Retention, Churn & Expansion
Preventing cancellations, renewals, reactivation, upsells, cross-sells, NRR, and durable customer relationships.
48%
Best tweets about Customer Success
50 Best Tweets About Customer Success (2026)
Discover the best tweets about customer success, covering onboarding, adoption, retention, expansion, health scores, support, teams, and operating playbooks.
Customer onboarding, adoption, retention, expansion, health scoring, support, team operations, metrics, and firsthand company lessons.
- Creators
- 44
- Updated
Original Xholic analysis
What 50 top Customer Success posts reveal
The largest themes in this set are retention, churn and expansion (48% of tweets) and onboarding and activation (36%). Posts frequently discuss faster time-to-value, customer feedback and usage signals, and post-sales practices such as health tracking, renewals, expansion and reactivation. AI appears as a proposed tool for onboarding and customer-success workflows, while several posts emphasize customer context, fit and responsiveness. [2079993565019795637, 2083954605533065561, 2037149683651371479]
- Dominant tone
- Positive
- Median score
- 7.63
- Leading format
- Story
- Recent posts
- 46%
66% of posts
All-time engagement
36% of posts
Published in 90 days
Conversation map
The themes creators return to
Onboarding & Activation
First-login UX, setup completion, integrations, early wins, aha moments, and reducing time-to-value.
36%
Voice of Customer & Discovery
Customer conversations, advisory groups, surveys, NPS, feedback loops, and extracting product or marketing insight from customer evidence.
28%
Customer Relationships & Responsiveness
Founder and CEO engagement, empathy, strategic curiosity, fast responses, champion development, and trust-building with customers.
26%
Customer Health & CS Operations
Health scoring, churn-risk detection, account prioritization, renewals, support handoffs, playbooks, and operational systems for post-sales teams.
24%
Customer-Led Product Strategy
Using customer behavior, requests, willingness to pay, and success outcomes to prioritize features, validate roadmap choices, and avoid bad-fit customization.
20%
AI-Enabled Customer Success
Using AI agents and unified customer data to automate onboarding, analyze signals, prioritize accounts, and trigger proactive interventions.
16%
CS Team Design & Expertise
Hiring, evaluating, structuring, and enabling customer success teams, including industry credibility and forward-deployed implementation roles.
16%
Tone and stance
Sentiment Positive leads
Author posture Supportive leads
Performance benchmark
- Median likes
- 25
- Median reposts
- 1
- Median replies
- 6
- Median views
- 1.9K
Posts with media make up 44% of this collection. Their median all-time score is 5.44, compared with 8.41 for text-only posts.
Format mix
- Story 36% · score 3.26
- List 34% · score 22.2
- Opinion 24% · score 5.50
- Announcement 6% · score 11.0
Consensus and debate
Where creators agree, and where they do not
Shared view
Activation is frequently linked to retention
Several posts argue that customers should reach product value early. They emphasize first-use wins, reducing onboarding friction, identifying an aha moment and studying where customers stall. [2013280318086885607, 2082503953124860062, 2077088387010281563, 2070628211617067475]
Shared view
Customer evidence is presented as an input to decisions
Posts recommend drawing on behavior, support tickets, calls, CRM context and direct customer conversations to identify friction and inform product, messaging and operational decisions. [2083954605533065561, 2035349468241895916, 2011090956867473471]
Shared view
Post-sales work is framed as part of growth
Several contributors place retention and expansion within a broader GTM system, mentioning structured onboarding, health metrics, champion programs, reactivation and usage-based upsell triggers. [2036805330504446232, 2042316668358009208, 2073792770557485208]
Shared view
Customer relationships require ongoing attention
Posts recommend direct CEO contact, curiosity about customers, early expectation-setting and responsiveness as ways to strengthen customer interactions. [2074209515906723971, 2039247912321110294, 2071879627770057184, 2034418055389032871]
Open debate
Manual learning versus early onboarding automation
One post recommends personally onboarding early users before automation, while another proposes onboarding agents as an early investment for vertical AI companies. These are differing recommendations rather than measured comparative results. [2079993565019795637, 2037149683651371479]
Open debate
Enterprise implementation support versus customization risk
One post describes forward-deployed implementation roles as important for complex AI deployments; another warns that extensive requests from a single enterprise customer can pull a product roadmap toward one-off work. [1946335852940099713, 2061460456032649473]
Open debate
Operating metrics versus the broader conditions of renewal
Posts propose NRR, churn, health and time-to-value as operating metrics. A health-tech operator adds that executive alignment, champions, integrations and workflow fit can also affect renewal decisions. [2013280318086885607, 2077455406599651432, 2078250399803261155]
What performs
Patterns behind standout posts
List posts had the highest median score among reported formats
Lists had a 22.189 median all-time score, compared with 3.26 for stories and 5.5 for opinions. The two highest-scoring outliers were posts on customer intelligence and startup retention. [2083954605533065561, 2079993565019795637]
Onboarding and AI themes had above-overall median scores
Onboarding & Activation had a 10.41 median all-time score and AI-Enabled Customer Success had a 21.25 median, versus 7.63 for the full set. Example posts discuss new-account ramp-up, AI onboarding agents and customer-data workflows. [2013410692444102793, 2037149683651371479, 2083954605533065561]
Text posts had a higher median score than media posts
Media appeared in 22 posts (44%). Its median all-time score was 5.44, compared with 8.41 for text posts in this set. [2037149683651371479, 2027158846196547997]
Statistical standouts
- View standout post 1 Score 3240.9 · 424.76× median
- View standout post 2 Score 1486.3 · 194.79× median
- View standout post 3 Score 343.2 · 44.98× median
- View standout post 4 Score 162.7 · 21.32× median
- View standout post 5 Score 124.2 · 16.27× median
Creator landscape
Who shapes this conversation
The five most represented creators account for 20% of the selected posts.
-
1. Ayman Al-Abdullah 🧱
@aymanalabdul
2 posts
-
2. Dan Rosenthal
@dan__rosenthal
2 posts
-
3. Harshil Tomar
@Hartdrawss
2 posts
-
4. Jason ✨👾SaaStr.Ai✨ Lemkin
@jasonlk
2 posts
-
5. Luke Sophinos
@lukesophinos
2 posts
-
6. Nick Mehta
@nrmehta
2 posts
Top repeat creators covered retention and GTM operations
The two highest-scoring repeat creators in the analytics were Ayman Al-Abdullah (median all-time score 94.1) and Dan Rosenthal (67.41). Their cited posts discuss CEO metrics, customer discovery, GTM stages, retention and expansion. [2013280318086885607, 2034419640504598614, 2036805330504446232, 2042316668358009208]
Several posts use firsthand operating examples
Examples include running a customer advisory board, hiring for vertical-SaaS customer success, advocating empathy for enterprise customers and direct CEO outreach. These are contributors’ reported experiences and recommendations. [2035349468241895916, 2074908663169298723, 2079577019420193250, 2074209515906723971]
Since the previous snapshot
What changed since Aug 12, 2026
- 78% of the selected posts remained.
