Marketing KPI Dashboard

B2B companies dramatically overspend on paid search with very low ROI because the reports & metrics they use ALLOW IT to happen. All you need to measure is two core revenue metrics: 1. $ Closed Won Revenue : $ Ad Spend (Lagging) Example: For every $1 we spend on Google ads, we get $2.20 in revenue. You should be targeting an absolute minimum of 1:1. Very few B2B companies I interact with ever get this minimum baseline metric. 2. $ HIRO Pipeline : $ Ad Spend (Leading) Example: For every $1 we spend on Google Ads, we get $10 in HIRO pipeline. Our HIRO win rate is 25% historically, so we can project forward that we’ll get approx $2.50 in revenue for every $1 investment in Google Ads. ___ This will immediately tell you whether your investment in paid search is working (Paid Search is one of the Top 3 largest annual Marketing expenditures at most B2B companies). Then, break down these metrics by each core campaign group: 1. Branded 2. High Intent Non-Branded 3. Low Intent Non-Branded 4. Competitor With this view, you’ll probably see that the blended ROI you see on paid search is actually being propped up by Branded keyword conversions that would’ve happened anyway, while non-branded and competitor campaigns are bleeding big losses & negative ROI. __ If B2B companies evaluated their paid search investment through this simple, logical lens, they would spend 50-75% less on paid search every month. Because that investment is clearly not driving actual business outcomes or positive ROI when evaluated through this lens. Which would create a large additional budget that could be deployed to much more effective GTM programs. #b2b #marketing #google #gtm #sales p.s. Paid search is a 100% demand capture channel. By definition, if someone makes a search, it's a signal of intent. The only appropriate way to measure demand capture is how much of that intent you've captured into sales meetings, pipeline, and revenue. Don't overcomplicate it. p.p.s. You don't need any fancy technology to do this. Implement persistent UTMs and track it to opportunities in Salesforce against the converting contact.

My email got an open rate of 83% and CTR of 42% instead of usual 50% and 22%. What I found out next shocked me totally- I was thrilled and patting myself on my back only to be taken into deep shock when I started analysing what did I do right. I noticed my email platform (Brevo) has filters for "Apple Mail Privacy Protection" and "bot activity." I was unaware of them so clicked them out of curiosity. Real opens dropped to 39% and CTR of 1.14% ( 3.53% if we take open rate as the base). Only a few people have clicked on my link. That's a 60% inflation in my open rates. 😶🌫️ I had no idea Apple pre-loads emails and bots scan them, both counting as "opens." Have I been optimizing for a meaningless metric this whole time? My actual engagement rate is 3.6%, not the 83% open rate I thought I had. Now I'm deep-diving into the data: 📍 Analyzing click heatmaps - WHERE are those people clicking? 👥 Exporting emails of actual clickers - WHO are our true readers? 🎯 Planning remarketing campaigns - targeting ONLY engaged subscribers 🧹 Considering a list purge - do I remove the ones who never engage? 📊 Building segments - "clicked in 30 days" vs "ghosts" I feel like I've been marketing to phantoms. Apple pre-loads emails. Bots scan them. Both count as "opens." I've been fooled. Questions for my marketing network: What's your REAL open rate after filtering? Do you delete inactive subscribers or try to re-engage them? Which metrics actually matter in 2025? Has anyone cracked the code on improving click rates? Currently planning to A/B test everything, focus on clicks over opens, and maybe say goodbye to dead weight on my list. Am I overthinking this? Under-thinking it? Drop your brutal honesty below. 👇 #EmailMarketing #DataAnalytics #MarketingMetrics #DigitalMarketing #MarketingStrategy

