Rob Charlebois

So many #Startups book office hours with Kevin Maney and I because they are struggling with their #CategoryDesign strategy. 7 times out of 10 they are stuck on a category name. And we tell them to forget the name, focus on their category point of view first. Once you understand the problem you solve, the ramifications of not solving it, and the outcomes of solving it...then the name becomes obvious! Wait for the drop the mic moment! If you're ready for the name...here are some tips:

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Top One Percenter Academy is on track to hit our Best Case scenario forecast this Quarter. It's a modest Best Case Quarterly ARR amount that pales in comparison to what I am used to forecasting when I was working for someone else. But that’s why this feels so much better. Because it’s no longer someone else’s number. It’s not hitting the number that feels the best anymore. It’s how we are able to hit the target that feels amazing. It’s a great sign when: - 1 new Q1 customer bought 100% more within 90 days of the initial purchase. - 3 new Q2 customers all separately talked about wanting us to create a similar module for leaders they can purchase next. All within their 60 days of purchase. - Multi-year deals are the norm now - Customers are raving about the partnership within the 1st 2 weeks of kick-off - Every customer offers to be a reference for us anytime - Customers from $30M ARR to $700M ARR are all seeing success - ASP is increasing - Companies are voluntarily introducing us to their VC or PE firms - VCs and PE firms are voluntarily introducing us to portfolio companies - CROs are presenting one or two slides to their boards about us Customers are already excited only a week or two after kicking off with us. They see -their sales reps are getting better. -immediate improvement. -ongoing improvement week over week. -more reps being successful. I love watching our customers' salespeople go through their repetitions. Knowing their competitors are falling further and further behind every single day. There is no way the competition is making their sales reps master their sales craft like this. Not a chance their competitors' sales reps are working to get better with this level of detail, precision and dedication. I love knowing one day soon our customers’ competitors will wonder how they fell so far behind so fast. They will think it all happened overnight not knowing it's been happening every day for months. #toponepercenter #sales #compete

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Why some SaaS companies 🚩 struggle to grow on cloud marketplaces? These 5 root causes may not be what you expect. 1️⃣ Strategic Cloud GTM Misalignment The most critical blocker isn’t technical—it’s strategic. Many companies treat cloud marketplaces as "just another channel," but success demands a fundamental GTM shift. Winning in cloud marketplaces requires embracing a partner-led, customer-centric, consumption-focused model where you align with the cloud provider’s priorities—not the other way around. You’re entering ecosystems of Amazon Web Services (AWS), Microsoft Azure, or Google Cloud as their partner, not the reverse. 2️⃣ Cloud & Customer Centricity Gap The "build it and they will come" approach fails spectacularly on marketplaces. Successful ISVs deeply embed themselves in the cloud ecosystem by: Mapping their solution to the cloud provider’s growth areas and strategic initiatives. Understanding how and why customers discover, evaluate, and buy solutions in cloud marketplaces and on each cloud platform. Aligning GTM motions with the cloud provider’s sales cycles and engagement models. 3️⃣ Immature Co-Sell Many SaaS companies struggle with co-sell readiness, held back by ingrained direct sales cultures, concern of conflict (channel/competition) and lack of Cloud GTM understanding. Incentives: Sales teams aren’t motivated (or de-motivated) to collaborate with cloud reps or sell through marketplaces. Value Proposition: SaaS companies fail to articulate how their solution complements the cloud provider’s offerings and drives customer value. Program Knowledge: ISVs often miss out on cloud program benefits because they don’t meet requirements or focus enough on eligibility. 4️⃣ Lack of Alignment and Internal Resistance The most insidious obstacle often comes from within: Siloed Departments: Sales, marketing, product, and finance don’t collaborate effectively, hindering a unified marketplace strategy. Leadership Gaps: Executives may not fully grasp the strategic importance of cloud marketplaces, leading to misaligned priorities or underinvestment. Not leveraging marketplace data and insights and not integrating MP into your sales and company operations 5️⃣ Cloud-Native Product Reality Success on cloud marketplaces goes beyond GTM strategy—your product must also be ready... Ideally its architecture should leverage cloud-native services to enhance consumption and scalability. 📈 What This Means The gap between leaders and laggards in cloud marketplaces is widening. Those who treat Cloud GTM as a transformation, not just another sales/partner channel, are experiencing rapid growth. Others risk being left behind in what’s quickly becoming the largest software distribution channel. 💡 What’s the biggest obstacle you’ve encountered? _________ PS. Accelerate your #growth on #cloud marketplaces with Cloud GTM Leader Course. Last chance to join Cohort 9 starting Jan 14th (tomorrow) - https://lnkd.in/ejc7S4Pb

