Interactive Ads Development

Should you retarget by intent? We ran the test... Most B2B retargeting looks something like this: Someone visits your site, any page at all…and immediately: they’re getting hit with “Book a demo” or “Start your free trial” ads. No nuance. No context. Just one-size-fits-all messaging chasing every visitor around the internet. It’s simple. It’s easy. But also pretty broken. Here’s why: > Not everyone on your site is in the same headspace. > Blog readers aren’t ready to talk to sales. > Product page visitors are curious but not convinced. And people on the demo page? They’re this close but something’s holding them back. Treating all three the same? That’s how you burn ad dollars without actually building pipeline. So we ran a test. One of our clients had a basic retargeting setup. One campaign. One CTA. One generic message. We broke it apart and rebuilt it based on intent. ___________________________ Here’s how we segmented it: Blog readers Top-of-funnel folks in research mode. → We showed them value-first content: guides, checklists, downloads. Product & feature page visitors Mid-funnel visitors sniffing around the solution. → We served ROI calculators, interactive tools, and “how do you stack up” style CTAs. Pricing/demo page visitors Bottom-of-funnel leads with real buying signals. → They saw direct “Book a demo” and “Start your trial” ads with tons of social proof. ___________________________ Here’s what happened over 60 days: Old campaign (one-size-fits-all): > Low click-through rates (~0.4%) > Modest form fill volume > Demo-to-close rates hovering around 17% New segmented retargeting: > 3.1x higher CTR > 2.4x more total form fills > 29% increase in demo-to-close conversion from high-intent segments ___________________________ Better message-match. Cleaner funnel transitions. Better results.

my competitor and i launched identical linkedin campaigns. same budget, same audience, same product category. i crushed him 8:1 on deal conversion. he was confident going into the test. better product. stronger brand recognition. more funding. bigger team. we both targeted VPs of sales at 500+ person companies. same demographic criteria. same ad creative quality. $10K budget each. month one results: me: 47 deals closed. him: 6 deals closed. he was convinced i got lucky with better prospects. "let me see your targeting strategy," he asked. i pulled up my dashboard. "i don't target demographics at all." "what do you mean? you're running linkedin ads." "i target behaviors." i showed him my approach: instead of job titles, i track content consumption. instead of company size, i monitor website journeys. instead of industry filters, i watch engagement patterns. "i built an audience of people who've consumed competitor content in the last 30 days. downloaded sales automation guides. attended webinars about pipeline management. visited pricing pages of tools like ours." my "audience" wasn't demographic. it was behavioral. "linkedin lets you upload custom audiences," i explained. "i upload lists of people who've shown buying behavior. then i target those lists with ads." he was targeting people who might need our product. i was targeting people actively shopping for our product. "how do you identify buying behavior?" he asked. "third-party intent data. website pixel tracking. content engagement scoring. competitor analysis tools." i showed him my process: week 1: identify companies researching sales tools. week 2: find individuals at those companies consuming content. week 3: build custom audiences from behavioral data. week 4: launch ads to pre-qualified prospects. "demographics tell you who someone is," i said. "behavior tells you what they're doing." he was advertising to VPs of sales. i was advertising to VPs of sales currently shopping for solutions. same title, completely different mindset. my prospects were already in buying mode. his were just scrolling linkedin. the conversion difference made perfect sense. he rebuilt his entire approach: behavioral targeting instead of demographic filtering. intent data instead of job title assumptions. shopping behavior instead of profile characteristics. next month's results for him: 52 deals closed. 9x improvement over his original campaign. the lesson was clear: demographics describe who people are. behavior reveals what people need. target the behavior.