Open rates are the most misleading metric in sales. They make you feel like you’re getting traction but reality, the data is completely broken. Here are 4 reasons why (and what to actually measure): 1. Email clients handle open tracking differently Gmail and Outlook handle tracking pixels in totally different ways. Send the same email and Gmail might show 60% opens, while Outlook shows 40%. That’s a 20% delta — if the pixel even fires at all. 1. Apple Mail killed open tracking Apple’s Mail Privacy Protection preloads emails, images, and pixels before a user even sees the message. So your platform logs an open… but the person never read it. This impacts every iOS user so….basically everyone. 1. Bots and security scanners inflate opens Enterprise security tools scan inbound emails for threats which includes opening and parsing them. This triggers your tracking. Now you think your subject line crushed it, but half your opens were bots. Nobody read it. 1. Pixel blocking tools everywhere The opposite is also true: real opens that don’t get tracked. Chrome extensions, ad blockers, and privacy tools can all suppress pixels entirely. So someone could open your email, read it top to bottom, maybe even forward it and your platform will show zero engagement. Here’s what you should measure instead: 1. Reply rate This is the single most important metric in the entire game. It answers the only question that matters: Did a human engage? Every reply is good. Yes. No. Even “stop emailing me.” They show Google and Microsoft that humans are responding to your emails. That you're not just some bot dumping generic outreach into the void.  No replies = you're either in spam, or your message is irrelevant. 1. Bounce rate A bounce means the email address is dead or fake. If your bounce rate is above 1%, you’re seen as a spammer. And that flag doesn’t just apply to one campaign, it pulls down your sender score across the board. Even your best emails stop reaching inboxes. If you don’t fix your list, you're just spraying garbage. 1. Opt-out rate This one tells you whether you’re hitting the right audience. When someone unsubscribes or worse, reports you, what they’re saying is: “You’re not relevant. I don’t want to hear from you.” And they’re not wrong. If your targeting was on point, if your messaging was contextual, if your outreach spoke directly to their pain they wouldn’t be opting out. Even if they don’t respond right away, they’d read. They’d stay in your pipeline. They’d keep the door open. This is usually a result of lazy ICP work. Either you’re going too broad, or your criteria are completely misaligned with what the market actually looks like. ——— We built the entire Forge stack to solve exactly this: → Leadsforge to source clean, qualified data → Salesforge to execute multichannel outreach at scale → Warmforge to protect your domain health behind the scenes Open rates don’t build pipeline. Replies do.

Marketers, are you still measuring email the old way? We get told email is dead, but everyone reading this has most likely read an email, logged in using it & made a purchase with it. So it's not dead, but how we judge its effectiveness hasn’t evolved fast. We’ve relied on open rates & click-through rates (CTR) — metrics that, frankly, are no longer fit for purpose. Why open rates are no longer reliable Open tracking depends on image loading, which Outlook often blocks, & Apple & Gmail preload by default. As a result, you might see machines open, not human ones. And proper visibility is vanishing with more “text-only” creatives or image-blocked environments. And CTR? It’s got its own problems Think about user intent. If a customer reads “50% off this weekend” in your subject line, they may just go straight to your site—no click needed. Even Gmail’s AI summarising content & extracting voucher codes means users engage without clicks. Email is quickly becoming a powerhouse for brand awareness, but it doesn't have the metrics to prove this. So, what should we look at? As the rest of adtech races toward incrementality, attention, and post-impression attribution, email needs to catch up. Here’s how: 1. Conversion Attribution (Beyond Last Click) Don't stop at click-based conversions. Track who received the email, & assign influence weightings to openers, clickers, & even non-clickers who later convert. This mirrors how display and social now assess "view-through" impact. 2. Frequency & Multi-Touch Engagement Did the recipient open on mobile in the morning, revisit via desktop, & convert on payday? That’s a multi-touch journey. Look at repeat site visits, device switching, & re-engagement post-send. 3. Pay Day or Trigger-Based Lift Create holdout groups and measure uplift around high-conversion moments (e.g., end-of-month). This mirrors the incrementality testing often used in paid social or programmatic, proving that email drives behaviour, not just volume. 4. Attention Metrics Use tools to estimate dwell time on emails or the time between opening& clicking. These are soft proxies for intent, similar to how platforms measure scroll depth, hover rate, and ad exposure time in other channels. 5. Site Quality Metrics Did email recipients spend longer on site, view more pages, or have higher AOVs? Your session quality tells you if email delivers high-intent traffic, something brands already monitor from Google Ads or affiliates. 6. Ask them! Simple, but powerful: survey your audience. What emails did they find valuable? Did it change their behaviour? Self-reported attribution, done well, can give you what click-tracking can’t. Email deserves more credit than. If adtech is shifting toward attention, incrementality, & deeper behaviour analysis, email should, too. Let's measure actual impact, not just opens & clicks. I bet you will discover that email isn't just for conversion but also a branding-building superpower.

