The Wire

Real-time updates from ANZ tech sales

about 1 month ago
News

24 Australian startups raised $91 million this week, Fluent Commerce takes $46m

## The Numbers 24 Australian startups raised $91 million this week. Fluent Commerce took half of it: $46 million led by Bain Capital for its AI-powered retail order management platform. The rest came from a mix of early-stage rounds, including 19 companies in Startmate's latest cohort, plus deals in legal tech and defence tech. ## What Fluent Commerce Does The Sydney company helps retailers like JD Sports, L'Oréal, and LVMH track inventory and deliveries. Enterprise clients, global names, seven-year gap since their last raise in 2019. That gap matters: it signals they were not burning cash to hit vanity metrics. Bain Capital led the round. Arrowroot Capital led their $33 million Series B back in 2019. ## Sales Implications Fluent Commerce sells to enterprise retail. That means long sales cycles, complex implementations, and likely a small but experienced AE team focused on strategic accounts. AI-powered order management is not a quick close. The $46 million will fund scaling, which typically means hiring. For enterprise SaaS in Sydney, expect AE comp in the $140k-$180k OTE range, possibly higher for senior enterprise roles with retail vertical experience. ## The Broader Context This week fits the 2024-2025 funding trend: Australian startups raised $5.4 billion across 810+ companies in 2024, up 68% year-over-year. Seed rounds average $2.8 million, Series A sits at $18 million. Sydney and Melbourne take 75% of total funding. B2B dominates. AI takes 24% of deals, fintech 28%, healthtech 18%. The top 10 deals took 70% of Q3 2025's $1 billion. Capital is concentrating in proven execution, not spray-and-pray. ## What This Means for Sales Professionals Funding activity signals hiring. When 24 companies raise in one week, that translates to SDR, BDR, and AE roles over the next 6-12 months. Fluent Commerce alone will likely add enterprise AEs and possibly a VP Sales if they are scaling into new regions. For quota carriers: track which verticals are getting funded. Retail tech, legal tech, defence tech all raised this week. Those sectors will be hiring, and early hires at well-funded startups often get better equity and faster promotion paths than later joiners. ANZ startup funding is up, but comp still lags US by 20-30% for equivalent roles. Know your worth, check Glassdoor, and negotiate.

SmartCompany
about 1 month ago
News

Appetise raises $7M selling grocery behaviour data to FMCG brands

## The Deal Appetise closed a $7 million Series A led by Icehouse Ventures, 18 months after making a bet that killed $400k in consumer revenue. The Christchurch-based company ditched its $4/week meal planning subscription, made the app free, and started selling the behavioural data to FMCG brands instead. The math worked. Revenue hit $3.5 million, up from $1.2 million six months prior. Australia now drives 70% of growth, with 70 brands signed including Kraft Heinz and Lee Kum Kee. ## What They Actually Sell Appetise runs two platforms. Consumers get a free meal planning app with 2,000+ recipes and supermarket-integrated shopping lists. Brands get Appetise Insights: behavioural data showing how 110,000 households actually plan meals and buy groceries, not what they report in surveys. Co-founder Toby Hilliam calls it "the largest food and beverage behavioural research panel in Australia" compared to traditional 18,000-person survey panels. The pitch: observed behaviour beats reported behaviour. ## The Sales Angle This is the B2B consumer data play in action. Free product builds the user base. User base becomes the dataset. Dataset becomes the revenue engine. For sales teams selling into FMCG or retail, Appetise is now a competitor to traditional market research firms, but with real-time purchase intent data. Worth noting: 70 brands in 12 months suggests strong product-market fit in Australia, but also indicates they are still in land-grab mode. Series A capital likely funds AE headcount to scale that 70 into enterprise accounts. For anyone tracking the ANZ B2B data and insights space, this validates the consumer-to-enterprise data model. The short-term revenue sacrifice was real. The 3x growth in six months suggests they timed the pivot right. ## The Context Appetise originally launched as MenuAid in 2021. The 2024 rebrand and business model pivot followed $4 million in earlier funding. This Series A brings total raised to $11 million. The company operates across Australia and New Zealand, with COO Elise Hilliam co-founding alongside Toby.

