Lead Scoring and Segmentation

𝗗𝗢𝗡'𝗧: Download/webinar sign-up → send leads to sales. 𝗗𝗢:       Match the next step/CTA with the buyer's intent level. Don't propose marriage on the first date. Instead, ask yourself:  What does the buyer actually want? 𝗛𝗜𝗚𝗛 𝗜𝗡𝗧𝗘𝗡𝗧 𝘈𝘤𝘵𝘪𝘰𝘯: Book a demo call 𝘐𝘯𝘵𝘦𝘯𝘵: Get a demo and evaluate the fit 𝘕𝘦𝘹𝘵 𝘴𝘵𝘦𝘱𝘴: Let ICP buyers book a call with AE directly. Actually provide the demo, pricing and discuss their use-case. 𝗟𝗢𝗪 𝗜𝗡𝗧𝗘𝗡𝗧 𝘈𝘤𝘵𝘪𝘰𝘯: A buyer downloads a piece of content, or registers for a webinar 𝘐𝘯𝘵𝘦𝘯𝘵:  To learn Possible next steps that match the intent: - Connect before the webinar to ask what they're hoping to learn - Follow up after the webinar asking their feedback, and offering more resources on the topic - Offer them newsletter sign-up upon content delivery - Progressive profiling (using marketing automation to collect more info about needs, goals, and priorities—and using these insights to provide more relevant content) 𝗠𝗘𝗗𝗜𝗨𝗠 𝗜𝗡𝗧𝗘𝗡𝗧 𝘈𝘤𝘵𝘪𝘰𝘯: Visit high-intent pages; several buyers spent 30+ min on website 𝘐𝘯𝘵𝘦𝘯𝘵:  Considering a vendor (but not yet ready to book a call) 𝘕𝘦𝘹𝘵 𝘴𝘵𝘦𝘱𝘴: provide a personalized buying experience for high-value accounts. Here is how: When an account is engaged, the next step is account qualification (if it's a right fit) and account segmentation (to what tier it belongs). We do tier segmentation to define what level of personalization to use. Tier 1 accounts (highest revenue potential): 1-1 highly personalized campaigns Tier 2 accounts: vertical-based and job-role based personalization. Tier 3 accounts: should be generated via demand generation programs. 𝐀𝐜𝐜𝐨𝐮𝐧𝐭 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 Collect all the publicly available insights about the strategic initiatives of the qualified accounts and map out the buying committee. Map your value proposition and content to the needs, JBTD and challenges you discover. 𝗔𝗰𝗰𝗼𝘂𝗻𝘁 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 Specific activities and channels to engage the target buyers (of a specific account), create awareness and distribute your personalized value proposition and content. These include: 1. Social engagement and social selling 2. Content collaboration 3. 1:1 content distribution 4. 1:Few content distribution using paid 5. 1:1 and 1:Few direct mail 6. Events (virtual events, local micro events, breakfast meetings, round tables, etc.) 7. Communities The key is to have clear agreements with sales on who does what. --- 70% of B2B buyers are frustrated with their buying experience. This is an opportunity: better buying experiences will help you stand out. So review all your CTA with sales, asking yourself: What is the actual intent of the buyer, and what is the best and fastest way to serve them at this step of their journey?

I've come to the conclusion that traditional ICP scoring is fundamentally flawed. After implementing AI-driven ICP analysis across multiple organizations, we've confirmed what many have suspected: traditional lead scoring fundamentally misidentifies opportunity. Prospects that conventional models would deprioritize are consistently becoming valuable customers. Traditional scoring relies on an overly simplistic framework: • Static firmographics, focusing too much on industries • Limited persona data • Internal stale customer data (often inaccessible) • Minimal external signals (depending on which tools you use) Let’s take FinTech as an example. Traditional models might label all financial technology companies the same, but AI can identify the ones that, for example, support open banking APIs. Traditional scoring would waste resources on "FinTech" prospects that will never convert due to technical incompatibilities, whereas AI-driven scoring would disqualify them immediately. Another example: A company might want to acquire customers in the beverage production industry, but only work with non-alcoholic beverage producers and health-focused food manufacturers. Traditional scoring treats "Food & Beverage" as one big category, overlooking these crucial distinctions. The AI scoring processes we’re building are evaluating hundreds of variables simultaneously, identifying complex patterns that predict actual buying behavior. They incorporate real-time external signals, granular sub-industry behaviors, and dynamic weighting that evolves with results. We're building these processes using a mix of Ai technologies like OpenAI, Anthropic and Clay.