"What ad metrics should you track?" 🧵 Dara Denney's framework from $100M in ad spend: Dara splits her metrics into TWO categories Primary KPIs: Amount spent, results, cost per result, ROAS Storytelling KPIs: Frequency, CPM, CTR, CPC, hook rate, hold rate, watch time Primary KPIs determine winners. Storytelling KPIs explain WHY they won. Ex: Frequency shows scalability (when it hits 3 to 4 in a few weeks, creative may be tapping out). Hook rate reveals attention grabbing power. Hold rate and watch time demonstrate ability to keep attention. Then she analyzes creative qualitative data The basics you're prob doing today like Format: Does the UGC style or static format affect performance? Creator: Is a specific person consistently delivering winners? Messaging: What specific words/hooks are working wel? Imagery: What visual elements are driving engagement? Then she maps messaging to the user journey You need to have the right creative mix From every stage of awareness Ex: Unaware stage: "Hate doing your makeup" Problem aware: "Get a full eye look fast" Solution aware: "Our $14 eyeshadow stick beats the $34 one" She tracks EVERY test with these - Initial hypothesis (why run this test?) - Performance vs. account benchmarks (% better/worse vs AVG) - Detailed messaging analysis (which hooks worked and why) - Demographic breakdowns (which age groups responded) - Placement analysis (where it performed best) - Concrete next steps (ex: scale budget, iterate, stop) Including competitor messaging changes Look for hyper specific patterns: Formats they double down on Visual approaches Using THIS reporting cadence 👇 WEEKLY Last 7 days top performers, test updates, action items MONTHLY Creative retros with full test breakdowns, competitor tracking QUARTERLY Format analysis, product comparison, agency/creator benchmarking Final words from Dara: "Being data driven does not just mean looking at the numbers. The people behind those metrics are individuals – that's why messaging analysis and understanding where they are in their journey is the most important qualitative data to making creative that converts" -- 👋 P.S. Want more content like this? Get our Motion newsletter Thumbstop (Read by 47,000+ marketers every Sunday)

Want to unlock 20% more value from your email metrics? I've just published a deep dive into the metrics that truly matter beyond basic open rates. From Clicks-to-Opens Rate (CTOR) to Subscriber Lifetime Value, learn how to measure what matters for your email campaigns. Whether you're struggling with engagement or looking to optimize your strategy, these insights will help you make data-driven decisions. At Prospect Engine LLC, we've helped 190+ B2B companies generate consistent sales meetings using these exact principles. Curious to learn more? Check out my detailed guide below! 👇 #EmailMarketing #B2B #MarketingMetrics #SalesStrategy

Do bots inflate email click-through rates? Yes, but not nearly as much as they inflate open rates. In a previously published analysis, we found that roughly two-thirds of reported email opens were not generated by actual humans. Apple Mail Privacy Protection, proxies, and security tools can make open rates wildly misleading. Clicks are not nearly as bad. We reviewed several campaigns. For example: Campaign 1 Reported CTR: 4.4% Likely real CTR: 3.9% Campaign 2 Reported CTR: 1.5% Likely real CTR: 1.3% One frustrating part: Klaviyo already has bot click filters, but they are turned off by default. In fact, we did this analysis using Klaviyo’s own bot click filtering. So yes, about 11% of reported clicks appear to be bots or security tools. But that distortion is not catastrophic compared to open rates, which can be totally misleading. The hierarchy is pretty clear: Open rate: mostly broken CTR: imperfect, but still useful Revenue per recipient: best metric So do not diagnose campaign performance from open rates alone. Look at CTR and revenue per recipient together. If opens are high but clicks are weak, your engagement may be overstated. If clicks are strong but revenue per recipient is weak, your offer, audience, landing page, or conversion path may be the issue. And if both CTR and revenue per recipient are weak, you may have a deeper deliverability or list quality problem.

