Salesloft MCP Demo Server

# Customer Interview Transcript: Gaming Studio Sales Challenges **Date:** January 2, 2026 **Duration:** 32 minutes **Interviewer:** Marcus Chen, Regional Sales Director, Salesloft + Clari **Interviewee:** Catherine Hall, VP Sales, Vertex Games (Gaming/Entertainment Tech, $70M ARR) **Location:** Virtual (Teams) **Recording:** [Consent obtained] --- ## Executive Summary Catherine Hall leads sales for Vertex Games, a mid-market gaming studio with multiple hit franchises and a portfolio approach to revenue generation. The conversation reveals four critical pain points: (1) Fragmented creator economy requiring hyper-segmentation in go-to-market, (2) Platform dependency risks affecting sales messaging and product strategy, (3) Seasonal spikes requiring precision pipeline management, and (4) Enterprise procurement delays when working with major publishers. Catherine is exploring Revenue Intelligence tooling to improve sales efficiency and forecast accuracy. --- ## Full Transcript **[00:00]** **Marcus:** Catherine, thanks so much for taking the time today. I know sales cycles are packed right now, especially heading into Q1. Before we dive in, I'd love to understand what you're managing on your end. You've got 40-person team selling across gaming, right? **Catherine:** Yeah, exactly. So we're a studio with five franchises in active development and live service games. Revenue breaks down roughly 30% from direct-to-consumer DTC through our platform, another 30% from publisher partnerships, and then about 40% from—it's a mix of licensing, esports revenue, and strategic partnerships. It's honestly a bit of a portfolio company at this point. **Marcus:** That's fascinating. So you're not a single-game studio. **Catherine:** No, which creates this interesting challenge because each revenue stream has its own sales playbook, its own timeline, and frankly, its own buyer persona. It's not like traditional software sales where you're selling to IT and it's the same motion every quarter. We're juggling independent creators, mid-tier publishers, enterprise studios, streaming platforms, and brand partnerships all at the same time. And the seasons matter way more than they do in typical SaaS. **Marcus:** Walk me through that—the seasonal piece. Because I think a lot of enterprise sales leaders I talk to think of seasonality as a bonus, not the core driver. **Catherine:** [laughs] Yeah, it's completely different. Our calendar is tied to game releases, esports seasons, and content drops. We've got a major franchise title launching in Q2—$50 million+ marketing investment behind it. That release is the anchor point for everything: our creator partnerships, our licensing deals, our enterprise bundle negotiations. Then post-launch, we've got seasonal content drops every 6-8 weeks. Each one is a mini-release with its own marketing push. **Marcus:** So if a deal doesn't close before the game launches... **Catherine:** It gets pushed. Or it morphs entirely. Publishers want to lock in creator exclusivity deals and marketing commitments before the game goes live. Once it's live, they've moved on to the next title. I've got deal cycles that are literally 90 days from discovery to close because they're tied to a launch date, not to fiscal quarters. That completely changes how I forecast. **[03:45]** **Marcus:** That's a huge insight. Let me ask about the creator economy piece—because I'm hearing from a lot of studios that creator and streamer relationships are becoming a core revenue driver, but also a fragmentation nightmare. **Catherine:** Oh man, that's exactly it. So we work with creators across Twitch, YouTube Gaming, TikTok, Discord communities, and these independent platforms that are popping up. Each platform has different economics, different audience behaviors, and different leverage. A top Twitch streamer might have 100K concurrent viewers but a smaller Discord community with higher engagement. They're not fungible. **Marcus:** What does that mean for your sales motion? **Catherine:** It means segmentation is brutal. I can't have a single "creator partnership" motion. I need to understand: Are we targeting tier-one streamers for brand awareness? Are we going after mid-tier creators with smaller but engaged communities? Are we recruiting casual creators just to expand our content library? Each segment has different requirements, different CACs, different deal economics. And they all move at different speeds. **Marcus:** Give me a specific example. **Catherine:** So we had a deal last year with a top-tier Twitch streamer. 