Transitioning to New Business Models

Salesforce just fired the starting gun on a seismic shift in how we pay for software. At Salesforce #Agentforce, they announced they’re moving away from the traditional per-seat SaaS model to a consumption-based pricing for their AI agents. This is huge. Why? Because it signals the end of paying just to have access to technology. Instead, we’re moving toward paying for outcomes—the actual value delivered. Think about it. In a world where AI agents can perform the job functions of entire departments, does it make sense to charge per seat? Probably not. Here’s what’s changing: - From access to outcomes: Companies will pay for what the AI actually accomplishes. - From subscriptions to value: Pricing adjusts based on usage and results. - From Software-as-a-Service to Agent-as-a-Service: Technology that collaborates with you as a partner This isn’t just a tweak in pricing—it’s a radical upending of commercial models for large SaaS companies. What does this mean for businesses? - Budgeting will evolve: Costs align directly with value received. - ROI becomes clearer: Easier to measure the direct impact of technology investments. - Greater flexibility: Scale usage up or down based on needs without worrying about seat counts. It’s an exciting time, but also a challenging one. Is every SaaS company ready to embrace a model where companies pay directly for the value they receive? At Uniti AI, we’ve been thinking along these lines. We price our AI agents based on the amount of work they do, not on how many seats a company has. I believe this is the future. What do you think? Is the per-seat model on its way out?

We're about to see an onslaught of consulting and IT services firms going big on working with AI platforms to deploy agents in the enterprise. And if you don’t understand why it’s happening, it’s an opportunity to reset your understanding of how the real world works. The real world will need a ton of help actually getting agents going in the enterprise. Companies deal with significant legacy tech stacks they need to modernize, data in tons of fragmented tools, knowledge that isn’t captured or digitized, and change management needed to actually utilize agents effectively. And they have to do all this while still running their business day-to-day, unlike startups, who can generally just design their organizations from the ground up to deploy agents into new workflows designed for them. This is why there is so much opportunity for companies (software or services) to actually deploy agents in specific domains and workflows. This remains a big opportunity for both existing services providers but also tons of new services startups as well. Every new technology wave produces a new era of consulting firms that can deliver on that technology. We're seeing this a ton at Box, both in partnering with new forms of technology consultancies as well as existing systems integrators that are building out all new agentic practice areas to help enterprises work with their unstructured data and agents. These service providers will have the benefit of being able to work across multiple data platforms, as well as see common practices that work or fail within an industry. This knowledge ends up being incredibly valuable right now, especially given how fast things are changing. A corollary to this is also that the forward deployed engineer (FDE) model is going to be alive and well for a long time because companies will want to have their vendor actually help drive the change management and implementation for their new workflows. There’s no shortcut to getting this work done for the enterprise, and the vendors are going to have to do a lot of this or risk low adoption. All of this type of work is going to be in high demand for quite some time, and it's incidentally another example of jobs that aren’t actually going away.

I have sat in budget meetings watching CFOs scrutinize every marketing line item like it was discretionary spending. Meanwhile, sales got a standing ovation for hitting their numbers (as they should). Here’s a secret, though: marketing drove 60% of that pipeline. But we were still defending our existence while sales were celebrating theirs. That's the cost-center trap. And it's about to collapse. Marketing departments will shift from cost centers to revenue centers. Not in five years. Sooner. Here are the 5 shifts that will define this transformation: Shift 1: You'll own a revenue number, not a budget number. No more "marketing spend as % of revenue." You'll carry a revenue target. - Your team gets measured on dollars generated, not dollars spent. - You'll have a P&L conversation, not a budget defence. - If you hit your number, you earn more investment - just like sales. This flips the entire dynamic from justification to acceleration. Marketing ROI should be computed on long-term basis, not short-term. Shift 2: Vanity metrics die; revenue attribution becomes your scoreboard. Impressions and engagement won't save your job. Revenue impact will. You stop reporting activity and start proving outcomes. That's when marketing earns its seat at the strategy table. Shift 3: You'll manage a portfolio, not campaigns. Marketing isn't linear. Most bets fail. A few win big. That's the game. - Core bets keep revenue steady and predictable. - Test bets push into new channels or segments. - Moonshots swing for breakthroughs that could 10x results. You'll review your portfolio like a venture fund, not a campaign calendar. Shift 4: Your "marketing budget" becomes a revenue investment with expected returns. New brand launches might invest 15-25% of revenue into marketing. Sustaining brands stabilize at 5-10%. But here's the shift: you'll forecast the return on that investment just like a sales quota. Leadership will ask, "If I give you $2M, what revenue do you deliver?" You'll answer with a number, not a narrative. That clarity transforms marketing from an expense into a growth engine. And this transformation will be painful, because attribution models are not at all accurate. Shift 5: Growth and Marketing merge into one team. Silos between growth, product marketing, and brand are obsolete. You'll operate as one revenue engine. Everyone, from content to conversion, works toward the same number. No more "brand builds awareness, growth drives conversions." You all drive revenue. That unified focus changes how you hire, plan, and win. The marketers who own revenue outcomes will lead. The ones defending budgets will get left behind. #marketing #business #entrepreneurship #work

