Personalized Notification Approaches

People are different. Context matters. Things change. Eric Hekler’s mantra is one of those deceptively simple ideas that should be obvious, but isn’t. It’s why so many so-called behavior change interventions flop, and why we keep getting notifications at the worst possible moments. Most health and wellness apps still take a static, one-size-fits-all approach. They assume if a certain nudge or goal worked once, it’ll work forever. Or that people are predictable, logical creatures who will of course go for that lunchtime walk just because their phone suggested it. Instead, what if we designed personalized, perpetually adapting interventions that actually respond to a unique person’s evolving needs? 👭 1. People are different → Personalization A 10,000-step goal might inspire one person but overwhelm another. A sleep tracker that rewards “consistent bedtimes” might help some, but stress out shift workers or parents of young kids (ask me how I know). Instead of assuming what works for some will work for everyone, interventions should learn from the individual and adjust accordingly. 🏖️ 2. Context matters → Just-in-Time Adaptation The best nudge in the world is useless if it arrives at the wrong time. A reminder to “take a walk” while you’re in back-to-back meetings? Ignored. A bedtime notification while you’re still out with friends? Deeply unhelpful. Instead of blasting out advice, interventions should consider real-world constraints. When is the person actually in a suitable position to act? 👛 3. Things change → Perpetual Adaptation Motivation isn’t a constant. Life gets in the way. What worked last month might not work this month. A smart intervention doesn’t just set a goal and hope for the best! It adjusts over time, just like a good coach. Take a sleep coaching app. Instead of rigidly telling you to sleep at 10 PM every night (good luck with that), it could: ✔ Personalize recommendations based on your actual sleep patterns. ✔ Adapt to context, recognizing that late work nights or weekend plans shift your bedtime. ✔ Adjust over time. If you consistently ignore bedtime reminders, try something new. Maybe it suggests a wind-down routine instead. Or nudges you 15 minutes earlier at a time rather than expecting a sudden 10 PM shutdown. And stops bugging you altogether if you’re already hitting your sleep goals. This is the future of behavior change — interventions that are smart enough to meet people where they are, when they’re ready, in ways that actually make sense. Now, your turn: What’s an example of an intervention (digital or otherwise) that actually adapted to you?

Tired of generic LinkedIn messages filling your inbox? Brex just set the bar higher with their Champagne Campaign 🥂— and it’s not about cold outreach, it’s about thoughtfulness and results. Most days, my inbox 📩 is flooded with cold, non-personalised LinkedIn messages. Sure, some of these may convert, but they lack connection. Compare this with what Brex did—an ABM campaign that targeted the right audience, at the right time, and made a real impact. In 2018, Brex was a small team with 30 employees and no customers. Instead of blasting out messages, they targeted 300 startups that had recently raised funding. They didn’t stop there—each of these startups received a bottle of Veuve Clicquot champagne 🍾 with a handwritten note 🗒 from Brex’s CEO and a personalised followup email a week later to ask for a demo. 𝐓𝐡𝐞 𝐫𝐞𝐬𝐮𝐥𝐭? A 75% demo booking rate. Of those demos, 75% converted to customers. Net result - 169 new clients from just 300 prospects. All of this with a campaign spend of only $19,000. This approach worked because it’s intentional and personal — Brex took the time to target companies who were at the perfect moment to need their product and followed up with a thoughtful touch. It’s a far cry from the mass outbound methods so many agencies push, which often fail to create meaningful connections. 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲: Outbound works—but it works better when it’s personal. Stop sending generic messages and start crafting thoughtful, targeted campaigns that create real results. Have you tried personalised outreach in your campaigns? Let’s connect and talk about how ABM can transform your sales approach. #OutboundSales #ABM #PersonalisedMarketing #LeadGeneration #MarketingStrategy #BusinessGrowth #SalesTactics #MarketingROI

Most IoT teams get notifications backwards. They start complex and wonder why users ignore them. Here's the 4-phase framework that actually works: ➞ Phase 1: Foundation (Essential Functionality) Start simple. Device status, error alerts, basic thresholds. Manual opt-ins, fixed delivery schedules, basic open rates. Nothing fancy, but it works reliably. ➞ Phase 2: Enhancement (Expanded Connectivity) Add depth. Hardware diagnostics, maintenance reminders, richer data inputs. Rich media notifications, time-sensitive alerts, offline queuing. Begin A/B testing preferences. ➞ Phase 3: Optimization (Contextual Intelligence) Now it gets interesting. Location-aware alerts, behavior-based timing, environmental context. AI starts prioritizing what matters most. Personalization based on actual usage patterns. ➞ Phase 4: Innovation (Self-Optimizing Systems) The pinnacle. Predictive alerts that prevent issues before they happen. Cross-device intelligence, edge-powered decisions, ML-driven delivery optimization. The system learns and adapts without human intervention. The mistake I see repeatedly? Teams trying to jump straight to Phase 4. Your notification system should mirror your product maturity. Start with reliable basics, then layer on intelligence as you understand your users better. The best IoT notification systems don't feel smart - they feel invisible. Users get exactly what they need, exactly when they need it, without thinking about it. What phase is your notification system in? Are you building on solid foundations or trying to skip ahead? ♻️ Repost if you believe great UX starts with simple, reliable notifications ➕ Follow me, Nick Tudor, for more practical insights on building intelligent IoT systems