800K followers. The negotiation took four months. It was one person, but they had managers, legal, brand managers involved. Very enterprise-like. At the same time, we were trying to sign up 200 micro-creators—5K to 20K followers each—who just wanted a simple affiliate deal. But we needed to vet them, ensure they aligned with our brand, make sure they had the production quality. That's a different sales motion entirely. **Marcus:** So you've got multiple playbooks just for creators. **Catherine:** Multiple playbooks, different messaging, different contract templates, different pricing models. And here's the kicker—the tier-one creators, they're usually signed to management companies. You're not actually selling to the creator. You're selling to their business manager, their agent. It's like enterprise sales but the "enterprise" is a person. You've got eight different stakeholders in a discussion with someone who just wants to play video games for money. **Marcus:** How are you currently managing the qualification and routing? **Catherine:** Honestly? It's a mess. My BDRs spend a lot of time on the phone with people we probably shouldn't be investing in. We've got a basic tiering system—we use follower counts, engagement rates, growth velocity—but we're not really predicting lifetime value or our actual ability to convert them. So we're chasing creators who look good on paper but don't actually move the needle for us. And we're not identifying the breakout micro-creators who could become tier-one partners. **[07:20]** **Marcus:** This is where I think intelligence tooling could help, but let me first understand the bigger picture. You mentioned platform risk. That sounded significant. **Catherine:** Yeah, that's keeping me up at night. So platform dependency is existential for studios like us. Let's say we've got a huge creator base on Twitch—we've invested, we've provided exclusive content, we've built community. Then Twitch changes their algorithm, or YouTube launches a competing game platform and pays creators more. Or there's a controversy and we have to distance ourselves from certain creators. Suddenly, your entire marketing channel is at risk. **Marcus:** Has that happened to you? **Catherine:** Not to that extreme, but we've had platform policy changes that affected our economics. Twitch changed their revenue split model a few years ago. YouTube's cut of ad revenue shifted. These aren't our platforms—we have no control. And our enterprise customers care deeply about this. When we're pitching a partnership deal with a major publisher, they ask: "What's your exposure if Twitch de-prioritizes gaming? What if a scandal hits one of your top creators?" We need to articulate that we're not dependent on any single platform. **Marcus:** How does that affect your product strategy? **Catherine:** We're increasingly building our own platforms and communities. We've got a Discord server we're investing heavily in. We're building proprietary streaming infrastructure. We're creating subscription tiers that are platform-agnostic. That's all a risk hedging strategy. And when we're selling enterprise partnerships, we have to message that heavily. We tell clients: "We reach audiences across platforms, and we're not vulnerable to platform algorithm changes because we own our own infrastructure." That's become a major differentiator in our pitch. **Marcus:** So your sales messaging is directly tied to platform risk management. **Catherine:** Completely. And we have to be honest about it because enterprise partners do their due diligence. If we claim we're platform-independent but we're really 60% Twitch-dependent, we lose credibility. So we've had to invest in platform diversification just to be able to make that claim in sales conversations. **[10:15]** **Marcus:** Let me pivot to something different—unit economics. Because with 40 people on your sales team and $70M ARR, I'm doing the math and that's... that's not a high-ACV business necessarily. **Catherine:** [laughs] No, we're not selling million-dollar deals. Our average contract value across all segments is probably $80K to $200K, with a wide distribution. Direct creator partnerships might be $20K to $50K. Publisher deals are higher, $300K to $800K. Brand partnerships are all over the place. So we need volume. We need a lot of deals moving through the pipeline to hit our number. **Marcus:** What does that do to your sales process? **Catherine:** It means efficiency is everything. I can't afford to have my AE spending three months on a single deal that's $40K. I need to move deals faster, automate the parts that don't require human touch, and really nail qualification so we're not wasting time. That's why self-service models are becoming more important for us. For lower-ACV partnerships, we want creators to be able to sign up, review terms, and agree without a sales call. **Marcus:** Are you doing that now? **Catherine:** Some. We've got a self-service tier for micro-creators and affiliate partners. But it's