Account-Based Selling

My client fired their entire SDR team on Tuesday By Friday, their pipeline had grown by 60% This sounds impossible It's not After auditing 50 B2B sales organizations over 10 years, I've uncovered the most expensive myth in modern selling: → The belief that MORE activity at the TOP of your funnel will fix conversion problems at the BOTTOM Let me share what actually happened: This mid-market software company was spending $350,000 annually on their 4-person SDR team - 100+ cold calls per rep daily - 17 meetings booked weekly - "Incredible metrics" according to leadership - But their close rate? A devastating 1.2% The VP of Sales was convinced they needed MORE outreach, MORE automation, MORE top-of-funnel I suggested something different: pause all prospecting for 7 days Instead, we had their account executives do something radical - engage with the 215 prospects already in their pipeline who'd gone cold after initial meetings Using a framework we developed: - 65 prospects responded within 24 hours - 41 booked follow-up meetings - 23 re-entered active buying cycles - 6 closed within 14 days (total value: $212K) The shocking revelation? - Their pipeline wasn't empty - It was overflowing with neglected opportunity. This company didn't have a lead generation problem. They had a lead nurturing catastrophe. By reallocating resources from mindless prospecting to strategic engagement, they've now: - Reduced CAC by 60% - Shortened sales cycles by 30% - 2x their close rate The counterintuitive truth: Sometimes the fastest path to growth is to stop chasing new opportunities and start converting the ones you've already earned. What percentage of your marketing and sales budget is focused on prospects who've already shown interest vs those who haven't? That ratio reveals everything about your future growth trajectory P.S. If you need help with your sales, send me a message

For my first 16 years in tech sales, I averaged 240K/year W2 income. In my last 4 years, I averaged 720K/year. In order to triple my income, I had to change my sales approach entirely. Here's what I changed: I started using a new approach that I now call Yo-yo selling: 🪀 Yo-yo selling emphasizes starting at the executive level, conducting thorough discovery within the organization, and then returning to the executive with a tailored business case. Like holding a yo-yo, you are constantly in communication with the Executive Sponsor and updating them as you collect information and conduct deep discovery lower down in their organization. You are literally going up and down the organization, but always taking everything back to the Executive Sponsor to surface your findings along the way. Here's a breakdown of the framework: 🎯 𝐈𝐚𝐧 𝐊𝐨𝐧𝐢𝐚𝐤’𝐬 “𝐘𝐨-𝐘𝐨 𝐒𝐞𝐥𝐥𝐢𝐧𝐠” 𝐅𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤 This strategy involves a three-step process: 1. Start at the Top (Executive Engagement) Initiate contact with a senior executive to understand their most pressing challenges, the reasons behind the need for change, and the consequences of inaction. If your solution aligns with their needs, secure their sponsorship for further discovery within their organization. To secure the Executive Meetings, it's essential to create a tailored POV (point of view) on where you think you may be able to help them based on your initial research of their highest level goals and priorities. Chat GPT has made this research a LOT faster now. 2. Conduct In-Depth Discovery (Middle Management) Engage with department heads and key stakeholders to uncover the day-to-day challenges they face. Focus on understanding their processes, pain points, and the implications of current inefficiencies. Gather direct quotes and insights to build a comprehensive view of the organization's needs. 3. Return to the Executive (Present Findings) Compile the insights gathered into an executive summary and business case. Present this to the executive sponsor, highlighting how your solution addresses the identified challenges. Tailor your demonstration to focus solely on relevant aspects that solve their specific problems. 🚀 Why It Works 1. Accelerates Sales Cycles: Engaging executives early ensures alignment and expedites decision-making. 2. Builds Credibility: Demonstrates a deep understanding of the organization's challenges and showcases a tailored solution. 3. Facilitates Internal Buy-In: By involving various stakeholders, you ensure that the solution meets the needs of all parties, increasing the likelihood of adoption. I'm pleased to share that that Yo-yo selling was recently awarded as a Top 15 Sales Tactic of All Time by 30 Minutes to President's Club, and I received a cool plaque for entering the 30MPC Hall of Fame. Since I have no chance of entering the Hall of Fame for my baseball or golf game, this is a nice consolation prize 😁

