"Just curious, how's your forecast looking?" My CEO friend asked me. The weekly forecast review. The monthly pipeline call. The quarterly business review. All centered around one flawed model: Asking reps to predict the future based on gut feeling. "50% chance of closing." "Strong verbal commitment." "Just waiting on final approval." These phrases hide a painful truth: We have no idea what's actually happening inside our deals. I changed how we forecast last quarter: Instead of: "How do you FEEL about this deal?" We now ask: "What have they actually DONE?" - Has the economic buyer viewed pricing? - Have technical stakeholders reviewed security docs? - Have end users looked at implementation plans? - Is the champion actively sharing content internally? Behavior doesn't lie. Words do. We tracked content engagement across 200+ deals: Closed deals: Prospects engaged 7+ times in final two weeks Lost deals: Engagement dropped to 0-1 interactions before going dark The deals your team is most confident about? Often the ones with the least actual buyer engagement. Here's how we transformed our approach: Every opportunity now has a digital space where we can see: - Exactly who is engaging with what content - Which stakeholders are involved (even ones we haven't met) - Where deals are getting stuck - When interest spikes or drops Our forecast accuracy improved INSANELY. Stop asking reps what they "think" will happen. Start measuring what buyers are actually doing. The best indication of deal health isn't what prospects tell you. It's how they behave when you're not watching. Do you know what your buyers are really doing? Or are you still forecasting based on feelings? Agree?
Sales Forecasting Techniques That Actually Work
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Summary
Sales forecasting techniques that actually work focus on tracking buyer behavior and measurable signals rather than relying on subjective opinions or outdated pipeline stages. These methods improve accuracy and provide a clearer picture of deal progress.
- Focus on buyer actions: Track specific behaviors such as stakeholder engagement, document reviews, and communication patterns to assess deal health instead of relying solely on CRM stage probabilities.
- Incorporate time-based metrics: Use data like conversion velocity and days to close to predict when deals are likely to finalize, ensuring forecasts align with historical trends.
- Adjust pipeline models: Build forecasting models that account for real conversion rates, behavioral signals, and decaying deal viability to avoid overestimating revenue potential.
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Forecasting off pipeline stages is like using self-tanner before a beach trip. It gives you false confidence, washes off fast, and fools absolutely no one who gets too close. “30 opps in stage 3 × 40% = $1.2M forecasted.” Bueno. Now subtract the 9 deals that haven’t moved in 30+ days. Then subtract the 5 with no economic buyer involved. And the 8 that don’t have next steps or a MAP. Still $1.2M? lol nah...didn't think so. Stage-based forecasting is pretty broken, mainly because pipeline stages are opinions. Velocity and conversion, on the other hand, are facts. Buyers don’t care what CRM column they’re sitting in. They care about friction, fit, and fear. And your forecast should reflect all three. Here’s how to fix it: 1. Pair conversion rate with conversion velocity. - Let’s say Stage 3 deals have a 30% win rate. - But they take 52 days to close on average. - If it’s day 50 of the quarter, and that deal just hit Stage 3? It’s not real revenue. It’s next quarter’s homework. One RevOps team I know added “days to close by stage” into their forecast model. They realized 63% of late-stage pipeline wouldn’t close in time based on historical cycle length. The result? They re-weighted forecastable revenue by stage age × velocity. Forecast accuracy jumped 21% in two quarters. 2. Use behavioral signals, not just stage tags Stop assuming every Stage 4 opp has a 60% chance of closing. Start tagging based on buyer actions - not rep motion. What to track: - Was an economic buyer involved in the last call? - Did the buyer ask about implementation timeline? - Has procurement been looped in? - Are multiple stakeholders engaged and documented? Deals with 3+ of these signals close 2 - 3x more often. AND they close faster. Build a behavioral scoring model and overlay it on top of your CRM stages. 3. Build pipeline coverage by real math Forget the “3x coverage” rule of thumb. If your conversion rate from Stage 2 to Close is 18%, and your quarterly target is $1M, you don’t need $3M in pipeline. You need $5.56M in qualified opps. Idea: A CRO we work with built a stage by stage conversion model with time-based decay curves. They found that 22% of their pipeline had aged out of viable range, and 19% of Stage 1 deals had <5% chance of conversion. So they cut their pipeline headline by 41% - and finally forecasted accurately for the first time in six quarters. tl;dr = Forecasting isn’t about hope. It’s judgment × math × motion. If you’re still forecasting based on pipeline stage alone, you don’t have a sales process. You have a spreadsheet-shaped fantasy. And fantasy doesn’t hit number.
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Your CRM thinks that deal is closing. Your buyer isn't even thinking about you. Monday morning pipeline review. Your rep says "500K deal, proposal stage, 80% probability." Three weeks later? Radio silence. Deal hasn't moved. Buyer isn't responding. Now you're scrambling to replace that revenue. I don’t know if you didn’t know but… Your CRM stages measure what YOU'RE doing, not what the BUYER is thinking. That's exactly why your forecast accuracy is like flipping a coin. As a former #1 sales director who managed 110 reps, delivered $190 million annually in new business. I've seen this problem destroy quarterly forecasts, kill sales momentum, and get really good sales leaders completely fired. But I've also seen the fix. When organizations implement the ADVANCED method, their forecast accuracy jumps from 60% to 95% plus within the first quarter. ADVANCED tracks buyer progression, not seller activity: A - Acknowledged Problem (10%) Documented acknowledgment of a specific costly problem. "This security breach cost us $2 million and we need to prevent it." D - Documented Issue (15%) Written evidence. Email, internal memo, project brief. Something tangible that says this problem is real and needs solving. V - Validated by Team (25%) Multiple stakeholders agree this problem impacts executive-level metrics. Not one person complaining. A - Authorized by Executive (40%) An executive officially sponsors solving this problem. They've mandated their team to evaluate solutions. N - Narrowed to External (60%) They've decided they can't solve this internally. They're committed to buying from an external vendor. C - Chosen as Vendor (75%) You're the preferred vendor. They've stopped talking to competitors. The scope reflects all stakeholder input. E - Established Timeline (85%) Implementation timelines based on business outcomes. Not arbitrary dates. Timeline driven by business need, not sales pressure. D - Deal Terms Finalized (95%) Commercial terms agreed. Pricing approved. Contract in legal review. All decision makers confirmed. I was working with a $50 million e-health company. They had $30 million in pipeline in "proposal stage." When we applied ADVANCED? A very small percentage was actually at closing stage. Most hadn't gotten execs involved. Most didn't have multiple stakeholders. Most didn't have documented issues. They were sending proposals thinking deals would close. But they were creating false forecasts and fooling themselves. Your pipeline is either built on buyer reality or seller fantasy. There's no middle ground. — Sales Leaders, think you’re leaking revenue somewhere? You might want to check this out: https://lnkd.in/g8M-ah5s