SmartCompany
about 1 month ago
News

SaaStr cuts sales team 10 to 1.2 humans, adds 20 AI agents

# SaaStr cuts sales team 10 to 1.2 humans, adds 20 AI agents Jason Lemkin just posted the ratio that should worry every sales leader: his company spent $500,000 on AI agents last year versus $10,000 on Salesforce. That is 50x more on agents than CRM. The SaaStr founder went from 10+ humans in sales to 1.2 humans and 20+ AI agents. Same net productivity. He is not predicting what 2026 sales teams will look like, he is running one. The shift is not theoretical anymore. Lemkin's advice to sales leaders: deploy an AI agent yourself. Not through an agency. Not by delegating to your team. Do it yourself so you understand what changes. For junior sales and GTM roles, his message is clear: embrace it or get left behind. Be the person who knows how to run agents, not the one replaced by them. The question is not whether AI replaces sales roles. It is which ones, and how fast. Lemkin breaks it down role by role in his full post, separating what AI can handle today from what still requires human judgement. If you are still running a 2021 sales org structure in 2026, you are already behind. The companies figuring out the human-plus-agent model now are the ones that will scale efficiently. The ones waiting for clarity will be playing catch-up with worse unit economics. Worth noting: this is not about eliminating salespeople entirely. It is about fundamentally rethinking which tasks justify headcount versus agent spend. The best sales leaders are already making that calculation. **Related:** Sales automation trends 2026, AI predictions for sales teams, how AI changes sales jobs, future of sales teams with AI.

SaaStr
about 1 month ago
News

Investors now sit in on live prospect calls during fundraising diligence

## Investors now sit in on live prospect calls during fundraising diligence Forget reference calls. VCs are asking founders to pitch real buyers while they watch. Amanda Robson, GP of Modern Technical Fund, introduces founders to prospects in her network who have never seen the product. Then she sits in on the pitch as a fly on the wall. The shift is straightforward: reference calls are backward-looking. They tell you who already bought, not who would buy. Existing customers like the founder, they have favorable early-adopter contracts, and they want the company to succeed. They are incentivized to give a rosy review. A live buyer has no skin in the game. Their feedback is raw and objective. ### Why it works **It tests real positioning.** Can the founder clearly articulate what problem they solve, why it is urgent, why it is different, and why now? Watching someone lead a call and someone react to it in real time tells you more than a 15-minute reference call ever will. **It measures urgency-to-budget.** The most critical question in diligence is not "Does this work?" It is "Is this a priority?" By watching the pitch, the VC can see exactly where the product sits in the buyer's mental hierarchy. Nice-to-have gets "That is interesting, let us touch base next quarter." Urgency gets "How fast can we get this integrated? Who else are you working with in my industry?" **It removes access bias.** You are not just hearing a polished narrative after the fact. You are watching how the founder handles objections, where they lean in, where they hesitate, and how they adapt. ### What it means for sales teams If your company is fundraising, your sales team needs to be ready. This is not just about the CRO doing reference calls. Your AEs might be running live pitches with investors listening in. Prepare your team: tighten positioning, know your numbers, practice objection handling. Investors are not evaluating the product in a vacuum anymore. They are evaluating how well you sell it to someone who does not already believe. From the founder side, it is also a win. Even if the prospect does not convert, you get immediate market feedback. You learn what resonates, what falls flat, and where the story needs work. This trend aligns with broader 2026 fundraising reality: investors want live traction, not narratives. Companies like Monaco, which recently raised $35M from Founders Fund, are being built for this world: AI-native CRMs targeting Seed and Series A sales teams, emphasizing efficiency and leverage without headcount expansion. The bar for diligence just moved. Sales performance is no longer behind the scenes. It is the main event.