I’m extremely bullish on account-based GTM motions in 2026. As AI makes generic outreach cheap and ubiquitous, differentiation comes from precision, relevance, and deep context around a small set of high-value accounts. This sounds wonderful on paper until it’s time to set up a modern account-based GTM engine. IYKYK. For help I turned to Dan Rosenthal from Workflows.io. They’ve set up 250+ GTM systems including dozens of ABX implementations over the past year. Dan put together what I think is the most comprehensive & useful guide to *modern* ABM with HubSpot, Claude Code, Clay & best-of-breed tech. Read the full deep dive in Growth Unhinged here: https://lnkd.in/eyF9bgyb There are 7 steps — follow these in this order: 1️⃣ TAM & stakeholder mapping Dan recommends combining 3+ data sources to reach 90%+ of TAM coverage w/o blowing through your budget. AI research agents help qualify the list based on website content & do the merge/de-dupe. 2️⃣ Account research Most companies Dan works with gather 30+ custom data points with Claude Code & MCPs. Some interesting ones: closest coffee shop next to their office, competitor tech usage. 3️⃣ CRM cleanup & enrichment Nobody’s favorite step, but you can’t skip it. 4️⃣ Signal tracking Intent signals are hot. Reps also don’t trust a lot of them. And many signals have commoditized. The most valuable signals are from your first party data (website visitors, gated content, product usage, event attendance, outreach replies, etc.). 5️⃣ Awareness scoring If you embrace ABX, you need a way to see where you stand with your target accounts (no, MQLs/SQLs don’t work). Identified > Aware > Interested > Considering > Evaluating. 6️⃣ Demand generation With the scoring in place, reps can focus on the warmest accounts who already show interest. Use a mix of 1:1, 1:few, and 1:many campaigns. (Pro-tip: Dan says event invites have been a great CTA in outbound.) 7️⃣ ICP pipeline progression reporting Success can be harder to quantify w/o an arbitrary MQL goal. The upside: you’re now collecting far richer data about what resonates with your target accounts. — I hope you find this guide as useful as I do. Let me know what you think 🙏 -KP

The 2025 Account-based Marketing Playbook I'm rebuilding the ABM motion for a unicorn SaaS. Here's exactly how: 1️⃣ Total Addressable Market Map You should have data on every company in your ICP. In this case: ↳ Their Salesforce CRM had 2500 accounts ↳ Sourced from ZoomInfo + Cognism ↳ We did a CRM download. ↳ Added industry matches scraped from the internet using DiscoLike. Meaning we had WAY more accounts. But not all were qualified. 2️⃣ Develop ICP model Few companies study their ICP like a science: ↳ Analyze closed won for signal trends. ↳ Study highest-spend customers. ↳ Find commonalities among closed-lost. ↳ Backtest model against closed won. Now, you have a model to score your TAM map. 3️⃣ Account research + company scoring The point of ABM is that you focus on the right accounts: ↳ Automate account research using Clay. ↳ Deploy research agents to scrape info from websites. ↳ Add enrichments from data providers. ↳ Feed data into AI scoring prompt. ↳ Categorize accounts into Tier 1, Tier 2, Tier 3, and unqualified. Send data on qualified accounts back to the CRM. 4️⃣ Find relevant contacts at company Multithreading is key when it comes to ABM: ↳ Use Clay, Apollo.io, or Icypeas to find people by title. ↳ Key decision makers are Tier 1. ↳ Management end-users are Tier 2. ↳ Operational end-users and Tier 3. ↳ AI scoring prompt to categorize. Big deals require buy-in from all three tiers. 5️⃣ Track first- and third-party signals This is to prioritize accounts when timing is right. 1st party signals: ↳ Outreach replies. ↳ Data straight from your CRM. ↳ Ad insights w/ Fibbler, Vector 👻, or Influ2. ↳ Product usage w/ Amplitude, Mixpanel, or Heap. ↳ Website visits w/ Warmly, RB2B, or MeetVisitors. ↳ LinkedIn signals w/ Common Room, Teamfluence™, or Trigify.io. This makes up your engagement score: ↳ Aware (0-40), Interested (41-70), Evaluating (71-100) 2nd party signals: ↳ Review sites like G2, Capterra, or ColdIQ. ↳ Champions w/ LoneScale, UserGems 💎, or Champify. ↳ Tech integrations w/ Crossbeam, PartnerStack, or Reveal. 3rd party signals: ↳ Job openings w/ Clay, PredictLeads, or PDL. ↳ Funding w/ Crunchbase, PitchBook, or Owler. ↳ Company initiatives w/ Clay, Serper, or 10-K reports. ↳ People changes w/ Clay, LoneScale, or UserGems 💎. ↳ Tech stack w/ BuiltWith, HG Insights, or Wappalyzer. ↳ Social signals w/ PhantomBuster, Trigify, or Common Room. These make up your intent score: ↳ Low (0-40), Medium (41-70), and High (71-100) 6️⃣ Composite score and CRM enrich In Clay, this data is composited into one priority score. And sent back to the CRM. 7️⃣ Segment actions based on scores Strategy for Tier 1 acquisition: ↳ 1:1 outreach ↳ Focused ad spend ↳ Event invites + warm intros ↳ Personalized videos + landing pages For Tier 2 and 3s, you can automate: ↳ Email outreach w/ Instantly.ai ↳ Linkedin outreach w/ HeyReach ↳ Multichannel sequences w/ lemlist Comment if you'd like the full res graphic 👇