One DM made me write this post immediately. I haven't posted in 3-4 days. Then Aananddika Sood's message landed in my inbox. Subject: "Spotted Something You Might Want to Update" "Arre yaar, itna personal touch ki AI ka baap bhi nahi kar sakta." What she did: ↳ Actually read my About section. ↳ Noticed it still said 2024 (we're in 2025). ↳ Pointed it out genuinely and then pitched her services. What most people do: → Copy-paste templates. → Generic compliments. → Obvious sales pitches. Basically: Zero personalization. The difference? Her DM felt like a friend pointing out something I missed. Not a stranger trying to sell me something. This is what I call the "Value First" approach: Give before you get. Help before you pitch. Care before you close. I always tell people: Study the DMs that work on you. Analyze what made you respond. Reverse engineer the psychology. Yesterday, Jatin (my energetic buddy), put as a part on the list of his exclusive 50 Founders whom people should follow. What happened due to that? I was taken by surprise. The reciprocation effect took over. The next time he asks me anything, I am more likely to say "Yes". Coming back, Aananddika's message worked because: ↳ She invested time in understanding my profile ↳ She solved a problem I didn't know I had ↳ Her pitch felt like a natural extension AI can generate thousands of messages. It can't replicate human observation. It can't build a real connection. It can't create genuine care. The best DMs don't feel like DMs. They feel like conversations. They feel like real help. They feel like care. What's the result? → Free publicity for doing outreach right. → I'm writing this post about her approach. → That's the power of personalized messaging. What's the best cold DM you've ever received? P.S. Yes, I updated my About section. Sometimes it takes a stranger to spot what you've been missing.

Personalizing AI Recommendations: A Leap Forward in User Experience ... The research, titled "Reinforced Prompt Personalization for Recommendation with Large Language Models," introduces a novel approach to tailoring AI recommendations for individual users. 👉 The Challenge of Personalization We've all experienced the frustration of staring at a blank search box, trying to articulate our needs to an AI system. Whether searching for a product, movie, or content, it's often difficult to convey our unique preferences and context. Current AI systems typically use a one-size-fits-all approach, which can lead to generic or irrelevant recommendations. 👉 Introducing Instance-wise Prompting The researchers propose a shift from task-wise prompting (using the same prompt template for all users) to instance-wise prompting. This means personalizing the AI's input for each individual user, allowing for more nuanced and accurate recommendations. 👉 The RPP Framework: Tailoring AI Interactions At the heart of this innovation is the Reinforced Prompt Personalization (RPP) framework. Here's how it works: 1. Multi-agent reinforcement learning optimizes prompts for each user 2. Four key prompt patterns are personalized:   - Role-playing: Adapting the AI's persona to match user preferences   - History records: Utilizing relevant past interactions   - Reasoning guidance: Customizing the AI's analytical approach   - Output format: Tailoring how recommendations are presented  👉 Efficiency and Quality Improvements The RPP framework brings two significant advancements: - Sentence-level optimization: Instead of tweaking individual words, the system works at the sentence level, dramatically improving efficiency. - Carefully crafted action spaces: This ensures high-quality prompts while keeping computational demands manageable. 👉 Versatility Across AI Models One of the most promising aspects of this research is its broad applicability. The RPP framework has shown effectiveness across various types of large language models: - Open-source models (e.g., LLaMa2) - API-based models (e.g., ChatGPT) - Fine-tuned models (e.g., Alpaca) 👉 Real-World Impact The potential applications of this technology are vast: - E-commerce: More accurate product recommendations based on individual shopping patterns and preferences - Content streaming: Personalized movie, music, and video suggestions that truly reflect a user's taste - Digital marketing: Tailored ad experiences that resonate with each consumer's interests and needs 👉 Breaking the One-Size-Fits-All Barrier The researchers demonstrate that RPP significantly outperforms traditional recommender systems, few-shot methods, and other prompt-based approaches. By moving beyond generic prompts, AI systems can now provide recommendations that feel truly personalized. The paper in comments.

