Using Retargeting Ads In Ecommerce

You saw the ad. You ignored it. You saw it again. Still ignored. Now you see it 6 more times. Welcome to modern D2C retargeting. Most D2C brands retarget like everyone’s always interested. Spoiler: they’re not. We audited 14 Indian D2C brands in April. Different categories. Different spend levels. ↳ But one common problem across the board: → Retargeting was quietly eating up 25–30% of ad budgets… and delivering almost no real lift in conversions. ↳ Here’s what we saw again and again: → Brands targeting the same audience across multiple campaigns. → 30-day visitors are still being hammered with BOFU ads on day 27. → High-frequency users keep seeing offers they’ve already ignored. → Everyone gets the same retargeting creative, no matter their intent level. And the worst part? Meta charges a premium to show ads to warm audiences or even if they’re cold in behavior. ↳ Why this hits harder in India: → COD mindset means More hesitation, slower decision → Lower trust in new D2C brands → Most retargeting is not segmented by behavior or timing You're not nurturing. You’re nagging. ↳ What I suggest brands to do instead: → Cap frequency and refresh retargeting ads weekly. → Use behavioral segments, not just "all visitors". → Retarget with timing logic, not desperation. ↳ My Fix for Smarter Retargeting Strategy 1. Segment your retargeting audiences → 1–3 days: Hot. Hit with offer. → 4–7 days: Educational reminder → 8–14 days: Testimonials, COD trust → 15–30 days: Low-cost nudges, not hard sells 2. Set frequency caps for warm pools → Don’t let the same person see your ad 6–10 times. → It hurts trust and inflates CPC. 3. Use intent-based retargeting triggers → Add to cart ≠ View content ≠ 10 sec video view → Each needs a different message and urgency 4. Rotate your creatives weekly → Fresh visuals and new hooks equals higher re-engagement without annoying the user 5. Track spend split between cold vs warm → If warm is eating 40%+ of budget with low conversions then pull back and fix segmentation. → Swap "Buy Now" with reminder, education, or social proof style creatives. Recap: ✅ Over-retargeting is a silent budget leak in Indian D2C ✅ Meta doesn’t care how relevant your retargeting is, you need to fix it ✅ Smart segmentation and message match means better ROI and trust ✅ Most CAC spikes come from lazy retargeting, not bad ads ✅ Treat retargeting like a nurture funnel, not a sales wall It’s not that your retargeting isn’t working rather it’s working too hard on the wrong people. Sometimes scaling starts by cutting what’s quietly bleeding your best budget. Spending ₹10L–₹50L/month and not sure if your retargeting is actually working? Let’s chat. A 30-min chat could save you lakhs in silent leaks.

Meta just dropped a new game-changer tool! Frequency Control for Sales campaigns is finally here. It matters a lot for creative testing. Study shows that after 4 views, performance drops by 60% Your ad might not be bad. It might just be shown too often to the same people! But now we can control it, not only in Reach objective but in Sales. I've seen frequency spikes after just $20 in ad spend on some ads. Now, we can limit that. Quick facts about the new feature: ↳ Only for lifetime campaigns  ↳ Activates after 7 days of running ↳ Not compatible with cost/bid control ↳ Won't work with A+ audiences Despite the limitations, I want to test this for our clients. Controlling the frequency could improve our creative testing process: ☑ Effectively spend your budget ☑ Reduce creative fatigue ☑ Improve performance Fresh eyes = better results. Have you tried it yet? Share insights below! 👇

A/B Testing in Google Ads: Best Practices for Better Performance Introduction to A/B Testing A/B testing in Google Ads is a crucial strategy for optimizing ad performance through data-driven insights. It involves comparing two versions of an ad to determine which one delivers better results.  Set Clear Goals Before conducting A/B tests, define clear objectives such as increasing click-through rates or conversions. Having specific goals will guide your testing process and help you measure success accurately.  Test Variables To effectively A/B test ads, focus on testing one variable at a time, such as the ad copy, images, or call-to-action. This approach will provide clear insights into what elements are driving performance. Create Variations Develop distinct ad variations with subtle differences to compare their impact. Ensure that each version is unique enough to produce measurable results but relevant to your target audience.  Implement Proper Tracking Set up conversion tracking and monitor key metrics closely to evaluate the performance of each ad variation accurately. Use tools like Google Analytics to gather meaningful data. Monitor Performance Metrics Regularly review performance metrics like click-through rates, conversion rates, and cost per acquisition to identify trends and patterns. Analyzing these metrics will help you make informed decisions. Scale Successful Tests Once you identify a winning ad variation, scale it by allocating more budget and resources to drive maximum results. Replicate successful strategies in future campaigns. Continuous Optimization Optimization is an ongoing process, so continue to test, refine, and adapt ad elements to enhance performance continuously. Stay updated with industry trends and consumer preferences. Analyze Results After conducting A/B tests, analyze the results comprehensively to understand the impact of your optimizations. Use the insights gained to inform future ad strategies. Summary  Following best practices for A/B testing in Google Ads can significantly improve the performance of your campaigns. By testing, analyzing, and optimizing ad variations, you can enhance engagement, conversions, and overall ROI. #MetaAds, #VideoMarketing, #DigitalAdvertising, #SocialMediaStrategy, #ContentCreation, #BrandAwareness, #VideoBestPractices, #MarketingTips, #MobileOptimization, #AdPerformance

