Account-Based Marketing Essentials

I’m amazed by the level of creativity that’s going into identifying target accounts these days. You used to be lucky if you could find a list of companies in a specific industry with a certain number of employees. At one point not long ago I had an offshore research team dedicated to finding the right accounts! Now the parameters available are truly endless. Some examples I've been digging lately: - Scraping job posts to target companies w/ specific initiatives - Scraping job posts to target companies w/ specific tech/software - Scraping SEC filings before PR announcements - Finding companies w/ a "get started" button on their website - Finding companies w/ a public security page - Finding ICP accounts where 2+ users from the same domain have viewed marketing assets (docs, webinars, etc.) in the last 30 days - Finding companies w/ an unusually high ratio of [x] function as a % of total employees - Finding the next employers of past champions & any hire on their team - Using AI to find 'look-a-likes' of the best existing customers - Using AI to find all competitors of the best existing customers What this means for B2B teams: 1. You can't have a static account list anymore. If you're targeting the same accounts in July as you did in January, may I suggest a refresh? 2. Back-test hypotheses based on real data around CW & CL accounts. Ideally pull in data points on deal size and expansion/churn, too. (I like measuring the expected ARR per 100 opps). 3. Manually review the top ICP accounts w/ sales & CS to ensure buy-in. 4. The account/domain isn't enough. Part of identifying your ICP means knowing the exact right *people* & where they are in the buying journey. 5. Don't trust a black box. This is too important to not have an owner internally. And, most importantly, have some fun w/ this. The opportunity for creativity is incredible (never thought I'd say that!). #icp #marketing #gtm

ABM will never be dead, but the old-school way of approaching ABM is definitely dead (as a doornail). Most "ABM" programs still look like what I was doing in my late 20s and early 30s (circa 2015-2017) >> Static target lists >> One-size-fits-all nurture tracks >> Months of manual personalization That doesn’t work when buyers self-educate, switch channels mid-cycle, and bring 10+ stakeholders into every deal. Lucky for me, I have a Tofu guide that helps define different plays you can run to pull your ABM out of 2015: Competitive Displacement → Go on offense. Target competitor accounts with comparison content, peer proof, and coordinated blitzes. Customer Lookalike Campaign → Take your best wins and mirror them. Use AI to find accounts that look like your top customers and show them proof they can’t ignore. Tier 1 Omnichannel Blitz → Don’t wait for signals. Surround your most strategic accounts with personalized microsites, direct mail, and peer-led content. Competitive Intent Intercept → When a target account shows interest in a competitor, move fast. Counter-pages, battlecards, and rapid-response ads flip the narrative. Signal-Qualified Web Visitors → Pricing page traffic isn’t noise. De-anonymize, personalize, and act before your competitor gets the next meeting. Customer Expansion Campaign → The highest ROI play isn’t new pipeline. It’s expansion. Use product and CS signals to spot growth opportunities inside your base. The shift is pretty simple, and something we should all remember. You need to move from campaigns you launch and cross your fingers.... to systems that listen and adapt in real time. ABM done right isn't just account-based, it's contact-based AND it orients around signals.

I recently talked with a fellow marketer about account scoring in #ABM.  They struggled to adapt to the recent privacy law, which made me think: We must rethink how we do this. Account scoring is evolving. It's moving way beyond simple intent data.  You need a new approach to find these high-potential accounts in a privacy-first world. I call it Account Scoring 2.0. But why? ➖Traditional intent data is becoming less reliable.   ➖Privacy regulations are changing.   ➖Third-party cookies are fading away.   ➖We can't rely on old methods.   ➖We need to be more innovative. 👉🏾 Using Account Scoring 2.0 helps you focus on first-party data. This is data you collect directly from your target accounts like: Website visits. Content downloads.    Engagement within your emails.  Collecting and analyzing this data is valuable. It's also privacy-compliant. 👉🏾 Other things to look out for are behavioral signals.  Look out for target accounts engaging with your content.    Are they attending your webinars?  Are they interacting with your sales team?  These actions show interest and suggest potential. 👉🏾Predictive modeling plays a key role too. You can use AI to analyze first-party and behavioral data.  This helps you predict which accounts are most likely to convert.  It allows you to prioritize your efforts. Remember, it's about working smarter, not harder. 👉🏾 Don't forget contextual data; it matters, too.  What's happening in the market?  Look for industry trends that align with your offerings.  Are there changes in your target accounts' businesses?  Understanding the context helps refine your scoring. Look at Account Scoring 2.0 as a strategy, not just technology. It's more about understanding your ideal customer profile. It's about aligning sales and marketing and building relationships while respecting privacy more efficiently. What are your thoughts on the future of account scoring? Have you used it before? #b2bmarketing #marketingstrategy

