Target Account Selection

I've seen reps burn through 6 months of quota chasing the wrong accounts. All because they thought "bigger is better." Then I did the math on my wins. ✓ 91% had certain sales tools ✓ 74% were actively hiring for revenue roles ✓ 67% had recently raised funding or gone public in the last year This wasn't luck. There was a clear pattern. Enter: the power of Ideal Customer Profile meets intent data. Here's a framework you can live by: 𝗗𝗲𝗳𝗶𝗻𝗲 𝘆𝗼𝘂𝗿 𝗜𝗖𝗣 𝘄𝗶𝘁𝗵 𝗿𝗲𝗮𝗹 𝗱𝗮𝘁𝗮 (𝗻𝗼𝘁 𝗴𝘂𝘁 𝗳𝗲𝗲𝗹𝗶𝗻𝗴𝘀) * What's the average deal size of your wins? * What industries close fastest? * What technologies predict success? 𝗟𝗮𝘆𝗲𝗿 𝗶𝗻𝘁𝗲𝗻𝘁 𝗼𝗻 𝘁𝗼𝗽 𝗼𝗳 𝗜𝗖𝗣 𝗺𝗮𝘁𝗰𝗵 * Are they researching your category? * What's their buyer committee doing? * When are they in active evaluation? 𝗦𝗰𝗼𝗿𝗲 𝗮𝗰𝗰𝗼𝘂𝗻𝘁𝘀 𝗯𝘆 𝗯𝗼𝘁𝗵 * High ICP + High Intent = Chase hard * High ICP + Low Intent = Nurture * Low ICP + High Intent = Qualify fast or pass We use Demandbase to detect intent, orchestrate plays and engage the right accounts - at exactly the right moment. Result? No more wasting time on "exciting" logos that would never close. Started focusing on accounts that fit the profile AND showed buying behavior. Bottom line: Spray and pray is dead. Precision targeting wins.

If I became CMO of a $5M ARR B2B startup, here's what I'd do in my first 30 days to 2x ICP pipeline: 1. Create a list of every target account in my ICP. I'd ask sales & CS about which factors make a great account. Then I'd bring in real-life data, analyzing all won/lost deals over the past 18 months to see which factors led to the highest expected ARR per 100 opps (equation: win rate x average ACV x NRR x 100). These factors would almost certainly include industry, company size, and geo. But I'd look to go a level deeper factoring in tech signals, hiring signals and other indicators of buying intent. 2. Identify all the most relevant contacts at those target accounts. I'd start with initiator and champion personas. Users, influencers, and exec buyers could come later. This data used to be hard to access, unreliable & expensive -- that has quickly changed. 3. Figure out where those target accounts are in their buying journey. If there were 1,000 accounts in my ICP, how many were we able to identify & market to? How many are aware of us (i.e. visiting the website, engaging with ads, opening emails, etc.)? How many are interested (i.e. viewing an interactive demo, visiting high-intent pages, starting a free trial)? And how many are considering a purchase (i.e. they're sales pipeline)? From there, the bottlenecks become obvious to the entire team. It's time to tackle them. 4. Build a pod around the biggest bottleneck. I'd spin up 10+ tests in the first week. The variables I'd play with: the account signal, the message, the channel, the offer, and the level of 1:1 personalization. (A manual approach would be fine to start with -- I can automate what works later.) The lowest hanging fruit is usually to convert aware/interested accounts into pipeline. This might mean warm outbound to convert website visitors, testing personalized video over LinkedIn, offering exec access, etc. 5. Create a 🔥 content asset that I know will resonate with my target accounts. My starting hypothesis: a State of X report featuring interviews & quotes from my ICP. I'd start with highly referenceable existing customers for social proof (low-hanging fruit). I'd then use the report as an excuse to message ICP prospects (the side-benefit: account-specific insights to personalize campaigns). I'd build this report in public -- creating a content <> community flywheel -- to already drum up interest from my ICP well before the report was published. -- Why this 30 day plan works: (a) it's focused on the best-fit accounts, (b) it brings tight alignment between marketing <> sales, (c) it creates quick wins -- earning trust to take bigger swings, (d) it's the best possible onboarding, and (e) it's aggressive -- setting the bar high. And, if it doesn't work, perhaps I'd propose another brand refresh 🙃 #marketing #icp #abx

