The Wire

Real-time updates from ANZ tech sales

17 days ago
News

FAL hit $100M ARR in 2 years, broke SaaS margin math

## The margin problem is not going away FAL (fal.ai) hit $100M ARR in under two years serving 2M+ developers and 300+ enterprises including Adobe, Canva, and Shopify. Co-founder and CTO Gorkem Yurtseven says the company learned what most AI infrastructure businesses are figuring out the hard way: your margins are worse than SaaS, and they are not improving. Every new user costs real money to serve. GPUs are expensive. Inference is expensive. The assumption was that model costs would drop and save everyone. They have not. As older image models got cheaper to run, customers moved to new video models that cost dramatically more. Software advances faster than hardware. Net result: lower margins than before, and no relief coming. Yurtseven's advice: build pricing that reflects real cost to serve from day one. Do not assume you can fix it later. ## High-usage customers can wreck your economics In traditional SaaS, your biggest users were your best customers. More usage meant more value, more expansion, better NRR. In AI infrastructure, high-usage customers are high-cost customers. If your pricing does not account for that, you are subsidizing your largest accounts. FAL tracks wallet share: the percentage of a customer's total generative media spend flowing through the platform. The metric reframes expansion. It is not just about growing accounts. It is about growing the right accounts in the right way. ## Annual quotas broke during the hiring process FAL tried to hire a head of sales. The candidate wanted a quota and commission structure. The team calculated what doubling in a year would look like as an OTE target. During the interview process, they grew roughly 50% of that annual target. The quota became meaningless before the hire was made. At 50% quarterly growth rates, annual targets are guesswork. FAL now runs shorter-term quotas (monthly or quarterly) where they can course-correct when the business moves. For now, the team operates on target earnings without hard quotas. It is not a permanent solution. It is an honest response to an unpredictable environment. Worth noting: FAL has one public sales listing (Senior Account Executive), suggesting a small but growing sales function focused on enterprise adoption. No CRO or VP Sales is named. The company is backed by Sequoia Capital. ## What actually matters FAL watches three metrics closely: logo quality and diversity (big names across different verticals), wallet share (not just usage), and cost per inference (the number that determines if the business model works). The positioning play mattered. FAL committed to "generative media platform" specifically, not general AI infrastructure. The buyers for image models are completely different from the buyers for language models. Different use cases, different budgets, different decision makers. Being the clearest answer to one specific thing beats claiming to do everything. FAL was founded in 2021 by Burkay Gur (ex-Coinbase ML) and Gorkem Yurtseven (ex-Amazon), with Head of Engineering Batuhan Taskaya (Python core developer). No ANZ presence or operations mentioned.

SaaStr
18 days ago
News

Mangomint VP Sales hits 7.2x ARR-to-OTE with 8 demos per day, $4K ACV

## The Numbers Marshelle Mooney, VP of Sales at Mangomint, is running a remote SMB sales org that hits 7.2x ARR-to-OTE. For context: 3-5x is typical in SMB SaaS. Anything above 6x is rare. The setup: $4K initial ACV, five-day sales cycles, eight demos per AE per day. Fully remote team. Customer base is salons and spas, classic high-volume SMB. The company is at 150 people total. That ratio means reps are booking seven times their on-target earnings in ARR. If an AE has $100K OTE, they are closing $720K in ARR. The math works because Mooney knows her unit economics cold: four hours of selling time per deal, 30 focused hours per week, and she can see exactly when a rep's pace is off because all calendars are public. ## The Operating Model Mooney spent two years running what she calls "the AI kitchen sink." More tools, more dashboards, more call intelligence layers. It made things worse. Information lived in six places. Reps did not know where to look. Managers lost visibility. The fix was subtraction, not addition. She consolidated the entire revenue org into two surfaces: Slack and Notion. Everything else either feeds into those or gets cut. The model has three layers. **Clarity:** every playbook, objection handler, comp detail, and product update lives in Notion. If a rep has to Slack someone for an answer, this layer is broken. **Cadence:** every functional leader posts a weekly update, minimum bar is one main thing. Reviews and one-on-ones run on predictable schedules. **Co-pilot:** this is where AI actually lives, but it only works if the first two layers are solid. Most teams skip straight to layer three. That is why most AI implementations fail. ## The Automation Layer Mooney pushes data to reps instead of waiting for them to pull it. Card failures route instantly to the account owner. Win rate changes surface in Slack before the weekly review. Call summaries from Momentum (their call intelligence tool) push automatically into Notion and Salesforce. The principle: if information requires effort to find, most reps will not find it until there is a problem. By then it is too late. The stack is Momentum for call intelligence, Snowflake for data warehouse, Sigma for dashboards. But the tooling is not the story. The story is that automation only drives efficiency after you fix fragmentation. ## What This Means for SMB Sales Low ACV, high volume, constant rep churn: that is the standard SMB playbook, and it is inefficient by design. Most orgs throw bodies at the problem when pipeline slows. Mooney's approach is different. She knows the math, she built the operating model first, and she cut tools instead of adding them. The 7.2x ratio is the output, not the goal. The goal is a system where reps spend 30 focused hours per week on revenue activities and leadership knows within days when something is off. Worth noting: Mangomint is U.S.-focused salon and spa software. This is not enterprise SaaS. This is high-velocity SMB with short cycles and low ACV, which makes the efficiency metrics even more notable. Most SMB orgs accept 3-4x ratios as the ceiling. Mooney is proving that is a choice, not a constraint.