1 Metric to improve LinkedIn Ads ROI by 2-5x (no joke) FREQUENCY - What should it be? How to control?? What is frequency, and why is it so important? It's the average number of ads from a given campaign in a given time frame that the typical prospect will see. Example: 90-day retargeting campaign frequency = 5 Meaning: The average prospect in this campaign sees five ads over 90 day period Result? A frequency of 5 in a 90-day period is much too low to have any significant conversion result. Correction: Increase budget or reduce audience size to increase frequency Explanation: So here is the part that most don't seem to understand...what is a good frequency level, and how do I monitor and control it? 1. To view frequency correctly, you must view it through the proper time-frame. There is a different frequency depending on what time frame you look at. 7 days, 30 days, 90 days etc. Looking at the 90-day frequency number when the campaign has only been running for 30 days? This is inaccurate information. You must view it in a time frame where there was data the whole time for it to be accurate. So, for newer campaigns, you'll need to consider a 7-day or 30-day frequency and then do some math to assume a 90-day frequency. 2. Control frequency - The main two levers to control frequency are budget and audience size. Increase budget = increase frequency. Decrease audience size = increase frequency. 3. The most typical mistake I see when it comes to frequency -Low frequency in retargeting campaigns Typical actions that could save $10,000+ in most ad accounts A. If the frequency is too small and the budget isn't easy to increase..look to reduce retargeting audience size by adding in qualifying filters. Possible criteria: 90-day website visits (all traffic not just LinkedIn ads traffic..so yes..this includes Google ads traffic, SEO, organic, and any other paid) 90-day company page visits 90-day cold ad interaction Additional qualifying filters layered on top to reduce audience size AND seniority director level and above AND job function business dev (this is actually how LinkedIn classifies almost all C-suite decision-makers) + marketing functions AND company size 50-200 (have the budget) AND Geography USA + Canada (where we do the most business) Usually, adding in these filters will reduce the audience by 1/2, doubling the frequency and improving the retargeting audience's quality. That's my tips for the day around ad frequency : ) #Linkedinads #marketing #b2b #abm

What I learned after 100+ failed outbound campaigns (at a $400,000 MRR agency): Most flop because they're aimed at people who were not going to buy anyway. (Too) many companies still run outbound like so: - Pull a lead list from their CRM or a generic B2B database - Fire off 100 cold emails/week to “hit quota” - Hope and pray something sticks And they have no idea why prospects are on their list in the first place. If you’re not starting with the right inputs, it doesn’t matter how good your cold email is. It’s still a shot in the dark. One way to fix this is through intent data: For example, here are some signal plays we run for ColdIQ and our clients: 1. First-party intent: Who’s visiting your website Not everyone fills out a form, but that doesn’t mean they’re not interested. We use tools like Instantly.ai and Vector 👻. They track anonymous visitors and identify who’s checking out our content, landing pages, or product pages. This gives us a warm list of people who are already aware of us. Even if they haven’t raised their hand yet. First-party intent can also come from: - Product usage (e.g: Common Room, Pocus) - Social engagement (e.g: Teamfluence™, Trigify.io) 2. Second-party intent: Champion job changes Let’s say someone loved your product at their old company. They just switched jobs. Now they’re in a new buying position, possibly with budget and urgency. Tools like Common Room and Unify help us track job changes across our network and historical CRM contacts. We can re-engage with a hyper-relevant message, right when they’re getting settled in. Second-party intent can also come from: - Review sites (e.g: G2, Capterra) - Affinity signals (e.g: Crossbeam, WorkSpan) 3. Third-party intent: Research at scale Most often, you need to go outbound into entirely new territory. That’s where third-party data comes in. Pulling insights from: - hiring trends (e.g: LoneScale, Mantiks, PredictLeads) - tech stack changes (e.g: BuiltWith, Similarweb) - funding rounds (e.g: PitchBook, Crunchbase) or from custom AI agents (e.g: Relevance AI, Claygent) We use Clay to build many of these workflows: - Filter for buying signals - Enrich contacts in real-time - Score and segment dynamically - And combine multiple data sources The result? You’re increasing your odds of reaching out to the right person, with the right message, at the right time. Better targeting = better reply rates = better pipeline. Whenever your outbound is underperforming, start by reviewing your data strategy. What intent signals are you tracking in your GTM motion right now? Would love to hear what’s working for you 👇