The MQL was never what we wanted — it was just what we could measure. Time to fix that. What we actually want are engaged buying groups showing legitimate purchase intent. Not just one person downloading an eBook, but multiple stakeholders from a target account actively researching and demonstrating they're moving through a buying process. HAND RAISERS I’d argue that the best way to measure this is a steady stream of actual hand-raisers who genuinely want to talk to Sales. This was a key metric we used at Marketo. Real hand-raisers: ✅ Show demonstrate legitimate purchase intent ✅ Have genuine budget and timeline constraints ✅ Want to validate decisions, not collect information These people (and accounts) convert. They close. Sales velocity and win rates increase dramatically. WHY WE NEED LEADING INDICATORS But… buyers are far along their journey before raising hands. 6sense research shows 81% of buyers have a preferred vendor by first contact, and 85% have established requirements before reaching out.  In other words, they’ve already basically made their decision by then. So… we also need earlier signals (e.g. leading indicators) to help us know we’re on the right track. This leads to the following framework: TIER 1: TARGET ACCOUNT ENGAGEMENT Web visits, content downloads, etc. from the right accounts TIER 2: MEANINGFUL MOMENTS Real engagement from decision makers at target accounts, including executive attendance at your events or dinners, participation in your community discussions, and live discussions with your team. (This is especially important in the Age of AI, where increasingly AI will disintermediate our traditional digital signals, like web visits and email opens.) TIER 3: BUYING GROUP FORMATION & INTENT Activities that show purchase intent, including multiple visitors from the same account, intent signals, and pricing/ROI research. TIER 4: HAND RAISER Genuine inbound requests to engage with Sales. So, this means we should also be tracking: ✅ Account Coverage: What percentage of our target account list is showing engagement? ✅ Buying Group Velocity: How quickly are accounts moving through the journey stages? ✅ Engagement Intent: Are we seeing surface-level interest or genuine research behaviors? ✅ Multi-threading Success: How many stakeholders per account are we reaching? The beauty of this approach is that it gives both Marketing and Sales much richer intelligence. Sales isn't getting a random lead who filled out a form, they're getting context about an entire buying group's journey, key stakeholders, and specific interests. And it forces marketing to think like sales, activating buying committees, not generating individual leads. The MQL obsession has created what I call “lead theater” — lots of activity that looks productive but doesn't move the revenue needle. This is a better way. #B2BMarketing #MarketingAutomation #AccountBasedMarketing #LeadGeneration #MarTech

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

I just convinced our CEO to do something kinda wild. We have 2,000+ companies on our target account list. Then we built custom microsites for each one using Mutiny. And now? We're sharing it all. The entire ABM playbook. Our full target account list, how we built it, how we're actioning it — everything. Why? Because I'm tired of vague "thought leadership" that doesn't actually help anyone. So we decided to just... show our work. Fair warning: You might see your company on our list. You'll definitely spot some of your competitors. You're going to walk away with a blueprint for ABM that you can steal shamelessly. Honestly? I'm a little nervous about this. It feels like we're giving away the secret sauce. But I also believe that when we all level up together, everyone wins. So, here it is. Our entire ABM strategy, laid bare. No gates, no sales pitch. Just real, actionable insights from what's working for us right now. Go to mutinyhq [dot] com/abm-accounts. Take a look and let me know what you think. I'll be hanging out in the comments, ready to dive deeper on anything you find interesting (or spicy!)

ABM is NOT for everyone. Here's a checklist to assess ABM fit and readiness for your org. 𝗔𝗕𝗠 𝗙𝗜𝗧 1. Long sales cycle (>180 days) If your sales cycle is short and transactional, focus on demand capture and generation instead of ABM. 2. ACV (average contract value) > $30k. Will it pay off to proactively market and prospect a specific set of accounts? I suggest considering ABM if the ACV of your best customers is higher than $30k. 3. Hybrid sales: product + consulting + training. ABM is extremely important when you don’t only sell products, but also sell your expertise in solving challenges your buyers have. It includes product training, consulting alongside implementation, and training on best practices. 4. Current ICP accounts < 1000 companies If your market is limited to 500–1000 companies across the globe, you have no other choices than ABM. Note: this doesn't include any company that could potentially have a need for your product, but companies (industries, size, geographies...) you know how to sell to. 5. Multiple buyers     If you usually deal with multiple people (3+) who influence the buying decision, ABM is a perfect strategy. I weigh and prioritize the first three points. Here is why. Your market can be more than 1k companies, or you might sell to an SMB where you don’t have lots of decision-makers, but ACV is high. E.g. Software development companies. If ABM is a right fit, next check your readiness to launch it. 𝗔𝗕𝗠 𝗥𝗘𝗔𝗗𝗜𝗡𝗘𝗦𝗦 1. Do we have clear ICP (Ideal customer profile) and account qualification criteria to build a list of companies that are likely to buy our product? 2. Do we have a deep understanding of our verticals, including the vertical value proposition and collateral?     3. Do we have a clear playbook to create awareness inside target accounts, generate demand, and activate them?     4. Can we create a dedicated ABM team that doesn’t have pipeline pressure and has time to build ABM motion?     5. Do we have an alignment between marketing, sales, and executives on how to measure the campaign’s progress and performance? Define leading and lagging indicators to measure campaign progress and get approval from execs and sales. --- I’ve shared this, not to stop you from launching ABM. I wanted to show that ABM is not for everyone, and is not a silver-bullet solution based on an air cover and lead gen on steroids that can convert a wish list of accounts into your customers. ABM is a strategic motion to identify companies that need your product, personalize your solution to them, and generate long-term customers. To develop this motion, your company should allocate the resources and build a foundation. There are no shortcuts. And if ABM is a right fit for your company, check out this guide we created with Andrei Zinkevich, with a step-by-step process that we use to develop a successful account-based demand generation model and ABM strategy: https://lnkd.in/dAaGArXc

