Tracking Ecommerce Conversion Rates

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.

Crowning a New Term: “Iceberg Metrics” 🧊 ✨ I’m calling it: Iceberg Metrics represent KPIs that only reveal the tip of what’s really happening below the surface. Metrics like abandoned carts seem simple but often mask much more—checkout friction, hidden costs, trust issues, and more. To truly understand and optimize, we need to dig deeper. Here’s how to dive into the “iceberg” of abandoned cart rates: 1. Establish Baseline Metrics: Start by gathering data on current abandoned cart rates, session times, and bounce rates using heat maps and session recordings to see where users drop off. 2. Segment the Audience: Analyze users by behavior (first-time vs. repeat visitors, mobile vs. desktop) and traffic source (organic, paid, email). 3. Experiment Hypotheses: Develop hypotheses for abandonment reasons—shipping costs, checkout friction, distractions, or lack of trust signals—and test them. 4. Run A/B Tests: Test variations like simplifying the checkout process, showing shipping costs earlier, adding trust badges, or retargeting abandoned cart emails. 5. Use Heat Maps & Session Recordings: Examine user behavior in real time. Look for confusion or hesitation, where users hover, and whether they engage with key information. 6. Contextualize Results: Analyze how changes impact overall user flow. Did simplifying checkout help, or did other metrics like bounce rate increase? 7. Ecosystem Approach: Examine how tweaks affect the full journey—from product discovery to checkout—balancing short-term improvements with long-term goals like lifetime value. 8. Iterate: Refine solutions based on experiment findings and continuously optimize the customer journey. This one’s mine, folks! #IcebergMetrics #OwnIt #DataDriven #EcommerceOptimization #NewMetricAlert Cheers, Your cross-legged CAC and CLV buddy 🤗

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

One of the best conversion wins? Actually listening to your customers. It’s easy to get caught up in optimising buttons, headlines, and landing pages. But often, the real answers are already out there — if you know where to look. Last month, a founder I work with was stuck at a 2% conversion rate. Instead of diving straight into CRO tools, we did something simple: 𝐒𝐩𝐨𝐤𝐞 𝐭𝐨 15 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫𝐬 𝐰𝐡𝐨 𝐡𝐚𝐝 𝐫𝐞𝐜𝐞𝐧𝐭𝐥𝐲 𝐛𝐨𝐮𝐠𝐡𝐭. What we learned: 💡 Their biggest buying fear wasn’t addressed anywhere 💡 The pricing page created confusion rather than clarity 💡 The language on the site didn’t match how customers talked But we didn’t stop there. We also layered in 𝐬𝐨𝐜𝐢𝐚𝐥 𝐥𝐢𝐬𝐭𝐞𝐧𝐢𝐧𝐠 — pulling insights from reviews, competitor reviews, social posts, and forums — to add a broader view on top of the direct conversations. The result? Depth from interviews. Scale from social data. A full picture of what customers really needed. And after updating the messaging, 𝐜𝐨𝐧𝐯𝐞𝐫𝐬𝐢𝐨𝐧𝐬 𝐣𝐮𝐦𝐩𝐞𝐝 𝐟𝐫𝐨𝐦 2% 𝐭𝐨 7.8%. No ad spend. No new tools. Just better understanding. Real growth starts when you stop guessing and start listening — properly. When’s the last time you checked not just what your customers say to you… but what they’re saying when they think you’re not listening? #CustomerInsights #GrowthStrategy #ConversionRateOptimisation

If you want influencer campaigns that convert, start with YouTube.   It is not the newest platform, but it remains the most effective for driving measurable sales, and too many brands underuse it.   Here’s why YouTube wins for conversions: ▶️ Direct response capability: links in descriptions, pinned comments, and QR codes create multiple, trackable conversion paths. ▶️ Search and discovery: videos keep being found via YouTube and Google long after publication. ▶️ Extended half-life: content continues generating views and conversions months later. ▶️ Deeper relationships: longer watch times build trust, which raises purchase intent and conversion rates.   Short-form content drives awareness quickly, but it rarely sustains conversion momentum on its own. YouTube content compounds: an initial campaign can continue to deliver value for weeks and months, softening CAC as evergreen views accumulate.   Think about YouTube as a performance channel, design creator briefs with conversion in mind, use clear CTAs and optimise descriptions for search and direct response. When integrated into the funnel, YouTube frequently outperforms other platforms on ROAS and lifetime impact.