ROAS = Really Over-estimating Ad Success Here's how to fix it: It doesn't matter how much return your ads make if the sales were going to happen anyway. You need to look at the incremental return on ad spend (iROAS). The 'i' really matters. It means you're trying to measure sales caused by advertising, (using test <> control methodology) rather than just counting sales regardless of causality. Given how much is spent in performance this is probably the single biggest step the advertising industry can take in 2025 to improve effectiveness. Analytic Partners found 35 cents from every $1 spent on advertising is wasted due to optimizing exclusively to last click metrics like ROAS. That wastage is advertisers paying for existing sales. When you're next shown ROAS results ask where's the 'i'? iROAS is just the start. Consider the full picture: - What's the value of incremental sales you're driving? - What's the cost factoring non-media costs (creative production etc)? - What's the cost of goods sold (production, returns etc)? - How much incremental profit are you driving? - What's the long term incremental impact? Incrementality should be non-negotiable in 2025.

Open rate and click rate aren’t the only ways to tell if your newsletter is successful. Here are 8 ways to measure success that aren’t the usual metrics: ❶ Active list size — What percentage of your list has engaged with an email in the last 90 days? List growth only matters if those new readers are opening and clicking. ❷ Net Promoter Score — Not enough newsletters measure feedback as one of their core metrics. So the next time you run a survey, try asking the Net Promoter Score question, which follows the format: “On a scale of 1 to 10, how likely are you to recommend our newsletter to a friend or colleague?” The results should give you a decent sense of reader satisfaction, and you can compare your results to those from previous surveys to understand if you’re improving your newsletter over time. ❸ Customer acquisition cost — If you spend money to grow your email list, be sure to closely track customer acquisition cost, or CAC. This measures the cost to acquire one newsletter subscriber. So, let’s say you spend $1,000 on a series of ads and bring in 500 new subscribers. Divide the cost of the campaign ($1,000) by the number of subscribers (500), and you’ll get the CAC — in this case, $2. (For most newsletters, a CAC in the $1-3 range is normal.) ❹ Payback period — Let’s say it costs $2 to acquire a newsletter subscriber. Payback period looks at that CAC, as well as the estimated lifetime value of a subscriber to show you how long it will take to make your money back on that one new subscriber. (beehiiv’s Newsletter Navigator tool is great for calculating CAC and payback period —> https://lnkd.in/ePyWqST7) ❺ Spam complaint rate — Use Google Postmaster to track the percentage of Gmail readers who mark your email as spam. Gmail says you should always be below a 0.1% spam complaint rate, and a 0.3% rate is a massive red flag. If readers are marking your emails as spam, it means you’ve got to fix your growth or content strategy (or possibly both!). ❻ Time on site from newsletters — If your content is super long, it's not enough to see that readers clicked through. The real question is: Did they spend time on site actually reading your content? (For my newsletter, if I see readers spending less than three minutes on average on a story, I know I’ve missed the mark.) ❼ Reactivation rate — As the number of inactive readers on your list grows, it’s wise to run a reactivation campaign to win back these readers. The first time you run a campaign, anything between a 2-5% reactivation rate would be considered a success. I’ve found that at best-in-class newsletters, you might see a reactivation rate of anywhere between 5-15%. ❽ Reply rate to your welcome email — Ask something specific in your welcome email, then calculate how many readers reply. Those early replies often help with deliverability — and can help you better understand your audience, too!

We analyzed over 27 million cold emails. Here are key insights into mailbox activity and performance: 📊 open rates: - Across all non-agency campaigns globally, the average open rate is 26%. - Open rates remain stable across workdays but drop 6-9% on weekends. 📊 reply rates: - Smaller, highly targeted campaigns (1-50 prospects) have a reply rate nearly 3x higher than mass campaigns with 1001-5000 prospects. - Campaigns with a bounce rate under 2% enjoy a 60% higher reply rate than those with 20%+ bounce rates. - Initial emails have the highest reply rates (~1%), with subsequent follow-ups seeing diminishing returns (30% as effective by the 5th or 6th email). 📈 mailbox volume and performance: - Mailboxes sending 1-20 emails daily have reply rates four times higher than those sending 101-200 emails daily. - 21-50 daily emails see a balanced performance, with over twice the reply rates of high-volume senders. 🔑 key takeaways ↳ Personalized, concise, and well-segmented campaigns drive higher engagement. ↳ Maintaining a low bounce rate and optimizing email volume per mailbox is critical for maximizing results. ↳ Send no more than 3 messages in sequence. Have you noticed similar patterns in your campaigns?