Data Analytics In Sales

Last week, I heard from a super impressive customer who has cracked the code on how to give salespeople something they’ve always wanted: more selling time. Here’s how he transformed their process. This customer runs the full B2B sales motion at an awesome printing business based in the U.S. For years, his team divided their time across six key areas: 1. Task prioritization 2. Meeting prep 3. Customer responses 4. Prospecting 5. Closing deals 6. Sales strategy Like every sales leader I know, he wants his team to spend most of their time on #5 and #6 — closing deals and sales strategy. But together, those only made up about 30% of their week. (Hearing this gave me flashbacks to my time in sales…and all that admin tasks 😱) Now, his team uses AI across the sales process to compress the amount of time spent on #1-4: 1. Task prioritization → AI scores leads and organizes daily tasks 2. Meeting prep → AI surfaces insights from calls and contact records before meetings 3. Customer responses → Breeze Customer Agent instantly answers customer questions 4. Prospecting → Breeze Prospecting Agent automatically researches accounts and books meetings The result? Higher quantity of AI-powered work: More prospecting. More pipeline.  Higher quality of human-led work: More thoughtful conversations. Sharper strategy. This COO's story made my week. It's a reminder of just how big a shift we're going through – and why it’s such an exciting time to be in go-to-market right now.

Sales Navigator should be your highest ROI sales tool. Instead, it's a $40K+ expense that might have you scratching your head. The default workflow? Find prospects in Sales Nav. Then send the same message to everyone. That’s the real issue. And if you’ve got 99 problems, this breakdown makes sure LinkedIn outreach ain’t one. Because each filter deserves its own message. Take this one: “𝗬𝗲𝗮𝗿𝘀 𝗶𝗻 𝗖𝗼𝗺𝗽𝗮𝗻𝘆: < 𝟭 𝗬𝗲𝗮𝗿”. Perfect for calling out transition pain. “Was talking to a VP of Sales who's 7 months in. They said [insert challenge]. Are you seeing that too?” That's just one of twelve. Now, imagine your team building 𝟭𝟮 𝗰𝘂𝘀𝘁𝗼𝗺 𝗺𝗲𝘀𝘀𝗮𝗴𝗲𝘀 tied to filters. Instead of recycling the same script 4,000 times. Let's run the numbers for a team of 10 reps sending 20 messages daily (4,000 monthly) at a $20k ACV: Old Way (Generic Messaging) • 4,000 messages/month • 1% response rate = 40 responses • Assume 25% of responses convert to meetings = 10 meetings • 10 meetings × $20K = $200K pipeline New Way (Filter-Specific Messaging) • 4,000 messages/month • 5% response rate = 200 responses • Assume 25% of responses convert = 50 meetings • 50 meetings × $20K = $1M pipeline That’s a 5X pipeline lift without adding anything crazy. Just better targeting, better messaging, and a system built for LinkedIn. This is why some leaders think LinkedIn "doesn't work" while others are winning big with it. Sales Nav isn’t the issue. Lack of systems is. It’s simple to roll out, even if your team’s never done this before. If you manage 15+ reps and want to swap notes on what I'm seeing for LinkedIn outbound, just shoot me a DM.

Every team talks about intent, triggers & signals Very few know how to act on it.   The truth? 👉 Most "intent signals" are just passive data exhaust. 👉 And most GTM teams aren't wired to act on them fast enough to matter.   Intent without infrastructure = no replies. Cold Email without the right timing = ignored. LinkedIn engagement that no one follows up on = wasted.   So here’s what we do instead 👇   We treat intent like infrastructure ☑ If someone hits a pricing page → RB2B flags it → Clay auto-enrichs → lemlist sends an email ☑ If someone engages with a competitor → Apify triggers an “alt vendor” play ☑ If a company raises $10M → Clay surfaces the jobs they're hiring for → If they hire for GTM roles, then lemlist sends an email   Intent is only useful when your system knows: 1. What happened 2. Who to send it to 3. What to say 4. When to say it 5. And how to follow up   Most teams never get past #1. Intent isn’t insight. Intent is activation.   If your GTM isn’t built to react in <24 hours, you don’t need more signals. You need better wiring.   Want to build the system? Let’s talk.   #coldemail #gtm #intentdata #salescaptain #clay #signals