- The creator count changed by -2.
- The leading sentiment remained stable.
How this analysis was made
Themes, sentiment, stance, and post format are classified per tweet. All counts, shares, medians, creator concentration, freshness, and performance comparisons are then calculated directly from the published snapshot.
Xholic's all-time score compares engagement while accounting for reach, post age, and creator consistency. It is used for relative comparisons within this collection.
This report analyzes the exact 50-post snapshot shown below. AI identifies editorial categories and drafts explanations; all statistics are calculated from the snapshot, and every narrative claim is checked against cited posts before publication.
Best Customer Success tweets
Top Customer Success tweets from 44 creators
Ranked 01–50
- 01
@gregisenberg ·
Every startup should have a daily markdown file called "what_the_market_is_telling_us.md" It updates every morning from the places where customer truth already lives: 1. Stripe for who pays, upgrades, downgrades, and churns 2. PostHog for what people actually do in the product 3. Intercom or Plain for support tickets/complaints 4. Granola or Gmeet transcriptions for sales calls/ customer interviews 5. HubSpot or Salesforce for CRM notes/lost deal reasons 6. Linear, Jira, or GitHub Issues for bugs and feature requests etc 7. Ideabrowser MCP for outside market signal: startup ideas, trend reports, social/search demand, AI research reports, and builder prompts that show what people are starting to want before it shows up in your own customer data. Basically, the file should notice what changed in the business this week and not just be this summary of here’s what happened (which I think a lot of people have their agents do). Why this is valuable: 1. Maybe new buyers are using different words than they were a month ago. 2. Maybe trial users are getting stuck in the same place. 3. Maybe upgraded customers all touched one feature right before they paid. 4. Maybe churned customers keep mentioning setup confusion. 5. Maybe sales calls are suddenly losing to a competitor you used to beat. 6. Maybe support tickets are revealing a workflow your product accidentally became responsible for. You get the point. The fastest way to PMF is understanding customers better than anyone else, and the highest signal customer insight is usually a change in behavior. So I’d have the agent update the file every morning with the pattern it found, the receipts behind it, and the product or GTM decision it might affect. For example: “3 customers who churned this week all mentioned setup confusion, and 2 of them never invited a teammate. This looks more like an activation problem than a pricing problem, so I’d look at team invite and onboarding before building another analytics feature.” A little helpful tip for all those out there looking to get more from their LLMs.
- 02
@fin465 ·
We went from 0 to 1,000+ paid customers in our first 20 weeks by religiously following these @ycombinator 12 rules: 1/ grow retention before growth. we didn't run a single growth campaign until we hit 90% weekly retention. scaling a leaky bucket just means you fail faster 2/ ignore everyone who isn't your customer. i stopped reading competitor blogs, industry news, and most of twitter. the only company that can kill you in year one is your own 3/ manual is faster than perfect. our first 50 users each got a personal onboarding call from me. you can't automate what you don't understand yet 4/ validate before you build. we put a credit card gate on @origamichat on day 2. it's easy to convince yourself people want your product when nobody's paying 5/ ugly product > no product. we shipped a barely-working version to 30 people in a week. real users teach you more in 7 days than 6 months of polishing in the dark 6/ your customers write your roadmap. i still spend 3 hours a day on user calls. every feature we've shipped came from a conversation, not a planning session 7/ fire bad fits early. we've fired customers who were wrong for our product. 10 people who love you beat 1,000 who kind of like you. every time 8/ ship every week without exception. we push code to production every friday. consistency compounds in ways you can't see at first 9/ stay small longer than feels comfortable. we were 2 people for a very longtime. Headcount is not progress. every great startup was embarrassingly small for embarrassingly long 10/ know your burn, know your runway. we track default alive on a whiteboard every week. scary but necessary. most startups don't die from the market, they die from running out of time 11/ expect things to break constantly. we've had 3 near-death moments. the game isn't avoiding fires, it's how fast you put them out 12/ honest conflict > polite silence. brutal honesty with your cofounder is the cheapest insurance you'll ever buy good luck and dont forget to have fun
- 03
@nikitabier ·
Before I took this job, I got breakfast with @joshelman, one of the first product managers at the company and my mentor for the last 10 years. He said getting new accounts ramped up on X has been one of the app's toughest challenges -- and the most important thing to unlock growth. And it's obvious to people who use the app: once you get out the mainstream timeline of news & politics and into your niche, you really unlock the magic of X. However, X is an interest-based graph, you can't simply "sync your contacts" and have a relevant feed. Power users like me have spent years finding accounts and curating our timeline. But that problem is now getting fixed: Over the last 6 months, we've been iterating each day to make it quicker & easier for new accounts to find their interests on X. The pieces are finally coming together -- and it's been amazing to watch.
- 04
@aymanalabdul ·
Metrics you should track weekly as a CEO: • Cash in the bank (not just revenue) • APRR (A-Player Referral Rate) • NRR (Net Revenue Retention) • Customer Acquisition Cost • Revenue per employee • Lifetime Value • Churn Let me break these down: 1. Cash in the bank Cash in the bank is the only number that cannot lie Revenue is an opinion. Profit is an opinion. Cash is reality If revenue is growing but cash isn’t: - You’re over-hiring - Over-investing - Over-reinvesting - Or getting killed by taxes, inventory, or burn If there’s only one metric I’d bet on long-term, it’s this: Is cash growing year over year? 2. APRR (A-Player Referral Rate) If your A-players: - Refer other killers → culture is healthy - Don’t refer anyone → secretly working on their side hustle High performers wouldn’t recommend places where they wouldn’t work long-term Low APRR means your best people are quietly hedging 3. NRR (Net Revenue Retention) High NRR means: - The product is expanding - Customers are upgrading - You’re solving a real, growing problem Low NRR means: - You’re leaking value - Or your product is incomplete In simple terms: do your customers want more of you, or can competitors steal them away? 4. CAC (Customer Acquisition Cost) If CAC isn't shrinking year over year, you're not building a brand You're renting attention Rolex advertised like crazy in the 60s Now they throw a Rolex on a celebrity, call it a day, and they’re sold out for years 5. Revenue per employee How much revenue does each role actually unlock? Founders often over-hire in anticipation of revenue You hit $5M, think you need a bigger team to keep growing, so you hire Revenue stays flat What happened? You hired to make work easier for existing members - not to remove the bottleneck that was actually blocking growth If a role doesn't pay itself back in 90 days, you end up with twice the overhead for half the profit 6. Lifetime Value LTV measures whether you're solving the whole problem or just part of it e.g. most gyms solve one problem: working out Lifetime Fitness solves the entire problem stack of their average gym-goer: childcare, pools, date night drop-off, cafes, & co-working $30-40 in extra operating cost for 10x the membership price If you're not expanding to serve your customer end-to-end, someone else will 7. Churn The inverse of NRR. The percentage of customers who leave One of my clients found that if a customer makes it to Day 74, they stay forever They built an entire team around those first 74 days - usage, onboarding, engagement, everything And 2025 was their best year ever Find your Day 74. Then engineer everything around getting customers there Track these weekly And I will see you at $100M 🤝
