparing direct and indirect revenue impact for influencers vs other channel types. We can see that 𝟴𝟬% 𝗼𝗳 𝗶𝗻𝗳𝗹𝘂𝗲𝗻𝗰𝗲𝗿 𝗿𝗲𝘃𝗲𝗻𝘂𝗲 𝗶𝘀 𝗱𝗿𝗶𝘃𝗲𝗻 𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗶𝗻𝗱𝗶𝗿𝗲𝗰𝘁 𝗶𝗺𝗽𝗮𝗰𝘁𝘀. That is people who are impacted by the influencer reach but do not click or use voucher codes. Old fashioned broadcast impact. The same way brands have been built for years through broadcast channels. That puts influencer campaigns in line with how revenue is driven through YouTube or Social Awareness. To put that into context, for 𝗲𝘃𝗲𝗿𝘆 £𝟭 𝘆𝗼𝘂 𝘀𝗲𝗲 𝘁𝗿𝗮𝗰𝗸𝗲𝗱 𝗮𝗴𝗮𝗶𝗻𝘀𝘁 𝗰𝗹𝗶𝗰𝗸 𝗯𝗮𝘀𝗲𝗱 𝗽𝘂𝗿𝗰𝗵𝗮𝘀𝗲𝘀, 𝘁𝗵𝗲𝗿𝗲 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗮𝗻𝗼𝘁𝗵𝗲𝗿 £𝟰 𝗶𝗻 𝘂𝗻𝘁𝗿𝗮𝗰𝗸𝗲𝗱 𝗶𝗺𝗽𝗮𝗰𝘁 𝘄𝗵𝗶𝗰𝗵 𝗼𝗻𝗹𝘆 𝗲𝘅𝗶𝘀𝘁𝘀 𝗯𝗲𝗰𝗮𝘂𝘀𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗶𝗻𝗳𝗹𝘂𝗲𝗻𝗰𝗲𝗿 𝗿𝗲𝗮𝗰𝗵. And we can see that when we look at the other channel impacts: • Paid social campaigns perform 20%-30% stronger with influencer support than without. • Paid search campaigns show 15%-20% stronger CTR and significantly softened diminishing returns impacts with influencer support. • Brand searches increase up to 30% with strong influencer reach. Those impacts all drive purchases which are “tracked” against other channels, but these uplifts wouldn’t exist without the influencer impacts. When we model these behaviours back we see 80% of value is driven through indirect impacts. If you are measuring and optimising towards the 20% then you are missing the real way these campaigns drive value.