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The secret to getting 25-100X more customer feedback (...and it's not lengthy surveys) Most companies struggle to get meaningful customer insights. The industry average response rate for NPS is a measly 1-4% once a year. But TheySaid is getting 11-14% response rates 12-16 times per year! How? 3 key things: 1️⃣ Personalized questions — We only send 1 question per customer. It's tailored to their role and stage, asking about what THEY care about. 2️⃣ Respect their time — Customers will give you 5 seconds, not 30 minutes. Keep it short, sweet, and relevant to them as a human being. 3️⃣ Close the loop — The #1 reason customers don't give feedback is they think you won't act on it. We built a system to action EVERY response within 2-24 hours. When you ask personalized questions, respect their time, and show you're listening... You create a positive cycle of customers giving feedback and getting better service & value. It's a win-win! But generic NPS surveys that only benefit the company? Forget it. Customers just don't care. If you want to learn how to get exponentially more customer insights... Watch this video breaking down the 3-part formula:

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#gtmopsdebates: Is is harder to get GTM/Rev Ops projects complete in 2024 vs. 2014? My POV: TLDR: Yes. For many reasons. But one counterintuitive reason is the amped-up pressure since 2021 on SaaS causing: (1) More stakeholders. CFOs, senior leadership, and other executives are stepping into conversations they weren’t involved in before. Everyone wants a say. This leads to more opinions and priorities to navigate. (2) Slower decision-making. When more people get involved, the decision-making process slows down. Approvals take much longer. (3) Higher expecations on the outcomes. To get approval to work on a project the Ops teams have to justify the hell out of it. Then, after putting their neck on the line, they are under intense pressure to make sure it lives up to expectations. And too much pressure can lead to micromanagement and overthinking. (4) Less budget for projects. Less budget means less expertise available for the project. This leads to missteps, repeat attempts, and mistakes. Now, there is a solid counterargument that this is all good and necessary. It's good to: Only work on mission-critical work. Get more stakeholders in the room. Have high expectations. Be budget-conscious. BUT it can make projects harder to compete. It's the classic: FAST, GOOD, CHEAP. You can only have two. So if you want GOOD + CHEAP, you can't have FAST. p.s. I'd argue that most B2B SaaS companies need GOOD + FAST. So they need to get used to giving their Ops teams the resources they need.

