Common Mistakes In Sales Metrics Tracking

Most metrics aren’t broken. But the way companies use them is. ☑ Optimising for the measure instead of the mission ☑ Reporting the number, not the reality ☑ Chasing KPIs instead of fixing systems Let’s talk about how companies game metrics — and what to do about it. ☑ 1. Focus on what’s measured ↳ Call centres reduce average call time by ending calls early — even if problems aren’t solved. ☑ 2. Cherry-pick the data ↳ Only show top 10 customers. Hide the 90 others bleeding revenue. ☑ 3. Change definitions ↳ “Retention” becomes “hasn’t cancelled” instead of “actually engaged”. ☑ 4. Go short-term ↳ Boost sales with end-of-quarter discounts. Kill margins. Burn future demand. ☑ 5. Misalign incentives ↳ Reward production by volume, not quality. Create more waste to hit a number. ☑ 6. Massage the data ↳ Adjusted EBITDA? Translation: "Ignore all the inconvenient costs." ☑ 7. Optimise in silos ↳ Marketing sends low-quality leads. Sales can't convert. Blame flies. ☑ 8. Classic Goodhart’s Law ↳ “When a measure becomes a target, it ceases to be a good measure.” Here’s why it happens: 1. Poor system thinking 2. Bad incentives 3. Weak governance 4. Culture of fear Here’s how to stop it: ↳Use leading and lagging metrics ↳Audit behaviour, not just outcomes ↳Run “metric integrity” checks ↳Triangulate truth, not just data If you care about strategy, culture, or execution — fix how you measure. Ps. if you like content like this, please follow me.

A team celebrated a 31% lift in conversion rate after a big optimization push. I conducted an incrementality test to ensure accuracy. Real lift: 4%. The other 27 points were noise, seasonality, and people who would have converted anyway. We'd have hit our number with 80% of the budget. That's when I stopped trusting conversion rate as a primary metric. And I started looking at every dashboard in the building differently. Here are 5 reasons your CR is lying to you in 2026, and what to actually measure instead: 👉 Cookie deprecation killed half your tracking, but nobody updated the dashboard. Your "conversion rate" is now calculated against a known sample, not your full traffic. Fix: move to server-side tracking with consent-mode modeling, and start reporting a confidence range on every conversion metric, not a single number. 👉 AI assistants are now sending you traffic with no referrer. ChatGPT, Perplexity, Gemini, and Claude are increasingly the first touch in B2B buying journeys. The people who arrived because an AI recommended you are getting credited to "direct" or "organic." Fix: track branded search trends and direct traffic growth as leading indicators. If they're climbing, your AI-mediated demand is working, even if your dashboard can't see it. 👉 Most of your "conversions" would have happened anyway. Without incrementality testing, you're attributing conversions to campaigns that the customer was going to do regardless. The honest number is almost always 20 to 40% lower than your dashboard shows. Fix: run geo holdout tests at least quarterly. Pick 5 markets to turn off paid ads for 30 days and compare them. The gap is your real incremental lift. 👉 Last-click is still secretly running your reporting, even if you've moved on. The first touch (the creator post, the podcast, the AI mention) almost never gets the credit. Fix: pair your platform reports with marketing mix modeling (MMM) at least twice a year. MMM is the only attribution method that can see what your tracking can't. 👉 Your CR moves more from market timing than your work. When category demand spikes, your CR goes up. Fix: index your conversion rate against your category's search volume trend. If your CR rose 12% but category demand rose 18%, you didn't get better. You got carried. Here's the part that should sit uncomfortably with you: Most marketing teams in 2026 are reporting metrics that are 30-50% wrong, with confidence intervals that nobody publishes, on dashboards built before the AI search wave even started. What's the metric your team is still reporting that you privately know is broken? Follow #socialJJ to read more of my posts. 