Two years ago, while working on marketing analytics, I faced a challenge in optimizing ad spend for a digital campaign. The marketing team was running social media ads, but despite high traffic, the conversion rate remained low. Instead of increasing the budget, we turned to SQL and data analysis to identify inefficiencies. Breaking Down the Problem with SQL 1️⃣ Finding the Best & Worst Performing Ads We analyzed click-through rates (CTR) and conversion rates for each ad campaign. SELECT campaign_id, ad_id, COUNT(DISTINCT user_id) AS clicks, COUNT(DISTINCT CASE WHEN purchase = 1 THEN user_id END) AS conversions, COUNT(DISTINCT CASE WHEN purchase = 1 THEN user_id END) * 100.0 / COUNT(DISTINCT user_id) AS conversion_rate FROM ad_clicks GROUP BY campaign_id, ad_id ORDER BY conversion_rate DESC; 🔹 Insight: Some ads had a high CTR but low conversions, meaning they attracted traffic but failed to convert. 2️⃣ Identifying Wasted Ad Spend We checked if ads were targeting low-value customers who rarely made purchases. SELECT ad_id, COUNT(DISTINCT user_id) AS total_clicks, COUNT(DISTINCT CASE WHEN customer_lifetime_value < 50 THEN user_id END) AS low_value_clicks FROM ad_clicks ac JOIN customers c ON ac.user_id = c.customer_id GROUP BY ad_id ORDER BY low_value_clicks DESC; 🔹 Insight: A large portion of the budget was spent on users with low lifetime value, leading to poor ROI. 3️⃣ Finding the Best Audience Segments To optimize targeting, we analyzed which customer segments converted best. SELECT age_group, location, COUNT(DISTINCT user_id) AS total_visitors, COUNT(DISTINCT CASE WHEN purchase = 1 THEN user_id END) AS conversions, ROUND(COUNT(DISTINCT CASE WHEN purchase = 1 THEN user_id END) * 100.0 / COUNT(DISTINCT user_id), 2) AS conversion_rate FROM customer_data GROUP BY age_group, location ORDER BY conversion_rate DESC; 🔹 Insight: The highest converting customers were from specific age groups and cities, which weren’t the primary ad targets. Challenges Faced Data Volume Issues: The dataset contained millions of ad clicks, so I used indexed filtering to improve performance. Attribution Problems: Some users converted days after clicking the ad, so we used attribution modeling instead of last-click conversions. Budget Reallocation Resistance: Marketing teams were hesitant, so we presented data-backed ROI projections. Business Impact ✔ 20% decrease in ad spend waste by cutting low-value audiences. ✔ 15% increase in conversion rate after retargeting the right audience. ✔ Better marketing decisions through data-driven campaign optimization. Key Takeaway: SQL isn’t just for reporting—it helps businesses make smarter marketing decisions and maximize ROI. Have you used SQL to optimize marketing campaigns? Let’s discuss!

Meta Ads Showing to the Wrong Audience? Here’s Why (and How to Fix It) A travel company messaged me recently: “Our Meta Ads are getting trash leads. Most of them are totally irrelevant. We’re targeting properly, but the audience feels wrong.” If you’ve ever faced this, you’re not alone. And no, it’s not just “bad targeting.” Here’s the truth: Meta doesn’t show your ads to who you want, it shows them to who it thinks will act. If your system teaches it the wrong behavior, you’ll keep attracting the wrong crowd. Here’s how to fix it (step by step): 1. Fix Your Conversion Signal (Most Important) Meta follows your signals, not your dreams. If you’re optimizing for “Leads” but your form is too easy to fill, you’re training Meta to find cheap form fillers, not qualified travelers. ✅ Add friction, longer forms or qualifying questions ✅ Track post-lead quality (via Offline Conversions / API) ✅ Optimize for High-Intent Leads (custom conversion) The better your signal = the better your audience becomes. 2. Narrow by Behavior, Not Interests Interests ≠ Intent. Instead of “Travel Lovers” or “Vacation,” try behaviors that match buyers: ✅ Engaged Shoppers (Meta filter) ✅ Frequent International Travelers ✅ Lookalikes from high LTV clients Behavior > Demographics > Interests. 3. Feed Meta Clean Data If your pixel can’t see clearly, it can’t optimize smartly. ✅ Use CAPI + Pixel (proper deduplication) ✅ Push value data for better event ranking ✅ Verify Event Match Quality > 8 Poor data = poor delivery = poor leads. 4. Audit Your Ad Creative You attract what you show. If your ad looks like a generic “budget trip”, you’ll get budget leads. ✅ Showcase your best packages ✅ Use visuals that reflect your target audience ✅ Write copy that filters (“For families planning Europe trips in 2025”) Your creative = your first layer of qualification. 5. Split-Test by Funnel Intent Not every clicker is a buyer, guide them. Run TOF ads (awareness) → retarget MOF (education) → close BOF (offers). This funnel filters curiosity from commitment. If every ad is BOF, you’re shouting at strangers. 6. Monitor Lead Quality Feedback Loop Don’t just count leads, score them. ✅ Tag leads as “Qualified” vs “Junk” ✅ Feed back via Conversions API ✅ Build lookalikes only from qualified conversions Quality loops = better delivery over time. The Big Picture: If your ads are hitting the wrong people, don’t blame the algorithm. Train it. Meta listens but only to your data, creative, and intent. Start optimizing for the right action, and you’ll start attracting the right people. ------ Salman Munir | CEO of AdLinked 👉 Follow me for next-level Meta Ads strategy. I break every update into actionable steps, not jargon.