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A poorly executed #customersuccess strategy will kill your #NRR for years to come. I've seen it first-hand too many times over the years. Here is how you deliver a well-executed CS strategy to drive great NRR and ultimately, business growth: 🛣️ 𝐔𝐬𝐞 𝐭𝐡𝐞 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝐑𝐞𝐯𝐞𝐧𝐮𝐞 & 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐉𝐨𝐮𝐫𝐧𝐞𝐲 The first step in any customer success strategy is understanding the full & dynamic revenue & customer journey. This means not just knowing what your customers do, but why they do it. How and why did they buy your services? How do they move through their journey with you (rarely ina straight line!)? By understanding their motivations, you can better anticipate their needs and deliver solutions that truly add value. And don't forget, the old-school customer journey is not the standard anymore, you need to use the full, dynamic revenue & customer journey to get the full picture. This stretches from pre-sale to post-sale and allows for the customer to move in and out of journey phases/stages dynamically. 📈 𝐏𝐫𝐨𝐚𝐜𝐭𝐢𝐯𝐞 𝐄𝐧𝐠𝐚𝐠𝐞𝐦𝐞𝐧𝐭 Customer success is not a reactive function. It's about being proactive, anticipating customer needs, and addressing them before they become issues. You have to ensure that your strategy is aligned around, and fosters, a proactive CS culture and process that allows your team to execute effectively. This not only improves customer satisfaction, but also reduces churn, and creates more expansion opportunities. Both key factors in improving NRR. 📊 𝐃𝐚𝐭𝐚-𝐃𝐫𝐢𝐯𝐞𝐧 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐌𝐚𝐤𝐢𝐧𝐠 In the #SaaS & #CS world, we have access to a wealth of data. By leveraging this data, we can make informed decisions that drive customer success. This could be anything from identifying usage patterns to predict churn, to understanding which features drive the most value for customers and beyond. And it needs to go beyond telemetry, usage etc. Also capture, track and understand customer goals and other qualitative data points. One problem is that this data is often siloed or hard to access, so make sure you have systems (like RevSetter) that can bridge that gap and allows CSMs to effectively action the data & insights. 🤝 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐚 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫-𝐂𝐞𝐧𝐭𝐫𝐢𝐜 𝐂𝐮𝐥𝐭𝐮𝐫𝐞 Customer success should not be the responsibility of a single department. It should be ingrained in the company culture. When everyone in the organization understands the value of customer success, it becomes a strategic priority that drives business growth. This is why the dynamic revenue & customer journey, the engagement focus, and the proactive mindset are so important. When those are present - and a strategic & customer-centric approach is adopted by the CEO & leadership - the sky is the limit. Leverage these four building blocks and your CS strategy and execution will thank you for it ✅ *** 🛎️ If you enjoy my content, follow me for more ♻️ Repost to share with your network

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Struggling with SaaS growth? Here are 4 challenges to tackle immediately

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25% of ABM programs are built on Quicksand! Forrester’s account-based Marketing(ABM) report's key takeaway was that one in four ABM programs is designed for failure. You may ask why ABM is important. According to a Gartner study, ABM lifts several vital sales metrics, including a 28% increase in overall account engagement and a 25% rise in the MQL to SAL conversion rates. But, misconceptions about ABM can hinder its effectiveness. Here’s an excellent ABM failure list by Gabe Rogol, CEO of Demandbase, based on observation of over 1,000 ABM programs. Two things which resonated with me were -  ▶️ ABM should be CEO-driven, not just a marketing tactic and   ▶️ Integrating ABM into the entire tech stack Two things which can be added IMO are- 1️⃣ 1-to-1 ABM programs should be run if the ACVs exceed 1M; otherwise, it's a wasted effort. 2️⃣ ABM is not just Sales and marketing alignment. To derive the maximum benefits, it must cover the product team and customer success. What has been your ABM experience? Do share your thoughts

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🔥 SaaS GTM Strategy Hot Take – Do ABM buying stage models using intent data work? The short answer is yes. 🧐 Consider This Statistician George Box famously quipped, “All models are wrong, but some are useful.” This seems to be true with ML-based buying stage models. They are not perfect, but they can be quite useful. In simple terms, a buying stage model is designed to predict the likelihood of an outcome occurring, in this case, a qualified opportunity being opened. It’s just a more sophisticated version of the old-school MQL scoring model made popular by the MAP platforms. Those were rule-based models using limited data and based on intuition and opinion. Today’s models leverage thousands of intent signals from third-party sources and your marketing programs, website, and CRM programs. They weigh the frequency, recency, and volume of the intent signals. And they’re dynamic: The model adjusts as more input data is provided and outcomes occur. 💡 Rethinking Your Strategy Of course, your marketing and sales teams should prioritize an ICP account that shows surging engagement on your website. If you have a strong brand in the category, at any point in time, that may be about 5% of the total Serviceable Addressable Market (SAM). What should you do with the other 95%? Especially if, according to @6sense research, 84% of them will have a favorite in mind when they contact your sales team. 🚀 Creating Pre-Purchase Preference 🚀 By leveraging a combination of ICP and Buying Stage segmentation, you can run campaigns to help your potential customers understand the “why change” and “why now” aspects of your solution. You can provide them with clear criteria for solving their problem and arm them with the value drivers for the business case. And, maybe give them some FOMO by showing name brands who’ve been successful in doing it. 🤔 Still Skeptical? 🤔 The great thing about models is that we can backtest them. That is, we can run the model on a known set of inputs and outcomes and see how effective it was at predicting the results. It’s not uncommon for good buying stage models to be 3-5 times more predictive than ICP targeting alone. The image below shows one such ABM program, from initial account targeting to increasing intent and a closed-won deal. Total time: less than six months for a $100K ARR deal. 💰💰💰 💬 Let's Discuss ❓What programs are you running for ICP accounts that are not yet “in-market”? ❓What intent data sources are proving to be more valuable than others? ❓Are your sales teams leveraging the intent data signals to inform their outreach messaging and strategies? ——— 👍 Like this? 🤔 Comment to share your thoughts ♻  Repost to share with your network #abm #b2bmarketing #saasgtm #gtmstrategy #b2b #tam #gtmalignment #pointbreakgtm