- 05
@JasonrShuman ·
The best vertical AI companies in 2027 won’t just have an onboarding team. They’ll have a team of onboarding agents. Onboarding doesn’t fail just because it’s slow. It fails for two reasons: First, the setup never gets finished. The integrations stall, the data migration drags, and the customer is stuck in a half-configured product that can’t deliver value. Second, even when setup is done, nobody engineers the jaw-dropping moments that make a customer feel the ROI. They get a generic walkthrough instead of an experience that changes how they work. AI solves both sides. If I were building a vertical AI company today, here’s where I’d invest before hiring a single onboarding rep: https://t.co/gWIzCzQRpi config and migration agents. An AI that interviews the customer about their workflows, auto-generates the system configuration, connects their integrations, and migrates their data. The 3-week services engagement that delays time-to-value is gone. This is the foundation. Nothing else works until this is right. 2.A digital twin of the customer’s real environment. Clone their actual data, workflows, and integrations into a sandbox. Every demo, every training moment happens in their world, not with fake data they can’t relate to. This is what makes the magic moments feel real. 3.A cross-customer activation engine. Study how your highest-value customers reached their aha moment. Find the pattern. Auto-sequence every new customer through the fastest path to value based on companies like them. Don’t hope they find the magic. Engineer it. https://t.co/LT1fDAT34v AI voice agent that delivers the magic moments live. Not a chatbot. A voice agent that calls the customer on their schedule, walks them through the specific workflows that will blow their mind, and doesn’t move on until they’ve felt the product working for them. https://t.co/L7XHvCJHbN AI avatar that makes onboarding feel human. A synthetic video persona that greets the customer by name, references their specific use case, and walks them through the workflows that matter most to them. Not a Loom library. A 1:1 experience at scale. 6.A predictive intervention agent that protects the magic. AI that detects when a customer is drifting, skipping logins, ignoring features, disengaging, and autonomously re-engages them with the next jaw-dropping moment. Not a drip campaign. A system that continuously pulls them back to value. The mental model shift for founders: onboarding is a two-part problem. Get the setup right so the magic is possible. Then relentlessly engineer the moments that make your customer feel the ROI. The companies that nail both sides will have activation rates and NRR their competitors can’t touch. Dialed in on this in Vertical AI? I want to talk.
- 06
@dan__rosenthal ·
We've helped dozens of YC startups and enterprise B2B companies build their go-to-market motions. All of our top performing accounts follow this exact 6-stage modular system: (bookmark this): 1️⃣ The 6 stages: → Traffic Generation → Lead Capture → Lead Nurturing → Qualification → Conversion → Retention & Expansion Each stage feeds the next. Retention feeds traffic. That's what makes it a flywheel instead of a funnel. 2️⃣ TRAFFIC: There are 4 channels that actually work in B2B right now: • Content marketing (LinkedIn, SEO, YouTube, podcasts) • Paid ads (Google, LinkedIn, Meta, Reddit) • Outbound (cold email, LinkedIn DMs, calls) • Partnerships (referrals, integrations, joint webinars) Pick 1 or 2 first. Validate before adding more. 3️⃣ CAPTURE: Most teams stop at landing page forms. But capture goes way beyond that. • Lead magnets (checklists, templates, calculators) • Social followers as a passive signal • Social engagement (comments, DMs, shares, poll responses) Every one of these is a signal you can activate later. 4️⃣ QUALIFICATION: Most GTM systems break right here. AI-driven lead scoring combines firmographic signals with behavioral signals. Smart forms with progressive fields enrich the profile over multiple interactions. Automated intent signals route high-scoring leads to reps in realtime. 5️⃣ RETENTION: Companies underinvest here and it costs them. • Structured onboarding and regular business reviews • Private communities and champion programs • Usage-based upsell triggers • Referral and affiliate programs Track NRR, CLV, and customer health score. — You don't have to activate everything at once. Pick 1-2 channels per stage. Validate that the unit economics work. Then expand. The teams that scale are the ones that prove each stage works before adding complexity.
- 07
@Hartdrawss ·
The 10 decisions that determine whether your app survives the first 90 days or joins the graveyard : 1. the problem you pick : if people won't pay before you build, you don't have a product, you have a hobby. 2. who gets the first 100 users : 10 people who'd pay before launch beats 10,000 signups from a Product Hunt spike that never come back. 3. the first screen : we redesigned one onboarding screen for a client and conversion went up 2x. 40% of users drop off before they see your core feature. 4. your pricing model : one paywall decision in week 1 determines your max revenue for 12 months. most founders set it too low and never recover. 5. retention over vanity : 500 daily active users is worth more than 50,000 downloads with 2% retention. 6. your tech stack : that free Supabase tier handles 500 rows. 50,000 users hitting your API costs $1,200/month. choose early, pay later. 7. where you launch : shipping on a Tuesday afternoon gets you crickets. a coordinated launch with a pre-built list of 200-300 warm clicks changes everything. 8. the first impression in the store : your first screenshot drives 70% of conversion. most founders spend weeks on the product and 10 minutes on the listing. 9. how you handle auth : broken login on day one kills more apps than bad code. authentication that fails under load is a silent churn machine. 10. whether you keep building or start distributing : the founders who win ship fast and spend the next 90 days on marketing, not features nobody asked for. get these 10 right and everything else is just execution noise.
- 08
@codyplof ·
I know I talk about Claude a lot lately but there’s another thing I’ve been just as obsessive about lately and that is talking to customers. I have a Customer Advisory Board of 250 customers currently and I’m the only one in it right now. I talk to them daily, send multiple surveys per week, etc. We also have a FB group of 90k people that I’m active in as well daily. Not only is going above and beyond extremely important to us but our # goal this year is to be customer obsessed. We now won’t make any decisions without their input. In planning some in person forums as well. Almost no cost but the value has been insane in just a few months. And there’s really no reason anyone can’t be doing this.
- 09
@DanielSmidstrup ·
Hermes is my first employee. Its job is to find ways to create value for ClimbX every day. Without a clear use case, AI agents become another distraction. So my first real use case is "customer success" for ClimbX. It runs every morning and reviews: 1. Trial and paying user counts 2. Login-to-trial conversion 3. Unusual user behaviour 4. Users who may need help 5. Features people are not using It only has read-only access to usage data. Every morning, Hermes then gives me three actionable things we can do: 1. Get more data 2. Talk to a specific user 3. Keep improving ClimbX based on what the data shows That turns product activity into a simple daily loop: 1. Find the signal. 2. Take action. 3. Make the product better. The goal is simple: turn product activity into clear actions before small problems become churn.