Targeting the right audience is key. Don't waste your ad spend on the wrong people. Smart targeting boosts engagement and conversions. Here are key strategies to help you hit your audience like a sniper: ↳ Define your ideal customer. Build detailed buyer personas. Think about age, gender, location, interests, and pain points. Use surveys and social media insights to gather data. ↳ Leverage advanced targeting options. Platforms like Google Ads and social media have powerful tools. Target by demographics, interests, and geography. Use layered criteria for niche segments. ↳ Utilize lookalike audiences. Target users similar to your existing customers. Platforms can find these people based on shared traits. This increases your chances of engagement. ↳ Retarget for higher conversions. Focus on users who interacted with your brand but didn’t buy. Retargeting keeps your brand fresh in their minds. Encourage them to complete their purchase. ↳ Test and optimize continuously. Try different ad formats, visuals, and copy. A/B testing helps you find what works best. Use observation settings to gather data before full commitment. Optimization tips to enhance your strategy: ↳ Use intent-based targeting. Focus on users actively searching for products like yours. These users are more likely to convert. ↳ Exclude negative keywords. In PPC campaigns, remove irrelevant keywords. For example, if you sell luxury products, exclude "cheap." ↳ Analyze campaign data regularly. Review metrics like click-through rates and conversion rates. Adjust strategies based on performance trends. ↳ Personalize ad creative. Tailor visuals and copy to fit specific audience segments. Younger audiences may prefer vibrant designs, while older ones favor professionalism. ↳ Choose the right platform. Different platforms attract different demographics. Facebook reaches a broad audience. LinkedIn targets professionals. Instagram appeals to younger users. Pinterest is great for creative niches. Benefits of precise audience targeting: - Higher ROI: Your ads reach users likely to convert. - Improved engagement: Personalized messages resonate better. - Cost efficiency: Avoid wasting budget on the wrong audience. - Increased brand loyalty: Connect with the right people for stronger relationships. When you refine your approach and using these strategies, you can create effective paid advertising campaigns. Focus on targeting the right people at the right time for the best results. Remember: Precise audience targeting boosts your ROI. It improves engagement and cuts costs. And connecting with the right people builds loyalty. What are you thoughts about this?