Last week, the CRO of a $36M ARR SaaS turned to us. They missed their Q4 forecast by 28%. The board wasn't happy. Here's the playbook we used to fix it. 𝗖𝗢𝗡𝗧𝗘𝗫𝗧 I talk to dozens of sales leaders every month. This CRO is not an exception: • Inaccurate forecasts due to poor visibility • Poor visibility due to missing CRM data • No clear process & accountability 𝗛𝗲𝗿𝗲'𝘀 𝗮 𝗽𝗿𝗼𝘃𝗲𝗻 𝗽𝗹𝗮𝘆𝗯𝗼𝗼𝗸 𝘁𝗵𝗮𝘁 𝗵𝗲𝗹𝗽𝗲𝗱 𝟭𝟬𝟬+ 𝗕𝟮𝗕 𝗦𝗮𝗮𝗦 𝗖𝗥𝗢𝘀 & 𝗥𝗲𝘃𝗢𝗽𝘀 𝘁𝗲𝗮𝗺𝘀 𝗳𝗼𝗿𝗲𝗰𝗮𝘀𝘁 𝗮𝗰𝗰𝘂𝗿𝗮𝘁𝗲𝗹𝘆: ✅ 𝗙𝗶𝘅 𝟭: 𝗦𝗮𝗹𝗲𝘀𝗳𝗼𝗿𝗰𝗲 𝗗𝗮𝘁𝗮 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 The cornerstone of effective deal reviews and visibility into pipeline & forecast health. 1️⃣ Activity data: WHY IT MATTERS: • Emails/meetings not logged = unclear deal velocity • No engagement = high risk of deal slippage • Use activity data, not gut feel E.g. • Last activity date • Next meeting date • Email reply rate  .. SITUATION: The CRO & RevOps team faced 3 issues: 1. Reps forgot to log activities 2. Auto-logging failed (poor opp & contact role mapping) 3. Most opps lacked contact intelligence (who’s involved, decision-maker, multi-threading) No activity/contact insights = no visibility. SOLUTION: Auto-capture emails & meetings with a solution that identifies contact roles. Ideally with an Outlook Add-In/Google Extension to improve opp mapping (e.g. Weflow does this). 2️⃣ Salesforce data entry: WHY IT MATTERS: • Often missing key fields (e.g. MEDDIC) • Bad CRM data = poor deal reviews & forecasts SITUATION: 76% of their MEDDIC fields were not populated. Reps hated updating Salesforce. = managers lacked deal visibility. SOLUTION: An AI notetaker that auto-extracts and updates MEDDIC fields in SFDC from call transcripts (e.g. Weflow). ✅ 𝗙𝗶𝘅 𝟮: 𝗙𝘂𝗹𝗹 𝗩𝗶𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗶𝗻𝘁𝗼 𝗗𝗲𝗮𝗹 & 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗛𝗲𝗮𝗹𝘁𝗵 WHY IT MATTERS: To improve deal reviews & forecasts, managers need leading indicators of deal health: • Push count • Configurable warnings • Multi-threading & velocity  .. A pipeline coverage dashboard (CQ, Q+1) creates extra visibility. SOLUTION: Embed insights in Salesforce or use revenue intelligence/forecasting tools (like Weflow). ✅ 𝗙𝗶𝘅 𝟯: 𝗖𝗼𝗺𝗯𝗶𝗻𝗲 𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁 𝗠𝗲𝘁𝗵𝗼𝗱𝗼𝗹𝗼𝗴𝗶𝗲𝘀 & 𝗠𝗼𝗱𝗲𝗹𝘀 SITUATION: They ... 1. Only forecasted new logos (ignoring expansions/renewals) 2. Used weighted forecasts + spreadsheets (highly inaccurate) SOLUTION: • Opp record types for expansion/renewals • Auto-create renewal opps upon closed-won • Combine models: 1. Deal-by-deal submission & review (+ auto roll-up) 2. Dynamic weighted 3. ML-based (They now run this in Weflow) 💭 𝗖𝗹𝗼𝘀𝗶𝗻𝗴 𝗡𝗼𝘁𝗲 I didn't touch upon revenue cadence/process due to character limits (but we helped fix this too). WHAT WOULD YOU ADD? 👇 ____ PS: We built Weflow to help B2B SaaS revenue teams forecast accurately. Take a product tour (on desktop): https://lnkd.in/eXHt-i6q

