Xavier Phua

Sellers and sales leaders fail when they obsess with scaling: - More calls - More leads - More emails - More meetings - More opportunities Without nailing: - ICP - Discovery - Messaging - Buyer journey - Value proposition AI makes “scaling” easier and more tempting than ever before. But you are better off to 2x what works than to 10x what doesn’t.

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COPY AND PASTE ⬇️ Steal this plug & play prompt for upsells from Sunny Huang, Director of Strategy at Gong. “i am trying to upsell into this account. identify any challenges we can sell into, or new teams that would want to try gong. for challenges, they need to be challenges that we can sell more existing licenses into, or sell our Engage or Forecast solution against. for new teams, prioritize explicit mentions over just listing other teams that exist at the company. for new teams, also be specific about the use case they're looking for, and the person to talk to. ignore any contractual mentions.” This prompt works like a high-powered metal detector – spotting upsell opportunities that might’ve slipped past you. It’s especially useful for recently transitioned accounts and large internal teams where context can easily get lost. Pro tip: Set your analysis timeframe to focus on recent activity. Companies shift fast, and your insights should reflect that. (In Sunny’s example, he used a trailing 6-month window.)

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Sales reps are flying blind, still, in 2025. And it’s resulting in pipeline targets and quotas being missed. Opportunities you should be working are invisible and time/energy is being wasted on the wrong prospects – whether they’re poor fits or just not in a position to engage. This is signal blindness. In a data-rich world, where the best GTM teams are using data as a competitive advantage, you risk experiencing slow growth and even losing your market. Signal blind orgs either don’t have access to the data/signals that they need or they do, but they can’t surface, organize, or act on data and signals effectively. The good news is, this problem is solvable and Common Room customers are solving it. The bad news is it gets bigger as you grow. So solving it becomes really important early in your GTM maturation journey. We speak with many companies with hundreds of customers and thousands of customer data points, but struggle to operationalize this data. They’re missing key capabilities like: - Spotlighting in-market accounts before competitors - Automatically researching organizations and delivering insights to reps - Quickly prioritizing accounts based on actual buying signals - Building micro-campaigns that are hyper-relevant to target audiences - Rapidly testing different plays and measuring which ones move the needle If you think you might be signal blind, ask yourself: Why are my reps consistently failing to hit their booked meeting targets? Because their outbound messages hit at the wrong time, get ignored, or get sent to spam. Why? Because their messaging isn’t relevant—and they’re not even sure they’re sending it to the right person. Why? Because they’re not incorporating data, signals, and context into their outreach. Why? Because they don't or it's impossible to hunt it down and stitch it together from various point solutions. Or because it’s buried in a spreadsheet or dashboard that can’t be actioned on. Once you get to this point you know you need a scalable solution. You then have 2 options. 1. You can build a better system internally – I’ve tried this. It’s really hard, requires multiple solutions, some dashboarding wizardry, and a lot of process management. 2. You can use a platform like Common Room to sit at the center of your signal strategy and get started immediately on the work of building a revenue engine fit for 2025 and beyond. If not, competitors with 20/20 “signal vision” will pick off opportunities you don’t even know exist. It’s worth asking yourself: How much longer should I let my team fly blind.

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One of the key sales metrics Miro’s Strategic Accounts team is laser focused on is our Walk in Conversion Rate: How much of the total $ value of pipeline we have on Day 1 ends up CW by EoQ. We’ve 3X’d this metric in the past 2 years, are now consistently delivering 40%+, and have gotten it north of 60% in a couple of quarters. We put these improvements down to focusing on 5 things: ➡ A Buyer Centric Sales Process: We redesigned our sales process to align more closely with how our customers make their buying decision and included customer verified exit criteria at each stage. We ‘win the stage’ by achieving a combination of MEDDPICC and customer oriented exit criteria and we don’t skip stages. Not skipping  = more qualified opportunities, fewer deals stalling between S2-S4, increased win rates, average deal sizes, and pipeline velocity. ➡ Customer Centric Deal Qualification: The exit criteria at S1 are designed to ensure the opportunity is anchored in solving a meaningful business problem for the buyer i.e., can we articulate a customer validated problem statement grounded in the 3 Whys and a solid “I”. This helps us qualify out early and often and ensure we don’t invest time in opportunities where a) Miro - as the premium/most sophisticated offering in the market - is not the best option for the buyer and/or b) we would be trying to solve a surface level customer pain. ➡ Tightening our Operating Rhythm: Two major changes we made: 1:Introducing thrice quarterly pipeline scrubs (Week 3, 6 & 10) helps ensure we walk into each quarter with solid pipeline hygiene and 2: Introducing a standing 2.5 hour weekly Deal Review Block on Tuesday mornings, alternating week to week between Top 5 CQ & Top 5 NQ Deals. ➡ Deepening our Partnership with Professional Services: We now involve our PS team from S2 on all opportunities tied to a significant deployment. In these deployments, we’re selling PS assisted workflow transformation vs licenses and - in CoM language - this team are experts in conveying “How We Do It” and “Where We’ve Done it Before”. They help us communicate the business outcomes a scaled Miro deployment can deliver (e.g., ~60% reductions in development cycles for physical and digital products), and increase customers’ confidence in our ability to deliver these outcomes for them. ➡ Decision & Paper Process: Partnering with our Champions to co-create a Mutual Go Live Plan that maps out the steps each side needs to take to deploy the solution by a certain date. This helps us build an accurate understanding of the various steps, stakeholders, and timelines in play, and reduce the chances of a late stage stick in the spokes. Related, Miro was just listed #18 in Forbes Cloud 100. If you’re interested in being part of what we’re building, check out our current openings (link in comments)

