Rajiv Ranjan

Here’s how GTM Engineering work can be extremely valuable for CS teams ⬇️ CS teams have been slow to adopt GTM Engineering as a supporting function, compared to how quickly their sales, marketing, and revops counterparts have begun utilizing it. In their recent blog post, Mishti Sharma and Varun Anand highlight CS as a department that is perfectly eligible for GTM Engineering support. They touched on an important point, which I hope sparks ideas for a lot of companies. The topline is that Clay + new AI tools allow CS teams to more easily do proactive work instead of just reactive work. This is the biggest shift I’ve seen across our own client portfolio. Here are a few systems GTMEs can build with Clay to help support a CS team and shift their posture from reactive to proactive and revenue-driving. 1. Account Health Monitoring Automatically surface at-risk accounts based on usage, support history, and engagement trends. Enrich monitor your 1st party data for these signals, enrich for 3rd party data, then push an actually useful task to the appropriate account manager. 2. Champion Tracking Track job changes and engagement shifts so your team stays ahead of renewal risk and expansion blockers. 3. Expansion Intelligence Use product signals to proactively identify upsell opportunities and draft outreach sequences. 4. QBR Automation Automate data pulls and deck creation so QBRs are consistent, faster to produce, and more focused on outcomes. 5. Proactive Support Prevention Spot friction early—low usage, poor onboarding, or bug activity—and intervene before it turns into a ticket. I put together a graphic that shows how GTM Engineers can drive real impact CS teams. Hope this sparks ideas for your team! Is anyone doing this currently for their CS org? #customersuccess #cs

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Left Microsoft, built a 20,000 CR company, and donates 40 lakh every year. 1. During his 8-year stint at Microsoft, Samir Bodas created history by becoming the director for SME – Sales and Marketing, Microsoft's first foray into small businesses. He was responsible for anti-piracy, licensing, and demand generation. However, the dot-com boom burst in 2000. 👇🏻 2 He left Microsoft, wanting to start his life from scratch. In 2002, he joined Disha Technologies, an early-stage IT Services firm, as its CEO, focusing on software testing and quality. He led the brand from 1 CR in sales to an acquisition by the Indian IT company Aztecsoft for 54 CR in just two years. 🙌 3. Samir returned to Pune, India, and was seeking new ideas. He met Monish Darda and got inspired by him to start a startup together. They began searching for ideas and discovered that business contracts were ripe for disruption through the use of cloud and AI. Samir wanted to take action. 🤔 4. In 2009, he decided to start a company with dual headquarters in Bellevue (USA) and Pune to attract customers globally. He named it after a suggestion by his wife on the Latin word "certa," meaning "trust." Icertis was born. 🚀 5. The idea was simple ⏩build a "Salesforce of contract management". Companies can digitise all contracts into a single repository and extract critical insights for risk and compliance. But companies were still not convinced. 🤔 6. Companies found no strategic value, and he had to compete for a limited share of enterprise IT budgets. He then pivoted to software-based contract lifecycle management solutions, providing automated clause analysis, obligation tracking, and workflow enforcement. And it worked. ✅ 7. As it helped Mercedes-Benz achieve a cycle-time reduction of 80%, Microsoft, Airtel, Hyundai, and Johnson & Johnson became its customers. Samir was now scaling on a 100% cloud infrastructure. By 2015, he raised 37 CR led by Greycroft. 💰 8. Within a year, Icertis had scaled to 500,000 users and 2 million contracts. Samir was building "the foundation of commerce" through contract intelligence. As it scaled to 750,000 users and 2.5 million contracts by 2017, it raised 162 CR led by B Capital Group. 💸 9. Samir grew with his famous FORTE (Fairness, Openness, Respect, Teamwork, and Execution) principle to over 3.5 million users and 4 million contracts processed by 2018. Five of the world's ten most valuable companies were its customers. And finally, the big news came on July 17, 2019. 👇🏻 10. Icertis raised 792 CR led by Premji Invest at a valuation of 6890 CR. It became the first contract lifecycle management unicorn globally. 🦄 11. Today, Icertis manages over 10 million contracts in more than 40 languages and across 90 countries. It is valued at 20,300 CR. 📈 However, Samir Bodas still donates Rs 40 lakh to over 170 non profit organisations every year. 🙏 #startups #india #casestudy For more such stories, read my book - Startups of Bharat, on Amazon!