𝗬𝗼𝘂𝗿 𝗥𝗢𝗔𝗦 𝗶𝘀 𝘂𝗽, 𝗯𝘂𝘁 𝗿𝗲𝘃𝗲𝗻𝘂𝗲 𝗶𝘀 𝗳𝗹𝗮𝘁. 𝗛𝗲𝗿𝗲’𝘀 𝘄𝗵𝘆 𝘆𝗼𝘂𝗿 𝗔𝗱𝘀 𝗱𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱𝘀 𝗺𝗶𝗴𝗵𝘁 𝗯𝗲 𝗹𝘆𝗶𝗻𝗴 𝘁𝗼 𝘆𝗼𝘂. One of the most common mistakes I see, even at large brands and seasoned agencies, is focusing too much on ROAS without asking the real question: 👉 How many of those conversions are truly incremental? 𝗧𝗵𝗲 𝗣𝗮𝘁𝘁𝗲𝗿𝗻 𝗜 𝗦𝗲𝗲 𝗘𝘃𝗲𝗿𝘆𝘄𝗵𝗲𝗿𝗲: ✅ Facebook Dashboard: "Conversions up 37%!" ✅ Google Ads: "ROAS through the roof!" ✅ GA4: “+15% conversion lift from Performance Marketing” ✅ Agency Report: "Best performance ever!" ❌ Your CFO: "Why is revenue flat?" It looks like you're scaling profitably, but actual business growth is not keeping up. 𝗪𝗵𝗮𝘁’𝘀 𝗥𝗲𝗮𝗹𝗹𝘆 𝗛𝗮𝗽𝗽𝗲𝗻𝗶𝗻𝗴:  • Your ads are targeting your own employees who already use company discounts  • You’re retargeting existing customers again and again  • You're mixing new user acquisition and remarketing into the same campaign  • Paid performance looks strong, but it's cannibalising organic and direct channels  • CRM and revenue metrics remain flat because paid is simply taking credit for demand that already existed You are not actually acquiring new customers. You are just recycling your warmest audience. 𝗪𝗵𝘆 𝗬𝗼𝘂𝗿 "𝗥𝗢𝗔𝗦 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗲𝗱" 𝗖𝗮𝗺𝗽𝗮𝗶𝗴𝗻𝘀 𝗔𝗿𝗲 𝗔𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗦𝗮𝗯𝗼𝘁𝗮𝗴𝗶𝗻𝗴 𝗬𝗼𝘂:  • Automated campaigns are the worst offenders: PMax and ASC will absolutely target your warmest audience if you don't set up the campaign correctly.  • Algorithms take the easy path: Why find new customers when your employees and loyal Cx convert at 5x conversion rates?  • Platform incentives ≠ Your incentives: They make money when you spend more, not on actual business growth.  • Vanity metrics feel good: A ROAS of 5 sounds better than "₹312 cost per truly new customer" 𝗛𝗼𝘄 𝘁𝗼 𝗙𝗶𝘅 𝗜𝘁: 1. Run an Exclusion Audit  • Exclude employees and dealers using Customer Match  • Block internal IP addresses  • Build audience rules (for example: 20+ visits with no purchase likely means internal traffic) 2. Fix Your Campaign Structure  • Always separate acquisition campaigns from remarketing campaigns  • Avoid letting PMax or ASC optimise without oversight  • Use custom conversion events that trigger only for completely new users 3. Track the Right Metrics  • Monitor new user growth using CRM data instead of relying only on ad platforms  • Focus on measuring incremental lift, not just what platforms attribute  • Track customer acquisition cost (CAC) specifically for new users, not the blended number It is easy to chase ROAS that looks impressive on a dashboard. It is harder, but far more meaningful, to drive incremental business growth. Curious if others are seeing similar patterns, let me know in the comments.