I just watched an AE lose a $1.2M deal after running a "successful" product trial that the prospect LOVED. After 8 weeks of work, the CFO killed it with five words: "Let's try our current vendor." This happens because most reps treat trials as product demos instead of what they actually are: RISK ELIMINATION EXERCISES. After analyzing 200+ enterprise sales cycles at companies like Salesforce, HubSpot, Thomson Reuters, and Workday, I've identified the exact framework that separates 80%+ trial conversion rates from the industry average of 30%. Here's what most reps get wrong: They skip qualification and jump straight into the trial. Big mistake. Before any trial, ask these 3 questions: → "What happens if you don't solve this problem in the next 90 days?" → "How have you tried solving this before?" → "Who else is affected by this problem?" These eliminate 68% of unqualified trials before they start. Next, define success upfront: → Technical requirements that must work → Business metrics they expect to see → Timeline for implementation → User adoption patterns needed Get confirmation: "Just to confirm, if we demonstrate these criteria, you'd be ready to move forward with purchase by [date]. Correct?" Map every stakeholder: → Technical buyers (include every trial user) → Economic buyers (CFO/budget holder) → Political influencers (who can kill deals) → Current solution advocates (who benefits from status quo) For each person, document their personal win/loss scenarios. Have legal review agreements BEFORE starting trials. "We typically have legal review the agreement structure ahead of time so there are no surprises later. Would you be open to having them review a blank agreement while the trial is running?" Finally, handle the current vendor objection upfront: → "Have you discussed these challenges with your current vendor?" → "What was their response?" → "What specific capabilities do they lack?" Document these answers to build your business case. Results from this approach: ✅ Trial conversion: 32% to 83% in 60 days ✅ Deal size increased 40% ✅ Sales cycle shortened 37% ✅ Forecast accuracy improved 92% ✅ 43% less time on unsuccessful trials Stop running trials. Start running risk elimination exercises. — P.S. Sales Leaders, want to ACTUALLY move the needle in your org and find an extra $2 to $10 million of hidden revenue? Go here: https://lnkd.in/gDexefD5

Client: "We need to focus our ABM on the big names in the industry. You know, the Fortune 500 types." Me: "So, what makes them a good fit for your business?" Client: "Well, they're big and have big budgets." Me: "Okay, but do they need what you offer? Are they a good fit for your ideal customer profile?" Client: "Hmm, I'm not sure... We haven't looked at it that way." Me: "And what about potential value? Will those big names bring in the most revenue? Or are there smaller, faster growing companies with more potential?" Client: "That's a good point. We haven't considered that." Me: "And strategically, does it make sense to go after those giants? Or are there smaller companies that align better with your long term goals?" Client: "Hmm, I see what you mean." Me: "Let me put it another way: Have you ever seen a small company achieve amazing results with a product like yours?" Client: Thinking.. "Actually, yes! There's that one company..." Me: "Exactly. Account selection in #ABM isn't just about chasing big names. It's about finding the best fit for your business, potential value and strategic alignment." Client: "Tell me more..." Me: "Don't get me wrong, big accounts can be great. But those smaller accounts can sometimes bring surprising value and become your biggest wins." Client: "This is making me rethink our entire strategy." Me: "That's the idea. ABM is about finding the accounts that will benefit from your solution and align with your long-term goals." Client: "So, how do we find those accounts with potential?" Me: "Dig deeper. Look beyond size and revenue. Consider their needs, growth potential and their strategic fit. Sometimes, the hidden finds are the most valuable." Client: "This is eye opening. I'm excited to explore this further." Me: "Great. Think over quality over quantity." #b2bmarketing #demandgeneration #marketingstrategy