SaaStr
18 days ago
News

Why B2B SaaS companies under 20% growth are quietly dying

## The Numbers That Matter Jason Lemkin, founder of SaaStr and former EchoSign CEO, posted a reality check for B2B SaaS growth. Two thresholds matter: under 20% YoY growth puts you in the Danger Zone. Under 10% is the Dead Zone. The Danger Zone is not about total revenue. It is about where that revenue comes from. Companies growing sub-20% are typically extracting value from existing customers through retention, price increases, and upsells. New logo acquisition has stalled. Pipeline is weak. The business feels fine internally because revenue still ticks up, but the new business motion has stopped working. Okta is the example. Revenue up 11-12% YoY, but they added only 85 net new $100k+ customers in Q3 FY2026. For a company at their scale, that is standing still on new logos. UiPath is similar: revenue up 16%, ARR growing 11%, with net new ARR declining for several quarters. Both companies have strong net revenue retention from their existing base. Expansion is carrying the load while new business dries up. ## What This Means for Sales Teams When companies hit the Danger Zone, sales teams see it first. Territories shrink. Quota gets adjusted down or includes more expansion targets. Comp plans shift from new logo accelerators to upsell and cross-sell. Ramp periods get longer because there are fewer deals to close. Historical quota attainment data shows that companies in the Danger Zone see attainment rates drop from 70-80% to 50-60% as pipeline generation slows. SDR teams get cut or reassigned to account development. AE headcount freezes. The CRO starts talking about efficiency instead of growth. The Dead Zone (sub-10% growth) is worse. This is not a sales problem. This is a product-market fit problem. Dropbox is the example: paying users flatlined at 18M, revenue declining YoY. CEO Drew Houston is betting on Dash as a re-founding play. Asana is knocking on the door: 9% growth in Q4 FY2026, guidance for 7.5-8.5% in FY2027, NRR at 96%. When NRR drops below 100%, the existing base is contracting. No amount of sales optimisation fixes that. ## The SMB Trap Lemkin calls out the SMB tax: low average MRR per customer means you need thousands of net new logos every quarter just to maintain baseline growth. If your average customer pays $200/month and you need 20% growth, the acquisition volume required is enormous. Churn feels painless per logo, but the replacement burden is brutal. CAC does not drop just because the ticket is smaller. For ANZ teams, this maps to the local mid-market and SMB SaaS plays that looked smart in 2021 but are now grinding against the math. Median B2B SaaS revenue growth in 2025 sits at 28%, down from 47% in 2024, per OpenView and Bessemer benchmarks. Bootstrapped SaaS companies average 20% growth at $3M-$20M ARR. VC-backed firms face higher expectations and are hitting the Danger Zone harder. The fix for the Danger Zone: rebuild the new logo motion. The fix for the Dead Zone: re-found the company. Most sales teams do not get that second option. They get layoffs instead.

SaaStr
18 days ago
News

Two years of declining growth: what actually works to turn it around

## The Market Split The B2B SaaS market has bifurcated hard. Top quartile companies at Series A stage are growing 515% year over year, per ICONIQ data. AI-native startups are hitting 360% new logo velocity compared to 71% for non-AI peers. Some are reaching $100M ARR in 1-2 years instead of the historical 5+. Meanwhile, 35% of B2B companies are declining year over year, the highest rate since 2020. Public B2B SaaS growth settled at 11% CAGR in 2024, down from 30%+ in 2021. Private companies are doing better at 25-26% median growth, but two years of linear decline means you are sliding toward the bottom. ## What Actually Works **Product-market fit reality check:** Two years of decline usually means the market shifted or your product did not keep up. Visit your top 10 customers in person this quarter. They will show you a path to growth. **Net new customer velocity:** This is the number founders mask first. You can cover declining new customer acquisition with price increases and expansion revenue for a while, but sustained slowdown in net new logos means your product is losing market relevance. Get more customers now. Raise prices later. **NRR compression:** Median net revenue retention for private B2B companies has fallen to 101%, down from 2021 highs. Top performers maintain 111%+. Best-in-class public companies sit at 120-125%. If you are below 100%, that is your most urgent problem. But do not harvest your existing base while new logo growth dies quietly. **New leadership energy:** After two years of slow growth, morale follows the revenue chart down. One exceptional new VP who has seen a turnaround breaks the pattern. One VP of Sales, one VP of Marketing, or one CRO who knows what getting back to growth actually requires. ## The Sales Team Reality Industry-wide, sales efficiency metrics declined across ARR bands in 2023. Median B2B SaaS growth for $50M-$100M ARR firms hit 12% in 2023 versus planned 21% for 2024. Companies over $100M ARR grew 12% against planned 29%, per Pavilion benchmarks. The worst thing you can do is blame macro headwinds and wait. The companies accelerating right now did not get there by waiting it out. Go talk to customers, fix net new customer velocity, bring in fresh leadership, and decide which side of the bifurcation you are going to be on.