Supercharge Your Facebook Ads: 6 Data-Backed Experiments Digital Marketing Pros Can't Ignore Let's dive into some high-impact Facebook Ads experiments backed by real data. Here's what you need to be testing: 1. Hook Magic: Those first few seconds are crucial! Test different hooks to grab attention. Bold statements, intriguing questions, or eye-catching visuals can make all the difference. 2. Thumbnail Impact: Don't sleep on thumbnails! In one study, changing thumbnails led to a 96% difference in cost per install[3]. Test these proven performers:   - Close-ups of faces (especially those resembling your target audience)   - Close-up patterns   - Thumbnails highlighting pain points with an "X" sign 3. Landing Page Optimization: Got the click? Now convert! Test various designs and ensure consistency between your ad and landing page. A/B testing can significantly boost your conversion rates. 4. Single Image vs. Carousel: Not sure which format to use? Test both! Single images can be powerful, but carousels offer a dynamic way to showcase multiple products or features. 5. Audience & Creative Testing: Dive deep into A/B testing. One study found that dynamic creative campaigns with 12 different combinations (e.g., two thumbnails, three headlines, two video lengths) yielded statistically significant data. 6. Ad Length Dynamics : Is shorter always better? Test 30-second ads against 60-second ones. One experiment showed a $10,000 video outperformed both $1,000 and $100,000 versions, proving that mid-range production can be most effective. Remember, Facebook's A/B testing tool allows you to compare performance across variables like copy, images, audiences, or campaign objectives. Keep testing, keep learning, and watch your ROI soar! Which experiment are you itching to try first? Drop your thoughts below! 💡 #FacebookAds #metaads

Mastering LinkedIn Retargeting: The Long Game of Prospect Conversion Not every prospect is ready to buy right away. Some prospects convert with just a few interactions, while others need a more patient approach, converting only when the timing is right. In fact, some prospects take 40, 60, 80+ touchpoints before making a decision. The Essential Retargeting Funnel This is where a strategic retargeting funnel becomes essential. The key is structuring your campaign to maintain brand visibility for prospects who aren't immediately ready to commit. A basic campaign strategy involves two core layers (yes, there is more you can do and a ton of tactics that expand beyond this, but this is the basic foundational approach): > Cold/Awareness Layer > 90-Day Retargeting Layer Initial Retargeting Strategy For the first retargeting phase, we're targeting individuals who've shown initial interest in your company or offer. We typically build audiences from 90-Day: 👉 Website visitors 👉 Company Page engagers 👉 Recent ad interaction participants At this stage, we allocate a more substantial budget to stay prominently visible. The content mix focuses on: ➡️ Thought Leadership Materials: Blogs, articles, whitepapers, expert posts ➡️ Social Proof: Testimonials, reviews, success stories Beyond the Immediate Conversion LinkedIn advertising is fantastic for identifying your target audience, but it doesn't guarantee immediate conversion. Your funnel should capture quick wins while simultaneously nurturing long-term prospects. Low-Budget Sustained Engagement Tactics To keep your brand top-of-mind for slower-converting prospects, leverage these cost-effective ad formats: → Text Ads → Spotlight Ads → Follower Ads For Matched Audiences, extend your parameters to 180 days: ✅ 180-day Website Visits ✅ 180-day Company Page Visits ✅ 180-day Single Image Interaction Campaign Setup Hack When configuring this long-term setup, remember to 𝗘𝗫𝗖𝗟𝗨𝗗𝗘 the 90-day audiences. This strategic move allows you to: 👴 Isolate an audience that hasn't engaged in 3-6 months 🔎 Focus more of the budget on recently engaged prospects 📈 Maintain a low-budget presence for potential long-term conversions The magic is in persistence and strategic visibility. Not every prospect is ready today, but with the right approach, you'll be at the front of their minds when they are. #linkedinads #b2bmarketing #linkedincowboy