Your reps aren't losing deals because of bad messaging. They're losing because they're calling the wrong accounts. Here's one play/signal that is ensuring we go after the right accounts as an AI GTM platform (converting at 3x standard outbound): Companies hiring for AI roles adopted AI 2x faster last quarter. Translation: an open AI role is a buying signal if you action on it properly and couple it with first party data. Here's the play we run on it: 1. Filter to your patch Cross-reference your territory with a live AI-hiring signal. Example: California companies + an active AI/ML req. 2. Score the fit Pre-built GTM skills run account research on every match and rank them. Your reps stop guessing who to work first. 3. Find the warm thread Pull usage data from Snowflake to spot past power users, not just someone who worked at a previous customer, who now works at the target company. A former champion in a new role beats a cold contact every time. 4. Mine first-party context Surface use cases, relationships, and objections from CRM notes, Gong calls, and product usage. 5. Generate the outreach AI writes from the full account context: new role, hiring signal, prior exposure. Not "I saw you're hiring." Something they'd actually reply to. You now have a list of accounts that are more likely to be in-market, have previous power users, and you have the context of any previous conversations. That’s a list that will convert.

I’ve built and led sales teams from scratch. And there’s ONE channel I see revenue leak over and over again... (and it’s not that £50k event you spent scanning badges at a stand…) It's here.. Yep.. surprise surprise it's LinkedIn. Every team I look at, it’s the same pattern. Strong outbound. Decent process. But then you open the team on LinkedIn… and there’s no surface area. The problem is your outbound is a single touchpoint. Your LinkedIn presence is the environment that touchpoint lands in. And most teams optimise the first and ignore the second. If you want this to actually move pipeline, it needs to be treated like part of sales execution: 1. Stop thinking “posting”. Start thinking “account exposure” Your reps shouldn’t just post into the void, they should be visible around the accounts they’re targeting. That means: • commenting on ICP posts consistently • engaging before outreach (not after) • showing up in the same feed as their prospects You’re building recognition before you ever send a message. 2. Tie content directly to live deals Most content is generic because it’s disconnected from reality. Your best content is already in your pipeline: • objections that keep coming up • questions prospects ask on calls • where deals get stuck f it’s happening 5+ times in conversations, it should exist on LinkedIn. 3. Build “minimum viable profiles” across the team You don’t need creators, you need profiles that answer, fast: • what do you understand? • who do you help? • how do you think? Recent activity matters more than old experience. If someone lands on the profile and sees nothing recent, you’re back to zero. 4. Align posting with outbound waves Most teams treat these separately. Better approach: • rep warms up a segment (engagement + content) • then outreach starts • then content reinforces during follow-ups You’re not relying on a single moment anymore. 5. Don’t isolate this to SDRs Here is the BIG mistake. Your AE gets checked before the call, your manager gets checked mid-deal, if visibility drops at any stage, trust drops with it. This needs to be across the WHOLE sales chain. 6. Measure leading indicators differently You won’t see this purely in “likes”. Look at: • connection acceptance rates • reply rates by rep • speed to first response • profile views from target accounts • conversion rate • and of course inbounds (yes DO add UTM links on each sales rep profile) 7. Prioritise comments over posts early on Everyone focuses on posting. But comments: • get you in front of the right people faster • attach you to existing conversations • build recognition without needing distribution Most teams are still trying to win inside the sequence. The edge right now sits outside of it. If your team has no presence on LinkedIn, every outbound starts from zero. If they’re visible in the right places, outbound becomes a conversion layer, not just an entry point. That’s where the difference is 👌🏼