SaaStr
19 days ago
News

Anthropic takes 73% of new enterprise AI spend, up from 50% ten weeks ago

## The Numbers Anthropic now takes 73% of new enterprise AI spending, according to Ramp transaction data. Ten weeks ago, the split was 50-50 with OpenAI. That is the leading indicator that matters. Overall, Anthropic holds 32-40% of enterprise LLM market share, up from 12% in 2023. OpenAI sits at 25-27%. In coding specifically, Anthropic's share hits 42-54%. Total enterprise genAI spend is projected at $37B in 2025, with average firm spending climbing from $7M this year to $11.6M in 2026. ## Why This Matters for Sales Teams The shift is driven by workflow lock-in, not just product quality. Claude Sonnet and Opus models have become the default for coding and data analysis. Once a company spends weeks building AI workflows, dialing in outputs, and training on their context, they do not switch. The soft costs are enormous even when token pricing looks attractive elsewhere. For sales teams evaluating AI tools, this is the relevant question: are you building on the platform that enterprises are locking into? If your stack depends on OpenAI integrations and enterprise buyers are standardising on Claude, that is a planning problem. OpenAI still owns consumer mindshare. ChatGPT has the muscle memory. But the enterprise coding market, which drives the bulk of AI spend, is locking in now. Anthropic's consistency, contrasted with OpenAI's direction changes (headcount flat then double, agentic commerce then deprioritised, hardware then not), has created a smell that enterprise buyers notice. ## The Broader Context Anthropic, founded in 2021 by former OpenAI executives, raised over $8B including a $4B round from Amazon. The company is valued at $18.4B. API data shows 77% of usage is automation-focused. Ramp's customer base skews toward digital companies making these decisions first. Their data scientists are credible. The sample is not a lemonade stand. For sales orgs building AI into prospecting, lead gen, or account management workflows, the marginal buyer trend is the signal. Where enterprise spend is moving tells you where support, integrations, and ecosystem development will follow. Right now, that is Claude.

SaaStr
19 days ago
News

Support Fusion raises $1m, hiring GTM in Australia and US

## Support Fusion raises $1m, hiring GTM in Australia and US Melbourne startup Support Fusion closed a $1 million pre-seed round on March 24, led by Func Ventures and Exhort Ventures. Antler backed them earlier. Three Australian channel operators joined the round: Biagio LaRosa (CEO, Generation-e), Ryan Spillane (CEO, 360 Consulting), and Toby Alcock (founder, Paratira, former Global CTO of Logicalis). The company integrates ticketing tools like ServiceNow, ConnectWise, Jira, Halo, Freshworks, Autotask, and Zendesk. Target customers: managed service providers, system integrators, and enterprise IT teams running co-managed support models. Went live mid-2025, now operating in ANZ, US, and UK. ### The hiring plan Funds are going toward headcount in three areas: 1. **Go-to-market and alliances (Australia)**: Focus on vendor marketplace listings and co-sell deals. 2. **AI engineering**: Building agentic capabilities into the platform. 3. **US expansion roles**: GTM, partnerships, customer success, and engineering for 24/7 coverage across US and UK markets. No specific role counts disclosed. No comp details shared. ### What this means for sales teams If you are selling into IT service providers or enterprise IT teams, Support Fusion is worth tracking. Their growth pattern matters: nine months from launch to US/UK presence, plus early customer pull without outbound push. That usually signals product-market fit. For candidates: early-stage (pre-seed), Melbourne HQ, US expansion mode. Expect startup comp structures and ramp uncertainty. Ask about quota, territory definition, and what realistic attainment looks like when you are selling integration tools to MSPs. The investor mix is notable. Three operators from the channel side (Generation-e, 360 Consulting, Paratira) means product feedback will be direct. That can help or hurt sales cycles depending on how fast they ship changes. ### Market context IT support outsourcing and service desk outsourcing companies are the core TAM here. MSPs and system integrators run ticketing across multiple platforms. Support Fusion's pitch: stop manually syncing tickets between systems. The offshore staffing angle matters too, many MSPs run distributed teams across ANZ, US, and offshore locations. Integration tools that work across time zones and systems are table stakes. CEO Greg Rudakov said US and UK customers started pulling the product without them pushing. That is the signal VCs care about. Now they are hiring to scale it. No revenue disclosed. No team size disclosed. No comp ranges shared. Standard pre-seed opacity.

Startup Daily
19 days ago
News

OpenAI kills Sora video app, Disney pulls $1.4B investment

OpenAI killed its Sora video generation app on March 24, six months after CEO Sam Altman called it the "ChatGPT for creativity." Disney cancelled its reported $1 billion investment in OpenAI, tied to a licensing deal for 200+ characters through Sora. The deal, announced in December 2025, is dead. OpenAI shut down the standalone app, the API, and Sora's ChatGPT integration. The company gave no reason for the shutdown beyond thanking users who created content with the platform. ## What this means for sales OpenAI's $150B+ valuation relies on enterprise API revenue and ChatGPT subscriptions, not consumer video apps. Revenue hit $3.7B in 2024, driven by B2B deals and Microsoft's $13B+ investment across multiple rounds. The Sora shutdown signals a strategic pivot. OpenAI is redirecting resources toward core models and robotics, away from consumer fragmentation. That matters for anyone selling into or alongside the company's enterprise stack. For context: OpenAI has 3,500+ employees globally. Sales team size is not public, but likely dozens to low hundreds given the enterprise focus and Microsoft partnership channel. No named CRO or VP Sales. Fidji Simo runs applications as Chief of Applications. Sora launched in US and Canada only. ANZ presence is minimal: no dedicated offices, no disclosed headcount. Enterprise clients in the region are served through US and EU hubs. ## Market reality OpenAI dominated text-to-video with Sora, competing against Runway, Pika Labs, and Luma AI. Walking away from the consumer app while competitors double down tells you where they see the revenue. The Disney deal collapse is notable. A $1B commitment from a blue-chip enterprise partner does not fall apart quietly. Worth asking: what changed between December and March that killed a nine-figure licensing agreement? Bottom line: OpenAI is simplifying. Consumer video apps are out. Enterprise AI infrastructure and robotics simulation are in. If you are selling into this space or evaluating roles at AI companies, watch where the resources actually go, not where the launch announcements point.