Years ago, I was sitting in a quarterly business review. The VP of Sales shared we missed the revenue goal. 5 minutes later, the CMO shared that we hit our “lead goal” the past 3 quarters. The CEO asked, “What happened?” Real talk: what happened is that metrics became goals, and the team focused on hitting those “goals” without keeping the ACTUAL goal in mind A goal is a desired outcome you’re looking to achieve A metric is an indicator that determines your progress toward a goal Metrics inform if you’re on track to achieving a goal and should not be set as goals themselves When you make a metric a “goal”, you shift the focus from the original goal to the “metric goal”. As a result, the likelihood of missing the original increases as how you optimize towards the metric, not the goal. Most company annual planning includes setting goals for certain things: new revenue, revenue retention, net promoter score, etc. Each of those goals are then given a figure. Let’s pull the new revenue thread since that’s the one most of us are working towards. In this fictitious scenario, a company determines they need to drive $100 million in new revenue for the upcoming year. This is the goal. So the CEO passes this goal down to the marketing leader, who then wants to make this goal relevant to their team. And this is where the mistake happens - the marketing leader breaks the revenue goal down into the metrics that help drive the desired result (i.e. leads, pipeline, etc.) and sets goals for each of those metrics. This happens with leads all the time in marketing. You look at your funnel and start working backwards to understand what you need to produce moving forward. You see that you have a 25% win rate from stage 2 opportunities. You see that you have a 33% conversion rate from lead to stage 2 opportunity. So you did the math. For every 1 won deal, we need 4 stage 2 opportunities. For every stage 2 opportunity, we need 3 leads. So we multiply 4 by 3 and proclaim, “We need 12 leads to drive 1 won deal” So that metric of 12 leads is passed down to the team, but as a goal. Nobody wants to miss a goal, so we think of new or creative ways to drive more leads. And this is where lead gen forms, webinar sign ups, ebook downloads, and more were jumped upon as “lead sources”. Marketing teams started blowing their lead “goals” out of the water by 150-300%. Meanwhile, conversion rates from lead to stage 2 opportunities and win rates from those opportunities were dropping quarter over quarter. All because metrics became goals.

I met a sales team that tracks 27 different metrics. But none of them matter. They measure: - Calls made - Emails sent - Meetings booked - Demos delivered - Talk-to-listen ratio - Response time - Pipeline coverage But they all miss the most important number: How often prospects share your content with others. This hit me yesterday. We analyzed our last 200 deals: Won deals: Champion shared content with 5+ stakeholders Lost deals: Champion shared with fewer than 2 people It wasn't about our: - Product demos - Discovery questions - Pricing strategy - Negotiation skills It was about whether our champion could effectively sell for us. Think about your current pipeline: Do you know how many people have seen your proposal? Do you know which slides your champion shared internally? Do you know who viewed your pricing? Most sales leaders have no idea. They're optimizing metrics that don't drive decisions. Look at your CRM right now. I bet it tracks: ✅ When YOU last emailed a prospect ❌ When THEY last shared your content ✅ How many calls YOU made ❌ How many stakeholders viewed your materials ✅ When YOU sent a proposal ❌ How much time they spent reviewing it We've built dashboards to measure everything except what actually matters. The real sales metric that predicts closed deals: Internal Sharing Velocity (ISV) How quickly and widely your champion distributes your content to other stakeholders. High ISV = Deals close Low ISV = Deals stall We completely rebuilt our sales process around this insight: - Redesigned all content to be shareable, not just readable - Created spaces where champions could easily distribute information - Built analytics to measure exactly who engaged with what - Trained reps to optimize for sharing, not for responses Result? Win rates up 35%. Sales cycles shortened by 42%. Forecasting accuracy improved by 60%. Stop obsessing over your activity metrics. Start measuring how effectively your champions sell for you. If your CRM can't tell you how often your content is shared internally, you're operating in the dark. And that's why your forecasts are always wrong. Your move.

