Account Segmentation Approaches

Industry-based ABM v.s. Use Case-Based ABM. If your product has multiple use cases, stop targeting industry verticals, and start targeting clusters. VERTICAL-BASED ABM Most ABM programs create vertical-based list, messaging and content. But if those accounts have different use-cases and challenges, you risk ending with content and messaging that's either:  - Irrelevant to the majority of accounts you target - Generic, “common denominator” messaging that doesn’t differentiate you and doesn’t address the highest priority need CLUSTER-BASED ABM Cluster: group of companies with a similar challenge/use-case, despite their tier or vertical. With cluster targeting you can: - Cut through the generic noise with messaging, content and case studies that address the highest priority need that's top of their mind - Differentiate in a way that matters to them (by showing how you're supporting that use-case better than competitors) - Focus on accounts with a high probability to become a sales opportunity instead of just chasing vertical Tier 1 accounts EXAMPLE As an ABM lead for Hubspot, I might create an ABM program for B2B SaaS companies. After all, they all need sales and marketing tools. It’s also helpful to have industry related assets, case studies and messaging. But different SaaS companies have different buying triggers: - Switching from a legacy system, because they lack functionality and integrations - Companies that want to start ABM but their CRM/marketing platform don’t support it - Startups that outgrew their separate siloed tools You can already see how each of these use-cases deserves completely different messaging. --- Once you've defined the clusters, the next step is mapping accounts to them. Here is how. 1. Export all your won deals and segment them by use-case 2. Group all accounts by use-case and compare revenue metrics - Revenue - Average deal size  - Sales cycle length - Lifetime value  - # of successful case studies You'll be able to make an unbiased decision which clusters have a higher priority. 3. Select a top cluster aligned with your goals and run deal analysis  - Top 5 clients by LTV/ACV - Top 5 fastest deals - Recent 5 lost deals 4. Extract patterns - Firmographics - Technographics - Buying committee structure - Won and lost reasons - Signals and account insights that signal the specific use-case 5. Develop a cluster ICP with qualification & disqualification criteria --- Now you can build a highly targeted list of accounts that are more likely to convert into pipeline and be a good fit, and align your program with their high priority needs. We recently published results and a breakdown of four programs where a switch to cluster-based ABM generated $7 million in pipeline:  https://lnkd.in/dZWKNAbC

Hot take: If you're still segmenting customers solely by ARR and company size, you're leaving money on the table. After a painful realization, we completely overhauled our segmentation model: Our highest-paying enterprise customers weren't necessarily the most profitable or successful. Traditional segmentation missed these critical factors: Product usage patterns Growth potential (not just current spend) Support cost-to-revenue ratio Implementation complexity Use case maturity The result? We were over-serving some accounts and under-serving others based on flawed assumptions. Our new dynamic segmentation model includes: User adoption velocity Feature utilization depth Growth readiness score Technical maturity index Success potential metric The impact? 47% reduction in time-to-value 32% increase in expansion revenue More precise resource allocation Happier customers (and CS team!) A startup paying you $30K might have better product-market fit and growth potential than an enterprise paying $200K but struggling with adoption. Modern customer segmentation should be fluid, multi-dimensional, and focused on success potential, not just current value. What factors do you consider in your segmentation model? #CustomerSuccess #SaaS #GrowthStrategy #CustomerExperience

Teams who take a “boil the ocean” approach to outbound will fail. Here’s how to fix it and build sequences that actually drive results: Step 1: Focus your team on accounts most likely to buy now, invest at a premium, and become long-term customers or referral sources. This means moving beyond “anyone who fits the ICP” and zeroing in on high-priority targets. Step 2: Create deeper, more meaningful segments from that refined group. Traditional segments are great for organizing territories but fall short for crafting sequences that resonate. Instead, you need segmentation that helps your team speak the language of specific sub-groups. Use multiple layers of data—firmographics, intent signals, and contact-level insights—to break your TAM into smaller, actionable groups. Step 3: Launch micro-campaigns that target those precise segments with messaging designed to feel tailor-made. When you take this approach, personalization becomes scalable because it’s rooted in segmentation. Your reps don’t waste time on one-off customization, and your messaging feels 99% relevant to the prospect. I've been teaching this process as #ValueBasedSegmentation for the better part of a decade. It’s the key to building sequences that drive higher CTRs, replies, and engagement without tedious manual effort. ➡️ With this approach, you’ll: - Improve email performance - Write copy that prospects actually care about - Give your team a clear roadmap for focused outbound 📌 How are you helping your team build relevance into their outbound sequences?