Startup Daily
19 days ago
News

Eight ANZ startups raise $373m: Halter leads at $2.9b valuation

# Eight ANZ startups raise $373m: Halter leads at $2.9b valuation Eight startups across Australia and New Zealand raised $373.3 million this week. New Zealand agtech Halter led with a $314.4 million Series E, bringing its valuation to $2.9 billion. ## The Numbers **Halter: $314.4 million Series E** Peter Thiel's Founders Fund led the round. The virtual fencing startup is expanding into Australia, the US, and Europe. Previous rounds not disclosed in source material. **Other raises this week:** - Silicon Quantum Computing (amount not disclosed) - Cauldron (amount not disclosed) - Future Maintenance Technologies (amount not disclosed) - Cuttable (amount not disclosed) - Rumin8 (amount not disclosed) - Support Fusion (amount not disclosed) - Scanabull (amount not disclosed) Total confirmed funding: $373.32 million across eight companies. ## What This Means for Sales Teams Series E rounds typically precede significant go-to-market expansion. Halter's geographic push into Australia, US, and Europe suggests enterprise AE hiring in those markets within 3-6 months. Watch for roles in Sydney and Melbourne first. Agtech sales cycles run 6-12 months for enterprise deals. Teams entering new markets usually hire 2-4 AEs per region, plus SDR support. ## Context Halter's $2.9 billion valuation makes it one of the largest agtech companies in ANZ. The funding environment for late-stage startups remains active despite broader market headwinds. For sales professionals: funding announcements like this typically signal hiring 60-90 days out. If Halter's expansion plans hold, expect ANZ enterprise roles to open mid-year. *Note: Detailed funding amounts for six of the eight companies were not disclosed in source material.*

SmartCompany
19 days ago
News

ICONIQ data: Sales cycles drop 6 weeks, contract length shrinks 30%

# ICONIQ data: Sales cycles drop 6 weeks, contract length shrinks 30% ICONIQ Growth's January 2026 survey of 150+ B2B software companies shows the sales motion is getting faster but shorter. Average sales cycle dropped from 25 weeks in H1 2025 to 19 weeks in H2 2025. Deals under $10K ACV close in 6 weeks. Enterprise deals ($100K+ ACV) still take 24 weeks. The complication: contracts are shrinking. Sub-1-year deals jumped from 4% of new logos in 2023 to 13% in 2026. Three-year deals dropped from 28% to 23% over the same period. Buyers are moving faster but committing for less time. In an AI market where the best solution can shift in 6-12 months, multi-year lock-in feels like uncompensated risk. ## The numbers that matter for sales teams **POC conversion is the highest-performing motion.** Free trials and proof-of-concept converted at 50% to paid, up 14 points year over year. That beats SQL to Closed-Won (28%), Demo to Closed-Won (38%), and New Lead to MQL (28%). If your POC process is not a disciplined sales motion with dedicated support and clear success criteria, you are leaving pipeline on the table. **Sales is driving new logo pipeline, not marketing.** High-growth companies under $100M generate 62% of new logo pipeline from sales, 19% from marketing. Slower-growing peers: 47% sales, 34% marketing. The fastest-growing B2B companies are seller-led at the new logo stage. **AI adoption is creating 20-30% leaner GTM orgs.** At $10M-$25M revenue, high AI adopters run 20 GTM FTEs versus 35 for low adopters. At $100M-$250M: 125 versus 165. Companies with AI fully embedded in GTM show 67% of ramped AEs hitting quota versus 59% without. For SMB AEs, that gap widens: 106% attainment versus 80%. **NDR is holding at 110-123% despite shorter contracts.** Top-quartile NDR sits at 123% for companies under $50M ARR, 109% for $100M+ companies. Expansion is compensating for shorter upfront commitments. ## What this means for quota carriers Shorter cycles and shorter contracts mean more frequent renewals and expansion conversations. Your comp structure needs to account for this. If your OTE assumes 12-month deals and your average contract is now 8 months, your attainment math just changed. The 50% POC conversion rate is the number worth building around. High-growth companies are treating POC as a sales motion, not a technical exercise. That means dedicated resources, clear success criteria, and exec alignment before the trial starts. AI adoption is not optional if you want competitive quota attainment. The gap between high and low AI adopters is 8 percentage points at the AE level, wider for SMB and enterprise segments. That is the difference between hitting plan and missing it. ICONIQ's data shows top-quartile ARR growth reaccelerating: 111% for companies under $50M ARR, 91% for $50M-$100M, 33% for $100M+. The best companies are pulling away. They are doing it with leaner teams, faster cycles, and higher POC conversion. The rest are not keeping up.