𝗔𝗰𝗰𝗼𝘂𝗻𝘁-𝗯𝗮𝘀𝗲𝗱 𝗚𝗧𝗠 𝗶𝘀 𝗻𝗼 𝗹𝗼𝗻𝗴𝗲𝗿 𝗷𝘂𝘀𝘁 𝗳𝗼𝗿 $𝟭𝟬𝟬𝗸+ 𝗱𝗲𝗮𝗹𝘀. The rules have changed—are you ready? It used to be exclusive—reserved for those massive, high-value accounts. Why? Because it was too manual, too expensive, and too hard to scale. But today, the game is different. With account data becoming more accessible (almost a commodity now) and AI tools automating deep account research, we can shift our focus. 𝗘𝗻𝘁𝗶𝗿𝗲 𝘁𝗮𝗿𝗴𝗲𝘁 𝗺𝗮𝗿𝗸𝗲𝘁𝘀 𝗰𝗮𝗻 𝗻𝗼𝘄 𝗳𝗶𝘁 𝗶𝗻𝘁𝗼 𝘆𝗼𝘂𝗿 𝗖𝗥𝗠. 𝗬𝗼𝘂 𝗰𝗮𝗻 𝘁𝗮𝗶𝗹𝗼𝗿 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗲𝗳𝗳𝗼𝗿𝘁𝘀 𝘁𝗼 𝗴𝗼 𝗮𝗳𝘁𝗲𝗿 *𝗲𝘃𝗲𝗿𝘆* 𝗯𝗲𝘀𝘁-𝗳𝗶𝘁 𝗮𝗰𝗰𝗼𝘂𝗻𝘁—𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝘁𝗵𝗲 𝗯𝗶𝗴 𝗳𝗶𝘀𝗵. Sounds exciting, right? But let’s not sugarcoat it: pivoting to ABM is brutal. There are no real playbooks, and tactical resources are painfully scarce. But when we did, the results were jaw-dropping: → $350k in pipeline in just 90 days. → $7 in pipeline generated for every $1 spent. We are doubling down now—and shared the guide Here’s our ABM checklist: 1. Define your ABM goals & leading metrics. 2. Choose a level of personalization: 1:1, 1:few, 1:many. 3. Set up campaigns: account stages, scoring, and duration. 4. Select channels (LinkedIn was our starting point). 5. Build your target list: accounts, personas, etc. 6. Prep content, messaging, and ad formats. 7. Approve budget & resources. 8. Onboard tools/vendors to handle each ABM element. 9. Set up dashboards to track performance. Our unbundled tech stack? ~$1k/month across 8 tools: → HubSpot, Clay, BuiltWith, Apollo.io for list building. → Factors for ad pilot → ZenABM/Fibbler for intent recognition → Smartlead for prospecting. ABM isn’t easy, but the rules have changed. With the right tools, strategies, and mindset, it’s no longer just for the $100k+ deals. What’s stopping you from making the shift? #abm #marketing #gtm #saas

Sales and marketing both think they're doing their job right. And they are. That's exactly why nothing's working. The problem isn't effort or skill. It's that they're operating from two completely different understandings of the buyer's journey. Marketing builds campaigns, thinking buyers need awareness. Sales gets on calls and realizes they're already comparing solutions. That gap? That's where deals die. Here's how you close it: 1. Map the buyer journey together with both teams and break down ⤷ What actually triggers buyers to search?  ⤷ What confuses them most?  ⤷ What objections keep showing up?  ⤷ When both teams agree on this, everything else starts working. 2. Make marketing listen to sales calls This closes 50% of the gap instantly. Marketing finally hears the real objections, the tone, and the questions, and it makes their messaging sharp. 3. Let sales approve messaging before it goes live. Sales knows which phrases confuse people and which make them lean in. Use that. We have worked with 50+ B2B companies where aligning the sales and marketing efforts from the buyer journey turned their pipeline around in weeks. Deals closed faster. Conversations became productive. The blame game stopped. PS: Drop a 👍 if you've ever been caught in the middle of a sales vs marketing argument. #SalesAndMarketingAlignment #SMarketing #RevenueOperations #B2BMarketing #BuyerJourney