I increased my open rates by 17% with these 5 subject line tests: Your subject line is the first impression your email makes. It determines whether your audience opens the email or skips it entirely. Here are 5 subject line tests I ran that actually moved the needle (and why they work): 1. Add Personalization: Instead of: “Improve Your Email Marketing Results” I tested: “Chase, These Email Tips Could Boost Your Revenue” Why this works: Seeing their name feels personal and grabs attention in a crowded inbox. Personalization also shows you’ve tailored the content specifically for them. --- 2. Tap Into Curiosity: Instead of: “Email Marketing Strategies for Your Business” I tested: “You’re Leaving Money on the Table with Email” Why this works: Curiosity compels people to open. But the key is delivering on the promise—your content has to match the intrigue, or you’ll lose trust. --- 3. Create Urgency: Instead of: “How to Improve Your Email Campaigns” I tested: “Last Chance to Fix This Email Mistake” Why this works: FOMO (fear of missing out) gets people to take immediate action, especially when there’s a sense of a ticking clock. --- 4. Go Shorter: Instead of: “Here’s Everything You Need to Know About Email Marketing” I tested: “Better Emails, Today” Why this works: Short, punchy subject lines cut through the noise, especially on mobile where 50%+ of emails are opened. --- 5. Use Numbers or Specificity: Instead of: “Email Tips for Business Owners” I tested: “3 Subject Lines That Boosted Open Rates by 17%” Why this works: Numbers and specificity make your email feel actionable and credible. People know exactly what they’re getting. --- The Big Lesson: Your subject line is your email’s best salesperson. Start testing small variations today—personalization, curiosity, urgency, or brevity. Even a 1% improvement across a large list can make a massive impact. What’s the best subject line you’ve tested?

We collect more data than ever before. But in construction, we hardly touch it: Programme data, cost codes, production logs, fuel burn, cycle times, weather sensors, surveys, trackers. Even WhatsApp thread records. The digital age has given us more information than we know what to do with. The Dutch have a phrase: "Meten is weten" - to measure is to know. Yet in civil and marine construction, we often build first and understand later. Recently I was involved in a post-project review for a major marine project. With basic cost analysis, the pattern became crystal clear: Preliminaries were consistently underpriced across every tender. Site setup, security, permits, design support, contract management, head office overhead - they always needed more time and people than budgeted. But the truth is price prelims honestly based on actual data and you might not win the work. That's where data analysis becomes strategic - not just for pricing smarter, but for building smarter. Because data doesn't just show you where you're bleeding money and time. It shows you where you're strongest. That site team who finishes quay walls early every time? That dredger who hits top production curves despite weather delays? Double down on what works. The most commonly quoted phrase applies here: "Insanity is doing the same thing over and over expecting different results." Einstein probably never said it, but it rings true. Most contractors I know have the data sitting in spreadsheets, databases, and project files.  They just don't analyse it systematically. They repeat the same estimating mistakes. Ignore the same warning patterns. Miss the same optimisation opportunities. In a world full of assumptions and inherited practices, data is your sharpest tool. But only if you actually pick it up and use it.