❌ I never just define a Target Audience. ✅ I write down a full PROFILE 👇 As marketers, we often simplify our target audience down to basic demographics: ↳ Women, 25–34, middle-income, urban area. But real people aren’t bullet points on a slide. ⇢ They’re friends, partners, parents, professionals. ⇢ They wake up late on Sundays. ⇢ They binge-watch Netflix. ⇢ They juggle work meetings and grocery shopping. ... Let me show you what I mean👇 ⇲ Imagine you're marketing a shampoo brand. Your typical brief says: Female, Age 18–35, Income B bracket, urban area. ⇢ Now let’s bring her to life: Meet Emily 👩💼 ✤ A 29-year-old project manager living in Toronto ✤ She’s a mom of one toddler ✤ Plays tennis on weekends ✤ Loves Sephora, listens to crime podcasts, and shops at Loblaws ✤ Juggles daycare drop-offs and Zoom calls ✤ Cares about clean ingredients and also saving time Suddenly, you’re no longer speaking to a segment ⇢ You’re connecting with a human. ⇢ So, whenever you think of consumer behaviour, don’t forget these four things: ✤ Shopper ≠ Consumer Sometimes the person who buys isn’t the one who uses. ↳ Think about all the men using shampoo their partner bought. ↳ That’s why campaigns like “Buy him what’s made for him” (like what Axe or Old Spice has done) are aimed at women, not men. ✤ People are multi-dimensional ↳ On a Tuesday, Emily is a tired mom reheating leftovers. ↳ On Saturday, she’s hosting friends over and preparing a charcuterie board from Longo’s. ↳ On Sunday, she treats herself to Starbucks and nail-care. ⇢ Same person. Different needs. Different mindsets. ✤ Need-states change with context Emily’s food choices vary too: ↳ Quick weekday dinners? ⇢ HelloFresh or PC Blue Menu. ↳ Hosting brunch? ⇢ Maybe she’s grabbing bakery items from Whole Foods. ↳ Eating out with family? ⇢ Earls or Cactus Club. 👉 Brands win when they match the moment, not just the person. ✤ Self-concept drives decisions What Emily buys is influenced by how she sees herself: ↳ A mindful mom ↳ A career woman ↳ A modern, eco-conscious consumer Her choices are shaped by culture, social circles, and Instagram inspiration just as much as product features. 💡 The key takeaway? Don’t just build a customer profile. Build a persona. A full, layered story. That’s how your message truly resonates. #MarketingStrategy #ConsumerBehavior #BrandPersona #AudienceInsight #Storytelling #CanadianBrands #AdvertisingTips

Audience Insights is my favourite LinkedIn Ads feature and integral to campaign planning for me. Here's how I use it 👇 Back in the day, you had to rely on the Campaign Demographics report to work out who you were reaching with your ads. The problem with this alone is its reactive nature. You had to spend budget to better understand where you might be occuring wasted spend from any mistargeting and retroactively apply those audience exclusions. 💰 Then came along the ability to get the same great demographic insights - and many more - from Saved Audiences in the Audience Insights dashboard. Without needing to spend a dollar first. Before launching every campaign now, I'll draft a Saved Audience and check a few things: 1️⃣ I'll scan the Top 50-100 job titles that make it up and ask myself, are these the right people? 2️⃣ I'll check the company names report. Are these organisations I want to reach? I'll look at industries too. Are these sectors where we win or at least fit? 3️⃣ Look at the seniority and job function breakdowns. Is my audience skewed by a particular seniority layer that I could consider breaking out? Is my audience dominanted by a persona that I could run separately with tailored content/messaging? 💡Pro tip: These are especially insightful when using job title targeting as you'll learn how LinkedIn interprets your audience. (Note: desirable job titles can often sit in Entry or Senior buckets and sometimes get missed by Job Function + Seniority targeting alone. Likewise, there's often cases where you wouldn't want to target a whole job function but some titles within it could be super relevant.) 4️⃣ If you're running global campaigns, check the spread of countries you'd reach. 🌍 I'll often do this to map out a Total Addressable Market (TAM) and share this data back to the wider team. In the past, it's justified or prevented resources being wasted on localisation efforts. 