- 10
@Nate_Google_ ·
i keep getting asked about Grapevine -https://t.co/feTkRO9eTu we use this to decrease our churn and increase our subscription rate by learning the psychology behind why customers buy our products here are the exact questions that i often start with: 1. "What is the #1 health goal you are hoping to achieve with this product?" Insight: Allows you to send personalized education/reminders based on their specific "Why." 2. "How often do you plan on taking this supplement?" Insight: Identifies if their subscription frequency (e.g., every 30 days) matches their actual usage to prevent "product stockpile" cancellations. 3. "Did you switch from another brand to try us today?" Insight: Helps you understand what the "other guys" did wrong so you can double down on doing that right. 4. "How would you describe your experience with [Health Issue] before finding us?" Insight: Captures the "pain point" language you can use in retention emails to remind them of the progress they are making. 5. "How did you first hear about us?" Insight: Identifies which marketing channels bring in the most loyal, long-term subscribers versus "one-and-done" buyers. 6. "What was the main thing that convinced you to buy from us today?" Insight: Tells you if they value your science, your price, or your reviews, so you can reinforce those values in your churn-save flows. 7. "Have you ever tried this type of supplement (e.g., Magnesium, Collagen) before?" Insight: New users need "how-to" guides to prevent churn; experienced users just need easy management of their subscription. 8. "What is your biggest concern or hesitation about starting this new routine?" Insight: Lets you address fears (taste, side effects, price) immediately in the post-purchase "thank you" flow before they decide to cancel.
- 11
@jasonlk ·
Customers love, love, love to hear from the CEO This alone is one reason why start-ups have an edge Take advantage: - Go talk to 10+ of them a week - Do a user conference, it's OK to start small - Meet every larger customer in person - If there are bumps, just email them directly It's not perfect. It doesn't always work. But it is ... magical
- 12
@aymanalabdul ·
Every CEO should do this exercise with their customers… Put your best customers in a Slack chat and ask these 5 questions: - "Walk me through the last time you hit this problem. What happened?" - "What solutions have you already tried? Why weren't they good enough?" - "If you could wave a magic wand, what would the perfect solution look like?" - "What's at stake if this never gets solved?" - "What would solving this unlock for you?" Put them in a room together and you'll hear things about your product no NPS score will ever surface
- 13
@Hartdrawss ·
PRO TIP for FOUNDERS : your onboarding screen is the second UX decision your user experiences. most products nail the auth screen and then completely abandon the user the moment they log in for the first time. here's what we ship on every first-login state : 1/ give them a win in under 60 seconds > empty state is not a blank page. its an invitation. show them exactly what to do first > one action. not five. if the first screen has 5 CTAs the user does none of them > progress indicator if setup takes multiple steps. users dont abandon flows they can see the end of 2/ design for the confused user, not the happy path > tooltip on first login, not buried in a help doc > pre-filled example data where possible. blank forms are terrifying > "skip for now" on every non-critical setup step 3/ trust signals before they do anything > show them what they're building toward. screenshot, preview, or sample output > name them. "welcome, harshil" beats "welcome, user" in retention data 4/ then lock the backend > session scoped to the device. cross-device requires re-auth > onboarding state persisted so they continue where they left off, not back to step 1 the first 60 seconds after login determines whether they come back on day 2.
- 14
@dan__rosenthal ·
The standard GTM funnel that most teams run is outdated: → Traffic in → Leads out → Closed-won → Done The problem is modern B2B buyers don't move in a straight line. They research independently, loop back through multiple touchpoints, and talk to sales last. We set up a flywheel instead: 1️⃣ Traffic generation ↳ Content, ads, outbound, partnerships 2️⃣ Lead capture ↳ Forms, lead magnets, social engagement 3️⃣ Lead nurturing ↳ SDR touchpoints, retargeting, newsletters, community 4️⃣ Qualification ↳ AI scoring, intent signals, awareness stages 5️⃣ Conversion ↳ Demos, case studies, free tools 6️⃣ Retention and expansion ↳ Customer success, upsell motions, feedback loops Start with 1-2 channels that already work. Validate. THEN scale. The funnel ends at closed-won → The flywheel compounds from it.
- 15
@E_Bruxxx ·
Hard tech founders underestimate one thing constantly: distribution. Everyone obsesses over delivering breakthrough tech. And yeah, obviously important. Few obsess over procurement, channel strategy, deployment velocity, integration pain, customer onboarding, government sales cycles, etc. Graveyard of hard tech is filled with companies that had “better technology.” Shocking number of VCs still underwrite hard tech like science projects. Reality is most companies die in commercialization. Not the lab.
- 16
@MakadiaHarsh ·
My exact onboarding process that keeps clients from ever saying "this isn’t what I expected": Day 1: - 45-min kickoff call - I record everything - Client gets the recording Day 2: - I send a 1-page scope doc - Not 20 pages - What we're building - What we're NOT building - When they'll see it Day 3-5: - I build the first thing they can click on Day 5: - Loom walkthrough - Here's progress - Here's what's next - Here's where I need your input Expectations aren't set on the sales call. They're set in the first week of work.
- 17
- 18
@alexabelonix ·
The hidden revenue channel is keeping contact with people who already trust you. Most founders think revenue growth means more acquisition. But expansion and reactivation are often sitting right there: old customers old pilots old waitlist old users old champions old “not now” old newsletter replies old communities Build a touch system: product update case study new workflow relevant insight feature release personal check-in renewal reminder expansion idea The point is not to “nurture leads” like a dead marketing PDF. The point is to stay useful until timing becomes real.
- 19
- 20
- 21
@askwhykartik ·
AI is not killing dev jobs. It's killing devs who only know how to code. If you're learning development in 2025, forget "frontend vs backend." Learn this instead: → How to get a user from landing page to paying customer → Onboarding flows that don't confuse people → Paywalls that convert (psychology > design) → Animations and transitions that feel smooth, not cheap → UX that makes users stay, not bounce The devs making real money right now? They don't just build features. They build experiences that sell. AI writes the code. You bring the sales brain. That's the actual skill gap nobody's talking about.
- 22
@oliverbrocato ·
Over the last 2 months we hired 3 full-time Client Success Managers. The goal: 5x the quality we deliver clients. Their job is simple: Be the client’s ambassador. Serve the client above the company - and by doing that, serve the company. * Reduce churn * Increase product adoption * Upsell + cross-sell * Generate testimonials, case studies + referrals Take insanely good care of customers and everything else follows.
- 23
@daviefogarty ·
We launched EPL Oodies for kids and their parents and had no idea if the collaboration would work. We originally launched without a clear angle. We knew matching outfits could work, but we weren't sure how to market it. Then in a voice of customer meeting, we saw multiple customers commenting: "It was so fun to have a matching outfit with my dad at the game." Voice of Customer is a monthly presentation where our customer experience manager shares consistent feedback to the entire company. So we took that feedback, and it became the marketing angle. Father-son game day moments. The whole purpose of VOC is to surface marketing angles you'd never think of in a conference room. It also catches operational issues before they become disasters. If fulfilment is slipping or product quality is dropping, customers will tell you before the metrics show it. But if you want it to succeed, make it company-wide. Everyone from product to marketing to ops needs to hear what customers are saying. So if you haven’t heard of this before, set up a monthly Voice of Customer meeting. You’ll be surprised at the benefits it provides your business.
