SOLUS.ai

Happy Diwali, everyone!

Question: What do "Rip Van Winkles," "Copy Cats," and "Silent Sufferers" have in common? They're all sitting in your customer database right now. And they're all part of our new eBook, "The Book of Segments" – a fun collection of 48 distinct customer types that appear across retail, hospitality, QSR, and D2C brands (BFSI too!). 48 segments to think about, adapt to your context, and use to add some magic to your CRM and Retention campaigns. We had a blast putting this together, hope it's useful/ fun for you too! Our favorite? "Potential MVPs" – new customers showing high-value signals. Treat them right early, and they become your best customers. This post only has a few examples, for the full book the download link is in the comments, below:👇 #CRM #CustomerInsights #DataDrivenMarketing

Ramasubramanian (Ramsu) Sundararajan spoke at the CII India Innovation Summit - Innoverge 2025 on two things: 1. Why we need a mix of foundational In-India-For-India GenAI models such as those that improve Indic language capabilities, as well as a large application layer where people build agents and other apps for India and the world. 2. Transitioning from products to services is not always linear. Especially in the B2B space, there's a bit of a services business inside every product (because of the need to integrate with legacy IT ecosystems), and a bit of a product inside every services business (because of the repetitive nature of many tasks, including a lot that were considered higher-cognitive and therefore resistant to automation).

📖 In chapter 2 of the eBook on AI driven Hyper Personalization we tackle some ground realities: - CLM (Lifecycle Management) vs. GTM (Go-to-market): The tension and balance - Adoption of Models vs. Recommenders (no, they're not the same!) - The advent of Long-term measurement in addition to trigger level uplift measures - Channel evolution: What's up with whatsApp? - Going N=1 and it's impact on Brand and Tech Link to the full book (6 chapters + Appendices worth!) in the comments. 😊

After analyzing implementations across retail, financial services, and QSR industries, one thing is clear: The most successful companies have moved beyond basic segmentation to AI-driven systems that optimize at the individual level - what we call N=1 personalization. The gap between MarTech systems (that execute what you decide) and Intelligence Systems (that tell you what to execute) has never been wider. 📖 Download "The AI-First Approach to Hyper-Personalization" - our comprehensive guide covering real implementation playbooks, ROI measurement frameworks, and industry case studies. (Out here in the carousel is Chapter 1) Link to the full eBook in comments.

Register for our Webinar on the Future of CRM: AI Powers Everything. In this webinar, our Co-Founder, Sandeep Mittal will take you through the AI Agents in SOLUS with a focus on AI driven Segmentation, Campaign Ideation, and Analytics. 📅 Thursday, 25th September 2025, 3-4 PM IST Register here: https://lnkd.in/dDQ7aRuN #AI #MachineLearning #Webinar

Enterprise data science feels like an Indiana Jones movie - tunnels full of skeletons from those who tried before you. Except here, the skeletons are: - Sophisticated algorithms that never saw production - Elegant ML pipelines solving no real problems - Powerful AI systems gathering dust while users stick to Excel Swipe through to see the causes, and what it takes to fix this. #AI #MachineLearning #DataScience #BusinessStrategy #AIImplementation

How do you implement AI reliably at scale? After building multiple AI agents that handle millions of customer interactions, here are 8 learnings from our experience: #AI #MachineLearning #AIImplementation #MarketingTech #MLOps

We've all been there... 🎯 Your campaign deadline is tomorrow. You need to segment your customers for maximum relevance. You start with the best intentions: ✅ High-value frequent buyers who love Category A ✅ Recent purchasers with 2+ categories ✅ Dormant customers with specific brand affinity ✅ Geographic micro-segments by purchase behavior Two hours later... still waiting for segment counts. Four hours later... realized you need to adjust the criteria. Six hours later... the segments are finally ready but half are too small to be viable. Eight hours later... "Just send it to all active customers" 😅 Sounds familiar? There's a better way. What if you could create, test, and refine customer segments at the speed of thought? What if complex multi-variable segmentation on bill level data (this is where most things break) took seconds, not hours? That's exactly what AI-driven segmentation in SOLUS delivers. No more waiting. No more compromising on precision. No more settling for "good enough." Want a view of our all-new Segmentation module? Drop us a message right here! #MarketingAutomation #CustomerSegmentation #AIinMarketing #PersonalizationAtScale #MarTech

New blog on SOLUS: https://lnkd.in/gkbNCQ-J Prediction is difficult, especially about the future. While this quote (attributed to everyone from Yogi Berra to Mark Twain) might sound like a joke, it reveals a fundamental truth about predictive modeling in business: people change, markets evolve, and the only constant is change itself. In our latest article, we dive into the challenge of "concept drift" - when the relationships your ML models rely on shift over time. Whether it's gradual market evolution, seasonal patterns, or sudden structural changes, your predictive models need to adapt. Key takeaways: ✅ Frequent model retraining beats perfect initial accuracy ✅ Shorter prediction windows = more reliable models ✅ Focus on being "good enough" for decision-making, not pixel-perfect ✅ Out-of-time validation is your friend The goal isn't to predict the future with crystal ball precision - it's to stay ahead of the curve while your competitors are still using last year's insights. How do you handle concept drift in your predictive models? #MachineLearning #PredictiveModeling #AI #DataScience #BusinessIntelligence