5️⃣ Less useful but interesting nonetheless you can also see the shared skills and interests the audience has. I've sometimes used skills found here to expand or refine my targeting. *** When looking across the above attributes, you can exclude there and then any that are undesirable. Remember to apply and save your changes. You might have just trimmed up to 50% of an audience you would have otherwise launched and wasted spend on, doubling your efficiency. 📢 A word of caution, when excluding job titles, be mindful of any that contain "specialist". These behave like Russian dolls - they contain lots of other job titles. Exclude "marketing specialist" and you could be throwing out CMOs and Heads of Marketing too. *** Thanks for reading! If you like B2B marketing or paid media content, drop me a follow or connection request 👋 ~ Lee #b2bmarketing #linkedinads #paidsocial

Day 4 - CRO series Strategy development ➡Audience Segmentation Most marketing campaigns fail because they try to reach everyone. Smart businesses know that not all customers are the same. Here’s how to segment your audience for better targeting: 1. Define Your Segmentation Criteria Break your audience into meaningful groups based on: ◾ Demographics → Age, gender, income, education ◾ Geographic Location → Country, city, region ◾ Behavioural Data → Purchase history, engagement levels ◾ Psychographics → Values, interests, lifestyle choices The more precise the segmentation, the more effective the targeting. 2. Collect Audience Data Use multiple sources to understand your customers: ◾ Surveys & Interviews → Direct feedback from customers ◾ Website Analytics → Google Analytics, heatmaps, session recordings ◾ CRM Systems → Customer history, interactions, and purchase patterns Data removes guesswork. 3. Analyze the Data & Identify Patterns Look for trends: ◾ Are certain groups more likely to convert? ◾ Who engages most with your brand? ◾ What common traits do your best customers share? These insights form the foundation of strong segmentation. 4. Create Customer Segments Group people based on similar characteristics. Examples: ◾ High-value customers → Frequent buyers with high purchase amounts ◾ Engaged followers → Customers who interact on social media ◾ New leads → First-time website visitors Each segment requires a different marketing approach. 5. Develop Targeted Strategies Personalization is key. ◾ Young professionals? Use social media ads & video content. ◾ Older customers? Email campaigns may work better. ◾ High spenders? Loyalty programs & VIP offers. Speak to each segment in their language, on their preferred platform. 6. Test, Measure, and Optimize Not all strategies work equally. ◾ A/B test different messages within segments ◾ Track conversion rates, engagement, and retention ◾ Refine based on what performs best Optimization is an ongoing process. Why Segmentation Matters ✔ More Relevant Marketing → Customers receive messages tailored to them ✔ Higher Engagement & Conversions → People respond to what feels personalized ✔ Optimized Marketing Spend → Invest in what works for each segment ✔ Better Customer Experience → Customers feel understood and valued Businesses that segment their audience don’t just market better— They sell smarter. Are you using segmentation in your marketing? Share your thoughts below. See you tomorrow! P.S: If you have any questions related to CRO and want to discuss your CRO growth or strategy, Book a consultation call (Absolutely free) with me (Link in bio)

Struggling with sky-high LinkedIn CPL? Here’s how I slashed it by 45% for a B2B SaaS client—and what you can steal from my playbook. 𝐓𝐡𝐞 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞: 𝐀 𝐋𝐞𝐚𝐤𝐲 𝐅𝐮𝐧𝐧𝐞𝐥 𝐃𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐁𝐮𝐝𝐠𝐞𝐭 A fast-growing B2B SaaS client had a critical pain point: their LinkedIn Ads were generating leads at a staggering $300+ cost per lead (CPL). Their target audience—enterprise decision-makers in tech—was slipping through a generic campaign structure, wasting budget on irrelevant clicks and unqualified sign-ups. 𝐓𝐡𝐞 𝐃𝐢𝐚𝐠𝐧𝐨𝐬𝐢𝐬: 𝐖𝐡𝐲 𝐓𝐡𝐞𝐢𝐫 𝐀𝐝𝐬 𝐖𝐞𝐫𝐞 𝐌𝐢𝐬𝐬𝐢𝐧𝐠 𝐭𝐡𝐞 𝐌𝐚𝐫𝐤 After a deep dive, I spotted three gaps: 1. Overly broad targeting: They cast a wide net (job titles like “IT Manager” and “Director”), attracting passive scrollers, not decision-makers. 2. Static creatives: One-size-fits-all messaging that failed to resonate with nuanced buyer roles (e.g., CFOs vs. CTOs). 3. Bidding blind: Manual bids optimized for clicks, not conversions. 