Sales Hacker
about 1 month ago
News

AI agents closing deals, not AEs: Firebolt runs CS with 2 humans

## The Third GTM Motion Is Here Firebolt President Hemanth Vedagarbha told SaaStr AI Annual that B2B sales has entered a third era. Not sales-led. Not product-led. AI-led growth, where algorithms handle top of funnel before a human ever sees your deck. The pitch: your buyer is an AI agent (ChatGPT, Claude, Gemini) parsing your website, not a VP scrolling LinkedIn. Your mid-funnel is agent-to-agent negotiation. Humans show up late, if at all. ## The Customer Success Model: 2 Humans, Rest Are Agents Firebolt runs CS with one human rep for the US, one for rest of world. Everyone else is agents driving in-product engagement. QBR decks that used to take hours now take minutes, AI-generated with usage data and next-best-action recommendations. Predictive churn models start on day one of a three-year contract, not month 35. Vedagarbha claims 22% churn reduction when deployed this way. The CS rep's job shifts from data assembly to relationship management. ## What This Means for Quota Carriers Firebolt shared their three-year plan: scale from 200 employees to 1,000, but the majority will be agents, not people. That reframes every sales role. If your SDR motion is cold outreach setting appointments for AEs, you are playing a game being automated out from under you. The data backs the urgency. Median SaaS growth dropped from 36% in 2021 to 16.5% today. CAC is up 55% over five years. Customer churn is a $136 billion drag across the industry. Public SaaS valuations collapsed from 17x to 6.7x revenue. ## The ANZ Reality Check Firebolt has no disclosed ANZ presence: no headcount, no regional deals mentioned. This is a Tel Aviv-based cloud data warehouse competing with Snowflake and Databricks on speed (36x faster, they claim) and cost (5% of legacy systems). But the AI-led growth thesis applies here. If your top of funnel is being evaluated by AI agents before humans enter the process, your pitch needs to be machine-readable, not just compelling. That changes how you write positioning, how you structure pricing pages, how you think about what gets scraped and summarised. Worth noting: Firebolt has no public revenue data, no disclosed funding rounds, no named CRO or VP Sales. They are engineering-led, partnership-focused (recent tie-up with Jedify for Semantic Fusion), not traditional sales scaling. ## What Actually Changes If AI-led growth is real, here is what shifts for quota carriers: - Top of funnel optimisation becomes SEO for AI agents, not Google - SDR headcount stays flat or shrinks, agent-assisted prospecting scales - AE role tilts toward high-touch relationship management, not discovery calls - CS becomes data science meets account management, not reactive support - Comp structures lag behind productivity gains (they always do) The CISO becomes the new Chief People Officer, governing what agents can and cannot do. The traditional CPO role shrinks. Sales ops becomes sales and agent ops. ## The Unasked Question Vedagarbha did not address headcount implications for sales teams. If Firebolt scales to 1,000 employees but 800 are agents, what does that mean for AE hiring? For quota distribution? For OTE structures when your team is 20% human, 80% AI? Those are the questions that matter. The comp transparency conversation just got harder, because now you are splitting quota credit between humans and the tools they use. Who gets paid when an agent closes a deal? What does attainment look like when half your pipeline is AI-generated? No answers yet. But the model is already running at Firebolt and others. Worth tracking.

SaaStr
about 1 month ago
News

Anthropic hits $14B ARR in 14 months, coding tool at $2.5B

## The Numbers Anthropic hit $14 billion ARR in February 2026. The company was at $1 billion ARR in December 2024. That is $1B to $14B in 14 months, growing 10x annually for three straight years. The company closed a $30 billion Series G at a $380 billion valuation, up from $183 billion five months earlier. No B2B software company has scaled this fast. Not Slack, not Zoom, not Snowflake. ## Claude Code: $2.5B in Nine Months Claude Code, Anthropic's agentic coding tool, launched publicly in May 2025. It is now at $2.5 billion ARR. That number doubled since January 2026. Enterprise users represent more than half of Claude Code revenue. Business subscriptions quadrupled in the past two months. According to recent data, 4% of all GitHub public commits are now authored by Claude Code. Projections put that at 20% by year end. ## Enterprise Metrics The customer breakdown: - $100k+ customers grew 7x in the past year - $1m+ customers went from a dozen to 500+ in two years - 8 of the Fortune 10 are Claude customers - 80% of revenue comes from enterprises - 70 to 75% of revenue is pay per token API, the rest is subscriptions and enterprise contracts Anthropic monetises at roughly $211 per monthly user versus OpenAI at about $25 per weekly user. That is an 8x difference. Smaller audience, massively higher revenue per user. ## What This Means for Sales Teams If you are selling into enterprises that use developers, your buyer budget just got reallocated. Companies are spending billions on AI coding tools. Claude Code went from zero to $2.5B ARR faster than most SaaS companies reach $100M. Enterprise buying patterns: 79% of OpenAI customers also pay for Anthropic. Enterprises are not choosing, they are buying both. Multi vendor AI strategies are the norm now. For sales professionals in SaaS: AI agents are repricing the entire software market. Anthropic's automation tools triggered a global software stock selloff. If your product competes with what an AI agent can do, your buyers are already asking that question. ## The Funding Context This $30 billion round is the second largest private tech raise ever, behind only OpenAI's $40 billion. At $380 billion on $14 billion ARR, Anthropic trades at roughly 27x ARR. That multiple is actually compressing as revenue scales. OpenAI sits at about 30x. 36+ investors participated beyond the leads: GIC, Coatue, Sequoia, Lightspeed, Accel, Founders Fund, General Catalyst, Microsoft, Nvidia, Blackstone, Qatar Investment Authority, Fidelity. When you are growing 10x annually with Fortune 10 customers, capital finds you. Anthropic is now the third most valuable private company globally, behind OpenAI and SpaceX. IPO timing is when, not if.