I've watched 7 outbound teams go from <2% to +5% reply rates in under 60 days. All of them made the same shift: Static lists to signal-triggered outreach, heavy on tiering. The old way: → Generic "I noticed you're hiring" openers → Zero context on timing or need → 1-2% reply rates if you're lucky → Spray and pray to static lists The new way: → Signal-triggered outreach → 5-8% reply rates consistently → Hyper-relevant context in every message → Perfect timing based on actual buyer behavior So what signals actually move the needle? The ones we've seen work consistently: → Leadership changes (new VP Sales = new priorities) → Social engagement (commented on relevant content) → Funding announcements (budget just opened up) → Job postings (they're hiring for a role you solve for) → Tech stack changes (competitor install/uninstall) Although, the best signals are *always* gonna be hyper-relevant and custom to YOUR offer, eg. for Midnight Labs we've been monitoring dark web activity, amongst many other niche platforms for 'enterprise evidence'. But signals aren't just about personalization - they're about prioritization. Not every account showing intent deserves the same motion. 𝐓𝐢𝐞𝐫 1 - 𝐇𝐢𝐠𝐡 𝐢𝐧𝐭𝐞𝐧𝐭 + 𝐡𝐢𝐠𝐡 𝐟𝐢𝐭: Multiple signals firing. These get the full omni-channel treatment: cold call, personalized email, LinkedIn touchpoints, maybe even direct mail. You're investing real time here. 𝐓𝐢𝐞𝐫 2 - 𝐌𝐞𝐝𝐢𝐮𝐦 𝐢𝐧𝐭𝐞𝐧𝐭 𝐨𝐫 𝐟𝐢𝐭: One or two signals. Personalized sequences, but more automated. Still relevant context, just not the white-glove approach. 𝐓𝐢𝐞𝐫 3 - 𝐋𝐨𝐰 𝐢𝐧𝐭𝐞𝐧𝐭, 𝐛𝐫𝐨𝐚𝐝 𝐟𝐢𝐭: Part of your TAM, but no active signals yet. Nurture at scale. Keep them warm until they light up, or run a more generic sequence. The magic happens when you combine tools like Clay with this tiered framework. Example workflow: • Trigify.io catches a prospect engaging with competitor content • Clay enriches their company data and scores them by fit + signal strength • High-tier accounts get routed to your AEs for multi-channel outreach • Lower tiers flow into automated sequences with relevant personalization • Everything goes out within 24 hours of the signal • Same ICP. Different treatment based on actual buyer behavior. We built this exact system for a tech (SaaS, specifically) client last quarter. Before: 1.8% reply rate, generic messaging, one-size-fits-all After: 6.2% reply rate, signal-based tiering, right effort on right accounts We've compiled 150+ sales signals into a library - categorized by strength, funnel stage, and trigger type. Each one includes when to use it, how to action it, and which data sources to pull from. Comment "Signals" and I'll send it over when it's live.

Your outbound sequence is costing you replies. Here’s how we fixed ours. A few months ago, we ran outbound sequences targeting clients in a niche segment. We had: ✅ A solid contact list. ✅ A well-crafted email sequence. ✅ A good offer. And yet… silence. Open rates were decent. Clicks were happening. But actual conversations? Barely any. We dug into the data and found a pattern: we were treating every prospect the same, no matter how they engaged. Someone could: 🔹 Click a link to read our case study - but get the same generic follow-up as someone who never opened the email. 🔹Open three emails in a row - but never hear from a rep. 🔹Visit the pricing page - but get an email two days later instead of a timely outreach. Mistake? Relying too much on static, pre-set sequences, assuming people would eventually respond. But buying behavior is not linear anymore. We built an AI-driven workflow that adapted in real time based on prospect activity. Here’s how it worked: 📌 If a prospect clicked a link but didn’t reply → Instead of another generic email, we sent a follow-up referencing that exact content and expanding on it. 📌 If someone opened multiple emails but never clicked anything → We tested a short, casual email with a direct question—no fluff, just a conversation starter. (Example: “Hey [First Name], I noticed you’ve been checking out [Topic]. Is this something you’re working on right now?”) 📌 If they visited the pricing page → A Slack notification went to the SDR in real time, triggering a personalized email or LinkedIn message within 30 minutes, before they bounced. 📌 If someone engaged but didn’t respond after 5 touches → We paused email and switched to a LinkedIn or call, instead of spamming their inbox. Results? ✅ Better replies. ✅ Quality conversations with the right people. ✅ Fewer wasted follow-ups on cold prospects. Outbound is as much about timing, context, and relevance as it is about volume. Remember, buyers don’t follow your steps, they follow their own journey. #outbound #salestips #b2b