Here's a breakdown of what an Account-Based Sales model looks like. Designed to drive up win % while landing logos at a higher ACV $ upfront. The big idea: every deal gets a tailored set of account-specific docs, guiding a customer's buying process from problem → outcome. _____ → STAGES & FRAMEWORKS: - BDR/AE's collab on a research-backed POV + draft account plan ↓ - Which drives tailored outreach to engage buying teams execs early ↓ - Buying group collabs on a problem statement, mapped to the priority ↓ - SE's get a pre-demo brief, with a storyline scripted around this ↓ - AE's customer inputs above into a full biz case with target outcomes ↓ - Sales leaders get a written deal brief to spot gaps in < 60 seconds ↓ - Go-live plan shows a path from commercials to customer outcome ↓ - CS gets a handoff doc to guide transition post-sales ↓ - AM's get a written case for expansion to drive upsells Here, you're capturing each customer’s journey in a set of “living” docs that evolve and flow into each other: POV ↓ Account Plan ↓ Demo Brief ↓ Business Case ↓ Leader's Deal Brief ↓ Mutual Success Plan ↓ CS Handoff Doc 100% tailored for each account. Grab a set of editable frameworks for these here: https://lnkd.in/gG3XRbT2 ______ → PRINCIPLES: Written docs are the “container” your process lives in, because: (1) Content = context. Think of it like those Russian nesting dolls — each doc has context from the last doc nested inside the next one. e.g. POV drives a problem statement, that sits in the full biz case, which is context for a go-live plan, etc. (2) Content is evidence. It’s concrete, not abstract: - Less, "It was a good meeting, they're interested." - More, "Here are redlines adding data to our problem statement." It’s how we see where, exactly, a customer is in the buying journey. While making it visible to everyone. (3) Content is influence. It's in the room when you can't be. Scripting internal convo's happening about you, without you. ______ → EXECUTION: This isn't just for key accounts. It scales downmarket, too. It's why Fluint's AI is built around the first "living doc" that writes, learns, and redlines itself inside every deal  (see it here: fluint.io ) Letting you treat every account, like a key account.

It’s time to stop thinking like it’s 2005. Correlation may flatter your GTM story, but only causation proves impact. More than 80% of companies missed their sales forecast in at least one quarter over the last two years (Gong, 2024). In H1 2024, 49% of companies missed their revenue goals (GTM Partners Benchmark Report, 2024). At the same time, executives keep putting faith in attribution models that only tell a sliver of the story. 𝗛𝗲𝗿𝗲’𝘀 𝘁𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺: too often, data is interpreted in ways that confirm existing assumptions rather than test them. Harvard Business Review found that sales leaders are frequently blindsided by overinflated forecasts driven by “all-too-human behavior” (Harvard Business Review, 2019). GTM Partners research shows that poor data quality can cost companies up to 25% of annual revenue, yet 60% don’t even measure these costs. That’s value leakage every CFO cares about. It’s time to fix this. Here are 5 ways to make GTM decisions actually data-driven: 1. 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗻𝘂𝗹𝗹 𝗵𝘆𝗽𝗼𝘁𝗵𝗲𝘀𝗶𝘀: Harvard Business Review notes that “consistently accurate sales forecasts are rare because many companies fail to align their sales and marketing departments.” Assume your campaign 𝘸𝘰𝘯’𝘵 work—then try to prove yourself wrong.     2. 𝗥𝘂𝗻 𝗽𝗿𝗼𝗽𝗲𝗿 𝗶𝗻𝗰𝗿𝗲𝗺𝗲𝗻𝘁𝗮𝗹𝗶𝘁𝘆 𝘁𝗲𝘀𝘁𝘀: Compare your marketing results to a control group to see the actual lift your efforts create. MIT Sloan warns that confirmation bias leads us to “interpret ambiguous facts in light of preexisting attitudes.” Stop crediting natural growth to your LinkedIn ads.     3. 𝗕𝘂𝗶𝗹𝗱 𝗿𝗲𝗱 𝘁𝗲𝗮𝗺𝘀 𝗳𝗼𝗿 𝗺𝗮𝗷𝗼𝗿 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀: MIT Sloan recommends bringing together “different perspectives on the same issue” because organizational biases cloud interpretation. Create space for contrarians—the risks of blind spots are too expensive to ignore.     4. 𝗧𝗿𝗮𝗰𝗸 𝗹𝗲𝗮𝗱𝗶𝗻𝗴 𝙖𝙣𝙙 𝗹𝗮𝗴𝗴𝗶𝗻𝗴 𝗶𝗻𝗱𝗶𝗰𝗮𝘁𝗼𝗿𝘀: Research shows the average B2B buyer has ~31 touchpoints with a brand before deciding (Dreamdata, 2024). Your last-touch attribution is missing most of the story.     5. 𝗣𝗿𝗲-𝗿𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝘆𝗼𝘂𝗿 𝗲𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁𝘀: Record in advance your testing methodology and success criteria. This prevents “analysis after the fact” bias and ensures accountability when results don’t fit expectations. 𝗕𝗼𝘁𝘁𝗼𝗺 𝗹𝗶𝗻𝗲: If your data never challenges you, it’s not science; it’s storytelling. The companies that break through are the ones willing to let the data argue back. What’s the most obvious confirmation bias you’ve seen in GTM? #GTM #MarketingLeadership #causalinference