25% of B2B companies expect to use outcome-based pricing by 2028. That's a 5x increase from today's 5%, according to Kyle Poyar's latest research.   This will be a painful, but ultimately healthy transition.   Buyers never wanted software in the first place. They wanted solutions. As AI handles more work end-to-end, pricing migrates from inputs (seats, tokens, usage) to outcomes (cases closed, revenue recovered, risk reduced). Less "how much did you use?" More "did it actually work?"   Thought experiment: if code becomes a commodity and features ship instantly, value shifts from building features to guaranteeing execution. You’re not selling software—you’re selling outcome insurance.   Objections are real—attribution is messy, procurement habits are sticky, and buyers hate surprises. But these are solvable with instrumentation, shared definitions of success, and clear guardrails (Manny Medina). Over time, buyers will demand outcome-based pricing because it reduces their risk. Where outcome-based pricing already fits well: AI-enabled services. Services own end-to-end execution, so attribution is clean and incentives align. Mechanical Orchard is a great example—using AI to move mainframe workloads to the cloud, taking ownership of the entire journey. When you own the “last mile,” charging for success becomes straightforward.   AI customer support vendors have also been pioneers of this model. More vendor types are on the horizon.   If you’re a founder, here’s a simple path to test outcomes pricing: • Pick one mission-critical outcome your product directly influences. • Define a verifiable metric, baseline, and observation window with the buyer. • Cap downside (floor) and share upside (tiers/bonus) to build trust. • Instrument attribution now—event logs, holdouts, and third-party validation beat hand-waving later.   Start with one outcome. One customer. One measurable result you can guarantee. We're still early in this shift, but the direction is clear.   For those already experimenting with outcome-based pricing, what's been your biggest surprise? And for those that haven't yet, what's holding you back?

For half a decade, I thought I was tracking the right metrics I was wrong Revenue. Growth rate. ROAS. Conversion rate. New customers. Repeat revenue All important But they could tell me the business was growing without telling me whether that growth was making the company more valuable You can buy more traffic, discount more aggressively, and acquire less-profitable customers while the top line keeps going up The business gets bigger That doesn’t automatically mean its equity value does A stronger Brand should make future revenue easier to earn, more profitable, and less dependent on buying every sale Here are the 11 metrics I wish I’d started tracking sooner, framed as questions: 1. Are branded organic searches growing faster than revenue? 2. Are contribution dollars and contribution margin going up? Contribution Dollars = Revenue - variable costs like COGS, marketing, and shipping 3. Is direct and branded search revenue growing faster than overall revenue? 4. Is the gap between gross and net sales shrinking? This signals less reliance on discounts and fewer returns 5. Are 30, 60, and 90-day incremental LTV going up, excluding the first purchase? 6. Is reach growing as fast as—or faster than—revenue? 7. Have your worst days gotten better? One way to measure this: is the average of your 30 lowest-revenue days trending up? 8. For organic search, is revenue per session rising while sessions are growing or stable? 9. Is your share of branded organic searches growing versus your competitive set—at both the Brand and category level? 10. Is Baseline Revenue growing, both in dollars and as a percentage of total revenue? I define Baseline Revenue as revenue from direct traffic, organic search, and organic social referrals It’s imperfect. But if it’s rising in dollars AND as a percentage of revenue, good things are generally happening 11. Is Baseline Revenue per branded organic search going up? Branded searches are an imperfect proxy for the Brand you’re building. Baseline Revenue per search shows whether you’re monetizing it better If searches are soaring but Baseline Revenue per search isn’t, that’s something to audit — A few caveats: None of these metrics are perfect. You can game any of them They’re also mostly leading indicators—not the ultimate company scorecard The ultimate outcome is more operating profit and net cash over time The right metrics also change with the company’s stage, economics, and strategy. A five-month-old company shouldn’t use the same scorecard as a 100-year-old company But if you can honestly answer “yes” to most of these questions, there’s a good chance the quality of your growth is improving And that gives you a better chance of building a more valuable company—not just a bigger one Question for the people of the internet: What else do you track to understand whether growth is increasing the quality and equity value of the business?