- 24
@SimonHoiberg ·
I get nervous when a small SaaS I really like celebrates its first big enterprise customer too much. The contract is bigger, the logo looks good and then suddenly everyone forgets how expensive weird requests are. Custom report here, strange SSO setup there, one-off onboarding, special invoice terms, some permission thing nobody else needs and now half the roadmap is just keeping one customer happy. I have seen this too many times now. If one customer gets that much influence over what you build, many otherwise great products just starts degrading really fast.
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@floriandarroman ·
The mission is simple: → get to 20 trials a day → never get a day with 0 trial Since Monday we went all in into distribution and customers feedbacks. April 5th was our last 0 trial day. The goal is to reach a 20 trials/day average as fast as possible. We are pushing daily on: - Reddit - X - YouTube - Linkedin Until we find what works and double down on it. We also split our time with customers feedback (a lot of calls) to understand why they stay or why they leave. Then add the features missing. 2 rules: - Get a lot of customers. - Make them win.
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@peeplaja ·
We gave every person at Wynter 1 week to build their own AI agent. Budget of about 4 hours each. Today was demo day. Everyone presented what they built. Most had never built anything like this before. Some had zero technical background. Didn't matter. The combo of Claude for teaching and n8n for agent building made it possible for everyone. The average build time was about 3 hours. Here's what the team shipped: → Automated cold email mailbox manager that handles 726 sender mailboxes across domains. Used to take hours of spreadsheet work, now it's one click. → Customer onboarding tracker that monitors new pro customers through HubSpot, flags accounts needing follow-up every morning at 7am. → Renewals management assistant hooked into HubSpot and Gmail. Tracks status of every renewal convo, suggests when to check in. → Error notification workflow that triages support tickets, extracts key info, and determines if it's a bug automatically. → GitHub Actions for always-on development. A "file diet" that breaks down large code files, plus a daily test improver. → Automated unit test generator that writes tests for every new code change, re-reviews when the PR gets updated. → AI-powered test recommendation engine that analyzes patterns from past tests and suggests the next highest-impact test with methodology and ICP. → Interview process automation that creates ClickUp tasks and sends welcome emails the moment a new sale closes. → Copy variation generator that creates headline variants using different persuasive techniques, then lets you run a Wynter preference test with one click. → Support ticket triage bot. Enter a ticket number, get an instant summary with key details extracted. → Next test suggestion model that reads customer data and recommends three test ideas with methodology and hypotheses. → Stale PR notifier that pings Slack every Monday with the top 5 oldest unmerged pull requests, tagging the responsible people. → Competitive intelligence scanner that monitors daily articles about competitors and tracks homepage copy changes for positioning changes. I built my v1 in 90 minutes. Another hour for v2. The biggest takeaway across the board was the same. People realized they can actually do this. No deep technical skills needed. Just ask the right questions. One person said they completely changed their approach after 16 failed attempts and then it just worked. Another built their first AI automation in 2 hours having never done anything like it. That's the whole point. The fear of building AI tools is the main blocker for most people. Once you push through it once, you start seeing automation opportunities everywhere. Every team at Wynter now builds their own agents. Because they saw what's possible and want more.
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@ttunguz ·
What happens when technology evolves faster than your sales process can adapt? The last fifteen years, startups focused on building software around very well understood processes. We had built an assembly line for software sales, SDR to AE to customer success manager. We calculated ratios between these three total cost of sales and drove the factory to ever improved yields. AI is upending all of that. The underlying workflows are changing so quickly, software buyers no longer know what the ideal processes are, much less which is the best software to buy. Model capabilities have evolved at 10x improvements every two years. Users are grappling to understand how to take advantage of these advances while boards are pressing teams to adopt AI. A combination of all these factors has led to a reinvention of customer success : the forward deployed engineer. Forward deployed engineers (FDEs) are the new customer success managers, the new solutions architects. They spend their time working with customers, understanding business challenge, and using technology to solve them - selling usage & outcomes. In a software sales environment where buyers seek education, the underlying technology is advancing very quickly and there’s no stability. There’s no surprise that this role has become critical. OpenAI has offered consulting services as well as Anthropic for custom enterprise deployments. Anthropic builds specialized enterprise implementation teams. Sierra employs agent engineers. Palantir created this model. Their core insight, success comes from delivering outcomes on some software platform is now the standard for mid-market and enterprise software. The costs simply don’t justify themselves below price points of $100,000 or less per contract. Staffing a FDE costing $200k for a $10k contract - the math doesn’t work. These forward-deployed engineers take the core platforms of AI and then mold them and tune them to work, defining new ways of building sales and marketing. Marketing and engineering teams - for example, agent managers. The ability for customer success managers of the future to vibe code new platforms to deliver success on a basic platform is real . And it will be a requisite for these teams in an age where customer expectations of delivering value are shorter than ever. https://t.co/luEvGhkxgd
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@lukesophinos ·
Customer retention is an output. Outputs do not matter without the right inputs. The input that drives retention: time to value. Time to value is how long it takes a customer to hit the moment where your product clicks. The "aha" moment. The faster you get them there, the lower the churn. The longer it takes, the higher the risk they leave. Dropbox figured this out early. Their TTV metric is a user uploading their first few files. Once someone uploads a handful of documents, churn drops dramatically. So they optimized every pixel of the UI to push users toward that moment. Bumble did the same thing. Their former COO said the most important metric was successful conversations, defined as users trading phone numbers. Everything was built to create more of those. How to build your own TTV metric: Study your best customers. What do they have in common? How fast did they onboard? What did they do in the first 30 days? Study your worst customers. What made them unsuccessful? Where did they stall? Pick a metric and iterate. Speed matters more than perfection. Once you have the metric, hold people accountable to it. Tie compensation to TTV. Bonus teams quarterly on it. Track it weekly. Money drives behavior. Then bake it into the product. Build UI that pushes users toward the aha moment. Make TTV the center of your onboarding process. Talk about it constantly in all hands and standups. Strong time to value equals high retention. High retention is the foundation of every durable SaaS business.
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@Zubairey0 ·
One of the most underrated ways to beat competitors is not pricing. It’s not even always product. It’s customer success and response time. Saw this happen last week while helping a client with card issuance. We connected them with a few providers. One provider took days to reply. The other was responsive, clear, and kept the process moving. Guess who won the client? The responsive one. Same category. Similar offering. But one made the client feel like they were already being taken care of before the deal even closed. That matters more than people think. If a prospect has to chase you before becoming a customer, imagine what they think support will be like after signing. I even DM’d the other team and told them straight up: you didn’t lose because the client wasn’t interested. You lost because you were slow.