Here is how we went from "it's not going to work" sales skepticism to "ABM is driving discovery calls with our enterprise accounts" with Customs4trade team: Here are 5 pillars of our playbook. 1. ACCOUNT ALIGNMENT. We developed clear account prioritization criteria based on cluster definition, industry focus, and engagement signals - not just firmographics. 2. REPOSITIONED SALES REPS AS INDUSTRY EXPERTS. Our pilot sales team shifted from a standard sales messaging to: - Sharing valuable insights on customs automation challenges that their target audience cared about - Building relationships with the entire buying committee - Running in-depth research to identify the needs and the buyer journey stage of the target accounts. 3. VALUE-ADDED ENGAGEMENT OVER PITCHING. This playbook included multiple meaningful non-sales touchpoints to create awareness, including: - Content co-creation with the target buyers - Account-specific "love letters" mentioning target accounts achievements initiatives and - Thoughtful commenting on buyer posts 4. BUYER-CENTRIC WEBINARS. Instead of hidden product demos, we created an educational webinar for supply chain experts, revealing non-obvious mistakes in customs workflows, and how to handle them. Next, showing the best practices. Join promotion by marketing and sales helped to achieve a 50+% attendance rate. 5. WEEKLY SPRINTS. Every week became a sprint where, with the team, we reviewed and planned the next week, including: - What went right? - What can be done better? What can we immediately implement? - How can we work better together during the next sprint? - What distracted or get on our way in the last sprint? - What are the bottlenecks that slow down our velocity? - What should we publish next? - What new accounts should we research and engage? - What can we do to facilitate opportunity generation with the engaged accounts? THE RESULTS: - 10 discovery calls booked - 26 active focus accounts generated - Replies from accounts they'd been reaching out to for years - 4x increase in content impressions and sales profile viewers --- On Wed, we're going live with Joseph Threlfall (marketing) and Bowin Cai (sales) to dive deeper into their pilot program and case study. Save your spot here: https://lnkd.in/d9YEQwDd

Here's how I spent my Nov and Dec when I was Head of Demand Generation at Google. I ran a 10-figure ABM program and learned a few things over my 7 years there. Q4 isn't about hitting your current quarter's numbers. It's about ensuring Q1 doesn't start from zero. You can't afford to "figure it out" in the new year. You can't afford to spend February building what should have launched January 1st. Here's what I focused on every Q4: 👉🏼Data-Driven Account Targeting I didn't start with last year's account list. I started with the data. Which accounts closed deals in the last 12 months? What signals did they show before converting? Which accounts look exactly like them but haven't engaged yet? We rebuilt our target account universe from scratch every year. Not because the old list was wrong but because the market had changed. By Thanksgiving, we had our tiered account list ready: 200 accounts for full orchestration, 800 for scaled campaigns, 2,000 for programmatic reach. 👉🏼 Intent, Signals, and Segmentation We built segmentation around signal intersection. Each segment got different orchestration because a CFO researching cost optimization needs different content than a VP Engineering evaluating technical specs. By early December, we had 12 distinct marketable audiences mapped to specific buying scenarios. 👉🏼 Multi-Channel Orchestration We mapped every touchpoint across every channel for every segment. LinkedIn ads warming accounts while display maintained presence. Email sequences aligned to sales outreach cadences. Content syndication filling awareness gaps. Events timed to buying committee research patterns. Nothing launched in isolation. Every channel reinforced the others. 👉🏼 I see most marketing teams right now in one of two states: Scrambling to hit Q4 numbers, haven't thought about Q1, planning to "figure it out over the holidays." Or knowing they need to plan Q1 but overwhelmed by everything that needs to happen. If you're in either state, you're running out of time. At twelfth.agency, we help growth-stage teams build these same foundational elements: Data-driven account targeting using signals. Segmentation strategies that create marketable audiences. Multi-channel orchestration that coordinates marketing and sales. Content frameworks that enable personalization at scale. We're working with CMOs right now who want campaigns hitting the ground running on January 1st. Not strategy decks. Actual campaigns generating meetings. You have about 6 weeks to build your account universe, map your segments, design your orchestration, create your content foundation, and align your sales team. Check us out if you want to be ready for Q1. https://twelfth.agency