SaaStr
about 1 month ago
News

Atlassian CEO: Software not dead, but public SaaS index is broken

## The Revenue Stacking Problem Anthropic projects $149B ARR by 2029. OpenAI projects $180B. That is $350B between two companies in a $700B global software market, before you factor in Microsoft's $200B run rate. Mike Cannon-Brookes, CEO of Atlassian, pointed out what most coverage misses: the revenue stacking makes these numbers misleading. When Atlassian buys Anthropic, they pay AWS. AWS pays Anthropic. When Cursor does $1B in revenue, a chunk of that is the same billion flowing through the stack. The individual revenue number does not count the whole stack. Even accounting for stacking, the numbers are staggering. Scale Venture Partners' Rory O'Driscoll framed it: you are saying Anthropic becomes another Microsoft and OpenAI becomes another Microsoft. That is two new Microsofts feeding from the same CIO budget pile. The relief valve might be the trillion-dollar consulting and services market. AI could eat into systems integration spend around SAP, Oracle, NetSuite. That is budget that gets reallocated to more efficient software. But implementation consulting for AI itself is booming at Accenture and peers, while rote integration work gets automated. Swings and roundabouts. ## Software Is Not Dead Cannon-Brookes was direct: the idea that software as a category is dead is ludicrous. Businesses have always bought pre-built technology solutions. They did not write everything in assembly before, and they will not build everything from scratch with LLMs. He pulled up Atlassian's competitive docs from 2005, 2010, and 2015. A huge chunk of those companies are gone: merged, acquired, dead. That is capitalism. AI accelerates the cycle but does not change the pattern. ## The Real Problem: Composition For 15 years, median public SaaS growth held around 30%. Not because every company grew at 30%, but because when one slowed below 10%, PE took it private, and a new 60% grower IPO'd to replace it. That cycle broke. No new high-growth IPOs in years. PE bought the mid-tier. Big tech got better at M&A. Cannon-Brookes' SaaS CEO group from 2020 had 10+ public CEOs. Now it is him, Eric from Zoom, Aaron from Box, and Toby from Shopify. Almost everyone else got bought. What remains in the public index is a weird survivor set: too big for PE, too small for big tech, no new entrants. The average looks terrible, but it is a composition problem, not a death spiral. ## What This Means for Sales Teams If you are selling B2B software, the category is not dying. Your buyer's budget is getting reallocated, not cut. The challenge is positioning against both traditional competitors and AI-native alternatives that claim to replace entire categories. Watch where consulting budgets flow. When enterprises cut SI spend but increase implementation consulting for AI tools, that tells you where the real adoption is happening. The companies that survive this cycle will be the ones that ship fast and prove ROI in months, not quarters. For quota carriers: if your company is not in hypergrowth and not getting acquired, ask hard questions about the exit path. The middle is disappearing.

SaaStr
about 1 month ago
News

Techstars Sydney shuts down: NSW pulls funding after three cohorts

## Techstars Sydney shuts down: NSW pulls funding after three cohorts Techstars Sydney is closing. The NSW government declined to renew funding for the three-year-old accelerator program, which backed 36 startups across three cohorts with more than $60 million invested. Managing director Christie Jenkins confirmed she and her team are departing. No 2026 cohort will run. The closure follows a pattern. NSW has cut SXSW Sydney, closed the Sydney Startup Hub, reduced MVP Ventures funding, and stalled appointments to innovation councils. Investment NSW promoted Techstars as central to its Innovation Blueprint as recently as September 2025. Six months later, the program is gone. ### What this means for ANZ startups Techstars Sydney gave local startups access to 3,100 global mentors and 3,500 alumni companies. That network mattered for early-stage companies building enterprise sales motions or seeking intro paths to US enterprise buyers. The program selected around 12 companies per cohort from 560 applications in its final intake, up from 390 the prior year. The 2025 cohort included VetNotes (veterinary software) and Zipline AI (brand co-design). 43% of top applicants had women founders, 47% showed racial diversity. For sales professionals at ANZ startups: fewer accelerator paths mean fewer structured intro opportunities to enterprise buyers and fewer demo day showcases for early traction validation. Enterprise AEs selling to mid-market tech buyers will see a smaller pool of funded, accelerator-vetted companies entering their segments. Techstars globally has accelerated thousands of startups, with exits including Gainsight and DNSFilter (acquired Zorus). The Sydney program operated as a non-commercial accelerator arm backed by NSW funding rather than generating independent revenue. No word yet on whether the government will replace the program with alternative early-stage support. Based on the current trajectory, replacement seems unlikely.