How to move from one-size-fits-all ABM to a dynamic, cross-functional GTM strategy that targets your best-fit accounts ⤵️ 🟢 It’s no longer just account-based 𝘮𝘢𝘳𝘬𝘦𝘵𝘪𝘯𝘨, confined to a single department. Today, it’s an 𝘢𝘤𝘤𝘰𝘶𝘯𝘵-𝘣𝘢𝘴𝘦𝘥 𝘨𝘰-𝘵𝘰-𝘮𝘢𝘳𝘬𝘦𝘵 𝘴𝘵𝘳𝘢𝘵𝘦𝘨𝘺 - a cross-functional approach that unites the entire GTM team. 🟢 This shift represents a fundamental evolution in how we think about account engagement - one that breaks down silos and aligns marketing, sales, and customer success around a unified goal. The biggest hurdle in making this pivot? The outdated “pyramid-shaped” ABM deployment model that most account-based strategies are still built on. Originally rolled out in 2016, this model hasn’t kept pace with the rapid evolution of go-to-market innovation. Despite being outdated, it’s still widely used - leaving many teams stuck in the past while the market moves forward. 💡 The Modern Account-Based GTM Pyramid We partnered with ForgeX and Demandbase to redefine effective account-based strategies with a modernized GTM pyramid. Here’s how it works: 1️⃣ Enterprise ABM: Focuses on high-value, strategic accounts with personalized engagement. These top-tier targets need deep collaboration between ABM practitioners and AEs, especially in expansion scenarios, ensuring high-touch efforts drive impact. 2️⃣ Growth ABM: Acts as a scalable foundation, engaging a broader set of accounts through targeted efforts. SDRs play a key role in generating pipeline and engaging accounts at scale, covering from 50 to thousands of accounts. 🔄 Running both models together -- Integrated strategy: Enterprise ABM accounts are pulled from the top tiers of Growth ABM (Tier 1 and 2). If an account no longer fits Enterprise ABM, it seamlessly moves back to Growth ABM, ensuring resources are used effectively. -- Holistic GTM: This dual approach enables a comprehensive GTM strategy, balancing scale with precision for a unified, adaptable account-based approach. Check out full details on the modernized GTM pyramid: https://lnkd.in/gW4hZ3BC -- Every week, GTMnow publishes The GTM Newsletter, read by over 52,000 revenue professionals to stay up-to-date on go-to-market and scale their companies and careers. GTMnow is the media brand of GTMfund - sharing go-to-market advice from the top 1% of revenue operators, news, and our viewpoints from working with hundreds of portfolio companies.

Research is catching up to what we can see about how B2B buying is changing. The 3rs: 𝗥elationships, 𝗥ecommendations, and 𝗥elatability factors are taking centre stage. While product features, price, or brand recognition are in decline. Research from Warc reveals that emotional factors are more consequential in B2B buying decisions than rational levers. • Recommendations from similar customers or trusted colleagues are 3x more likely to tip the balance than cheaper prices • These recommendations are also 3x more influential than products promising better performance So cultural, social signals, and emotions are shifting decision-making. 𝗪𝗵𝘆 𝘁𝗵𝗲 𝘀𝗵𝗶𝗳𝘁? 2/3 of big-ticket B2B buyers are now millennials or Gen Z. 𝗧𝗵𝗲 𝗻𝗲𝘄 𝗽𝗹𝗮𝘆𝗯𝗼𝗼𝗸: This isn't about giving old tactics new names. It's about recognising that B2B buyers (especially younger ones) make decisions based on what their peers say and who they trust, not just specs and prices. 𝗪𝗵𝗮𝘁 𝗰𝗮𝗻 𝘆𝗼𝘂 𝗱𝗼 𝗮𝗯𝗼𝘂𝘁 𝗶𝘁? Stop treating B2B buyers like robots comparing spreadsheets. Focus on the right places to build relationships. LinkedIn (not spam), WhatsApp groups, Slack communities, industry events. Focus on getting more recommendations, and broadcasting them. Create customer communities where peers validate each other's decisions. Avoid the BS: fake testimonials, aggressive automation, undisclosed paid recommendations. Most B2B marketers still pump budget into feature comparisons. Your prospects aren't asking "what does it do?" They're asking "who else like me uses this?" Track where your best deals come from. It's not the trade show booth. It's Sarah telling James at drinks that your product saved her quarter. That's your real marketing channel now.