Most sales activity is just expensive theater. Your rep shows you their CRM activity: 100 calls, 50 emails, 20 LinkedIn messages. You think: 'Wow, they're really grinding!' Reality check: They're hitting 30% of quota. Here's what's happening: Motion without progress. Reps who are 'busy' all day but producing zero results. They mistake activity for achievement. Meanwhile, my top performers make 20 strategic touches and crush their numbers. What's the difference? Strategy. Low performers spray and pray: → Cold calling random lists → Sending generic email blasts → Connecting with anyone on LinkedIn → Attending every networking event → Responding to every RFP High performers are surgical: → Research before every call → Personalize every message → Target specific decision makers → Focus on qualified opportunities → Disqualify fast and move on It's not about doing MORE. It's about doing BETTER. But here's the problem: Most sales managers reward activity, not outcomes. They celebrate the rep who made 100 calls, not the one who closed 2 deals with 10 calls. They praise the person who sent 500 emails, not the one who got 5 meetings from targeted outreach. This creates activity theater. Reps learn to look busy instead of being productive. I learned this lesson running a $195M P&L. The metrics that mattered weren't calls or emails. They were: → Qualified opportunities created → Meetings with decision makers → Progression through sales stages → Pipeline velocity and conversion Stop measuring dials. Start measuring dollars. Stop rewarding motion. Start demanding results. Your reps will optimize for whatever you measure. Make sure you're measuring what actually drives revenue.

Not all metrics are meant to be tracked alone. Focusing on a single number can lead you straight into a false sense of progress. You reduce CAC by 10%. You increased ROAS by 20%. You drive 30% more signups. But revenue and profit doesn’t move. Retention drops. What happened? 👉 You optimised one metric, but ignored its sister. Every core KPI needs a sister metric, a complementary measure that ensures your efforts are actually creating value, not just movement. Here are a few examples: CAC + Contribution profit ROAS + Conversion value Traffic + Conversion rate Email signups + Revenue per subscriber Returning customers + Revenue growth per returning customer These pairs act as guardrails. Single metrics give you a snapshot. Sister metrics give you the full story. Track in pairs. Think in systems. Grow with clarity.

If the only metric your exec team cares about is pipeline created, Then they’re not seeing the full picture. C-level dashboards do tell a story. I agree, But usually the wrong one, at the wrong resolution, with the wrong cause-and-effect logic. And then... they ask Marketing Ops to “make the numbers better.” → Without changing the inputs. → Without cleaning the data. → Without aligning the teams. Here’s what you should be tracking instead → Not just pipeline velocity—pipeline quality → Not just cost per lead—cost per aligned buyer → Not just attribution—contribution clarity 3 Metrics Marketing Ops Should Own (And Execs Need to Learn How to Interpret): 1. Lag-to-Lead Time How long does it take from first lead capture to actual opportunity creation? If it’s bloated, no campaign will fix it. → Root cause: CRM architecture, scoring logic, lack of sales follow-up rhythm. 2. Operational Win Rate Forget sales win rate. Measure the qualified ops-to-closed ratio for GTM feedback. This tells you: Are we targeting the right personas? Are we delivering them in the right stage of readiness? 3. System Hygiene Score This isn’t sexy, but it saves millions in burn: % of contacts with missing data % of workflows with broken logic % of platforms not integrated with the source of truth Ops shouldn’t just report on performance. We should report on the system that delivers performance. You can’t scale what you can’t explain. And you can’t explain what you refuse to measure. It’s time we stop dumbing down dashboards and start training up leadership. #MarketingOps #RevOps #MetricsThatMatter #GTMStrategy #OpsLeadership #ExecutiveReporting