Ever wonder why 2M followers often mean 0 sales? Let’s talk about real influence beyond vanity metrics. Having worked on big brand campaigns and crunched the numbers firsthand, here’s the raw truth—no fluff, just facts: 🚩 Big followings ≠ Big sales Vanity metrics might impress, but if the audience isn’t engaged, it’s just expensive noise. 🚩 Micro-influencers (10K-50K) drive 4.2X better ROI Smaller creators build trust. And trust? That converts. 🚩 Story-driven content > glossy, static ads People don’t want a sales pitch. They want conversations, experiences, and stories they can see themselves in. 🚩 Non-glamorous networks hold real power Some of the most impactful voices aren’t influencers at all. They’re niche experts, community builders, and industry insiders—the ones who actually drive action. Real influence isn’t about who shouts the loudest, it’s about who people actually listen to. Brands that get this? They win. Brands that chase numbers? They burn budgets. #Marketing #BrandStrategy #InfluencerMarketing

Checkout optimization used to mean adding more payment methods. Today it’s about shaping the payment journey before friction ever shows up. Fintech Adyen just launched Personalize inside its Uplift suite. The headline feature is real-time Dynamic Identification, trained on trillions of transactions across its network. Why it matters: 37% of shoppers abandon when checkout takes too long. 72% of businesses say transaction fees are pressuring margins. Static checkout flows treat every buyer the same. Modern payment stacks can’t afford that. Personalize adjusts the experience in real time. It can: • Prioritize cost-efficient payment rails • Suppress unnecessary authentication • Surface risk signals before authorization • Route transactions based on identity and context Early data: • 9.4% lower payment costs on eligible traffic in year one of Uplift • 42% reduction in false positives • +1.19% average conversion lift, up to 6% for some merchants • Pilots showing up to 3% lower transaction costs • Tebi: 4.26% cost savings and 0.8% conversion lift This is not incremental CRO. The real shift is architectural. Checkout is becoming a data and feedback loop problem, not a front-end design problem. The platforms that unify acquiring, issuing, risk, and identity inside one system will compound advantages over time. If you’re running payments at scale: Are you optimizing a page… or optimizing a network?

In the past 4 months, I’ve audited 8+ companies' full GTM performance. The biggest insight? Most companies don’t have the right infrastructure to effectively measure results easily. Here are 10 infrastructure/reporting holes (outside of best practices) I’ve routinely seen: 1. Not capturing the conversion action. - What was the thing that the prospect did right before the opp was created? Ensure that it’s mapped from the originating contact to the opportunity object. This is the biggest hole. Bonus points if you’re also capturing the conversion campaign, source, and UTM fields. 2. Building on point 1, mixing offers and channels in the lead source/conversion action. - There should be a clear delineation between the category of the action (or Pipeline Source (events, lead gen, outbound, partner, declared-intent, etc.), the conversion type (list purchase, demo, chat, content syndication, gated content, etc.), the campaign, and the channel. I see a lot of inconsistencies here. 3. Inconsistent campaign structure - Having consistent, streamlined campaign naming conventions and outlines of how they’re set will have your future self jumping for joy. 4. Not creating deals from a contact - Not creating a deal from a contact means you can’t bring forward the mapped contact information to evaluate the performance of what’s closing and what’s not. 5. Not date stamping deal stages - which would allow you to determine qualified opp stages consistently vs. an arbitrary stage labeled as qualified (typically recommend the stage that has a win rate of >25%, as a new field, and evaluated routinely if not dynamically). I’ve seen pipeline inflation of $1M+ and deflation - meaning companies either are counting an excess in pipeline that leads to inaccurate forecasting or are too strict on the definition, resulting in not counting performance. Note: you can find these stages without date stamping, but I wouldn't classify it as easy. 6. Determining performance based on departments vs. the conversion, which goes back to point 1. This isn’t granular enough and can be misleading. 7. Not using qualitative data such as Self-Reported Attribution to understand how the demand was created. 8. Not incorporating headcount and software/tool cost into the marketing ROI 9. Inconsistent contact/lead creation process (depending on the object used), especially with outbound. You need to be able to see contact —> win conversion rates. 10. Not storing UTM fields Ensuring you have the right ops infrastructure in place is SO important, as is allowing your team to focus on foundations. Being able to truly connect the dots with performance quickly outside of relying on additional software (looking at you, Bizible) or, even worse, influenced models is a major growth lever.