basic—it's a website form and a contract template. We're not really using any smart sequencing or personalization. So we get a lot of dropoff. And we're probably missing some low-touch upsell opportunities because we just set people up and don't follow up. **Marcus:** What would better automation look like for you? **Catherine:** Ideal state? We'd identify a creator in our target segment, use data to predict their likelihood to convert and their lifetime value, and automatically send them personalized messaging and pre-filled contract terms based on their profile. If they're a Twitch creator with 15K followers and high gaming engagement, they get one contract template. If they're a TikTok creator with a younger audience, they get a different one. All self-service. Then, for the ones who show engagement signals, we automatically surface them to a sales rep. And we score deals so that my AEs are focused on the highest-ROI pipeline. **Marcus:** So you'd tier your sales effort based on predicted value. **Catherine:** Exactly. My VPs should be working enterprise publisher deals. My AEs should be on mid-tier partnerships. And my SDRs should be focused on high-intent creator outreach, not spraying and praying to a hundred micro-creators who have a 2% conversion rate. We're not doing that today. **[13:30]** **Marcus:** This is where Clari's intelligence and Salesloft's execution layer are really powerful together. But before I go into that, I want to understand your forecasting. You mentioned seasonal cycles. How are you forecasting with that level of variance? **Catherine:** We're using Salesforce, which is fine, but honestly, we're not using it super strategically. We log deals as we get them, we move them through stages, we have a quarterly forecast meeting. But the inherent problem is that our pipeline doesn't match enterprise software norms. In SaaS, you have repeatable stages: discovery, qualification, proposal, negotiation, close. Our stages are all over the place. A creator deal might go deal → contract → close in 30 days. A publisher deal might be introduction → business development → legal → executive alignment → close in 90 days. The sales motion is completely different. **Marcus:** So your Salesforce pipeline might show $150 million in opportunities, but how much of that is real? **Catherine:** [laughs] That's the problem. We've got a lot of deals in "discussion" that are pure exploration. They might never close. We've got deals that are in "legal" that are actually dead—they're just sitting there. And we've got deals that are going to close in two weeks that are still marked as early-stage because that's where they sit process-wise. My CFO can't trust our forecast. I can't trust it. **Marcus:** What would help? **Catherine:** I think I need visibility into deal momentum. Not just stage, but actual motion. Is the customer engaged? Are we getting responses? Have we sent an agreement? Is legal moving? That kind of thing. We need to know which deals are stuck and why. And we need to be able to see across deal types and creators to understand which segments are actually working and which ones are drain on my team. **Marcus:** That's where Revenue Intelligence comes in. It's analyzing customer touchpoints—emails, calls, meetings—to give you real momentum signals. So instead of relying on your AE's self-reported stage, you're seeing actual engagement velocity. **Catherine:** That would be game-changing, honestly. Because my forecast today is basically "hope plus historical patterns plus my VP's intuition." And when you've got such a diverse portfolio, you need more data-driven signals. **[16:45]** **Marcus:** Let's talk about enterprise. Because you mentioned publisher deals, and I imagine that's a different beast entirely. **Catherine:** Oh, completely different. So a major publisher—think EA, 2K, Activision—these are the enterprise deals. The economics are bigger, but the procurement process is glacial. We've got a deal right now that's in negotiation that started eight months ago. Eight months, Marcus. And it's not complicated—it's a marketing partnership and some content licensing. **Marcus:** Why is it taking so long? **Catherine:** Because enterprise procurement is insane at that scale. You've got procurement, legal, brand, marketing, partnerships, finance all weighing in. Each one has to sign off. Each one asks questions. Each one has some requirement. Our contract goes back and forth between their legal team and ours maybe twenty times. We get to "yes" and then a new executive joins and wants to revisit the terms. Or they have a mergers and acquisition happening and all deals are frozen. It's bureaucracy at scale. **Marcus:** How does that affect your planning? **Catherine:** It means I can't really count on deals closing when I