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@nrmehta ·
In enterprise AI startups, one of the top things I’d recommend hiring for is Empathy for the Enterprise. I proudly live in the Bay Area and have since college (don’t ask how long ago!) I love the spirit here: * Constant reinvention. * Not getting tied to the past. * Risk taking. * Copious wearing of Patagonia vests. But I also think those same virtues can cause people here to not be able to connect with corporate customers. I’ll often hear language like: * “What does that company even do anymore?” * “Do they still exist?” * “They have no idea what they’re doing.” * “Big companies are all politics.” I get it because you have to internalize the Goliath mindset and consider the David to be a lumbering giant, if you want to defeat your large competitors. But when you start applying this same psyche to your clients, you have a big problem (or at least I have a big problem with hiring people like that). Alternate framings are: * “Wow it’s incredible they’ve evolved what they do over time. Marriott Hotels started out as a root beer stand?” [true story] * “I’m so impressed by how they’ve weathered the storm and stayed alive for many times the amount of years I’ve been alive.” * “It must be so complex to run a company that big.” * “I can see why an organization that large has warring factions over time - each is operating from a point of logical local optimization.” Ultimately, I think it’s about curiosity. Curiosity about your customers, their business, their history, the tough tradeoffs they make and the humans that make them. Way back in time (like 3 years ago!), SaaS was a bit easier. You were selling more of a tool. So you needed to be somewhat curious. But your software was still slightly more abstracted from the client’s business than AI software is. Then still, the best Sales and Customer Success people (and founders) were deeply curious about clients. With AI, the bar has been raised. If we want our AI startups to transform enterprises, we’d better start getting as curious about them and empathetic for them as we are about the latest X fight over open versus closed models.
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@lukesophinos ·
Stop hiring "SaaS" Customer Success leaders for your vertical business. That CS leader with a decade at Salesforce or HubSpot? They probably won't work out. Here's why: Horizontal SaaS CS is built for sophisticated software buyers. Your customer is a VP of Marketing who's implemented fifteen tools. They understand adoption metrics, QBRs, and feature releases. Your CS leader drives product adoption, identifies expansion, manages renewals. Clean playbook. Vertical SaaS is different. Your customer is an HVAC contractor who started as a field tech twenty years ago. Works seventy hour weeks. Never used Salesforce. He doesn't trust the "Cloud" because he got burned by QuickBooks Online. His previous software was a filing cabinet and a spiral notebook. When your SaaS CS leader schedules a QBR to review adoption metrics, he has no idea what you're talking about. He just wants to know if his techs are logging jobs and whether he can stop doing payroll manually. The credibility gap kills you. At CourseKey, we sold to trade schools. I hired a CS leader from horizontal SaaS. Smart. Great resume. Within two months, customers said: "They don't understand our business." The breakthrough came when I hired someone who'd spent twelve years working at a trade school. She'd implemented technology. Lived through software migrations. Understood the pain intimately. When she talked to customers, they immediately knew she got it. Our retention went up twenty percent plus over the next twenty-four months. The rule: In vertical SaaS, industry credibility beats SaaS expertise every time. Hire someone who's spent five to ten years working in your target industry. Not selling to it. Working in it. Someone who's implemented technology and lived with the consequences. Trained users. Proved ROI. Dealt with the field tech who refused to use the tablet. You can teach them SaaS metrics in ninety days. You can't teach them ten years of industry knowledge. Hire from the industry. Teach them SaaS. Watch retention transform.
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@TheJobfather__ ·
Customer Success Operations is a sleeper role for people who understand customers, systems, and retention. CS Ops helps teams track renewals, onboarding, customer health, churn risk, and support handoffs. To build proof, create a mock customer health score. Include usage, support tickets, renewal date, NPS, and risk level. Then explain how a CSM should prioritize accounts based on that score. That is practical, visible proof.
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@neilpatel ·
Most products make users jump through hoops before delivering a single moment of value. Email verification. Profile setup. Forced tutorials. Plan selection. That's not onboarding. That's a gauntlet. The brands winning on retention flip the sequence. Core value first. Everything else second. #SaaS #ProductMarketing #CustomerRetention #GrowthHacking
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@AdamrahmanGTM ·
The outbound closed loop: + Identify best customers (highest retention + expansion) + Extract shared firmographic patterns + Rebuild ICP around those patterns + Target lookalikes with outbound + Track which new customers retain and expand + Feed results back into the loop Every cycle makes your targeting sharper.
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@frog_omo ·
Your best ops person just put in her notice. She runs enterprise onboarding. Every client. Every time. You open Confluence, looking for the process doc. There's a page called "Enterprise Onboarding." Last edited 14 months ago. Three bullet points. A broken Loom link. You call her and ask her to write it down before she leaves. She tries. But 4 years of instinct doesn't transfer to a Google Doc in two weeks. Your next enterprise client onboards at 68% success rate instead of 91%. This is not bad luck. This is the most predictable failure in SaaS, and almost nobody catches it until it's too late. 89% of SaaS companies hit a growth wall at $10M, $30M, or $100M ARR. The common diagnosis: wrong VP hire. Market fit. Sales execution. The actual cause: your business runs on memory, not systems. Researchers call it the OS gap, the distance between how your company actually operates and how your dashboard says it does. Three companies closed this gap on purpose. Here's exactly what they did: → @GitLab CEO Sid Sijbrandij (@sytses) wrote the first handbook entries himself. One non-negotiable rule: "The work has to end up in the handbook." Not Slack. Not memory. The handbook. 1,300 employees. 65 countries. Any employee finds answers without asking anyone. Any hour. Any timezone. Enterprise implementation success? Moved from 68% to 91% after formalising the process. → @Stripe In 2014, Stripe's long-term company goals weren't written down anywhere. COO Claire Hughes Johnson joined and wrote a 2-page document in her first week. Those same goals stayed relevant for 8 years. She replaced slide decks with narrative memos. Written decisions are circulated before every single meeting. Her framing: "Companies that don't document how they want to grow let external forces make that decision for them." → @zapier 100% remote since 2011. 17 time zones. 42 countries. They formalised the management structure at 15 employees, before it hurt. CTO Bryan Helmig's (@bryanhelmig) mandate: "All communication must be effective asynchronous." Remote stopped being a constraint. It became a competitive advantage. The pattern across all three: None of them documented everything at once. They identified the highest-risk processes first. Built from there. 80% of processes at most companies live only in someone's head. When that person leaves, the process leaves with them. Your enterprise onboarding shouldn't depend on one person's memory. One process. 90 minutes. This week. That's the move.
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@ShubhAgrawal26 ·
insanely easy to get customers for a low retention product, insanely hard to acquire them when they’re gonna retain for a long time. yes - the best businesses are the ones where people never cancel, insurance. utilities, banking, payroll, accounting, CRM etc which is why companies like brex, deel, rho, warp, attio need incredible sales teams, cracked marketers and setters and are willing to incur insane CAC to acquire customers because once they do - they typically don’t stop/switch and making them switch takes insane energy (money and time) on the other hand, products that have elite acquisition don’t have the ability to keep customers for 5-10 years as much so whenever you see me or any growth or founding person boasting about how much revenue we added - take it with a grain of salt, we’re consciously taking advantage of a phenomenon that exists in the market everyone wants more customers all the time - which is why they’re always looking for a better solution and are also willing to leave a product at the slightest difficulty. recognise there are different rules to each game.