"Deal's looking good. I'm in with the CMO." A colleague shared his excitement. I rolled my little eyeballs. "What?" he asked, confused. "Single-threaded deals die," I replied. Three weeks later: "CMO went on leave. Deal's stalled." I wasn't surprised. The average B2B purchase now involves 11+ stakeholders. Yet most reps are still playing the "one relationship" game. Old playbook: Find one champion. Let them "sell internally" for you. Hope for the best. Failure rate? About 80%. A recent client win taught me the better approach: Initial call with the VP of Sales. Great fit, but I asked: "Who else needs to be comfortable with this decision?" The list: - CRO (economic buyer) - IT Director (technical approval) - Sales Enablement (implementation) - 2 Regional VPs (end users) That's 6 people. Each with different: - Priorities - Objections - Questions Rather than pestering my champion to coordinate everything... I created a single digital room with: - Role-specific sections for each stakeholder - Tailored ROI calculations for the CRO - Security documentation for IT - Implementation timeline for Enablement - Quick-start guides for the Regional VPs My champion shared the link. The magic happened silently: Analytics showed the CRO viewed the ROI calculator 5 times. The IT Director spent 15 minutes on security docs. Both Regional VPs watched the training videos. I hadn't spoken to any of them directly. But they were all selling themselves. When we finally had the "decision call," everyone was already aligned. No last-minute objections. No mysterious "other stakeholders." No surprises. Here's what changed: Old approach: Pray your champion effectively represents you to people you never meet. New approach: Give every stakeholder what they need, even without direct access. Multi-threading isn't about scheduling more calls. It's about making yourself irrelevant to the process. The best deals close when stakeholders convince themselves...without you in the room. Are you still gambling on single-threaded relationships? Or building networks that sell for you? Agree?

After 20 years in the trenches of enterprise marketing, I've watched the pendulum swing repeatedly between hyper-personalization and scalable efficiency. 🔄 Here's the uncomfortable truth about ABM that most vendors won't tell you: 🤫 The obsession with 1:1 ABM is crippling marketing organizations that should be building balanced portfolios of engagement. 📊 In my experience leading marketing transformations across three continents, the most successful B2B organizations implement a deliberate mix of ABM approaches: 🎯 Strategic 1:1 ABM for those truly transformative opportunities where custom journeys deliver exponential ROI  🤝 ABM Lite (1:Few) targeting clusters of 20-100 accounts with shared pain points and industry characteristics—delivering personalization at a manageable scale  🚀 Programmatic ABM enabling broader market coverage while maintaining account-level relevance The secret isn't choosing one approach—it's orchestrating all three simultaneously in proportions that match your revenue architecture. When your peers boast about their ultra-personalized campaigns, ask them about their cost-per-acquisition metrics. The answer might surprise you. 💰 Remember: ABM isn't just a marketing tactic—it's a business approach that requires a very close sales-marketing alignment and executive sponsorship to drive sustainable growth. 🤝 What's your ABM mix looking like for 2025? 🔮 #ABM #B2BMarketing #Accountbasedmarketing #MarketingStrategy

Teams will increasingly include both humans and AI agents. We need to learn how best to configure them. A new Stanford University paper "ChatCollab: Exploring Collaboration Between Humans and AI Agents in Software Teams" reveals a range of useful insights. A few highlights: 💡 Human-AI Role Differentiation Fosters Collaboration. Assigning distinct roles to AI agents and humans in teams, such as CEO, Product Manager, and Developer, mirrors traditional team dynamics. This structure helps define responsibilities, ensures alignment with workflows, and allows humans to seamlessly integrate by adopting any role. This fosters a peer-like collaboration environment where humans can both guide and learn from AI agents. 🎯 Prompts Shape Team Interaction Styles. The configuration of AI agent prompts significantly influences collaboration dynamics. For example, emphasizing "asking for opinions" in prompts increased such interactions by 600%. This demonstrates that thoughtfully designed role-specific and behavioral prompts can fine-tune team dynamics, enabling targeted improvements in communication and decision-making efficiency. 🔄 Iterative Feedback Mechanisms Improve Team Performance. Human team members in roles such as clients or supervisors can provide real-time feedback to AI agents. This iterative process ensures agents refine their output, ask pertinent questions, and follow expected workflows. Such interaction not only improves project outcomes but also builds trust and adaptability in mixed teams. 🌟 Autonomy Balances Initiative and Dependence. ChatCollab’s AI agents exhibit autonomy by independently deciding when to act or wait based on their roles. For example, developers wait for PRDs before coding, avoiding redundant work. Ensuring that agents understand role-specific dependencies and workflows optimizes productivity while maintaining alignment with human expectations. 📊 Tailored Role Assignments Enhance Human Learning. Humans in teams can act as coaches, mentors, or peers to AI agents. This dynamic enables human participants to refine leadership and communication skills, while AI agents serve as practice partners or mentees. Configuring teams to simulate these dynamics provides dual benefits: skill development for humans and improved agent outputs through feedback. 🔍 Measurable Dynamics Enable Continuous Improvement. Collaboration analysis using frameworks like Bales’ Interaction Process reveals actionable patterns in human-AI interactions. For example, tracking increases in opinion-sharing and other key metrics allows iterative configuration and optimization of combined teams. 💬 Transparent Communication Channels Empower Humans. Using shared platforms like Slack for all human and AI interactions ensures transparency and inclusivity. Humans can easily observe agent reasoning and intervene when necessary, while agents remain responsive to human queries. Link to paper in comments.