hope they will. I have to forecast these deals as "likely to close sometime in the next 18 months" rather than "Q1" or "Q2." We do our best to estimate based on where they are in their approval process, but we're often wrong. I'll have a deal that looks like it's weeks away from close, and then it sits in their procurement queue for four months. **Marcus:** Have you tried to accelerate those deals? **Catherine:** We try. We've assigned senior people to stakeholder management. We've elevated to executive sponsorship when we can. We've tried to move decision-making up the chain. But ultimately, we're beholden to their process. And honestly, sometimes they're running multiple evaluation processes simultaneously—they're evaluating us and one or two competitors. We don't always know where we stand in that evaluation. **Marcus:** That's where deal acceleration tooling helps. If you could see that a deal is stuck in procurement, that their team has stopped engaging, that a competitor is gaining traction—that gives you signals to either push harder or pivot strategy. **Catherine:** Yeah, and I'd also want to know—are we actually preferred? Or are we one of three equal options? Because that changes how I allocate resources. If we're the favorite, I'll have my VP spend time on stakeholder management. If we're not, I might deprioritize and focus on a deal where we have better positioning. **[19:20]** **Marcus:** Walk me through what happens when a game releases. You mentioned that's an anchor point for your sales. **Catherine:** So let's use Q2 as the example. Our major title launches in May. Starting in January, we're in heavy outreach mode. We're pitching creator partnerships because we want exclusivity and content commitments before launch. We're closing publisher marketing deals. We're locking in esports partnerships and streaming platform features. All of this has to happen pre-launch because post-launch, the publisher's marketing budget is committed and the promotional windows are locked. **Marcus:** So your sales cycle compresses. **Catherine:** Massively. We need to identify targets, pitch, negotiate, and close in 90 days. If we miss that window, we miss the deal entirely—or it moves six months later to the next content season. That's why our pipeline structure doesn't match traditional enterprise software. We're not in a perpetual sales cycle. We're in project-based cycles that line up with launches. **Marcus:** How does your team prepare for that? **Catherine:** We do a lot of planning. In Q4, we're already identifying target creators, drafting partnership approaches, lining up preliminary conversations. January, we kick into execution mode. We're sending outreach at scale, qualifying responses, and starting conversations. February through April, we're in heavy negotiation and deal management. May 1st, if we haven't closed, we're probably not closing until post-launch. **Marcus:** And that happens five times a year—for each content drop? **Catherine:** For major content drops, yeah. Not all of them get the same intensity. A seasonal content update isn't the same as a new game launch. But the pattern is there. We have predictable peaks and valleys, and we need to staff for those peaks. That's another challenge—headcount allocation. I can't have forty sales reps sitting idle during off-season. So we've built some education and training into the valleys, we rotate people on partnerships and business development. But we're always trading efficiency for flexibility. **Marcus:** How is that reflected in your compensation and quotas? **Catherine:** [pause] That's complicated. We do quarterly quotas because our corporate financial targets are quarterly. But our actual deal cycles are seasonal. So we end up with Q1 being slower, Q2 being crazy with the launch, Q3 being recovery, Q4 being planning. We've tried to adjust quotas seasonally, but Finance doesn't love that. So we just live with the fact that we're always either ahead of or behind plan. **Marcus:** What if you could predict your Q1-Q4 revenue based on past seasonal patterns and real pipeline momentum? Would that help? **Catherine:** That would help with forecasting and goal setting. It would also help with cash flow planning. Investors care about that. If we're saying "we have $80 million in revenue this year but $30 million of it closes in Q2," that affects how we communicate with our board. **[22:15]** **Marcus:** Let me ask about execution. You mentioned you're using Salesforce. Are you using Salesloft today? **Catherine:** No, we're not. We have Salesforce, we have HubSpot for some creator-focused workflows, and we use Outreach for basic email sequencing. But we're not coordinating those well. So if a creator comes in through a HubSpot form, they're not automatically mapped to