Startup Daily
about 1 month ago
News

AI agents now drive B2B buying decisions, and they play favourites

## AI agents are making buying decisions, not just researching them When Jason Lemkin built SaaStr's AI tools on Replit, he needed email delivery, authentication, voice processing. The agent recommended Resend, Clerk, ElevenLabs. He picked all of them without demos, without G2 reviews, without a procurement process. That is happening across B2B now. According to Responsive's October 2025 survey of 350+ buyers, two-thirds rely on AI agents as much as Google when evaluating vendors. In software, that jumps to 80%. One in four B2B buyers use generative AI daily for vendor research. ## The bias problem nobody is talking about Here is what matters for sales teams: AI agents have favourites. They recommend based on training data, partnerships, and algorithmic patterns that are not transparent. When Replit's agent suggests HubSpot over competitors, is that based on fit, or on how HubSpot optimised for agent recommendations? This is algorithmic bias at scale. The same issues that affect AI lead scoring (undervaluing certain buyer profiles) and AI hiring tools (perpetuating historical patterns) now apply to vendor selection. If your product is not in the agent's top three, you are not getting evaluated. ## What this means for pipeline The playbook is changing: **Traditional B2B:** Prospect researches, reads reviews, requests demos, evaluates 3-5 vendors, negotiates. **AI-mediated B2B:** Agent surfaces 1-2 options, buyer trusts recommendation, deal velocity increases but consideration set shrinks. For sellers, this creates two problems. First, if you are not optimised for agent recommendations (whatever that means, because the algorithms are not public), you are invisible. Second, when agents make the shortlist, they compress sales cycles but also compress your opportunity to differentiate. ## The fairness question Lemkin frames this as bigger than SEO. He is right about the scale: 700 million people asking AI what to buy. But SEO had transparency. You could see rankings, understand algorithms, optimise accordingly. Agent recommendations are black boxes. Platforms like 6sense and Salesloft are launching AI agent tools for sales teams. Demandbase and Qualified are building agentic marketing workflows. But who is auditing the recommendation algorithms? How do we know which vendors get favoured, and why? ## What sales leaders need to do First, test it. Ask AI agents to recommend vendors in your category. See where you show up. If you are not in the top three, that is a pipeline problem. Second, understand the bias. AI agents trained on historical data will favour incumbents and well-funded brands. If you are a challenger or a regional player, the algorithm works against you. Third, demand transparency from the platforms building these agents. If Replit's agent recommends HubSpot, is that an editorial decision or a commercial relationship? Buyers (and their bosses) should know. This is not speculative. This is happening now. The question is whether sales teams will adapt before the consideration set gets locked in.

SaaStr
about 1 month ago
News

Salesforce runs 3 Agentforce pricing models at once, hits $540M ARR

## Three Models, One Product Salesforce shipped three pricing models for Agentforce in 18 months. All three are still running. October 2024: $2 per conversation. Elegant pitch, messy execution. What counts as a conversation when one customer query triggers 8 backend processes? Buyers could not model costs. Result: 5,000 deals in two quarters, only 3,000 paid. May 2025: Flex Credits at $0.10 per action. 100,000 credits for $500, each action consumes 20 credits. More granular, still unpredictable for enterprise procurement. Late 2025: Per-user licenses starting at $125/month. The Agentic Enterprise License Agreement wraps seats around your "digital workforce." CFOs get a number they can budget. CIOs get a contract shape they understand. Salesforce did not kill the other models. All three run simultaneously. ## The Numbers Agentforce hit $540M ARR by Q3 FY2026, growing 330% year-over-year. 18,500 total deals closed, 9,500 paid. That is 8% penetration across Salesforce's 150,000+ customer base. The multi-model approach is working better than $2/conversation ever did. Pricing opened doors instead of closing them. The per-user option gave enterprise procurement teams something they could actually approve. Salesforce had to discount. Heavily. A company that "just does not discount ever" gave steep concessions to get enterprises committed. But they got the deals done. ## Why This Matters for Sales Teams If you are selling Salesforce or competing against it, understand this: the pricing is not chaos, it is market discovery. Nobody knows what the right model for AI agents actually is yet. The PricingSaaS 500 Index tracked 1,800 pricing changes across the top 500 B2B and AI companies in 2025. That is 3.6 pricing changes per company in one year. Credit-based pricing grew 126% year-over-year. Seat-based pricing as the primary model dropped from 21% to 15% of companies in 12 months. For sales teams selling into this: your buyers are confused about how to budget AI. Three pricing models gives them three on-ramps. Match the model to how they want to buy, not how you want to sell. For sales teams using Agentforce: the $125/user/month model is predictable, but watch your actual credit consumption on the Flex model. The ROI depends on volume and use case. Get the calculator out before you commit. The market has not converged on how to buy AI agents. Until it does, expect more pricing shifts, more models, and more "competitive" deals where vendors discount to win early adoption.