𝗦𝗽𝗲𝗻𝘁 𝟲 𝗺𝗼𝗻𝘁𝗵𝘀 𝗳𝗶𝘅𝗶𝗻𝗴 𝗮 𝗰𝗹𝗶𝗲𝗻𝘁'𝘀 𝘀𝘂𝗰𝗰𝗲𝘀𝘀𝗳𝘂𝗹 𝗚𝗧𝗠 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆. 𝗥𝗲𝘃𝗲𝗻𝘂𝗲 𝗷𝘂𝗺𝗽𝗲𝗱 𝟴𝟬%. The manufacturing client came to me celebrating: → 15,000 monthly website visitors → 300 leads per month → "Best year ever" according to their team But revenue was stuck at 35 Cr. annually. 𝗧𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺? 𝗧𝗵𝗲𝗶𝗿 𝗚𝗧𝗠 𝘄𝗮𝘀 𝗼𝗽𝘁𝗶𝗺𝗶𝘀𝗲𝗱 𝗳𝗼𝗿 𝘃𝗮𝗻𝗶𝘁𝘆 𝗺𝗲𝘁𝗿𝗶𝗰𝘀, 𝗻𝗼𝘁 𝗿𝗲𝘃𝗲𝗻𝘂𝗲. Here's what was actually happening: - Traffic looked great - but 89% was from job seekers, not buyers - Leads were high, but only 3% had buying authority - Sales calls were busy, but the average deal size was declining 12% yearly - Marketing was "working" - but CAC had doubled in 18 months 𝗧𝗵𝗲 𝗵𝗶𝗱𝗱𝗲𝗻 𝗿𝗲𝘃𝗲𝗻𝘂𝗲 𝗸𝗶𝗹𝗹𝗲𝗿: They were targeting procurement managers instead of plant managers. Wrong persona entirely. 𝗧𝗵𝗲 𝗳𝗶𝘅 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸: 1. Revenue Reality Check Mapped every lead to actual revenue impact Found their "best" channel had 0.8% conversion to revenue Discovered their "worst" channel had 18% conversion rate 2. Persona Audit Interviewed 47 existing customers about their buying process Found 91% of decisions started with plant managers, not procurement Completely shifted targeting and messaging 3. Funnel Surgery Removed 12 lead generation tactics that brought volume but no value Invested heavily in the 3 channels that brought qualified prospects Changed from quantity-focused to quality-focused measurement 𝗥𝗲𝘀𝘂𝗹𝘁𝘀 𝗮𝗳𝘁𝗲𝗿 𝟲 𝗺𝗼𝗻𝘁𝗵𝘀: - Monthly visitors dropped to 8,200 (but the right audience) - Leads dropped to 89 per month (but 67% qualified) - Average deal size increased 190% - Sales cycle shortened from 8 months to 4.5 months - Revenue jumped from 35 Cr to a very good annual amount 𝗬𝗼𝘂𝗿 𝗱𝗶𝗮𝗴𝗻𝗼𝘀𝗶𝘀: Look at your "successful" metrics. Are they driving revenue or just making reports look good? Most GTM strategies optimise for applause, not cash flow. What metric are you tracking that might be misleading your revenue growth? #GTMStrategy #RevenueGrowth #B2BMarketing #SalesAlignment #CustomerTargeting #MarketingROI #GTM_Gyan

One of the most common mistakes that companies make is to focus too narrowly on a small set of metrics while overlooking the broader ecosystem of inputs that drive results. At Amazon, we rejected the conventional wisdom that Executives should focus on just a few high-level metrics. Instead, we spent years developing mechanisms to measure, analyze, and improve thousands of input metrics (actions) based on the impact they have on output metrics (business results). The key lessons from this approach are: 1. Do not limit the number of metrics you monitor – Track a broad set of metrics, add, delete, and edit them over time based on observed results. 2. Review both controllable inputs (leading indicators) and output metrics (results) – They must be reviewed in tandem to understand cause-and-effect relationships. 3. Regularly review, analyze, and adjust metrics – The metrics that Amazon tracks are continuously improved to more accurately represent the speed, quality, and cost of every customer-facing process. 4. Implement new product and process improvements designed to deliver improvements for your input metrics. If you have selected the right inputs, then improvements to your outputs will follow. 5. Control your processes by continuously reviewing all relevant input metrics to ensure they stay within desired tolerances as internal and external factors change over time. Following these steps uses the Six Sigma technique known as DMAIC - Define, Measure, Analyze, Improve, and Control. The typical approach is to focus deeply on metrics like sales and gross margin while spending little or no time measuring or managing elements of the customer experience. At Amazon, this focus is reversed.