Salesforce. If an AE sends them a Salesloft-equivalent email sequence, we're not tracking that progress in a unified place. **Marcus:** What would unified execution look like? **Catherine:** Honestly? We'd identify a target creator or partner, pull them into a system that knows their segment, automatically personalizes messaging and terms, sends them through a relevant cadence, and surfaces them to the right AE at the right time. And the AE would have all context—previous conversations, engagement signals, deal history. Right now, an AE might spend 30 minutes just gathering context from scattered emails, Slack messages, and Salesforce notes. **Marcus:** And if you add intelligence to that execution layer? **Catherine:** Then we'd know if our cadence is working. We'd know if the creator's engagement is dropping off. We'd know if we're wasting time on a dead deal versus putting effort on one that's gaining momentum. We'd know which messaging resonates with which segments. **Marcus:** Give me the ROI story for your CFO. You're spending money on software, and in return...? **Catherine:** [pause] We get faster deal cycles. We get higher win rates in the segments that matter. We reduce the time my AEs spend on admin and context-gathering. And we get better forecasting, which helps with cash flow and investor communications. If I can close deals ten days faster, that's material at our revenue scale. If I can improve our creator partnership conversion rate from 12% to 18%, that's material. And if I can free up fifty hours a month from my senior reps, that's about $50K a month in productivity. **Marcus:** That's the conversation. So software isn't just tooling—it's a revenue and productivity lever. **Catherine:** Absolutely. At our stage and with our complexity, we can't be efficient without the right tooling. And right now we're leaving money on the table because we're not smart about prioritization and we're not moving fast enough through the seasonal windows. **[25:30]** **Marcus:** Last thing I want to cover—risk. You mentioned platform dependency. Are there other risks in your revenue model that your board or investors are concerned about? **Catherine:** A few. Platform dependency is one. Creator churn is another. Our top five creators represent maybe 15% of our creator revenue. If one of them leaves, or stops streaming, or gets acquired by a competitor, that's a revenue hit. So we're always thinking about creator retention and replacement. Diversification is another—we need to make sure we're not dependent on any single franchise or content type. And regulatory risk—there's always something: loot box regulation, streaming platform policy changes, antitrust stuff around platform favoritism. **Marcus:** How does that affect your sales strategy? **Catherine:** It makes us cautious about long-term bets. We might not want to invest heavily in a partnership with a creator who's all-in on a platform that's under regulatory scrutiny. We want partners who are diversified, who have options. And we want to build our own assets—our own communities, our own platforms—so we're not leveraging other people's infrastructure. **Marcus:** And in your pitch to enterprise publishers? **Catherine:** We talk about our resilience and diversification. We show them that we have multiple revenue streams, multiple platforms, multiple creator partnerships. We're not vulnerable to a single market shift. That de-risks their partnership with us. **Marcus:** That's smart. And visibility into your pipeline and forecast helps you communicate that credibly. **Catherine:** Yeah, if my forecast is constantly wrong, nobody believes my risk narrative. If my forecast is solid and accurate, then when I say "we've modeled for platform changes," they believe that we're being thoughtful about it. **[27:45]** **Marcus:** Catherine, let me ask the obvious question. If I could give you a toolset that solved three things—pipeline visibility with real momentum signals, execution automation that's segmented by deal type, and better forecasting—what would that be worth to you? **Catherine:** [laughs] That's the pitch, right? Um, I think the honest answer is: it depends on execution. I've bought tools before that promised everything and delivered 30% of it. So I need to see how your platform handles our complexity—multiple deal types, seasonal cycles, diverse buyer personas. If it can handle that without requiring a massive custom implementation, and if it actually gives us the insights we need to move faster and forecast better, then it's worth probably 5-8% incremental productivity improvement. That's $3.5M to $5.6M in value annually at our scale. **Marcus:** And if it helps you close a major publisher deal one quarter earlier? **Catherine:** That's $10M-plus, depending on the deal size. But