SaaStr
about 1 month ago
News

Twelve B2B SaaS companies now trade below 2.5x revenue, some under cash

## The Numbers Twelve public B2B SaaS companies now trade below 2.5x revenue. Some sit under 1x. A few trade below their cash on hand. Combined ARR: $10 billion. Combined market cap: under $10 billion. This is not a broad market problem. Median public SaaS still trades around 3x revenue. The S&P is up 17.6% while the SaaS index dropped 6.5% over the same period. This is selective, and it is getting worse. ## What Puts You in the Club Seven patterns show up across every company in this group: **Growth stalled or went negative.** Eight of twelve are growing under 5% or shrinking. Median growth: roughly flat. When you stop growing in B2B, the market stops caring. Five9 at 13% growth gets 2.5x. Upland at negative 23% gets 0.2x. **The 2020 hangover never ended.** Every company peaked between 2019 and 2021 at absurd multiples. RingCentral hit 35x revenue. Teladoc hit $50 billion market cap. COVID pulled forward three years of demand. When it normalized, growth collapsed and never recovered. The difference now: rates are down, the market is strong, but these businesses are not recovering. This is structural, not cyclical. **No credible AI story.** Palantir trades at 50x revenue. CrowdStrike at 20x. Salesforce gets 7x at 8% growth because AgentForce is real. LivePerson does "conversational AI" and trades at 0.2x because being AI-adjacent without AI-native architecture makes you the disrupted, not the disruptor. Features bolted onto pre-AI products do not count. The market wants AI as the core value proposition and the core growth driver. **Profitability is unclear or negative.** Upland carries $301 million in debt. LivePerson refinanced to avoid defaulting on convertible notes. Domo has $140 million in debt against a $243 million market cap. Teladoc is still writing down the $18.5 billion Livongo acquisition. The companies inching toward profitability still cannot escape because profitability alone does not work. You need growth and profitability. Rule of 40 still matters. **Leadership instability.** Founder-CEOs resigning, messy transitions, second or third leadership teams in three years. When you are fighting for survival, executive churn kills momentum. Several companies are trying to execute turnarounds while managing the AI transition. That is nearly impossible to do simultaneously. **Category headwinds from AI-native competitors.** Some of these companies are not just missing an AI story. Their categories are being actively replaced by AI-native products. Budget is moving to hyperscalers ($470 billion in AI infrastructure spend), to vertical SaaS with domain moats (growing 20-31%), and to AI agents that automate workflows entirely. Horizontal platforms without AI defensibility are getting squeezed. Enterprises are consolidating around 275 apps per company, down from more. Seat-based pricing is weakening as AI reduces headcount needs. **Net revenue retention stalled.** NRR for top performers sits at 115-125%, driving 2.5x faster growth. For this group, NRR is flat or declining. Expansion revenue dried up. New logos are not enough to offset churn and contraction. ## What This Means for Sales Teams If your company fits these patterns, expect: **Flat or shrinking territories.** Budget is not growing. Customers are consolidating vendors, not adding them. Price resistance is real. Deals are taking longer, scrutiny is higher. **Quota relief is unlikely.** When growth stalls and profitability is unclear, leadership cuts costs, not quotas. Attainment across the industry is already sitting around 85% for realistic plans. At companies in structural decline, expect that to drop further. **Retention becomes the priority.** New logos are expensive. NRR is the metric that separates survivors from the 2x ARR Club. CROs are pivoting comp plans to weight renewals and expansion heavier. If your comp is still 90% new business, that is a red flag. **AI integration is table stakes.** If your product roadmap does not have AI as the core value prop by now, customers are noticing. Klarna dropped Salesforce and Workday. Publicis cut Adobe spend by 50%. Budget is moving to AI-native tools. If you are selling a horizontal platform without a credible AI story, you are fighting headwinds every deal. ## The Comp Reality No one is publishing updated OTE for these companies, but the pattern is clear: when stock comp craters and cash flow is tight, total comp suffers. RSUs granted in 2021 are underwater. New hires are getting lower equity packages. Base salaries are holding, but accelerators and President's Club are getting quietly restructured. If you are interviewing at a company trading under 3x revenue, ask: - What is historical quota attainment? - What is NRR trending? - What is the AI roadmap, and is it driving pipeline or just a feature? - How much of OTE is stock, and what is the strike price relative to current valuation? Those questions will tell you if you are walking into the 2x ARR Club. ## What Gets You Out Growth plus profitability. AI as the growth driver, not a feature. NRR above 115%. Leadership stability. Category tailwinds, not headwinds. Eight of these twelve companies will not make it out. They will get acquired for parts, go private at distressed valuations, or slowly bleed revenue until they are irrelevant. A few might turn it around, but the window is closing. The lesson: growth is not optional. AI is not optional. NRR is not optional. If you are flat, non-AI-native, and horizontal, the market is pricing you like you are already dead.