𝐓𝐡𝐞 𝐅𝐢𝐱: 𝐏𝐫𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐓𝐚𝐫𝐠𝐞𝐭𝐢𝐧𝐠 + 𝐇𝐲𝐩𝐞𝐫-𝐏𝐞𝐫𝐬𝐨𝐧𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 Step 1: Surgical Audience Segmentation Rebuilt audiences using LinkedIn’s Matched Audiences and layered intent signals: • Job functions: Narrowed to “C-Suite” and “VP-Level” in companies with 1,000+ employees. • Interest targeting: Focused on users engaging with competitor content or trending SaaS tools. • Exclusion lists: Filtered out junior roles and irrelevant industries. Step 2: Creative That Spoke Directly to Pain Points We A/B tested: • Role-specific carousels: For CFOs, ROI-focused stats; for CTOs, technical integration demos. • Video testimonials: 30-second clips of existing clients (similar industries/roles) sharing results. • Personalized CTAs: “Download the CFO’s Guide to SaaS ROI” vs. “See the Tech Integration Playbook.” Step 3: Bid Smart, Not Hard Switched to LinkedIn’s Conversion Optimization with a target CPL strategy, letting algorithms prioritize high-intent users. 𝐓𝐡𝐞 𝐑𝐞𝐬𝐮𝐥𝐭𝐬: • 45% Lower CPL in 60 Days • CPL dropped from 300 to 165 • Conversion rate surged by 60% (qualified leads only) • CAC reduced by 30% within 6 months 𝐓𝐡𝐞 𝐁𝐢𝐠 𝐋𝐞𝐬𝐬𝐨𝐧: 𝐐𝐮𝐚𝐥𝐢𝐭𝐲 𝐎𝐯𝐞𝐫 𝐐𝐮𝐚𝐧𝐭𝐢𝐭𝐲 𝐖𝐢𝐧𝐬 LinkedIn’s premium audience demands precision. By combining laser-focused targeting, tailored messaging, and smart bidding, we transformed a leaky funnel into a high-converting engine. Your Turn: Audit your LinkedIn campaigns today—are you speaking to everyone or the right one? #LinkedInAdsCPL #B2BLeadGen #AudienceSegmentation #HyperPersonalizedAds #ConversionOptimization #LeadGenHacks #SaaSMarketing #CPLReduction #DigitalMarketing

You’re Not Closing Deals Because You’re Targeting the Wrong People. A strong Ideal Customer Profile (ICP) is the difference between wasted effort and scalable growth. An effective ICP isn’t just about listing traits—it’s about truly understanding your target audience and aligning your outreach with their needs. Here’s how to build one that works: 1️⃣ Definition and Industry Focus → What industries are best suited for your product or service? Drill down beyond broad categories. Focus on specific sectors or niches that are naturally aligned with what you offer. → Example: SaaS companies focusing on automation, e-commerce brands prioritizing logistics, or local businesses seeking efficiency tools. Why It Matters: If your solution doesn’t align with the industry’s priorities, no amount of outreach will convert. 2️⃣ Decision Makers and Influencers → Who’s involved in the buying process? Don’t just target one role—map out the entire decision-making chain. → Target examples: Founder, CEO's, VP of Marketing, Sales Directors, and Operations Managers often hold the budget and influence. 3️⃣ Challenges and Pain Points → What’s keeping your ideal customers up at night? Understand the underlying problems they’re actively seeking to solve. → Examples: Struggling to generate consistent leads, juggling inefficient workflows, or high customer churn eating into profits. How to Discover Pain Points: - Analyze customer reviews in your industry. - Monitor conversations on forums, LinkedIn, and other platforms. - Conduct surveys or interviews with past clients. The more you understand their challenges, the easier it is to position your solution as the answer. 4️⃣ Success Factors → What outcomes matter most to your target audience? Focus on measurable results. → Examples: Improved efficiency, reduced churn rates, faster sales cycles, or achieving a specific ROI target. Clearly linking your solution to success metrics resonates with decision-makers who are judged by outcomes, not effort. 5️⃣ Budget and Negative Indicators → Can they afford your solution? If not, disqualify early. Spending time on leads who don’t have the budget is a surefire way to waste resources. → Example of negative indicators: Companies under 5 employees or industries with historically tight margins that rarely invest in external tools. Pro Tip: Use tools like Apollo.io or Clay to segment and filter out leads with low likelihood of converting. Additional Steps to Refine Your ICP - Run A/B Tests: Test campaigns on slightly different ICPs to see which converts better. - Feedback Loops: Regularly update your ICP based on performance data and client feedback. - Leverage Data Tools: Use tools like BuiltWith to uncover tech stacks or LinkedIn Navigator for role-specific insights. When your ICP is grounded in real data and actionable insights, everything improves—from your messaging to your results. What’s one unexpected insight you’ve discovered about your ICP?