Predict, Personalize & Perform : From Leads to Loyalty Let’s be honest—customer lifecycle marketing (CLM) in B2B used to be a fancy word for “email nurture” and “CRM segmentation. But today, with AI, machine learning, and predictive data models, CLM is becoming something much more powerful: ➡️ A living, learning ecosystem that adapts to each buyer journey in real time. Here’s how we’re seeing AI and ML revolutionize CLM in B2B: 🔍 1. Predictive Journey Mapping Machine learning algorithms are helping identify where an account or contact actually is in the funnel—not just where your CRM says they are. ✅ No more generic MQL > SQL flows ✅ Dynamic scoring based on behavior, content engagement, and intent signals ✅ Real-time stage shifts based on predictive fit and readiness — 📈 2. Hyper-Personalized Nurturing (at Scale) AI models now create content clusters matched to personas, industries, and even buying committee behavior. 🎯 Email sequences, LinkedIn ads, and landing pages are personalized based on: Buyer role Past touchpoints Predicted product interest ICP match + firmographic data It’s not just segmentation—it’s micro-personalization powered by behavioral AI. — 🔁 3. Intelligent Retargeting & Re-Engagement Using ML-powered intent data and anomaly detection, you can now: Spot churn risks before they happen Trigger re-engagement sequences based on drop-off patterns Retarget accounts that show subtle buying signals across web, search, and social Retention is no longer reactive. It's predictive. — 📊 4. Revenue Forecasting + Attribution Modeling Thanks to data science, we can model: Which touchpoints actually move pipeline Which leads are likely to convert within a time window How to attribute revenue across full-funnel programs—not just the last touch This gives marketing the credibility and confidence we’ve needed for years. — 💡 The CLM Stack of a Modern B2B Org Should Include: ✔️ Customer Data Platform (CDP) ✔️ AI-powered segmentation + scoring ✔️ Predictive content engines (LLMs + RAG) ✔️ Lifecycle orchestration tools (e.g. Ortto, HubSpot, Marketo w/ ML layers) ✔️ Analytics + BI layer for optimization 🧠 Final Thought: In 2025, CLM isn’t just “marketing automation” with better templates. It’s about building an AI-powered engine that understands, anticipates, and activates each step of the buyer journey. You don’t need more content. You need smarter orchestration. 💬 Curious to hear from other B2B leaders: How are you bringing AI into your lifecycle marketing stack?

The recent Gravy Analytics data breach has raised urgent concerns about the vulnerabilities in the advertising industry’s data access practices. Tens of millions of highly sensitive location data points—tracked through apps like fitness trackers, dating platforms, and transit tools—were exposed, endangering the privacy and safety of millions worldwide. This breach highlights a critical issue: ad bidstream data. In milliseconds-long ad auctions, vast amounts of device and location data are made accessible to advertisers and, often unknowingly, to data brokers. This unregulated ecosystem enables bad actors to exploit sensitive consumer data, potentially leading to deanonymization and misuse in harmful ways. The solution lies in adopting Proof of Provenance—a framework ensuring that all data is securely sourced, verified, and governed through protected processes and identifiers. By integrating transparent and privacy-preserving technologies, the ad industry can rebuild trust and better safeguard consumer data. At a time when privacy regulations are tightening and breaches are increasingly frequent, the industry must move beyond reactive measures to proactive, robust systems for privacy protection. Performance Privacy must be a cornerstone of all digital operations. What are your thoughts on the future of secure data exchanges in advertising? How do we ensure consumer trust while maintaining innovation? Let’s discuss! https://lnkd.in/e5kMTb93 #data #privacy #advertising #marketing #ProofOfProvenance #AI Precise.ai Qonsent

Less is more... and better The simplicity of minimalism vs. the visual impact of bold elements. Solid colors, clean but striking typography, and balanced compositions create a message that is understood in seconds and easily remembered. This style does not seek to fill space, but rather to give each element a purpose to convey confidence, modernity, and visual coherence. >>Why it works in beauty & personal care<< In a sector saturated with visual stimuli, this aesthetic stands out because: * Clarity of message: it eliminates distractions and focuses attention on what is important: the product and its value proposition. * Immediate recognition on social media: its clean, contrasting aesthetic stands out in feeds saturated with ornate images. * Differentiation: while many brands opt for complexity, bold minimalism is gaining relevance thanks to its strategic simplicity and high visual impact. >>Benefit for the brand<< Adopting this aesthetic is not only a visual choice, but also a strategic one: * It reinforces visual identity, making the brand recognizable even without displaying the logo. * It creates consistency across all channels, from packaging to digital campaigns. * It communicates that the brand has a clear message and does not need unnecessary embellishments to stand out. >>Impact on e-commerce and social media<< On Instagram or Pinterest, where the scrolling speed is high, bold minimalism generates a clear stop scrolling effect. Its contrasts, white space, and intelligent use of color immediately capture attention. In e-commerce, it improves the readability of information, elevates the perception of quality, and facilitates the purchase decision. In addition, it is perfectly suited to paid ads, where clarity and impact are key to increasing clicks and conversions. >>Future trend<< Bold minimalism is evolving with: * Textures and sensory materials. * Moving liquids and 3D effects to add depth. This balance between minimalism and visual richness will mark upcoming campaigns in beauty and personal care, driving engagement without losing the clean and strategic essence. Bold minimalism is more than a style: it is a tool for communicating with strength, consistency, and relevance. In a competitive market, it proves that sometimes less is not only more... it is also better. Featured Brands: Prmr Sulwhasoo Bread Belif Nolani Nuebiome Cheris I'm From Cosnori #BoldMinimalism #BrandStrategy #PackagingDesign #BeautyBrands