SaaStr
about 1 month ago
News

AI tools adding workload for sales teams, not cutting it

## The efficiency promise is not delivering AI was supposed to give sales teams more time for selling. The reality looks different. New research from UC Berkeley tracked 200 workers at a US tech company for eight months as they adopted generative AI tools. The outcome: people did more work, not better work. Product managers started writing code. Researchers took on engineering tasks. Sales teams filled what used to be breaks with AI-prompted micro-tasks. Work intensified. Natural pauses disappeared. The workday got longer and denser. ## The numbers tell two stories Individual productivity is up. Email processing is 25% faster with AI. Coding tasks complete 55.8% quicker. US productivity growth hit 2.7% in 2025, nearly double the previous decade's average. Generative AI contributed 1.1 to 1.3 percentage points of that growth. But here is the catch: 95% of organisations report no measurable return on AI investment, according to MIT Media Lab. AI adoption doubled since 2023. Usage jumped from 55% to 78% of organisations. The tools work at the task level. They are not working at the business level. ## What this means for ANZ sales teams If you are using AI for prospecting, email sequences, or proposal writing, watch for these signs: your day feels fuller but quota attainment is flat. You are checking AI output more than you expected. Small tasks are multiplying. The tools make individual tasks faster, but your workload keeps growing. The Berkeley researchers call it "intensification of work." Sales teams call it grinding harder for the same result. Worth noting: lower-performing reps see the biggest individual gains from AI, suggesting these tools compress skill gaps while creating new management overhead. Wharton projects AI productivity gains will peak in the early 2030s, then fade as implementation complexity catches up. That tracks with what we are seeing now: fast adoption, minimal business outcomes, and teams working harder to manage both the AI and the work it generates. ## The burnout risk The research found workers felt "empowered" by AI, taking on tasks outside their normal scope. That confidence came with a cost: wider job scope, fewer natural breaks, continuous work involvement. Over eight months, what felt like efficiency gains accumulated into overwork. For sales leaders: if your team adopted AI tools in the past year and quota attainment has not moved, you are not alone. The tools work. The business case does not. Yet.

Startup Daily
about 1 month ago
News

HotDoc sells to Potentia PE for $250M-$300M, Airtree partially exits

## HotDoc sells to Potentia PE for $250M-$300M, Airtree partially exits HotDoc, Australia's largest patient engagement platform, sold to private equity firm Potentia Capital in a deal valued between $250M and $300M. Potentia now holds majority stake, with health tech investor Acclivis Group joining as a partner. Original backer Airtree, which led HotDoc's $2.2M Series A in 2015, remains as a minority investor. CEO and founder Dr Ben Hurst confirmed the sale on Wednesday. The company serves 23,000 medical practitioners and 13 million active patients, processing 2.5 million appointments monthly. Nearly 1 in 3 Australians use the platform to book GP appointments, handle telehealth, and receive test results. ### What This Means for the Sales Team PE acquisitions typically trigger sales org restructuring within 6-12 months. Potentia will likely assess: customer acquisition costs, sales cycle length, quota attainment rates, and whether the current team structure supports aggressive growth targets or needs optimisation. HotDoc added 66 employees in October 2020 during its growth phase. No word yet on current sales team size, recent sales leadership hires, or whether Potentia plans to expand into enterprise hospital systems beyond GP practices. That expansion would mean new AE roles, longer sales cycles, and different comp structures. Airtree's partial exit after 10 years signals a liquidity event for early employees with equity. For current sales staff without significant stock, PE ownership usually means: clearer revenue targets, more aggressive quota setting, potential territory realignment, and pressure to prove ROI on every role. ### The PE Playbook Potentia operates healthcare and tech portfolio companies. Standard PE moves: implement rigorous pipeline forecasting, standardise comp plans, evaluate whether current OTEs align with market and performance, assess which sales roles drive the most efficient revenue growth. Hurst remains CEO, which provides continuity. But PE majority ownership means the growth mandate likely shifted from "build market share" to "optimise unit economics and prepare for next exit." For sales professionals watching this deal: PE acquisitions create opportunity for high performers who can operate in a metrics-driven environment. They also mean less patience for missed quota and underperforming territories. Know your numbers, document your wins, and understand your equity situation before any restructure conversations start.