SaaStr
20 days ago
News

SaaStr deploys 1 of 25 AI vendor pitches: deployment beats demo

# SaaStr runs 30 AI agents. 25 vendors pitched them this week. One got deployed. The difference: that vendor deployed the agent in five minutes instead of booking a demo. Jason Lemkin's team at SaaStr operates with three humans and 30+ AI agents. Their capacity for new tool evaluations is zero until after their May event. When five leading AI agent vendors reached out this week (plus 20 more via LinkedIn), the answer was uniform: talk in June. Except one vendor replied: "Give us five minutes. We will deploy it for you right now." They made time for that one. It is live. The other four are on the June list, if SaaStr has not found another solution by then. ## Deployment is the sale The winning vendor understood what most AI sales teams miss: Forward Deployed Engineers matter before the contract, not after. Every AI agent SaaStr runs successfully had dedicated FDE time. Every one. Palantir invented this model in the early 2010s because government agencies could not get to production without an engineer in the room handling messy data and specific workflows. Most AI vendors today use FDEs post-sale. The ones winning use them pre-sale. Marc Benioff told Lemkin on 20VC that even at $40B ARR, his biggest wish is getting AI agents deployed before contracts sign. Not pricing. Not product. Deployment. Salesforce did exactly that with SaaStr. They assigned FDE resources to configure Agentforce before the deal closed. Results: 1,000 ghosted sponsorship leads from SaaStr Annual, zero prior follow-up, 72% open rate after Agentforce deployment, 10%+ response rate, deals closing from six-month-old dead contacts. Salesforce is now SaaStr's AI agent hub because they deployed first and let results make the argument. ## Why this matters for sales teams SaaStr is not skeptical of AI agents. They run 30, generate over $1M in revenue from them, and spend $500k yearly on AI tools versus $10k on Salesforce. The technology works. The constraint is capacity. Every new agent takes minimum 30 days to production: data integrations, routing logic, edge cases, ongoing management. When a vendor says "we would love to get you set up" and the next step is a kickoff call, the honest answer is: not right now. The mental load is too high. When a vendor says "we will handle it" and actually does, the calculus changes completely. The deployment gap disappears. Value shows up immediately. Nothing goes on the list because it is already running. ## What this means for AI vendors The FDE model scales better than it used to. That is the part traditional software vendors have not internalized. Deployment before signature is not a services business. It is what sales looks like for AI agents in 2026. Vendors likely pitching SaaStr include Relevance AI, Beam AI, Ruh AI, Salesforce Agentforce, Zapier AI Agents, and Microsoft Copilot Agents. Most target enterprise customers (finance, healthcare, retail) with global integrations. ANZ-specific presence is minimal across leading vendors. The deployment rate Lemkin describes (1 in 25 pitches) tracks with broader AI agent adoption challenges: implementation complexity, integration friction, and capacity constraints hit even teams already running dozens of agents successfully. Worth noting: SaaStr spends 50x more on AI tools than their CRM. That ratio tells you where budget is moving for sales ops teams evaluating 2026 stack decisions.

SaaStr
20 days ago
News

Sophos scales CS for 600k customers, threat response under 4 hours

## How Sophos Built CS Ops for 600k Customers Teresa Anania (now CCO at Verint, formerly SVP Customer Experience at Sophos) built customer success into a revenue engine at scale. Sophos protects 600,000 organisations globally, runs over $1B in ARR, and operates 24/7 CS ops because cyber threats do not wait for business hours. The threat landscape shifted. AI accelerated attack speed and sophistication. Attackers now move in 3 to 4 hours, logging in rather than breaking in. Sophos structured CS to respond before customers know there is a problem. By the time a support ticket arrives, you have already failed your customer. ## The Attribution Model Anania ties CS touchpoints directly to retention and expansion. No vanity metrics. She tracks which CS activities drive renewals, upsells, and churn prevention. Dynamic segmentation assigns coverage based on risk, spend, and growth potential, not just ACV hard lines. For early-stage companies without perfect data: start at the end of the renewal cycle. Automate what you can measure. Crawl, walk, run. ## Structure and Scale Sophos uses a two-by-two matrix: customer risk versus revenue potential. High-touch CSMs for enterprise accounts showing growth signals. Digital-led motions for stable mid-market. The customer should never feel your org chart. Anania hires for "humble confidence", a specific combination of expertise without ego. Her 5-to-1 scorecard evaluates how CS earns trust over time. Inner and outer feedback loops turn NPS data into cross-functional action, not just a CS slide. ## ANZ Context Australia ranks among top countries for Sophos adoption. The company maintains ANZ presence with global 24/7 operations supporting the region. No specific ANZ headcount disclosed, but rapid MDR expansion (37% customer growth in 2024, 26,000+ MDR customers globally) suggests scaling in customer-facing ops. Sophos holds #1 rankings in G2's 2026 reports for Endpoint Protection, XDR, MDR, and Firewall across enterprise, mid-market, and SMB segments. Privately held following management buyout. Competing in a cybersecurity market projected to hit $267.7B by 2026. ## What This Means Retention is an all-company play. CS attribution models tie activity to revenue. Dynamic segmentation beats rigid ACV lines. If you are building CS at scale: measure what moves the number, automate the repeatable, and structure coverage around customer outcomes, not your reporting lines.

Sales Hacker
20 days ago
News

AI SDR deployment takes 60 days of training, not 3 days of setup

AI SDR deployment takes 60 days of real work, not the 3 days vendors quote you. The tech is live fast. The training that makes it perform like your best rep takes 60 days of focused effort. Most companies skip the training. That is why most AI SDR deployments fail. ## Week 1-2: Foundation work (2-3 hours daily) Pull 50+ real conversations from your best BDR. Not scripts. Actual conversations, exact tone, real objection handling. Feed the AI your product knowledge: customer data, past conversations, why anyone should care. Read every message the AI sends. Every one. Flag anything robotic or off-brand immediately. Most teams stop reading after day three. That is where it goes wrong. ## Week 3-4: Optimisation (1-2 hours daily) One variable at a time. Subject lines, CTAs, send timing, opening lines. Not all at once. The bar: is this response better than what your best rep would say? Not better than a mediocre rep. Better than your best one. Track which approaches get replies. The data will tell you things your instincts will not. ## Month 2+: Maintenance (30-60 minutes daily) By now the AI is performing. Your job shifts to catching edge cases, refreshing the knowledge base as your product changes, tightening guardrails based on real conversations. This is not set-it-and-forget-it. It is lighter-touch, but still real attention. ## Why most deployments fail 90% of companies skip the training work. They deploy, wait two weeks, see mediocre results, conclude AI SDRs do not work. They are wrong about the conclusion. They are right that it did not work. It did not work because they did not train it. Best-performing deployments share one thing: the team invested heavily in the first 60 days alongside the vendor. The vendors who actually help show up for 80% of that heavy lifting. They do not just hand you a login and a tutorial video. ## The actual timeline - Days 1-7: Technical deployment, data ingestion, initial config. Live quickly. - Days 8-30: Foundation training. Daily, intensive, non-negotiable. - Days 31-60: Optimisation. A/B testing, voice refinement, performance analysis. - Day 61+: Ongoing maintenance. Lighter lift, but still requires attention. Total time to a well-trained, high-performing AI SDR: 60 days if you do the work. Six months of frustration and a vendor switch if you don't. ## ANZ context This timeline matters more in ANZ markets where AI SDR adoption is tracking 6-12 months behind US deployments. Local teams asking about AI SDR ROI need to factor in the real 60-day ramp, not the 3-day vendor pitch. That changes the cost comparison versus hiring another human SDR on $80k base. The tools are not magic. The training is the product. *Source: SaaStr, Jason Lemkin*