The inbound led outbound funnel not working anymore. The Inbound led conversation takes over. The traditional funnel wasn’t built for how people buy, it was built for how companies want to sell. We see that the fastest growing companies already shifted from the old playbook They’ve replaced outbound with instant connections. That shift is called DM Selling. The average form conversion in 2025 is just 1.7%. Meanwhile, Knock AI customers routinely hit 83% reply rates once a prospect use their messaging app, far above email follow-ups. One of Knock AI customers saw an uplift of 30% in click to SQL after 2 months running. As a result, he replaced all forms on their website with DM buttons. Intent last 90 seconds today. Every delay or small friction leads to outbound chasing. Those who win don’t wait, they engage. The smartest GTM teams don't stop moving all inbound traffic to outbound, they capture the lead when their intent is high, they’re connecting faster. They follow 4 simple principles that define DM Selling: 1. Detect all places with high intent signals 2. Add the DM link to each of those places. When leads clicks on it, the conversation starts the moment intent appears, no forms or waiting. 3. Once the chat started on a specific thread, it continues throughout the buying journey. No restarts or lets switch to email. 4. Zero Friction: No jumping between tools or waiting for replies. A smooth, asynchronous dialogue from start to finish. DM Selling isn’t a new playbook. It’s the return to what actually works, human, instant, and buyer-led. If your prospects are already talking in DMs and you’re still waiting on forms, you’re not just behind. You’re invisible. Curious what DM Selling looks like in practice? DM me “Shift”, I’ll show you how the top GTM teams are already doing it.

Is the traditional SDR model obsolete? We just ran an experiment at Highperformr that suggests it might be time to rethink the entire sales stack. We looked at our funnel and realized we were falling into the classic trap: Marketing celebrates lead volume, while Sales struggles with conversion. So we flipped the script. We stopped measuring "Leads" entirely. Instead, we empowered our team to become "Full Stack Sellers." AI handles the research, enrichment, and initial qualification. Humans handle the consensus building, the strategy, and the closing. The moment we stopped incentivizing lead volume and started incentivizing positive conversations, our pipeline velocity skyrocketed. We saw a 2x revenue jump in two months. No new hires. No extra budget. In this week's episode, Sri and I discuss why the "Assembly Line" sales model is dying and how AI is enabling a return to relationship-first selling. If you are a sales leader still reporting on MQLs, you need to listen to this. "Outbound" podcast episode, link in the comment below. 👇

It feels contradictory of me to say this: ...inbound lead gen only is not going to work in 2025. Founders, CMOs & CROs, this is what to look for👇 I've always been doing inbound work throughout my entire career. But lately, I observed something about inbound lead gen: In some months, the leads would flock in. In others? Crickets. The problem with inbound is you can create demand (and you need that). But you can't anticipate consistent volume. And the worst thing about Sales & Marketing is: keeping the approach that doesn’t give a good outcome. So we took a step back to revamp our social selling workflow. Long story short. - Revamp demand-gen content, less output, more high-quality output. - Stopped inbound only. Started a mixed approach. - Built a multi-touch prospecting system. Here’s exactly what we do: 1. Add 150-200 contacts from ICP to my LinkedIn every week First build the list with Sales Navigator. Then add them to your account via connection request. Just so you know, you can automate this step. 2. Do a few quality posts aligned with your positioning. No cliché platitude, no selfie in Bali 😂 Not 5 times or 7 times a week. We do fewer posts, but higher quality. Here’s how: - 1-2 posts (with video or infographics) on problem-solving, success stories, objection handling (what we do) - 1-2 posts (bare text or with an image) attacking industry villains or showing subject matter expertise (what we don’t do). Then repost your content after 9 hours (or next day if you don’t post anew). This is how we use content to invoke demand across timezones. 3. Prioritize inbound-led outbound. Many B2B companies invest heavy effort and money in mass low-intent cold outreach. Result: extremely low response and close rate. Instead, we prioritize the audience with an inbound signal: - Track interaction thru comments, reactions, profile visit, connections. - Start convo in DMs to drive curiosity with solution-forward questions. - Not all contacts enter the pipeline. But those do, already qualify themselves. That makes it easier to book a demo call. Plot twist, some of this can also be automated. 4. Build a multi touch-points follow-up LinkedIn or socials alone won’t cut it. B2B buyers are sophisticated and they ain’t ready to convert with 1 or 2 touch points. So we enrich contact data with tools like Clay and plan a mix of follow-up strategies with email and LinkedIn message sequences. This is how we secure a higher response rate and land 15 - 20 calls a month. — The result so far. Predictable. But it’s no instant noodle. It took a lot of experiments with different tools. A thing about this approach: You don’t wait for leads to show up. But you can lead the way for them to come in. I'm on a mission to help 2 limited founders get 10-15 sales calls a month thru Founder Brand without spending more than 45 mins a week. Sounds sexy to you? Send me a DM "Socials" and let's chat.