SmartCompany
about 1 month ago
News

Shopify hits $11.6B revenue, 30% growth. Stock down 28% anyway.

## The Numbers Shopify closed 2025 at $11.6 billion revenue, up 30% year over year. Free cash flow hit $2 billion on a 17% margin. GMV grew 29% to $378 billion. They announced a $2 billion buyback and guided Q1 growth to low 30s, above Street expectations. The stock is down 28% in 2026 so far. Down 38% from its 52-week high. ## What Actually Matters for Sales Shopify now processes 14% of all US e-commerce. GMV growth is accelerating: 20% in 2023, 24% in 2024, 29% in 2025. At nearly $400 billion in transaction volume, they are speeding up, not slowing down. Shopify Payments penetration hit 68% of GMV in Q4, up from 45% five years ago. That is $248 billion in payments volume. Merchant Solutions (the payments-heavy segment) is now 76% of total revenue. Subscriptions are just 24%. They have become a fintech company that happens to sell commerce software. B2B commerce grew 96% for the full year. Every quarter cleared 84% growth, with Q4 at the low end. Brands like Carrier and Dermalogica are using Shopify for B2B now. The horizontal platform went upmarket without building a separate product. ## The Profitability Turn Free cash flow swung from negative $186 million in 2022 to positive $2 billion in 2025. Operating expenses dropped from 60% of revenue in Q1 2023 to 29% in Q4 2025. They divested logistics, cut headcount, and got disciplined. The gross margin compressed slightly as payments grew, but operating leverage more than compensated. ## The Market Reality Shopify trades at roughly 100x earnings, 73x forward. At some point, even strong growth has to meet valuation reality. The business is performing. The multiple is compressing. That is the story. For anyone selling into or around e-commerce: the underlying platform is expanding fast. GMV growth is accelerating. B2B is nearly doubling. The infrastructure layer is getting stronger, regardless of what the stock does on any given Tuesday.

SaaStr
about 1 month ago
News

eBay buys Depop from Etsy for $1.7b, chasing Gen-Z fashion resale

eBay is buying fashion resale platform Depop from Etsy for $1.7 billion in cash, marking another shift in marketplace consolidation strategy. The numbers: Depop has 7 million buyers, 90% under 34. Three million active sellers moved $1 billion in gross merchandise sales in 2025. The platform has grown since Etsy acquired it in 2021 for $1.6 billion, meaning Etsy exits with a modest gain after four years. ## What eBay Gets Depop runs on social commerce: Instagram aesthetics meets peer-to-peer selling. Founded in 2011 by Simon Beckerman, it targets Gen-Z with secondhand fashion and vintage clothing. The platform generates engagement beyond transactions: in its early days, users were hitting 13 million likes and 18 million follows daily. eBay CEO Jamie Iannone says Depop gets access to eBay's scale and operational capabilities. Translation: logistics infrastructure, payment systems, and cross-platform inventory management that smaller marketplaces struggle to build alone. ## The Marketplace Play This fits eBay's pattern of buying established vertical marketplaces rather than building them internally. Depop stays standalone, keeps its brand and platform. That suggests eBay learned from past integration missteps: let the acquired team run their playbook, layer in backend infrastructure where it helps. For B2B marketplace operators, the take is clear: vertical focus with strong demographic lock-in creates acquisition value. Depop owns Gen-Z fashion resale the way LinkedIn owns professional networking. That defensibility justifies premium multiples even in a category (peer-to-peer resale) that eBay already serves. Etsy's exit after four years signals something too: owning a social-first marketplace alongside its maker-focused platform did not generate the synergies they expected. Sometimes the best acquisition strategy is knowing when to sell. Depop continues operating independently. The 500-person team stays intact, headquartered in London with a New York office. No layoffs announced, which in 2026 M&A is worth noting.

SmartCompany