In the last 20 audits we uncovered 5 old-school "best practices" that kill pipeline: 1. LONG INQUIRY / SIGN UP FORMS. "Best practice" – qualify leads. Outcome: nobody wants to fill in 8 fields that can be easily uncovered (think about geo, title, etc). Solutions: - Leave only 2-3 questions that can't be uncovered with account enrichment and help to prepare for the discovery or profile account - Leave self-attribution field - Install Clay or Clearbit to enrich account with firmographics (title, geo, size, etc) 2. INQUIRY FORM DOESN'T LINK TO SALES REP CALENDAR. "Best practice" – internal routing to the relevant Account Executive based on input. Outcome: If buyers can't immediately book a call with you, they will go to your competitor. "Thanks for your inquiry! Somebody from our team will contact you in the next 48 hours". Missed opportunity. Solutions: - Use Chili Piper for automated routing or disqualification - Create a universal calendar and then do routing internally 3. SEVERAL QUALIFICATION CALLS BEFORE DEMO. "Best practice" - use BANT or MEDIC qualification ran by junior sales rep before the buyer will be able to talk to an experienced AE. Outcomes: Ghosting prospects & no show-ups on the next calls. Buyers want to talk to an experienced consultant to get their questions covered. Solutions: - Explicitly explain who your product is for on the landing page, what it does (features), how is it different from competition - Add FAQ - Add price estimate or ballpark - Add product overview video, sandbox account or interactive demo to get a sense of the product You'll be talking to qualified buyers and don't need a bunch of qualification calls. 4. FAKE URGENCY. "Best practice" - push buyers with time-limited discounts or price increase. Outcomes: Fake urgency smells miles away. You'll either get pushed to give a bigger discount or lose the deal. Solutions: - Help buyers to create internal business cases and budget justification to close deals In most cases, budget should be created and approved by CFO/CEO. Your Champions don't need to show the discount to get approval. They need to show time and budget investment+ efficiency category (increase productivity , grow pipeline, etc). 5. TRANSFERRING GATED CONTACT DOWNLOADS AND WEBINAR SIGN UPS TO SALES. "Best practice": use gated content and webinar sign-ups to generate "leads". Outcomes: sales reach out to buyers that are not sales-ready. Missed opportunity, huge unsubscribe rate. People don't download e-books or sign up for webinars because they want to get a bunch of automated emails and unsolicited calls from SDRs. They are interested in the topic and want to get professional content. - Most B2B companies we spoke to in 2024 mentioned pipeline generation as the key challenge and #1 priority. There are 2 low-hanging fruits: 1/ Reduce friction points created by obsolete playbooks 2/ Refine obsolete playbooks with the new programs aligned with how your customers buy

Just wrapped a call with a fashion brand struggling to scale past 20L monthly revenue. Their agency kept pushing for higher budgets, but ROAS tanked every time. Sound familiar? Here's the exact audit process I used to fix this: 1. Creative Analysis Map every ad by: ↳ Theme (offer/UGC/lifestyle) ↳ Spend levels ↳ Purchase data ↳ AOV impact ↳ Revenue Per Click ↳ Product < > Content creation mapping 2. Product Performance Check which SKUs are: ↳ Eating budget with no returns ↳ Converting but underutilized ↳ Driving repeat purchases 3. Landing Page Experience Review ↳ Navigation clarity ↳ Product visibility ↳ Price transparency ↳ Mobile experience ↳ Checkout blockers 4. Campaign Structure Look for: ↳ Traffic campaigns (Not entirely red flag) ↳ Broad vs. Targeted performance ↳ Creative consolidation ↳ Creative testing velocity (High Velocity ≠ Good performance always) 5. Catalog Management Analyze: ↳ Low-spend SKUs (<2% of budget) ↳ High-CAC products ↳ Return rates by product ↳ Revenue contribution 6. Price Point Testing Track: ↳ Conversion rates by price tier ↳ Bundle performance ↳ Collection page results ↳ AOV impact Key insight: Most brands find 70% of their problems in steps 1 & 5. What's killing your ROAS right now?