SaaStr
20 days ago
News

Rumin8 raises $4.3m, expands to NZ: agtech hiring watch

## Rumin8 raises $4.3m, expands to NZ: agtech hiring watch Perth-based Rumin8 closed US$3 million ($4.3m AUD) from New Zealand investor AgriZeroNZ to expand its livestock methane reduction business across the Tasman. The startup develops feed additives that cut cattle emissions while claiming to boost production and farm profitability. Founded in 2021, Rumin8 started with seaweed-based solutions but pivoted to what it calls "nature-inspired pharmaceutical ingredients." The company aims to decarbonise 100 million cattle by 2030. Big goal, now entering final commercial trials. ### The funding context This follows a $17m seed round in 2023 that brought in Bill Gates via Breakthrough Energy Ventures and Twiggy Forrest through Harvest Road Group. Other backers include Aware Super Sentient WA Growth Fund and Prelude Ventures. Total funding not disclosed, but the company is clearly raising to scale. ### What this means for sales No sales team hiring announced yet, but worth tracking. NZ expansion usually means local market entry: think regional AEs, partnerships, potentially field sales given the agtech vertical. Dairy is New Zealand's largest export, so the addressable market justifies boots on the ground. Agtech sales cycles run long (12-18 months is common for farm inputs), and closing farmers requires product validation and local relationships. If Rumin8 follows the playbook, expect NZ-based commercial roles once trials wrap. ### Agtech hiring patterns Recently funded agtech startups typically hire sales 6-12 months post-raise, after product-market fit validation. Comp in agtech lags pure SaaS (enterprise AE OTE in agtech sits around $140k-160k vs $180k+ in tech), but territory sizes can be massive in ANZ given farm distribution. Competitors in the livestock emissions space include ASX-listed Sea Forest and CSIRO spinout FutureFeed. Rumin8's pharma-ingredient angle differentiates, but it is still selling into conservative farming budgets. CEO David Messina mentioned aligning with commercial partners in target markets. Translation: channel strategy likely, which could mean partner account management roles rather than direct field sales initially. No public data on current headcount or sales org structure. Watch for NZ commercial lead appointments in Q2-Q3 2026 if trials progress.

Startup Daily
20 days ago
News

ACS cuts executives two weeks into new CEO transition

## ACS cuts executives two weeks into new CEO transition Dr Prins Ralston wasted no time. Two weeks into his role as CEO of the Australian Computer Society, he cut multiple executive positions. "A number of executive roles are being made redundant," Ralston told staff in a Tuesday email. "These are realignment decisions, driven by the need for a leaner and more appropriately focused organisation, not a reflection of the individuals involved." The ACS management committee approved the executive restructure on Monday. An all-staff meeting followed Wednesday. Ralston is the fourth ACS CEO in six years. He replaced Josh Griggs, who left suddenly after 18 months in March 2026. Griggs ran his own leadership purge during his tenure, shutting Melbourne's Bay City Labs and Brisbane's River City Labs in favour of a virtual offering. ### What the restructure looks like Operations director Betsy Gregg now reports directly to Ralston, overseeing Strategic Initiative Executives and their boards. Member Products and Services is being established as a new function under Enzo Cocotti, reporting to the CEO. Shared Services, led by CFO Wynand de Wet, now includes Sydney's Harbour City Labs, though ACS did not confirm whether that facility will remain open. ### More cuts coming "I want to be honest with you: this is the beginning of a transition, not the end of it," Ralston told staff. "There will be further decisions ahead as we shape ACS for the future as external factors such as the 26/27 Federal budget is announced." Ralston outlined priorities: member focus, operational efficiency, and growth in AI and cyber security. ACS recently received a $1.9 million federal government grant to co-design a voluntary national Cyber Security Professionalisation Scheme. ### What this means New CEOs often restructure in the first 90 days. What is notable here is the speed and the acknowledgement that more cuts are coming. Ralston signalled budget pressures and a need to streamline before growing. For sales professionals considering tech association roles or membership org sales positions, this is a reminder: non-profit does not mean stable. CEO transitions often mean executive churn, territory changes, and quota resets. ACS did not respond to questions about total headcount impact or specifics on which executive roles were cut.