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🔥 Hot Take: Traditional attribution is dead for #ABM, and inbound attribution is next on the chopping block. Here's why everyone's getting it wrong: We're still trying to force-fit MQL/SQL metrics into ABM when the reality is messier. Your target CTO didn't magically decide to buy after clicking that one LinkedIn ad. They probably talked to 3 peers at an event, read 7 dark social posts, and had 5 offline conversations before even hitting your website. The truth? Multi-touch attribution for ABM is a myth we need to kill. Instead of obsessing over "which touch drove the deal," smart companies should measure: 👉Account engagement velocity: Track frequency/depth of interactions across all stakeholders over specific timeframes with tools like Demandbase, Terminus (by DemandScience) etc. 👉 Buying group awareness: Monitoring key decision-maker content engagement, event attendance, and platform interactions with tools like SparkToro, CleverTap, Eventbrite etc 👉 Dark social mentions: Track branded conversations in private channels using employee/customer relationship networks and tools like Mentionlytics, BuzzSumo etc. 👉Competitive displacement indicators: Monitor competitor-comparison searches, RFP indicators, and tech stack changes with some new tools like Reo.Dev (for dev tools) and Semrush / Ahrefs equivalents. 👉 Intent signal clusters: Aggregate behavior patterns showing spikes across multiple buying group members with a mix of the tolls mentioned above and add open source and publicly available data to build an internal intent signal source. But here's where it gets interesting... AI is about to flip inbound attribution on its head too. When 70% of top-of-funnel content is AI-generated and every company has similar SEO optimization, the old "track everything" approach falls apart. Only those with the ORIGINALS will win. What does that mean? 👉 Unique data/insights only your company has 👉 Original research and thought leadership 👉 Social proof and community engagement 👉 Brand strength and authority signals 𝐓𝐡𝐞 𝐟𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐁2𝐁 𝐚𝐭𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧 𝐢𝐬𝐧'𝐭 𝐚𝐛𝐨𝐮𝐭 𝐭𝐫𝐚𝐜𝐤𝐢𝐧𝐠 𝐦𝐨𝐫𝐞 𝐭𝐨𝐮𝐜𝐡 𝐩𝐨𝐢𝐧𝐭𝐬 - 𝐢𝐭'𝐬 𝐚𝐛𝐨𝐮𝐭 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐛𝐮𝐲𝐢𝐧𝐠 𝐠𝐫𝐨𝐮𝐩 𝐛𝐞𝐡𝐚𝐯𝐢𝐨𝐫 𝐩𝐚𝐭𝐭𝐞𝐫𝐧𝐬 𝐚𝐧𝐝 𝐢𝐧𝐭𝐞𝐧𝐭 𝐬𝐢𝐠𝐧𝐚𝐥𝐬 𝐁𝐄𝐅𝐎𝐑𝐄 𝐭𝐡𝐞𝐲 𝐞𝐯𝐞𝐫 𝐡𝐢𝐭 𝐲𝐨𝐮𝐫 𝐫𝐚𝐝𝐚𝐫. ( what do you think, Emir Atli) Debate-worthy Prediction: By 2028, traditional marketing attribution platforms will be replaced by AI-powered intent intelligence systems that can predict purchases before the first form fill. Time to rethink everything we know about measuring marketing impact. Happy to chat and debate this with you over a call on my topmate.io/rapti 😂 Thanks for sparking this post Rejoe🤘 #B2BMarketing #AI #Attribution