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@keean_edward ·
you can learn a lot about what makes a good product by trying different SAAS products and observing your own behavior. today i've looked at two different tools for growing on X and within 10 minutes of using both, i canceled. i was genuinely interested in the idea of those products, it would be nice to have more followers. what i realized is that the reason i canceled those subs right away is where i've made the biggest mistake with my own SAAS. within 5 minutes of using a product you should know how to extract the value for your use case. good onboarding is not enough - you need to specifically direct people to the value and to do that you as the founder need to know exactly what specific part of the problem you're solving.
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@jasonlk ·
"When you hire a VP Customer Success or VP of Sales, before you send the offer letter ... Ask them to send you 2 customers to talk to. Any strong leader here will have 2 customers they worked with, that will take your call. Any."
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@TheChowdhary ·
Almost every YC founder I speak with has a "product graveyard" Here is ours: A few months ago we launched GitHub data as a new source I went through hundreds of sales demos, Intercom messages and feature requests... It was obvious that the market was looking for GitHub data at scale, mapped to the right person It would unlock several use cases: sourcing engineers by what they build, dev-tool companies building target lists from repo activity, screening candidates by commit history,... We pitched it to customers and they got excited, so we got excited Our data and ML team spent weeks mapping millions of GitHub profiles to the right entities and we scaled our infra to support this new use-case Months later - after launching all of this, only 48 customers have hit this endpoint in the last 90 days Even though the customers who did try it use it heavily, every day, the usage we expected just isn't there yet Was it our marketing? Was it a nice-to-have all along? we're still trying to figure it out Every company has a "product graveyard" - I don't think you can really avoid it We do everything it takes to minimize the amount of these features And while I still believe in this use-case (especially for recruiting) This is what we learned to do when we joined YC: 1) When someone asks for a feature, ask if they'd expand their contract if it existed - and quantify it as much as possible. by how much? starting when? 2) Try to sell the feature before building it - a contract contingent on shipping by a date. we did this in the early days and I push our sales team to do it today as well. many customers love thinking about new ideas and features, but it's literally not part of their buying decision 3) Every launch gets an owner. their job is to research - who asked for this feature? is it a must-have or a nice-to-have for them? - and then follow up with every one of them the day it ships
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@bmykhaylivvv ·
what %? what % of the problem will it solve for you? last week I was doing a research on one of the functionality at AiSDR and before talking to our Customer Success team I had 2 approaches for the implementation 1. quick-win which would take us 1-2 days to implement 2. pretty large architecture change which will give us 100% flexibility on the functionality we want, but it will take us the whole week to implement and will affect core of out system Oleg Zaremba suggest to ask “what % of the problem each of the solutiob will fix?” on the call with CS team and it appeared that our “quick win” solution will fix ~90% of the CS team problem having this information we should measure where it is worth spending such much more time on complex solution which will give us about 10% of the outcome 2 keyaways: 1. Talk to your team about the problems they have and do not guess 2. Ask right questions
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@imrayjohnston ·
The source of innovation last 2 years has come from this.. NPS survey. We started doing that a few years ago, and it's radically changed our company. (pictured is an 8-fig brand of our teams) Every month we send our brands an NPS question to get their feedback. We pipe it into our Slack for the whole team to see. Because of this feedback, we've: - overhauled creative systems - hired new roles - changed how we forecast for them - how we scale them - how we strategize with clients - AI creative It's literally been the seeds of innovation. Why struggle figuring out what to improve? Just do what your customers want and they will stay. Every founder I mentor (outside of running my BIZ) I tell them to do this. Over the next 1-2 years, your retention rate will go up.
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@rheejust ·
30% of new YC companies use Porter. We got there by doing the exact opposite of what every growth playbook says. After raising our $20M Series A, my chief of staff Shankar came to me with a plan. The natural instinct after raising is to expand: deploy resources across every channel and hope something compounds. How other well-funded startups run GTM: - Sophisticated multi-channel motions - In-person events - Partnerships etc. His pitch was reasonable: we need to start doing all of that. We need to mature. We need to expand. My thought was the exact opposite, because of one piece of YC advice I think about constantly: as you grow, you don't trade "[doing] things that don't scale" for only doing scalable things. → You just hire more people to "do things that don't scale." We needed to go more individual, more personal, and do more things that didn't scale. Every growth playbook tells you to diversify your channels at this stage. Instead, we focused everything into one place: we "spiraled in." We doubled down on the YC ground game: 1. The 1:1 founder relationships 2. The office visits 3. The hands-on customer success Obviously the other channels could work, but this one was already working, and we hadn't come even close to exhausting it. We put all our energy into making this one channel impossible to ignore, and the results were dramatically stronger than anything we could have achieved by spreading thin across ten channels at once.
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@chrisbarber ·
The value of ai coworker products is proportional to the integrations that someone has, data in and data out. AI companies would benefit from spending a lot of time observing users that do and don't have integrations set up. What are those who have it set up getting the most value from? What are those that don't doing without as workarounds? And, observe people in the onboarding/integration setup. Which points are confusing? Which permissions are scary? Goal is to remove the confusion and also show the benefits up front. Think about how this often happens in person or over text: you show your friend something cool, they ask how you did it, you show them, and then maybe you help them set it up. In that scenario, you've a) made the perceived reward really high and b) reduced the perceived effort and uncertainty. You want to replicate that experience for all users. How can all users see as much perceived upside, and have as low uncertainty, as one who got a demo and a personalized onboarding from their friend sitting next to them? (This applies both to signing up for the product in general, and to setting up each high-effort feature, e.g. each integration)
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@nrmehta ·
Be Curious: 5 Weak and 5 Strong Questions to Ask B2B Customers: Everyone in B2B, whether you're a brand new AI startup founder, an experienced software exec or a customer-facing individual contributor, wants one thing - stronger customer relationships. In a world where software is a commodity, relationships are often the difference between a win and a loss, a "closed" and a "not now" or a renewal and a churn. I've written about techniques to meet with customers. But what do you say when you see them across the Zoom screen or Starbucks table? I've been there when I asked the weak questions that showed a lack of curiosity, no point of view and no confidence: 1. "What's your feedback on our product?" (maybe they didn't even try it) 2. "What feature do you like the best?" (the buyer may have no idea) 3. "How do we compare to our competitors?" (me me me) 4. "What are your goals?" (as if the buyer wants to just open his/her OKRs and share them) 5. "Are you ready to buy this quarter?" (umm...) The common thread between those weak questions is that they are about you, not the customer. By contrast, there is a plethora of powerful questions the best ask. I've stolen many, including: 1. "I was able to meet with a dozen CIOs last week. Every single one seems to be struggling to figure out the productivity impact of AI. How are you handling that? I can even send you a survey we did around this." (shows you have expertise) 2. "I noticed your team was called out in the last earnings call in a good way. That's amazing. How did that make you feel? What are you doing to sustain the work?" (shows you're paying attention) 3. "I'm hearing more and more that this budgeting season is hard since 2027 is so murky. How are you approaching prioritization?" (shows that you get the real world) 4. "I can only imagine how many vendors you get pitched by about AI. Who are some of the best partners for you and what are they doing to truly help you?" (shows you want to be a true partner too and are open to feedback) 5. "Ultimately, software - including ours - are just tools. I've found that the real impact comes in making sure its rolled out aligned to the client's goals. Is there one company priority that you heard about in your CEO's all hands that we should align around for the deployment? Is there a milestone where a win by then would help the company?" (figure out how to strategically ladder up and start identifying a compelling date) As one of the all time great entrepreneurs said, it's about being curious...