Before you go full throttle this quarter, take 15 minutes to check these 3 things in your ABM program. 🔶 Are your target accounts actually your "best" fit customers? Take the criteria used to build the target account list. Use the **exact** same criteria to build a list in your CRM. Add the additional criteria of "Customer." This brings up a list of Customers that match your target account criteria. Do you want more of these customers? Cause with your program, that's what you're about to get. 🔶 Relook at your signals & triggers. Imagine for a moment that you're on the other end of your program. Specifically, look at WHEN you expect them to book a sales call. Would you? If you think, "I mean, probably." Rethink your triggers. Ideally, you'd nail the right message, right time, right place, right person at every stage of the program. I have never nailed it 100% of the time (If you have, I'm hiring). But typically, it's all good with a content-led program. Every touchpoint in a content-led program focuses on education. But the demo ask transitions from adding value to asking for the sale. You have to nail this piece. If your triggers aren't convincing you, they likely aren't convincing the buyers either. 🔶 Sufficient resource allocation. Do you have the following: 🔸 Executive buy-in 🔸 Partners in Sales 🔸 Operations support 🔸 Content support 🔸 A clear internal driver for the program timeline 🔸 A strategist 🔸 Distribution channel owners If yes, go for it. If not, get it. 1 person can take on multiple roles (shout out to my solo marketing friends) But you need to know who owns these roles. Otherwise, you're going to get stuck, and the program will fail. I'm confident I missed some things. But you should be able to pull out a quick sheet of paper and knock out this little exercise in the next 15 minutes. Other ABMers, what would you check out for a quick pulse check on a program? P.S. Bonus points if you send this to your team and compare answers. Especially on roles and responsibilities. If your team isn't answering that piece in the same way, things are definitely going to get dropped.

Unpopular take: Sales reps should never do their own list building. The best way to scale a GTM motion is to have one central target account list with every relevant company in the TAM. And everything works backwards from it: - Outbound - ABM ads - Targeted campaigns But I understand why teams don’t have this important GTM asset. Prior to AI, a proper TAM map was a massive undertaking that would’ve required actual data science. So most resorted to exporting a few ZoomInfo lists and calling it a day. Now, it’s way more accessible. Here’s how we map out TAMs in 9 steps (the 2026 way): 1️⃣ Start in the CRM • Enrich and analyze your closed won accounts to look for commonalities. • Get qualitative input from your GTM teams on what makes a great account. 2️⃣ Build your ICP model • Based on three sets of data: firmographics, technographics and account-fit signals. • Backtest your against closed-won. 95% should qualify if your model is right. 3️⃣ Diversified list-building • Pull broad lists from 2+ sources (e.g. databases like Apollo.io / Ocean.io, or scraping tools like Apify / Serper). • Don’t overly rely on filters (e.g. many software companies are not under the software development industry). 4️⃣ Data cleanup • Merge your separate lists into one source of truth. • Find missing data points (e.g. domains) and validate every domain is operational (free). 5️⃣ Initial qualification • Design a research agent to do initial binary qualification based on product/industry fit (e.g. is this actually an eCommerce brand?) • Use lower cost models like 4o-mini or Haiku given scale. 6️⃣ Deep enrichment • Order your enrichments so that the ones most likely to disqualify companies, are positioned first. • For qualified accounts, layer in custom research points relevant to your GTM. 7️⃣ Score every account that survives • Score every account into: Tier 1, Tier 2, Tier 3 • Avoid intent signals in your scoring, as this is purely account fit. 8️⃣ Stakeholder mapping • Analyze the titles typically involved in your deals and split them into: decision maker, champion, and influencers. • Source those titles at every company that qualifies. 9️⃣ Push it back to your CRM • Load companies, contacts, and custom properties into your CRM, depending on how big your TAM is (for large TAMs, just upload Tier 1s) • Turn the TAM map workflow into an automated CRM enrichment flow, so every record in your CRM gets the same custom research. --- The end result is a much easier time for reps. They don’t need to build ad hoc lists and if they want to do outbound. They simply build their segments from the CRM/data store. Allowing 90%+ of the effort to be spent on activity. Full guide below 👇