Startup Daily
21 days ago
News

Halter hits $2.9B valuation, $314M Series E: What it means for agtech sales

## The Numbers Halter raised $314.4 million Series E led by Founders Fund, valuing the NZ agtech at $2.9 billion. That is 3x their Series D valuation from June 2025, when they hit $1 billion on a $100 million raise. The company now has 1 million solar-powered GPS collars deployed across 2,000+ cattle farms in New Zealand, Australia, and the US. ## What This Means for Sales Teams Series E at this scale typically signals aggressive go-to-market expansion. Halter already employs 300+ people and operates on a subscription model: monthly fees per cow per collar. They expanded into the US in 2024 and are targeting UK, Ireland, and South America next. For context: Halter reported $17.5 million revenue with 600,000+ collars across 1,000+ customers as of 2024. The math suggests they are scaling fast, which means territory expansion and quota changes for existing reps. ## The Funding Stack Founders Fund led, with participation from Blackbird Ventures (Australia), DCVC, Bond, Bessemer, and others. Rocket Lab founder Peter Beck is an investor and board member. Andrew Fraser serves as President. ## Market Context Halter won NZ's Deloitte Fast 50 as the country's fastest-growing company in 2024. The company was founded in 2016 by Craig Piggott, who left Rocket Lab to build tech he saw his family's Waikato dairy farm needed. The product: virtual fencing via collar that uses audio cues and vibrations to herd cattle, controlled via smartphone app. US farmers have built nearly 100,000 kilometres of virtual fencing since Halter's 2024 launch there. That adoption rate matters if you are tracking agtech sales cycles and enterprise deployment timelines. ## What We Are Watching Geographic expansion plans, particularly UK and Ireland rollout timing. Sales team buildout in new territories. Comp structures for AEs selling into agriculture, which historically has different sales cycles than SaaS. Whether the subscription model scales as they move from early adopters to mainstream dairy operations. Worth noting: agtech sales often require longer educational cycles and hands-on demonstrations. If they are hiring into new markets, expect field-heavy roles with territory ownership.

SmartCompany
21 days ago
News

Canva acquires Doohly for $30M, adds DOOH to platform

Canva acquired Melbourne-based Doohly for $30M, adding digital out-of-home (DOOH) advertising to its platform. The deal means Canva now handles everything from design creation to physical billboard placement. Doohly, founded in 2020 by Sean Law and Tom Sawkins, runs a cloud-based platform managing digital billboards and retail screens. The company operates across ANZ and UK, with clients including KX Pilates, Mobil, Rebel Sport, and Liquorland. Previous raise: $650K from Archangel Ventures and Skalata. ## What It Means for Enterprise Sales Canva is building an end-to-end marketing platform play. Design tools brought in SMBs. DOOH capabilities target enterprise clients with physical retail presence. Worth noting: this is acquisition number six in two years, following Affinity and Leonardo in 2024. For sales teams selling into retail or physical locations, Canva just became a more complete solution. Previously, you designed in Canva, then exported to a separate DOOH platform. Now it is one workflow. ## The Numbers Law owns nearly 50% of Doohly, Skalata around 17%, Sawkins 14%. At $30M exit, that is $15M+ for Law, $5M+ for Skalata, $4M+ for Sawkins. Not bad for a company that raised $650K. Doohly was serving 4 billion+ creatives across 100+ networks in 13 countries. Client count grew from 11 to 19 since mid-2023. Lean operation, tech-driven revenue model. ## ANZ Context Second Melbourne adtech exit in recent memory. Doohly had strong ANZ partnerships: LUMOS in Australia, HYPER in New Zealand (500+ retail locations). Canva gets immediate local market access without building infrastructure from scratch. No word yet on Doohly team integration or whether Law and Sawkins stay on. Standard acquisition playbook suggests product gets absorbed, founders stick around for 12-18 months, then move on. This matters if you are selling design tools, martech, or advertising platforms. Canva keeps adding capabilities. They are not staying in their lane.

Startup Daily
21 days ago
News

Cauldron closes $13.25M Series A2, no sales team disclosed

## The Numbers Cauldron, an Orange NSW biotech, closed a $13.25 million Series A2 led by Main Sequence Ventures. Total funding now sits at roughly $26 million across seed ($10.5M in 2023) and Series A ($9.5M in 2024). The company develops continuous precision fermentation tech that cuts costs 30-50% versus traditional batch methods. Applications span food, agriculture, biofuels, cosmetics, and chemicals. ## What We Don't Know No public data on: - Sales team size or structure - Recent hires or hiring plans - CRO, VP Sales, or senior go-to-market roles - Compensation ranges for any roles - Revenue numbers or ARR For a company citing "faster-than-expected demand" and planning multi-facility expansion, the absence of sales org details is notable. Either they are not hiring yet, or the information is not public. ## The Context Cauldron runs a 25,000-litre facility in Orange, acquired via seed funding from CEO Michele Stansfield's prior firm Agritechnology (which included 35 years of R&D). Plans include a 500,000-litre facility and a network of plants across regional Australia. The company holds Australia's first 10,000-litre gene tech licence for scale testing. Fast Company named them among Asia-Pacific's most innovative companies this week. ## What This Means for Sales Pros Biotech startups at this stage typically build commercial teams post-Series A, especially when citing customer demand. If Cauldron starts hiring AEs or business development roles, expect: - Technical sales requirements (bioprocessing knowledge) - Long sales cycles (industrial contracts) - Enterprise deal sizes - Regional NSW or Sydney-based roles Worth tracking if you are looking at early-stage deep tech sales. Just do not expect comp transparency yet. **Series B equity note:** At $26M raised, Cauldron sits between Series A and B. Early-stage biotech comp typically skews toward equity over cash, with OTE structures less common than tech SaaS roles until commercial traction is proven.