I can't bank on that being repeatable. So I think the ROI story is productivity and forecasting, with upside if we can accelerate major deals. **Marcus:** What would I need to show you to earn a pilot? **Catherine:** Show me how it handles our creator segmentation and our seasonal cycles. Give me a clear picture of how your platform would map to our Salesforce and our existing tools. And be honest about what you can and can't do. I've had vendors oversell before, and it's worse than underselling. If I trust that you're being straight with me, I'll do a pilot for three months during our next content launch cycle—Q1 into Q2. Give us real volume to test. **Marcus:** Perfect. Can I send you a technical overview and a proposed pilot roadmap? **Catherine:** Yeah, do that. And maybe a demo where you're using actual gaming industry data—not generic SaaS examples. That would help me visualize how this applies to us. **Marcus:** You've got it. I'll have that to you by end of week. Catherine, this has been incredibly helpful. I feel like I understand the complexity you're managing now. **Catherine:** Thanks for asking the right questions. Honestly, most vendors just pitch their solution. You actually tried to understand our business first. That matters. **[32:00]** **Marcus:** I appreciate that. One last thing—can I follow up in a few weeks once you've looked at the materials? **Catherine:** For sure. And if things align, we can talk timeline for a pilot. **Marcus:** Perfect. Thanks again, Catherine. **Catherine:** Thanks, Marcus. --- ## Key Takeaways & Findings ### 1. **Creator Economy Fragmentation Creates Multiple Sales Motions** - **Challenge**: Vertex Games manages creators across five platforms (Twitch, YouTube, TikTok, Discord, proprietary), each with different economics and buyer behaviors - **Sales Impact**: No single creator sales playbook works. Tier-one creators require 4-month enterprise-like negotiations with agents/managers. Micro-creators need self-service, high-volume motion. - **Qualification Problem**: Current segmentation by follower count is insufficient; need predictive models for lifetime value and conversion probability - **Recommendation**: Implement segmented qualification rules and auto-routing based on creator tier, platform, and engagement signals. Separate low-ACV creator automation from high-ACV direct partnership sales ### 2. **Platform Dependency Risk Shapes Sales Messaging & Product Strategy** - **Challenge**: Heavy reliance on platform algorithms (Twitch, YouTube) creates revenue volatility. Policy changes, platform de-prioritization, or creator scandals can damage growth channels - **Sales Lever**: Platform risk is now a major differentiator in enterprise publisher pitches. Vertex Games claims platform-independence and community ownership as a value prop - **Execution Gap**: Sales team doesn't have easy visibility into exposure metrics (percentage of revenue by platform, creator concentration, platform policy risk) - **Recommendation**: Build risk dashboard showing platform exposure. Use this in enterprise pitches and in internal resource allocation. Train sales team to articulate resilience narrative ### 3. **Seasonal Deal Cycles Compress Sales Cycles & Require Intensive Forecasting** - **Challenge**: Major game releases (every 90-180 days) are anchor points. Enterprise deals, creator partnerships, and esports agreements all cluster pre-launch. Post-launch, deal activity drops dramatically - **Sales Impact**: Quota attainment is volatile (Q1 weak, Q2 strong, Q3 weak, Q4 planning). Sales team must ramp velocity quickly for launch windows; compensation and headcount planning is difficult - **Forecasting Problem**: Traditional quarterly quotas don't match seasonal cash flow. Investors want predictability but revenue is lumpy. Salesforce forecast accuracy is poor because pipeline structure doesn't reflect deal-type variability - **Recommendation**: Shift to seasonal quota profiles that align with launch windows. Build forecasting models that account for seasonal variance. Use contract value and historical close rates by deal type to predict revenue ### 4. **Low ACVs Require High-Efficiency Sales Motion with Automation & Self-Service** - **Challenge**: Average contract value ranges $80K-$200K (creator partnerships $20K-$50K). Need volume to hit revenue targets. Can't afford 3-month sales cycles on low-ACV deals - **Execution Gap**: Basic self-service exists but lacks personalization, smart routing, and follow-up automation. High dropoff rate. SDRs spending time on low-intent creators instead of high-value qualification - **Recommendation**: Implement AI-driven deal scoring and routing. Automate low-ACV creator onboarding with segment-specific contract terms and messaging. Redirect SDR time to high-intent outreach