Did you see that coming? I didn’t. TikTok banned in the USA. Imagine building your whole business strategy around one platform, only to have it pulled away overnight. It’s something that keeps me up at night as a founder. At Ocushield, I remember the exact moment we realised this risk. We were running a campaign on Meta, and they changed their algorithm. Bam – traffic dropped overnight, and so did our conversions. From that point on, we knew we couldn’t rely on just one platform for everything. So, we built multiple safety nets. First, we diversified where we sell: ✅ Direct-to-consumer sales through our own website. ✅ Retail partnerships like WHSmith & John Lewis ✅ Corporate sales by partnering with employers. ✅ International marketplaces like Amazon. Then, we diversified how we market: ➡️ Google advertising and SEO. ➡️ Email and SMS marketing (because owning your audience matters). ➡️ Meta’s platforms, but as part of a wider mix. ➡️ Even non-traditional channels, like QVC. Here’s the thing – you don’t need to rely on just one platform to grow. Diversifying might feel like extra work, but it’s what protects your business when the unexpected happens. Here’s how you can start: 👉 Build an email or SMS list. This gives you a direct line to your customers that no algorithm can take away. 👉 Test new sales channels. Look at retail, B2B partnerships, or marketplaces to expand your reach. 👉 Spread your marketing budget. Experiment with platforms like Google Ads, LinkedIn, or even influencer partnerships. The TikTok ban is a wake-up call for all of us: no platform or channel is guaranteed. Diversification isn’t just a smart move – it’s essential. What’s one way you’re diversifying your business to prepare for the future?

AI Agents Don’t Buy Seats—Why Your Pricing Should Follow Suit In the past 12 months, a clear pattern has emerged: as AI systems replace manual effort with automated intelligence, pricing structures tied to “seats” no longer reflect the value customers receive. Pricing models have surfaced as a hot topic with every portfolio company at Mosaic Ventures and is top-of-mind for nearly every founder building applied-AI products. When one person and an AI agent can outperform an entire legacy team, charging per user starts to feel arbitrary; what matters is how much business impact the product delivers. Founders are experimenting with three broad approaches: 1. Usage-metered plans that bill against tokens, API calls, or minutes of inference time. These create a direct bridge between consumption and margin and nudge teams to track cost from day one. 2. Outcome-based pricing that charges per lead booked, ticket resolved, or document drafted—tying revenue to measurable results. It’s the software analogue of value-based care. 3. Hybrid “starter bundle plus runway” tiers: a predictable monthly fee with a healthy allowance of AI credits, then pay-as-you-go beyond that. This balances budget certainty for customers with upside capture for the vendor. Across our portfolio, a few design principles keep showing up: 1. Anchor on a metric the customer already tracks. If your product shortens sales cycles, price per opportunity accelerated—not per login. 2. Bundle enough volume to eliminate credit anxiety. No one wants to ration prompts. 3. Expose real-time usage. Transparent dashboards prevent bill shock and build trust. 4. Instrument cost early. Metering and billing belong in the product backlog, not the finance queue. 5. Plan for non-linear jumps. When a model upgrade multiplies compute, re-grade tiers before your gross margin does it for you. AI’s promise is to shift human effort from repetitive execution to higher-order creativity. If our pricing still counts bodies instead of business results, we undermine that promise. The companies that map price to outcomes—while keeping the buying experience refreshingly simple—will capture the most upside. I’d love to hear how others are managing the move from seats to usage and outcomes. What’s working, what still feels messy, and where do you see the biggest opportunities to innovate on pricing? #appliedAI #pricing #startups