Most of us think we have a clear ICP. But when you look at the pipeline? It’s a wild mix of company sizes, industries, and personas — all getting the same campaigns & pitch. 3. Some deals move fast. Others stall for months. 2. Some channels print money. Others burn cash. 1. Some personas love the product. Others ghost after a demo. This isn’t a sales problem. It’s a segmentation problem. If we don’t know who our best-fit customers are, we’re running blind. Here’s how I segment 👇 Side note: Get the spreadsheet template along with step-by-step guide from my newsletter. Click the link in my profile to get a copy. 📌 Step 1: Pull Closed-Won Deals Your best customers leave clues — follow them. - Pull closed-won deals from the last 6-12 months. - Grab key data: Job titles, company size, industry, ACV, deal cycle. - Clean up your CRM (because it’s always messy). Why? Real data > gut feelings. Sell to who’s already buying. 🔍 Step 2: Enrich Your Data CRM data alone won’t cut it. Use Clay to enrich contacts (seniority, decision-making power). Pro Tip: Integrate Keyplay to your CRM have accurate industry tags added to your account. Add growth signals (hiring, funding, ad spend). Think of it as turning an old map into GPS with live traffic. 📊 Step 3: Find Your Winning Segments Look for patterns in your best deals: - Which industries & company sizes close the fastest? - What roles drive decisions? - Which channels bring in high-ACV deals? Example: Demos from Marketing VPs at Mid-market Dental SaaS = High ACV & 2x faster close rate. When they come from Paid Channel, the sales cycles are longer compared to when they come organically. Once you see the patterns, targeting becomes easy. ❌ Step 4: Learn from Closed-Lost Deals Your losses reveal what’s broken. - Pull & enrich closed-lost deals. - Identify why deals fell through — wrong fit? Wrong persona? Budget? - Which channels did these closed lost deals come from? - Compare all of these with your closed won patterns. Red flags to watch: - High demo volume, low conversion → Fix qualification/messaging. - Some industries never close → Stop targeting them. - Prospects ghost post-demo → Value prop isn’t landing. 📈 Step 5: Prioritize, Cut, Scale Put your segments into a 2x2 matrix: - High demo volume, high conversion → Scale this segment fast. - High demo volume, low conversion → Fix qualification/messaging. - Low demo volume, high conversion → See if it makes sense to prioritize based on if you have enough time, money, and people. - Low demo volume, low conversion → Stop wasting effort. Why? More focus = more predictable pipeline 🚀 👆Link to the template along with the full guide in my latest newsletter. Grab it by clicking on the link in my profile.

The Power of Lead Scoring: A Case Study One year ago, I worked with a tech startup with a big problem at hand... They reached out to me because their lead conversion was extremely low. Here's their story: This client faced a common struggle: Turning leads into customers. Despite their efforts, they couldn't crack the code. And there was one main reason for this—they had ZERO lead scoring in place. Now, I know what you might be saying “Jordan, what’s lead scoring?” Okay, so here's the deal with lead scoring: It's like having your own personal radar system for your sales and marketing efforts. You're basically assigning points to leads based on how interested they are in what you’re offering and how qualified they are—by a strict set of standards you create. So, instead of wasting time chasing after every lead out there, you can focus on the ones that are most likely to buy. It's all about working smarter, not harder. That's how you close more deals with less effort. Now, here’s the 5 part lead scoring system we put in place for this tech startup: Demographics: We looked at the industry, company size, job title(s), and location of their prospects. Behavioral Data: We monitored website visits, content downloads, and social media engagement. Engagement Level: The frequency that leads interacted with their content. By looking at this we were able to identify the most engaged prospects. Purchase Intent: Signals like demo requests or inquiries about pricing helped us to prioritize leads that were ready to make a decision. Lead Source: Understanding where leads came from provided insights into their level of interest and intent. Together, we introduced a cohesive lead scoring system—a smart move that changed the game for this startup. By implementing these five key criteria, they could finally stop wasting time and pinpoint which leads were worth pursuing. With this system in place, they saw incredible results. Leads weren’t just numbers anymore—they were real people with real needs. By focusing on the most promising leads, our client saw their conversion rates soar. In the end, it all came down to simplicity. By streamlining their approach and zeroing in on what mattered most, they saw record high sales numbers that year. P.s. - Does your company use lead scoring? If so, what’s the biggest challenge you’re facing right now? Thanks for reading. Enjoyed this post? Follow Jordan Nelson Share with your network to help others increase their sales with lead scoring.

You don’t need more leads. You need better segmentation. I’ve lost count of how many marketing and business leaders tell me they have a pipeline problem only to find out they actually have a positioning or segmentation problem. More leads ≠ more revenue if your ICP is off, your messaging is generic, or your sales team doesn’t believe in the leads you’re generating. Better segmentation = • Higher win rates • Lower CAC • Better customer success handoffs • Less marketing/sales drama You also get great customer satisfaction abd and an opportunity to build a stronger business too. What to do now? Identify your ICP, their attributes, behaviour, needs and values first - this is so important to your strategy. The answers we need are usually all hiding in your data, your teams heads and your customer interviews yet so many overlook this step. Before you pour more budget into paid, ask: Who exactly are we trying to reach and why with what, how and when? … and are they still the right fit for our growth stage? Then align your internal teams and goals to focus on the best fit customer and segment for your stage. Happy hunting and stay focused! #b2bmarketing #icp #revenuemarketing