JP Morgan just raised the risk of a global recession to 60% and everything feels a bit like a 🎪. Why is this relevant for product & growth? This isn’t just a headline - it’s a signal to rethink how we plan, prioritize, and position ourselves in the market. "Just solve customer problems." 🤡 Not quite Larry and Gary: It’s a good idea to make sure that you are becoming essential for a budget, and not a nice-to-have feature yourself. Here’s the reality: Recessions change customer behavior. Budgets tighten, decision-making slows, and the bar for ROI gets higher. For B2B SaaS companies, this means new customer acquisition slows down while cancellations increase, putting pressure on retention and lifetime value. So what should we do? Here are five actionable steps: 1️⃣ Focus on Retention: Build early churn signals into your customer success metrics. Retention is king during economic uncertainty. 2️⃣ Re-examine Your Value Proposition: Position your product as essential, not a luxury. Show clear ROI fast—this is what CFOs care about right now. 3️⃣ Adapt Pricing Strategy: Consider flexible contract terms or usage-based pricing that scales with your customers’ needs. Help them avoid cost-cutting decisions that impact you. 4️⃣ Prioritize Features That Deliver Immediate Value: Cut nice-to-have features from your roadmap and double down on solving urgent customer problems. 5️⃣ Help Sales & Marketing Articulate Economic Impact: Collaborate with your GTM teams to create ROI calculators and case studies that demonstrate cost savings or efficiency gains. As product leaders, our job is no longer just about chasing customer needs -it’s about assessing those needs against costs, risks, and the broader economic environment. If you’re not factoring in the macroeconomic landscape into your strategy, you’re missing critical data points that could turn things sour fast. The next couple of years will favor those who understand churn, retention, pricing dynamics, and ROI delivery over those who simply ship fast or check off Jira tickets. How are you adjusting your strategy to navigate this economic uncertainty? What questions do you have about recession-proofing your product or team? Shift your "greed roadmap" to a "fear roadmap". Full article explaining more why this is the case in the comments. P.S. I’m recording an episode with CFO CJ Gustafson soon to dive deeper into topics like R&D budgeting, AI’s impact on planning, and risk profiles for VCs/PE funds. Drop your questions for CJ below or in the article!

Just published my new piece in Forbes Technology Council: why predictive AI is becoming the dealership's secret weapon. And even if you are not in the automotive industry - there's a lot to learn here. Less than 5% of dealerships actually use their data to predict customer behavior. They're sitting on goldmines of sales records, service histories, and financing data - yet still operating on gut feel. The auto industry faces unprecedented disruption. EVs are surging (42% growth in Q1 2025). One in four buyers completes purchases entirely online. Supply chains remain volatile. In this environment, waiting for perfect data is a luxury dealers can't afford. We helped one of Israel's largest automotive groups rank past buyers by repurchase likelihood. By focusing on the top 5-10%, they achieved a 6x increase in conversion rates. And the model even revealed patterns their best reps hadn't noticed - like buyers over 50 being far more likely to return. The message is clear: dealerships that predict will pull ahead. Those that guess won't. Start small. Pick one underperforming decision. Test predictive insights against your current approach for 30 days. The results will surprise you. Read my full article: https://lnkd.in/dhRjhcpv 

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.

You want to deliver actionable insights? It all begins with thorough data validation. Follow these steps to avoid "garbage in, garbage out": 1. 𝗞𝗻��𝘄 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗦𝗼𝘂𝗿𝗰𝗲:    Understand how your data was gathered to assess its reliability. Ask yourself if you truly know where your data comes from.     2. 𝗖𝗵𝗲𝗰𝗸 𝗳𝗼𝗿 𝗖𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝗰𝘆:    Verify that data formats, labels, and measurement units are aligned. Look for inconsistencies, such as varying date formats.     3. 𝗘𝗻𝘀𝘂𝗿𝗲 𝗧𝗶𝗺𝗲𝗹𝗶𝗻𝗲𝘀𝘀 & 𝗥𝗲𝗹𝗲𝘃𝗮𝗻𝗰𝗲:    Confirm that your data is up-to-date and fits your analytical goals.     4. 𝗜𝗱𝗲𝗻𝘁𝗶𝗳𝘆 𝗮𝗻𝗱 𝗔𝗱𝗱𝗿𝗲𝘀𝘀 𝗗𝗮𝘁𝗮 𝗚𝗮𝗽𝘀:    Look for missing values that could skew your findings. Investigate why gaps exist and fix them through additional data collection or statistical methods.     5. 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗲 𝘄𝗶𝘁𝗵 𝗮 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗣𝗲𝗿𝘀𝗽𝗲𝗰𝘁𝗶𝘃𝗲:    Cross-check your data against business logic. Ensure that figures make sense in context, for example, by avoiding impossible values such as negative stock levels. Clarify any discrepancies with stakeholders. Your aim is to generate insights that can be trusted. What are your steps to ensure data quality? ---------------- ♻️ 𝗦𝗵𝗮𝗿𝗲 if you know the importance of data validation. ➕ 𝗙𝗼𝗹𝗹𝗼𝘄 for more daily insights on how to grow your career in the data field. #dataanalytics #datascience #datacleaning #datavalidation #careergrowth