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How long have we been talking about attribution in B2B and yet we're still looking for that silver bullet. Well, half of us it appears. Only 55 percent of marketers in our research are using ROI as a primary metric to evaluate marketing's effectiveness, and only 29 percent of marketers consider themselves successful at measuring attribution. And of those proactively using attribution models, only 31 percent feel confident that it's accurate. No doubt this is a very complex, politically charged issue. I'm proud of the work our team has done to build out our latest best practice guide: From First Touch to Closed Deal: A Comprehensive Guide to Marketing Attribution. It's a detailed, practical guide to attribution strategy with numerous examples of models, data taxonomies and other resources. No forms required, get a free copy in the comments below.

What I believe about how GTM is evolving: 1. B2B GTM has changed. Anything that could build pipeline is fair game. There might have been a time when marketing generated pipe & sales closed it. But that's not the world we live in now. We expect contributions from: - marketing (content, social, PR, etc.) - sales (cold email, cold call, intros/referrals, warm outbound) - product (free trials, lead magnets, interactive demos, programmatic SEO) - and even ops (automated outbound, intent data, AI tools) 2. Our old GTM metrics haven't kept up. And the MQL paradigm is broken. The obsession with MQLs creates a leaky lead budget with significant wasted spent. It encourages spray-and-pray demand gen tactics, and it makes it nearly impossible to know whether our efforts are influencing the right people at the right accounts. 3. An alternative approach: unified, account-based metrics. Why not focus on reaching our best possible accounts (ICP)? The data is far more readily available -- yes, even with LinkedIn bans -- through next-gen tech. If we shifted to an account-centric view, we'd measure: - How many accounts are in our ICP? - Where are those accounts in their buying journey with us? - What activities are most effective at influencing accounts along that journey? 4. I challenge you to make an ABX chart for your ICP accounts. Out of every account in your ICP, what % have you (a) identified, (b) are aware of you, (c) are interested in your value prop, (d) are considering you for a purchase, (e) are selecting a vendor, and (f) have chosen your product. 5. What matters is that you ultimately reach the right people & turn them into customers. And marketing can become the team responsible for orchestrating *everything* that contributes to pipeline -- not just "marketing-qualified leads". This likely means SDRs (& AI agents) shifting under marketing, too. 6. Next-gen GTM tech is making this a LOT easier to do. Although, yes, account-based reporting remains a pain. There are so ?? many ?? signals to consider. Run GTM experiments with test & control groups, measure the results, scale up what works so that it's always on. Emerging roles like GTM architects can help. -- The TL;DR: goodbye MQLs, hello ICP pipeline. PS, I'm dropping the full deck below. Please don't comment "MQL" for a copy ?? ?? For more next-gen GTM insights, don’t miss Growth Unhinged — my free weekly newsletter: https://lnkd.in/exTbjKaM #marketing #gtm #icp

The crew at ABM Answered blew me away. Their operation is a master class for quality content creation. I met with Sam Hall to record an episode and we talked about how to drive marketing results without expensive intent data tools. Here's a preview of the questions we got into. When Is the Right Time to Start ABM? from Saurabh Sanghi - MBA, CM “How do you explain all the great work marketing is doing without overcomplicating things?” from Matt Conway and Katie O’Neill from Noetic Sales Enablement AI in ABM: What’s Worth Using? from Juan Martienez from Autodesk And many many more. If you want to see the full transcript you can access the blog here: https://lnkd.in/g4SQWPzg