The hardest lesson in Customer Success? Not every account needs the same attention. I've seen too many CS teams burn out trying to give white-glove service to every single customer. Meanwhile, their highest-value accounts aren't getting the strategic partnership they need to expand. Here's the framework that works for me: 📍MAINTAIN (Low Risk, Low Value) Your efficiency plays. Automated onboarding, self-service resources, and health-check emails. Keep them healthy without burning CSM hours. 📍RETAIN (High Risk, Low Value) Your fire drills. Rapid risk diagnosis, short-term recovery plans, executive escalation. Get them stable or let them go gracefully. 📍EXPAND → 𝐇𝐢𝐠𝐡 𝐕𝐚𝐥𝐮𝐞, 𝐋𝐨𝐰 𝐑𝐢𝐬𝐤 Your growth engine. This is where the magic happens -QBRs, strategic roadmap discussions, champion programs, and co-marketing opportunities. → 𝐇𝐢𝐠𝐡 𝐕𝐚𝐥𝐮𝐞, 𝐇𝐢𝐠𝐡 𝐑𝐢𝐬𝐤 Your rescue missions have a massive upside. Jump in fast, diagnose issues, build recovery plans, then shift to expansion mode. 𝐌𝐚𝐭𝐜𝐡 𝐲𝐨𝐮𝐫 𝐂𝐒 𝐢𝐧𝐯𝐞𝐬𝐭𝐦𝐞𝐧𝐭 𝐭𝐨 𝐭𝐡𝐞 𝐚𝐜𝐜𝐨𝐮𝐧𝐭'𝐬 𝐯𝐚𝐥𝐮𝐞 𝐚𝐧𝐝 𝐫𝐢𝐬𝐤 𝐩𝐫𝐨𝐟𝐢𝐥𝐞. Your CS team shouldn't be stretched thin - they should be strategically deployed. What's your approach to CS segmentation? Drop a comment - I'd love to hear what's working (or not working) for your team

We run 5,000 Account-Based Advertising campaigns and deliver 1 billion ad impressions every month for our B2B customers. Here’s how we use Account-Based Advertising internally at Demandbase: BACKGROUND: As you can imagine, we are heavy users of Account-Based Advertising. We don't only sell it, we live it. Our goal is to focus on accounts with the greatest LTV. The primary levers we pull are segmentation, ad creative, and integration into our overall account-based GTM strategy: 1. Segmentation Segmentation is the foundation of our account-based advertising strategy. It enables the appropriate level of resources, the right message, and the right workflows to be focused on every account in our ICP. We segment accounts by starting more general and then get more granular, so each general segment has subsegments with greater levels of specificity. Here is our classification of segments: * Geo–country level * Revenue range - we have five revenue segments * Tiers - we have three tiers based on industry, technographics, and engagement scoring that define how much resources we put to each account * Journey Stage - we use custom stages that define where an account is in the customer journey * Product Interest - a combination of intent data and campaign responses 2. Ad creative Our goal is to the deliver the most relevant asset for the segment to drive the greatest engagement. We do that in three ways. First, we use an asset engagement heatmap. This shows what content assets are getting the highest level of engagement across channels and use those messages to target each segment. Second, we use dynamic creative that personalizes by industry and company name in real-time. Third, we use detailed and technical creative for re-targeting, after accounts have engaged with our website. 3. Integrating Advertising into our account-based GTM Account-Based Advertising by itself is only one component of an account-based GTM. Results will be limited if not thoughtfully integrated into a broader strategy. There are three key ways we do this at Demandbase. First, we orchestrate the same segmentation and creative strategy across Marketing and Sales Channels (i.e. LinkedIn, Meta, Google, Marketing Automation, Content Syndication, SEM, and Sales Automation). Second, we use the Tier segmentation to define the level of resourcing entitlements we give to each account. Tier 1 receives the most entitlements across Sales and Marketing (i.e. direct mail, 1:1 campaigns and experiences, and executive strategy sessions). Third, we create advertising response and engagement reports using UTM parameters for our SDR as a way to prioritize and personalize outreach. TAKEAWAY: Account-based advertising is a popular and effective use case for engaging accounts and providing air coverage. You can use segmentation and good creative to optimize its effectiveness. But its full potential is only realized when you integrate it into your account-based GTM strategy.

Most banks miss 94% of deposit potential by marketing to everyone the same. This is a fundamental failure in how banks approach deposit growth. Here’s how data-driven segmentation turns wasted spend into balance-sheet growth: As a 2x bank CMO, I watched banks pour millions into campaigns that treat all prospects identically. The same CD rate offer goes to a sole proprietor with $2,000 in excess balances to invest and a partner in a thriving medical practice with over $400k in excess balances to invest. Same message, same spend, wildly different potential value. The results prove the problem. While 81% of bankers expected deposit growth in 2025, actual growth came in just over 1% in Q1. The gap exists because most banks can't measure what truly drives deposit outcomes. The core issue is deposit concentration. The economics reveal why generic marketing fails: • Customer A: $300k average balances held elsewhere with only $23k held at yoru bank. • Customer B: $5k average balances held entirely at your bank already • Acquisition cost difference: Only 2x despite 60x deposit value • Result: Massive ROI disparity between customer segments Generic marketing treats both identically, systematically underinvesting where returns compound while overinvesting where they don't. Precision targeting flips this entirely. Using proprietary insights from Infusion to help understand each customer's capacity and propensity for growth, we identify which customers are most likely to not only respond but actually grow their total household relationship. You then tailor value propositions to what each segment actually needs, rather than just the rate. The impact is measurable. We helped one $8B community bank generate $497M in new low-cost deposits with 87 bps better cost of funds than their benchmark. Marketing investment payback was 1 month. Infusion has generated $25B in balance sheet growth for bank clients through this exact approach. We only get paid when you see verified results - actual accounts opened, deposits grown, loans originated - with no fee if we don't deliver. The banks winning in 2025 aren't spending more - they're reallocating from broad campaigns to surgical strikes on high-value segments. They're measuring every dollar against deposit outcomes, not impressions. They're gathering deposits without repricing existing portfolios. And they're closing the 94% gap through data-driven precision. Reach out to me to discuss how Infusion Marketing can grow your deposits, loans, and fee income through precision targeting that's actually accountable to your balance sheet.