AI-Powered lead scoring is one area of sales where AI gets put to ACTUAL good use. And it works like a charm. 𝟭 - 𝗜𝘁 𝗲𝗹𝗶𝗺𝗶𝗻𝗮𝘁𝗲𝘀 𝘁𝗵𝗲 𝗴𝘂𝗲𝘀𝘀𝘄𝗼𝗿𝗸 Relying on manual action from creative revenue people is a losing game. The dream was always AI algorithms processing vast amounts of data to determine what actually matters, and now it's here. Knowing > Guessing 𝟮 - 𝗜𝘁 𝘁𝘂𝗿𝗻𝘀 𝗱𝗮𝘁𝗮 𝗶𝗻𝘁𝗼 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 If you want to keep a sane mind, you can’t track every single source. • Salesforce CRM data • HubSpot marketing campaign results • Sales engagement platform interactions • Email opens and clicks • Website visits AI collects, processes, and finds the right patterns. 𝟯 - 𝗜𝘁 𝗰𝗼𝗻𝘀𝗶𝗱𝗲𝗿𝘀 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 𝗶𝗻 𝗰𝗼𝗻𝘁𝗲𝘅𝘁 This isn't about looking at variables in isolation. AI considers: • Temporal data (when did they interact?) • Categorical data (what industry are they in?) • Numerical data (how many Twitter followers do they have?) • Behavioural data (did they just visit the pricing page?) It's all interconnected, and AI sees the full picture. 𝟰 - 𝗜𝘁 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘀 𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗯𝗹𝗲 𝗿𝗲𝘀𝘂𝗹𝘁𝘀 Here’s what we found when we implemented this: • Only 4% of leads scored above 85 • These high-scoring leads had a 40% historic close rate Immediately we have a data-backed, new north star ICP to focus our sales team on. Sales teams don’t need more leads, they need fewer leads that convert, and they need priority updates in real time. 𝟱 - 𝗜𝘁 𝗱𝗲𝗺𝘆𝘀𝘁𝗶𝗳𝗶𝗲𝘀 𝘁𝗵𝗲 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 It shows you: • Which features have the highest impact on the score • How different variables are weighted • Why a lead received its specific score The hardest part of any sales team's pivot is buy-in. Now you have the data to back your claims, and your team is excited to make the switch. so. The question isn't whether AI-powered lead scoring is better. The question is: How much revenue are you leaving on the table by not using it? What's your current approach to lead scoring?

Stop treating all leads the same. Your lead engagement strategy needs to match lead temperature (hot, cold, & warm). 1️⃣ Hot Leads Maximize human interaction Deploy surround-sound approach Combine email, LinkedIn, and call touches Consider personalized gifts Focus on immediate engagement 2️⃣ Warm Leads (The Tricky Middle) Use intent data to gauge readiness Flex between marketing and sales touches Adjust based on buying signals 3️⃣ Cold Leads Keep it light and informational Share valuable content (surveys, research) Focus on education via blog posts Stay on their radar without being pushy Key Consideration: Match your approach to your GTM motion. A 10-customer annual target needs different handling than a 10,000-customer goal. Remember: Every spam campaign today = burned opportunities tomorrow. Reply with 🎯 if you'd like to discuss smart lead segmentation strategies #B2BSales #LeadNurturing #SalesStrategy #Marketing

According to HubSpot, 79% of top-performing sales teams attribute their success to uncovering hidden opportunities in their pipeline. You might be missing out: - 77% increase in conversions - 40% faster sales cycles If your sales process feels stuck, the issue may not be your pitch or product—it could be how you’re scoring your leads. Here’s the reality: Without a system to prioritize high-potential prospects, you’re wasting time on the wrong ones. Why Lead Scoring Matters 1. Higher Conversion Rates: According to the Harvard Business Review, companies using lead scoring achieve 77% higher conversions. 2. Increased Revenue: Aberdeen Group reports organizations with lead scoring see 18% more revenue growth. What is Account Scoring? It’s a data-driven method to: - Identify leads ready to convert. - Rank accounts based on conversion likelihood. - Focus on the prospects that matter most. 5 Steps to Implement Account Scoring 1. Define Key Characteristics:  • Think business size, industry, revenue, or engagement level. 2. Assign Values: • Score each attribute based on its likelihood to convert. 3. Rank Accounts: • Prioritize the highest scorers for immediate follow-up. 4. Regularly Update Scores: • Keep refining your data to stay ahead. 5. Automate the Process: • Use tools to flag high-priority accounts in real time. What’s the ROI? 💡 Companies using account scoring have achieved: 77% increase in conversions 40% faster sales cycles (Source: Harvard Business Review) Stop guessing and start targeting with precision. Account scoring isn’t just a sales tactic, it’s a game-changer. Focus on the right leads, close deals faster, and grow your pipeline with confidence. PS: Need help setting up account scoring? Let’s connect—I’d be happy to discuss how to make your sales process more efficient. #SalesOptimization #AccountScoring #PipelineManagement #B2BSales