and executive business development ### 5. **Enterprise Publisher Procurement Creates Extended Sales Cycles & Deal Acceleration Opportunities** - **Challenge**: Major publisher deals take 8-12 months due to multiple stakeholder approvals (procurement, legal, brand, marketing, finance). Contract redlines are extensive. Competitive evaluations run in parallel - **Sales Opportunity**: No visibility into competitive positioning or deal momentum. Sales team doesn't know if they're preferred or one of three equal options. Deals get stuck in procurement queues with no visibility to why or how to accelerate - **Recommendation**: Implement deal intelligence to track stakeholder engagement, decision-maker involvement, and competitive signals. Surface blockers (e.g., procurement queue, missing exec sponsor) to enable targeted acceleration. Use executive engagement strategy based on customer org structure ### 6. **Forecasting Accuracy is Undermined by Deal-Type Heterogeneity & Momentum Blindness** - **Challenge**: Current Salesforce approach treats all deals as having same stage progression. Creator deals (30-day cycles) and publisher deals (270-day cycles) are tracked identically. No visibility into engagement velocity or deal momentum - **Impact**: Forecast accuracy is poor. CFO can't trust numbers. Sales organization can't be data-driven in prioritization - **Recommendation**: Implement deal momentum signals (email engagement, meeting frequency, contract routing, legal progress). Create deal health scoring that weights momentum more heavily than stage. Build segment-specific forecast models ### 7. **ROI Opportunity: 5-8% Productivity + High Deal Acceleration Upside** - **Estimated Benefit**: Catherine estimated 5-8% productivity improvement ($3.5M-$5.6M annually) from better execution, forecasting, and visibility. Additional upside of $10M+ if platform enables accelerating one major publisher deal per year - **Pilot Readiness**: Strong fit for Q1-Q2 pilot during next content launch cycle. Requires platform to handle creator segmentation, seasonal cycles, and enterprise deal momentum - **Deal Risk**: Catherine will conduct vendor reference checks and requires honest scoping. Overselling features or underestimating implementation will kill deal --- ## Sales Conversation Notes ### Strengths of This Conversation - **Consultant positioning**: Interviewer asked discovery questions first, making Catherine the expert, building credibility - **Specific examples**: Creator partnership negotiations (800K Twitch streamer, 200 micro-creators) made fragmentation tangible - **Financial grounding**: ARR figure, ACV range, and productivity ROI estimates gave concrete business context - **Technical credibility**: Understanding of platform risk, seasonal forecasting, and deal structure showed industry knowledge ### Next Steps 1. **Send technical overview** showing how Clari + Salesloft handles segmented workflows and seasonal forecasting 2. **Propose 3-month pilot** aligned to Q1 launch window 3. **Schedule demo** with gaming industry data + Vertex Games deal-type examples 4. **Executive alignment** meeting with Catherine's VP Finance or CFO on forecasting ROI ### Competitive Positioning - **vs. Salesforce alone**: Add intelligence layer + execution coordination that Salesforce doesn't provide natively - **vs. Outreach alone**: Add revenue intelligence and deal health scoring specific to gaming industry sales cycles - **vs. Clari alone**: Add execution automation (Salesloft) that improves deal velocity, not just visibility --- ## Industry Context ### Gaming Studio Sales Complexity - **Revenue Diversification**: Studios like Vertex manage 4-5+ independent revenue streams (DTC, publishers, licensing, esports, partnerships) each with different sales motions - **Creator Economy Dynamics**: Creator partnerships are now material revenue—15-30% of studios' top-line growth. But creator churn, platform risk, and reputation management are ongoing challenges - **Seasonal Volatility**: Game launches, content drops, and esports seasons compress sales cycles and create feast-famine revenue patterns - **Enterprise Procurement**: When selling to EA, 2K, or Activision, deal cycles are 8-12 months with multiple approval gates. This creates forecast uncertainty and requires deal acceleration strategies ### Why This Matters for Salesloft + Clari Gaming studios represent an adjacent market with high complexity and low adoption of modern revenue ops tooling. They're not traditional SaaS (low ACVs, seasonal cycles, multiple buyer personas) but they're high-revenue and under-served by existing solutions. Tailoring the product demo and pilot to gaming-specific challenges (seasonal forecasting, creator segmentation, enterprise deal acceleration) differentiates from generic SaaS positioning.