🚨 Most companies think they’re segmenting customers. In reality, they’re just sorting accounts by size or spend. But true customer segmentation is about grouping accounts by behavior, needs, and growth potential—not just ARR. Here’s why it matters: 🔑 Renewal strategy → Your high-risk, low-engagement customers need proactive health checks, tailored success plans, and executive alignment. 💡 Upsell strategy → Your high-adoption, expansion-ready customers should get roadmap previews, advanced training, and joint business planning. ⚖️ Efficiency strategy → Digital-led engagement for your long-tail ensures consistent value delivery without stretching your CS team thin. Companies doing this well (think Salesforce, HubSpot, and ServiceNow) don’t treat all customers the same. They’ve built playbooks tailored to who the customer is today and where they can go tomorrow. 👉 Without segmentation, you’re flying blind—wasting resources on accounts unlikely to grow, while missing expansion signals from your strongest advocates. The real unlock? ✅ Use segmentation to prioritize where to invest, then align renewal and upsell motions accordingly. 💬 How does your company currently segment customers—and does it actually guide your renewal and growth playbooks, or is it just a reporting exercise?

The way most marketing teams do account segmentation today is a bit like fishing with a wide net and hoping the right fish show up. "All SaaS companies that visited our pricing page." Activate. That’s a fairly broad segment. You're spending budget on every SaaS company that happened to land on that page -- including ones that were never a real fit. Scout helps make this segmentation significantly more precise. Let me walk you through what it looks like in practice. One of our customers is in HR tech. Their product is most useful when a company is actively hiring at scale. So instead of all SaaS companies that visited their pricing page, they now target companies that visited the pricing page and have more than 10 open roles right now. Smaller list, considerably better fit. Another sells GRC software. The most valuable prospects for them are companies that don't yet have certain certifications -- so they can now filter accounts based on whether a company has SOC 2, ISO 27001, or other certifications already in place. A third sells interactive demo software. Their ideal customer doesn't have a free trial, because when one exists, a demo tool becomes less useful. They segment on that. On the internal data side, the shift is just as significant. "Active on the product" used to mean "has sessions in the product." Now it can mean: ➡️ Multiple sessions on the product page  ➡️ Cumulative time over 10 minutes  ➡️ More than one person from the company is engaging  ➡️ Engagement has increased over the last four months What Scout's agentic columns enable is combining external real-world signals with precise internal behavioral data -- so your segments reflect actual readiness to buy, not just accidental overlap with your ICP. You spend less. You reach better accounts. The rest follows.

“Should we add more CSMs, or add more CS Ops?” It’s the allocation question every CS leader faces as budgets tighten and expectations rise. The wrong choice can damage customer retention, blow the budget, or both. The best CS leaders are following a simple formula: Make tech investments where they create efficiency. Make human investments where they generate retention and growth. The Clear Division of Labor Technology excels at tasks requiring consistency, speed, and scale where human judgment isn’t critical: • Administrative work and data processing • Routine communications and follow-ups • Process orchestration and workflow management Humans excel at tasks requiring judgment, creativity, and strategic thinking: • Strategic guidance and complex problem-solving • Relationship building and value creation conversations • Turning satisfied customers into advocates But here’s where segmentation changes everything. Segmentation Drives Everything What works for enterprise accounts doesn’t work for SMBs: High-value segments require human investment. The impact on retention and growth justifies the cost. High-volume segments require tech investment. They value speed and reliability, and unit economics demand efficient delivery. Scaling Isn’t Just Automation — It’s Trust Many CS leaders assume scaling means automating everything. But trust - the foundation of customer success - scales through a strategic blend of tech and human touch: Trust scales through consistency- Reliable delivery of promises, whether automated or human Trust scales through competence- AI-powered insights helping CSMs provide better guidance Trust scales through transparency- Proactive updates that keep customers informed Trust scales through personalization - Understanding unique needs at scale The Resource Allocation Framework Your segmentation strategy drives your resource allocation decisions. Map your customer journey by segment and classify touchpoints as either: • Efficiency-focused (perfect for tech) • Growth-focused (requiring human investment) Then audit where you’re using expensive human resources on automatable tasks, and where you’re using automation for interactions that demand human judgment. CS organizations that execute this principle operate with fundamentally better unit economics. They deliver personalized, strategic value to high-value customers while serving high-volume customers efficiently. They aren’t choosing between efficiency and growth - they’re achieving both. The framework is simple: tech for efficiency, humans for growth. But applying it requires knowing your customers well enough to understand which approach builds the most trust with each segment. Where are you misallocating resources between tech and human investments?