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@joshuapliu ·
The real measure of success for your Health Tech startup’s partnership with a health system is NOT the ROI you demonstrate - it’s actually this: Whether the health system renews your contract, year after year. I can give you many painful examples I’ve experienced at @SeamlessMD where we hit all the targets and demonstrated ROI, only to ultimately fail: → The health system that used our product to cut LOS and readmissions across many service lines enterprise-wide… only for our executive sponsors and service line champions to all leave the organization, and the new folks who took over, just wanted to do things differently. → The hospital who piloted our product and reduced readmissions by 50%+... only for the CEO to tell us that if he reduced readmissions, the government would think he needed less money next year and fund them less. → The health system we helped cut LOS and readmissions across a few priority service lines… only to find out their C-suite signed a broader partnership with a “similar” vendor so we were disposable Early on in my career those were gut punches, but now that I’m 13+ years into this journey, those are just par for the course. Now I know better. I now recognize that having C-suite buy-in and alignment with a strategic priority matters more than any amount of ROI and clinical evidence we could generate (but we do work hard to measure results anyhow, because we care that our Tech actually improves patient outcomes!). If anything, my recurring experience is that “ROI” is used to justify a decision already made. I now recognize that for innovation that improves clinical outcomes - which often is not as important a priority as increasing revenue or decreasing clinician burnout - having strong champions is absolutely critical. And your champions won’t last forever… many often change roles, change organizations, etc. If you don’t continuously mobilize more and more champions all the time, one day you’ll wake up with a great ROI and no one who cares to fight for you at the annual budget meeting. Which means Health Tech startups need to earn those contract renewals year after year, and it’s not just about the numbers and ROI. Sometimes it is, but often it isn’t. It’s about engaged C-suite, engaged champions, deep integrations/workflow alignment, and so much more. Yes, this means you can’t “set it and forget it”. Most Health Tech startups aren’t selling Office 365 anyone can buy with a click - most of us are selling a mixture of Tech + Services + Transformation. That’s a lot of change. Which means you don’t truly know if your innovation is sticky until a health system actually renews. And even if it’s sticky right now… it may not be sticky forever. Even if you cut LOS and readmissions by 50%... it’s often not enough. You have to earn it. Again. Every single year. But if you do… you can have amazing health system partners for life.
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@mdjunaidap ·
The 3 questions I ask every customer call: 1. What were you using before this? 2. What stopped you from signing up? 3. If we disappeared tomorrow, what would you miss? Their answers tell you: ➭ Your real competitors ➭ Your friction points ➭ Your actual value Ask these. Take notes. Build better.
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@marty_kausas ·
Every CS leader in this room wanted to hear about one thing: How to implement AI Instead of talking about AI broadly, we walked through our own journey of how we scaled Pylon's customer success motion to thousands of customers across a mix of scaled and enterprise accounts. We showed specific examples live of how we prioritize accounts, what data is helpful, and more. The takeaways: 𝟭/ 𝗕𝗲 𝗵𝗼𝗻𝗲𝘀𝘁 𝘄𝗶𝘁𝗵 𝘄𝗵𝗮𝘁'𝘀 𝗻𝗼𝘁 𝘄𝗼𝗿𝗸𝗶𝗻𝗴 𝘁𝗼𝗱𝗮𝘆 I asked the audience how many of them use a Customer Success Platform today (~50% raised their hand). Then I asked how many of them are happy with what they have (0 people raised their hand). 𝟮/ 𝗜𝗳 𝘆𝗼𝘂 𝗰𝗮𝗻'𝘁 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲 𝘆𝗼𝘂𝗿 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗱𝗮𝘁𝗮, 𝗻𝗼𝘁𝗵𝗶𝗻𝗴 𝗲𝗹𝘀𝗲 𝗺𝗮𝘁𝘁𝗲𝗿𝘀. In CS you've historically been able to leverage quantitative metrics (like product usage), but that leaves all the qualitative stuff (emails, tickets, calls, etc) out. What's unlocked with LLMs is that you can now structure both. Aim to consolidate product usage, tickets, call recordings, notes, CRM data, calendar events, internal slack conversations, and more. 𝟯/ 𝗟𝗲𝘃𝗲𝗿𝗮𝗴𝗲 𝗔𝗜 𝗮𝗰𝗿𝗼𝘀𝘀 𝘁𝗵𝗿𝗲𝗲 𝗹𝗲𝘃𝗲𝗹𝘀: - Account-level (sentiment, priorities, contacts, meeting prep) - Book of business-level (who is upsellable, who is a risk of churn, who needs help) - All accounts (feature requests, trends, upcoming risks). — Thank you to all the attendees! Great meeting many of you and getting to chat about AI-enabling your post-sales teams. The talk did so well that I'm hosting a follow-up webinar on this topic on April 23! I'll deep dive into the points above (+ more), show you some of the AI workflows teams have set up in Pylon, and answer any questions live. Register to join: https://t.co/otYRIeUhBs
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@villageglobal ·
"Are you sure you really want to create a category? I always joke: 'I'm actually 25 years old. This is just what category creation does to you.'" @nrmehta ran the customer success platform @GainsightHQ as CEO for 13 years. Vista Equity Partners acquired the company for $1.1 billion in 2020. When he started in 2013, there were about a thousand customer success managers in the world. Now there are hundreds of thousands. @sniyogi sits down with Nick to talk about how it all happened. A few moments that stood out: "We went to Safeway, got the cheapest wine, the cheapest cheese tray. Put it on a ping pong table because we didn't have a conference table. 75 people showed up and stayed till 10 PM. They weren't there because of us — they were there because of each other." "I literally started going there, sitting in their lobby. I knew the Wi-Fi password. I knew the front desk receptionist — she was into Disney movies." "Humans buy software for their human needs and then they justify it to their business. I wanna get promoted. I don't wanna get fired. I'm worried about my job." "I decided to get up on stage, just coming off pneumonia, and literally talk about being lonely as a kid — which I was, extremely lonely."
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