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Product Marketers are naturally positioned to be the next Chief Strategy Officer, not CMOs. Why? While PMMs navigate the tactical marketing landscape (CMO territory), their strategic DNA runs deeper. They: - Sit at the intersection of product, market & customer - Drive business model decisions through pricing & GTM strategy - Are naturally inclined toward long-term strategic planning - Build frameworks that shape organizational direction Look at today's CSO priorities: 📈 Strategic initiative success 🛠️ Business model innovation ⬆️ Market expansion 👀 Staying ahead of disruption Sound familiar? This isn't aspirational - it's the daily reality for senior PMMs. The modern product marketer isn't just crafting value props – they're designing company futures. While CMOs excel at driving immediate business impact (crucial, but different), PMMs are inherently wired for strategic transformation. Thoughts? Would love to hear from PMMs who've made either of these leaps…

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B2B tech companies: WE'RE DATA-DRIVEN! But also: - We only have one person owning GTM data quality (+ million other things) - Our execs don't trust the reports - Our SFDC data/process = chaos So in reality: - Our SFDC reports haven't been refreshed since 2019 - Our whole team does excelympics every month for the board reporting - The tenure on the revenue teams is <1 year because everyone is burned out Fixing the data isn't easy. But it's not impossible. The first step is making sure you have the team to build what you need. Either internally or internal + external. A team that has the skills and is incentivized AND enabled to make the changes necessary (often an important piece that gets missed). You really can get to a better place where you have reliable data to make decisions. It just takes some effort and focus. #gtmoperations #marketingoperations #revenueoperations  

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Many optimization teams rush into A/B testing, missing critical steps that can significantly impact CRO success. Skipping these non-negotiable processes could lead to: - Wasted time - Drained resources - Missed opportunities Swipe to see the top 5 things to do when optimizing your page:

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Subject Line Pattern: 3+ words, selling, invites, my name Subject Line Pattern Interrupt: One word Preview Text Pattern: "Hi Will, I..." Preview Text Pattern Interrupt: "Looks like {thing}" Just do the opposite of bad.

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It's much riskier to NOT employ a nearbound/ELG approach to finding and winning customers. Still, it's perceived as risky by many following old GTM scripts. If you're going to take a risk as a GTM leader (you should), you need some data in your quiver. Luckily, the wonderful people at Crossbeam and Pavilion have joined forces to help get you some flaming arrows of data. If you're a GTM leader, jump in and help with this effort, and get early access to the data. Survey below!

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The GTM AI gold rush will fail if companies forget the BORING stuff. AI use cases need a well-architected foundation & data. 3 examples: (1) Want to set up an AI SDR to do personalized outreach? > You need to collect, standardize, and surface data on the buyer and their signals the right way. Otherwise the messaging will be crap. (2) Want to use AI to ask analytics-related questions (like what channel is performing the best)? > You need to collect the channel engagement data, tie the buyers to opportunities the right way, etc. Otherwise, the "insights" will lead you astray. (3) Want to set up a predictive AI account score? > You need to have a quality account database in CRM, set up integrations with enrichment tools & scoring tools, set up a method to highlight the top accounts for sales to work, and train your sales team. Otherwise, the score will be wrong and not trusted by sales. The requirement to not have a shitty foundation has never been greater in this AI era. And right now, AI can't do the job of fixing your data and architecting your foundation. That is up to your Ops team. So, by extension, your Ops team has never been as important as they are right now (if you don't want to be left behind by your competitors leveraging AI).

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The Ultimate GTM Playbook for High-Growth B2B Companies This playbook helps you answer two key questions for scaling success: 1. Are you ready to advance your GTM to the next level, or is it too early? 2. How can you structure your GTM using proven best practices and benchmarks? #playbook #gtm #growth #scale #product #b2b

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