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This is an outbound email from a $12b company. Made me cringe reading it 😵‍💫 - I was at IIT Roorkee 12 years back, that's far from what's top of my mind today. - reference of Thomso is such put-off, while many americans know about IITs, I have not come across one who knows what Thomso is, the most they can do is acknowledge that Roorkee is in the north Frankly, you lost me after these 2 lines but there are more issues - We are not a communication software and even if we are why do you need to put that in paranthesis - just because we have new capital doesn't mean it's the time to look into systems/processes - what is the key takeaway for me? 🤨 - why is your email so long? 😵 This is what is everything that's wrong about using AI without putting any thought in it. This is most likely a clay signal for funding announcement with some random personalization on my linkedin profile on a poorly written email. It's doing more harm than good. Stop lazy and stupid automation ❌ Despite all the flop, people still read emails. - Put effort in crafting a compelling messages. - Don't over rely on signals - I have got 30 vendor emails since we announced, you are more likely to get drowned than get noticed - Find your pitch before you scale it.

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Decoding Enterprise Tech with Srikanth Tanikella of Pavestone VC In a space where transformation meets complexity, enterprise technology in India is undergoing a pivotal evolution. We sat down with Srikanth Tanikella, Managing Partner at Pavestone VC, to unpack what it really takes to build and back scalable enterprise startups. In this insightful conversation led by Sandhya Bharti, Head of Editorial IP & News at Indian Startup Times, Srikanth shares: - His journey from driving 3.5x growth at CAMS Limited to becoming a hands-on VC - Pavestone’s sharp focus on enterprise tech and frontier science - Why AI-native SaaS is the next big wave - Key challenges founders face in GTM and org scaling - Tactical advice for both entrepreneurs and early-stage investors “Enterprise tech isn’t about flashy demos. It’s about solving structural problems and earning long-term trust.” – Srikanth Tanikella This is a must-read for anyone building or backing in the B2B SaaS and enterprise innovation space. Read the full interview: https://lnkd.in/etQq-iCR #IndianStartupTimes #EnterpriseTech #VentureCapital #B2BSaaS #StartupInsights #FounderFocus #AIinSaaS #PavestoneVC #SrikanthTanikella #InvestorInsights #IndiaStartups #StartupEcosystem

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I asked ChatGPT: Describe me based on all our chats — make it catchy! ChatGPT’s Answer: You’re a digital alchemist — part product visionary, part AI strategist, part market whisperer. A seasoned VP of Product at Jio, you’re not just building platforms — you’re architecting ecosystems. From simplifying telecom for SMBs to crafting AI-powered GTM playbooks, you think like a consultant, act like a founder, and ship like a PM on a mission. You chase clarity, detest gyaan, and expect every word — and every pixel — to earn its place. Your daughter? A rising star with a violin in one hand and leadership in the other. Your side quests? Satirical books, stock market dives, and building bots that know your taste in jackets and stocks. If there’s a formula for winning with tech, teams, and time — you’re writing it in real-time. ChatGPT is amazing ;)

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Here's what GTM looks like in 6 months to 1 year -- and which players will get left behind if they don't act now. Systems of Action (unknown MCP adoption): Kareem Amin and Varun Anand of Clay Systems of Record (unknown MCP adoption): Dharmesh Shah & Brian Halligan of Hubspot Systems of Information (MCP adopters): David Connors with The Swarm, #RoqRoqRoq Xever's Technographics, Ryan Buckley of Shovels ^-- And the system of Intelligence is Dario Amodei's Anthropic (MCP inventors) It's not just the MCP server that will connect all of this tissue, we will need other middleware like Ayan Barua's Ampersand (just launched MCP support) so that we're talking to our data, to our customer's data, and to our systems with robust connections so we are spending our time actioning not acting. Doug Bell and I will be first to march into this world with our weekly Cannonball GTM so that we can continue to disrupt ourselves. And we'll show brands the way to this future. But the tools we will adopt to have outsized outcomes in downsized amounts of times are those that CONNECT to our system of intelligence, not those that double down on, that insist that everything can be done in their own tool. Your differentiation in this new world is the QUALITY of your interoperability, not your ability to prevent it from happening. Get on board, now.