Demand Generation is an art and a science. Here are the 7 key reports of the Demand Generation Leader. ? Note: PLG and ABM metrics are not included, these will be in a separate post. ? ?? Lead Volume & Quality – This shows how many leads move from one stage to the next, from marketing qualified to closed/won deal. Poor conversion rates at any stage can signal inefficiencies, misalignment, technical problems, and/or process problems. ? ?? Pipeline by Source – This shows how many opportunities come from each source or channel, though you can also show deals and/or revenue. This can show weaknesses and also opportunities to double-down investment. ? ?? Cost Per Lead & Cost Per Acquisition – Cost per lead is how much you pay for each lead on average. Cost per acquisition is how much it costs to acquire a new customer. If your CPL or CPA is rising too fast, you might be overpaying for low-quality leads or hitting audience fatigue. This helps you course-correct before it impacts ROI. ?? Funnel Efficiency – This shows how long it takes for a lead to move to the next stage. The longer it takes, the more friction exists in your process. Tighten handoffs, improve nurturing, and shorten deal cycles to accelerate revenue. ?? Average Deal Size – This shows the average size of a sale by customer segment. Understanding deal size by segment helps you focus on high-value accounts and activities rather than chasing low-revenue deals. ?? Pipeline & Revenue Forecast – This shows how much money you are on track to make based on historical trends and data. Forecasting pipeline ensures sales and marketing are aligned on targets and allows you to adjust strategy in real time. ?? Meetings Driven by Channel – This shows how many meetings you are booking by channel. This can help optimize upstream activities since it is more top of the funnel than pipeline by source. Is this helpful to you? What report would you add or change? Big thank you to the marketing and GTM leaders that gave me direction for this diagram! Including, Shannon Renz VP Demand Gen at LaunchDarkly, Karen Naves SVP of Demand Gen at Tealium, Thao Ngo ?? SVP of Marketing at Uptempo, and Scott Vaughan Chief Market Officer and GTM Advisor. PS: I'm writing more about this in my weekly newsletter "The Marketing Operations Leader" subscribe for free to keep leveling up your knowledge https://lnkd.in/g_3YC7BZ #marketing #martech #marketingoperations #demandgen

ABM is Giving Way to ABX Let me explain this with an example of a fictional B2B SaaS company called CloudTalk in the cloud communications space. For years, CloudTalk thrived on traditional ABM—identifying high-value accounts, crafting personalized outreach, and nurturing leads through marketing campaigns. But soon, ABM stopped being a competitive advantage. Why? Every competitor was doing the same thing. Buyers—CTOs, IT heads, and procurement teams—were bombarded with similar messaging from multiple vendors. ABM had become a commodity. That’s when CloudTalk made the shift from ABM to ABX—Learn more about ABX from insights shared by steve armenti in his recent article on MarTech.org (link in comments). Why ABX? Because Buyers Expect More CloudTalk’s team started with a deep audit of their GTM strategy. Instead of just looking at target accounts, they examined revenue patterns, customer journey insights, and engagement data. The results were clear: - Their best deals came from unexpected segments—not just static ABM lists. - Leads stalled at the demo stage—messaging wasn’t aligned with real pain points. - Buyers wanted dynamic, real-time engagement—not just surface-level personalization. To stay ahead, CloudTalk evolved from ABM to ABX—aligning marketing, sales, and customer success across the entire customer lifecycle. How CloudTalk Shifted from ABM to ABX 1. Dynamic Targeting Over Static Lists Instead of relying on a fixed list of target accounts, CloudTalk blended first-party and third-party data to track "marketable audiences"—accounts showing real engagement signals. Example: A CTO of a fintech startup who downloaded a whitepaper on VoIP security, attended a compliance webinar, and engaged with CloudTalk’s LinkedIn posts wasn’t just a prospect—they were an in-market buyer. 2. Orchestration Across Buying Groups ABM focused too much on individual leads. ABX meant multi-threaded, multi-channel engagements across all decision-makers in an account. Example: CTOs received deep-dive reports on tech stack integration. - Procurement teams got a TCO (Total Cost of Ownership) analysis. - End-users were invited to "live test" CloudTalk’s AI-powered IVR system. 3. Agile, Modular Content Instead of One-Size-Fits-All Forget mass-produced eBooks. CloudTalk shifted to content that adapts to personas and intent signals. Example: A case study on VoIP security for fintech was repurposed as: - A one-pager for CFOs (ROI-focused). - A podcast episode for IT leaders (technical deep-dive). - A 30-second video for decision-makers (problem-solution narrative). 4. Account-Centric Metrics Over Lead-Based Metrics Instead of tracking just MQLs and SQLs, CloudTalk measured: - Which accounts showed strong buying intent? - How engaged were key stakeholders across the buying journey? - Were sales and marketing working together on real-time engagement signals? This revenue-driven approach led to better collaboration between sales and marketing.