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Predictive Enablement is transforming how we equip our revenue leaders. No longer just about delivering content or training on demand, predictive enablement leverages data and AI to: * Anticipate Skill Gaps: Imagine knowing which reps are about to struggle with a particular objection, product feature etc before it impacts a deal. Proactive, targeted coaching and training. RingCentral's enablement & Ops teams Kelly Molkenbuhr are launching The Revenue Standard which will be the framework to do just this. * Proactively Deliver the Right Resources: Instead of reps searching for answers serve it up. This is where Ringo I've talked about before is coming in for RingCentral. * Optimize Coaching & Training: By analyzing vast amounts of sales data – from call recordings to CRM activity – AI can pinpoint patterns in successful interactions. We are leveraging RingCentral's RingSense and Aviso AI to power this. * Accelerate Onboarding & Time-to-Quota: New hires can be brought up to speed faster with personalized learning paths and simulated scenarios Heather K. has a lot on deck to do just this! * Improve Forecast Accuracy: Account planning, opp planning and deal planning with AI Ratnadeep Chatterjee, MBA Michael Throssel and I have a few things up our sleeves to roll out in Q3! Predictive enablement isn't just a buzzword; it's a strategic imperative powered by AI and robust data analytics. It moves us from reactive problem-solving to proactive performance optimization, ensuring our go-to-market teams are always one step ahead. CC: Akshay Srivastava Joe Jacob Joe Fahrner Ayub Mohammed Amir Hameed Brandon Thomas Are you already exploring predictive enablement within your organization? What impact have you seen, or what challenges are you anticipating? #PredictiveEnablement #SalesEnablement #RevenueEnablement #AITech #Coaching #GTMStrategy

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Coaching new AEs (and SDRs aiming to make the leap) has taught me something: Too many get stuck deep-diving into product features from day one. I like to flip the script. Instead of product enablement, we focus on problem enablement. Here’s a GenAI-powered exercise we run on day 1: “For each of my key buying personas [insert your buyer personas], identify their top 3 strategic priorities or pain points. Then, describe how [insert your solution] specifically addresses those challenges in a way that drives measurable business impact.” This mindset shift helps new reps: ✅ Speak your buyer’s language ✅ Stand out from the crowd ✅ Add value immediately Breaking into an AE role? Or just started one? Don’t just learn the product — master the problems.

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Companies say they want CSMs to "drive value, not just revenue." Then they turn around and pay them like glorified support reps. Here’s where the math ain’t mathing: You expect CSMs to own renewals, drive expansion, and increase product adoption… ...but you comp them like customer service agents with a small retention bonus. 🤷🏻‍♂️ That’s a fundamental misalignment. The best revenue leaders don’t just pay CSMs more. They pay them differently: - Base salaries at AE-level (or close). Treat them as revenue drivers, not cost centers. - Variable comp split: 50% retention, 50% expansion. Lagging (GRR/NRR) and leading (upsells, adoption). - Clear line between CSM & AM. CSM = Expansion & retention. AM = Negotiation & new product cross-sell. Too many companies lowball their CSMs, then wonder why: - Retention tanks. - Growth stalls. - Top CSMs quit to become AEs. If you want CSMs to act like revenue drivers, pay them like revenue drivers. It’s not a cost. It’s a growth strategy.

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What Sales Enablement Leaders Really Care About... After a few recent conversations with sales enablement leaders, one thing is clear: The enablement function is evolving from “content delivery” to “confidence creation" to "revenue enablement". It’s no longer about the tools we deploy, it’s about how those tools prove readiness and performance. Here’s what they really care about 👇 1️⃣ Impact over activity They don’t want another dashboard of course completions. What they want is the proof that onboarding changes outcomes ⇾ faster ramp, earlier pipeline creation, better first-call execution. 2️⃣ Precision, not platform sprawl Enablement leaders are tired of overlapping tools that do 10% of each other’s job. What they value now are platforms that fit into their ecosystem instead of competing with it. 3️⃣ Confidence as the new metric Beyond content and process, they’re asking: “Are my reps truly ready to face customers?” Measuring readiness (through conversations, not clicks) is quickly becoming a differentiator. 4️⃣ Fewer commitments, faster validation They’re cautious with long contracts. A short, clear pilot that proves tangible improvement beats a glossy 12-month deal every time. 5️⃣ Data that builds credibility The question isn’t “how much training was done?”, it’s “how do I show my CRO that this made a difference?” Enablement leaders want visibility that earns them a seat at the revenue table. We often think of enablement as a support function. But when done right, it’s a revenue multiplier ⇾ aligning product knowledge, behavioral readiness, and data-driven validation into one motion. Curious, how are you measuring “rep readiness” in your organization today? #SalesEnablement #RevenueReadiness #SalesLeadership #SalesCoaching #AIEnablement

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