SmartCompany
21 days ago
News

Mr Yum CEO on merger reality: integration costs, nervous customers, profitability

When Mr Yum and me&u merged in November 2023, plenty of people quietly assumed it would fail. Kim Teo, now CEO of the combined entity, says the scepticism was not irrational. The first year looked ugly on paper. Integration costs were significant. The company carried a loss that doubters pointed to as proof. But Teo says the real work was not about the balance sheet: it was about keeping focus while everything changed. ## The merger reality Two rival hospitality tech firms, both based in ANZ (Mr Yum in Melbourne, me&u in Sydney), merged via all-stock deal. The combined entity now processes over $2 billion in annual dining transactions across 6,000+ food brands. It operates under the me&u brand with Teo as CEO. The first year priorities: customer migration, systems integration, team consolidation. Not glamorous. Expensive. Teo describes it as the "hard, unsexy work" that sets up the next phase. ## What they actually did No major changes during peak trading seasons. Focus on continuity of product, support, and platform. The goal: avoid disrupting customers while integrating two sales organisations that had competed fiercely for four years. Teo does not sugarcoat the challenge. Integration costs hit hard. Customers were nervous. The work was messy. But the alternative, she implies, was staying separate while burning resources on competition. ## Sales team implications The article does not detail sales team sizes, comp structures, or how many roles were consolidated. That is the transparency gap in most merger coverage: lots of talk about "culture" and "focus," not enough about what happened to the teams doing the selling. What we know: the merger aimed to build a "super product" and scale innovation. What we do not know: how many AEs, SDRs, or AMs lost roles, what the comp looked like post-merger, or how territories were redrawn. For sales professionals watching merger news, Teo's advice centers on focus and culture, not the operational details that determine whether your role survives integration. Worth noting for anyone evaluating a company mid-merger: ask about the roadmap, but also ask about quota relief, territory changes, and what "integration" actually means for your patch.

SmartCompany
21 days ago
News

Australia's AI edge: Data-rich industries, not frontier models

Australia's AI advantage sits in data-rich industries, not building the next ChatGPT competitor. That is the view from Lee Hickin, executive director of the National AI Centre, speaking at ARM Hub's Propel-AIR 2.0 robotics accelerator in Brisbane. "Where does Australia have data and insights and knowledge that is unique to us," Hickin told SmartCompany. The answer: mining, agriculture, healthcare, and other sectors where ANZ companies already own proprietary datasets that global players cannot easily replicate. While governments pour billions into sovereign AI capability and tech giants build data centres, Hickin argues the local edge is not in frontier model development. It is in sector-specific applications where Australia has decades of domain expertise and unique data sources. ## What this means for sales teams For sales professionals selling AI tools in Australia, this matters. The buyers are not chasing general-purpose models. They want tools that solve specific problems in industries where Australia actually leads. Salesforce pushed AI certifications hard in 2024. The Australian market response: cautious adoption in finance and retail, stronger uptake in resources and agriculture where the data story resonates. AI sales automation tools from Australian vendors are gaining traction because they understand local compliance and industry workflows. The comp play: Enterprise AEs selling industry-specific AI solutions in mining or agriculture are seeing stronger close rates than those pitching generic automation. Territory assignments are shifting to vertical specialisation. If you are carrying an AI quota in 2026, knowing the difference between frontier models and applied AI is table stakes. Australia's AI market is projected to exceed AUD 80 billion annually by 2033. The government committed AUD 2.5 billion through its National AI Plan. But the sales opportunity is not in competing with OpenAI. It is in tools that leverage Australia's unique industry data and expertise. Worth noting: 68% of Australian businesses have moved AI from pilot to production. That is higher than most markets. The buyers are ready, but they want solutions that fit local industries, not generic automation promises.

SmartCompany
22 days ago
News

Silicon Quantum Computing lands $20M NRF funding, no sales team details

## SQC adds $20M, still R&D-heavy Silicon Quantum Computing closed $20 million from the National Reconstruction Fund via SAFE note. The cash funds production scaling for quantum processing units and Watermelon, its quantum machine learning product. The investment is part of an ongoing round. No total raise amount disclosed. SQC has pulled in $280 million since 2017, including $83 million in seed from Australian government, UNSW, Telstra, and Commonwealth Bank. ## The revenue picture SQC reports "millions of AUD" in revenue from two products: Watermelon (quantum ML) and Quantum Twins (molecular simulation). They are targeting commercial-scale error-corrected quantum computers by 2033. Worth noting: that is a seven-year timeline in a market where timelines tend to slip. The company employs around 90 to 100 people. Breakdown: 70-plus technical staff, 20 commercial. No CRO. No VP Sales. No sales team size disclosed. For a B2B play targeting multinationals in defense, pharma, finance, telecoms, energy, and materials, that is a light commercial footprint. ## What this means for ANZ tech sales SQC operates as Australia's quantum computing champion: full-stack development from atomic manufacturing to software, fabricating chips at UNSW Sydney labs. CEO Michelle Simmons (2018 Australian of the Year) runs a research-first operation competing against IBM and Rigetti on silicon spin qubit technology. The sales angle: SQC sells via cloud and hardware deals to enterprise clients. But the org structure tilts heavily toward R&D. If you are tracking quantum computing sales roles in ANZ, this is not where the action is yet. The $20 million goes to production capacity, not go-to-market expansion. Funding rounds like this signal government backing and long-term potential. They do not signal near-term sales hiring. SQC's 2033 commercialisation target puts it in the "strategic partnership" phase, not the "build out an enterprise sales team" phase. ## The comp reality No sales roles posted. No comp data. If SQC does hire sales, expect it to look more like technical account management or strategic partnerships than traditional quota-carrying AE roles. Quantum computing sales at this stage means educating C-suite on seven-year roadmaps, not closing quarterly deals.

SmartCompany
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