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Customer discovery conversations at 36000 ft ✈️ Person sitting next to me was battling problems with delayed feedback -- iterating on ML solutions become even harder when the feedback loop is ~6 months; e.g. $ lending decisions ended up discussing few options around: - starting with periodic retraining on historic data - using proxy metrics for quicker feedback - consider online learning with delayed updates (eg SGD with delayed update) - survival analysis to model time-to-event outcomes (e.g. survival models treat these as censored observations) - using reward shaping Spending a week in San Francisco 🌉

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The rapid rise of Southern Indian states over the past decade is remarkable. Per capita income across the seven southern states has grown at an impressive average CAGR of 10% between FY14 and FY22, reaching approximately ₹2.7 lakhs ($3,300), compared to 8% for the rest of #india. Telangana, in particular, has doubled its per capita income in just six years. Cities such as Hosur and Kochi have emerged as new hubs for manufacturing and IT services, attracting major #investments from companies like Ola Electric, Ather Energy, and Tata Motors, all of which have established large-scale vehicle manufacturing facilities in the region. Established #business have adapted their strategies to leverage the #growth in the South. For example, HDFC Bank’s employee base has grown by around 97% in the Southern and Western regions, compared to 45% in the North. Kotak Mahindra Bank has expanded its branch network at twice the rate in the South and West as in the North. Southern states now account for 45% of Tanishq’s total demand, and Asian Paints’ Beautiful Homes service has 48% of its outlets in the South. Even startups like Zomato, Swiggy, and Zepto have a stronger presence in Southern India than in the North. Given these trends, focusing on the Southern market could be a highly effective #strategy for businesses over the next decade. #kneeledge

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From Data Mess to Sales Comp Success – Our Takeaways from #SalesComp25 When Sujeet Pillai & I took the stage at the #WorldatWork conference, we started with a simple question: "How confident are you in your sales incentive data?" The answers? Let’s just say…very few raised their hands for “Totally confident.” That’s the reality we’ve seen over 20+ years of working with sales compensation programs - even the most perfectly designed incentive plan can collapse under the weight of bad data. We spoke about: - Silent derailers like missing records, bad hierarchies, and inconsistent inputs - Real client stories—from financial services to insurance brokers to beverage giants—who overcame chaos and restored trust - Practical frameworks to detect anomalies, set up early warning systems, and save analysts from burnout - How automation doesn’t just reduce errors—it gives your team their nights and weekends back The message we wanted to leave the room with was simple: Data first. Because without clean, timely, accurate data—automation, dashboards, and comp models can’t deliver their promise. Our advice if you’re starting this journey: - Audit your last comp cycle and spot where data broke the flow. - Add just one regular data check and one alert to your process. - Automate one manual task this quarter. - Make clean data everyone’s responsibility. When data quality becomes a shared mission, you not only fix payouts. You rebuild trust, save time, and give your teams the clarity they deserve. Because in the end, Clean data = Happy reps. Happy reps = Better performance. We loved the energy, questions, and honest discussions at the session. Thank you to everyone who joined us! Aurochs Solutions Incentivate Solutions #SalesComp25 #SalesCompensation #DataQuality #IncentiveCompensation #Automation #Leadership #WorldatWork

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tl;dr: If you’re 40+ (in India), manage your exposure to personal debt carefully. Go debt-free if you can. Anecdotally, I see many in my peer group struggling to land career transitions in their 40s. There’s emerging evidence in the numbers as well. EPFO net payroll records are not a perfect measure but the trends offer a good proxy for employment dynamics. While net new subscriber additions for younger age groups (26–28 and 29–35) showed steady growth through 2024, the cohort aged 35+ tells a different story. Their numbers show erratic and sharp month-on-month fluctuations. This is a uniquely FY 2024-25 pattern when compared to the more predictable trends in prior years. Unfortunately, there isn't more granularity in the data to break this down specifically for those in their 40s. What could this signal? Possibly, a combination of fewer new hires among experienced professionals, higher exit rates without rejoining, and greater difficulty for mid-career workers to find jobs after layoffs. I’m not sharing this to alarm, but with the hope that it helps someone plan better. PS: AI might hugely influence this as well. FWIW, it took me less than an hour to extract source data, profile information, explore patterns, and create multiple visualizations using AI-assisted coding. There's no version of me doing this as fast without an LLM.

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