Using "Hey {first name}" in your marketing emails and calling it personalization is like picking up a rock and calling it a hammer. Technically, it works. But we have better tools now, and failing to take advantage of them is going to leave you choking on the dust of your competitors. Here's how to catch up with the times and use TRUE personalization to boost engagement, loyalty, and conversions: 1. Use dynamic content fields to customize emails based on customer attributes, behaviors, and preferences. Go beyond just {first name} – incorporate product views, past purchases, and customer lifecycle stage. Don't be creepy! Be conversational. You want the reader to feel like you understand their needs, not like you've been peeking through their blinds. 2. Set up behavior-triggered automations like browse abandonment and cart recovery flows. Make these highly relevant by including viewed products, social proof, and timely offers. Marketing is all about getting the right offer in front of the right person at the right time, and behavior-based emails are one of the best ways to do that on a consistent basis. 3. Implement Recency, Frequency, and Monetary Value (RFM) segmentation to deliver personalized messaging to different customer groups. Target VIPs, at-risk customers, and prospectives customers with specific messages to convert or retain them. 4. Create personalized journeys that adjust the user's experience based on customer data or actions. For example, if you're sending the exact same post purchase sequence to a repeat purchaser as you are for a first-time buyer, you're missing a huge opportunity. 5. Use replenishment flows for consumable products, reminding customers when it's time to reorder. Or, capture email addresses on PDPs for sold out products and notify them when the item in back in stock. Easy sales. Be careful to avoid these common personalization mistakes: 🙅🏼 Over-personalizing in a way that feels intrusive or creepy 🙅🏼 Sending irrelevant recommendations due to inaccurate or outdated data 🙅🏼 Over-segmenting to the point where segments are too small to be effective 🙅🏼 Using templated, robotic language that sounds unnatural The key is finding the right balance ––  personalized enough to be relevant and engaging, but not so specific that it becomes cringey or off-putting. When done well, personalization makes customers feel heard, understood and valued. This builds loyalty, increases engagement, and ultimately drives more conversions and revenue. Level up your personalization with one (or more!) of these strategies, and your KPIs are going to shoot up and to the right.

Ever wonder why your outreach feels like shouting into a void? Generic emails move, but they rarely arrive anywhere. Personalization, on the other hand, is the express route that lands straight on your buyer’s desk. As a founder at Almoh Media, I see this daily. First, inbox rules are stricter than ever. Google and Yahoo’s policies mean bulk, impersonal blasts are flagged quickly, while messages with human context reach further. Next, think about your audience. Decision-makers receive dozens of pitches every single day. What makes them pause is not a clever subject line alone, but a message that speaks directly to their role, current challenges, or even something they recently shared online. When outreach feels like a mirror of their world, it gets read. So, start with the basics. Use the correct name and company details to show attention to detail. Then go deeper. Reference their recent initiatives, align your solution to what matters in their market, and even match their tone. Small touches like these turn outreach into connection. Finally, timing is critical. More than half of the responses come within six hours, and nearly ninety percent within two days. So give your message breathing room before following up. For agencies and aggregators, personalization is not just a trick. It is the handshake that moves your email from clutter to conversation. Let’s stop sending noise and start creating dialogues that open doors. How do you personalize your outreach today?  Share your approach, I’d love to exchange ideas. #PersonalizedOutreach #FounderPlaybook #DigitalPR #InboxThatWins #Tausiftalks

8/10 DTC brands I audit have NO clue how to use SMS to generate revenue. Here are 7 things we do to make millions/mo with it: (BOOKMARK THIS) (1) How to Get Opt-Ins Without Being Pushy:   - Checkout Opt-In - Exit Intent Popup - Post-Purchase Flip - Email-to-SMS Bridge ---- (2) SMS Flows Welcome Series (3 texts): - Welcome + intro offer (15% off, valid 7 days)  - "How's your experience with [brand]?" + bestsellers - Urgency reminder (24 hours left on discount) Andoned Cart (2-3 texts): - "You left something behind" + cart link - "Still thinking? Here's 10% off to help." - "Last chance—cart expires in 6 hour.s" Post-Purchase (3 texts): - Order confirmation + tracking - "How to get the most out of [product]" - Cross-sell based on their purchase ---- (3) Content strategy: Value Content (send daily): - Restock notifications - Behind-the-scenes - Product care tips - Customer spotlights Campaign Content (2-3x per week): - New product launches - Flash sales - VIP early access - Limited-time offers ---- (4) Personalization : Generic "Hey [name], here's 20% off" kills loyalty. 4 ways to use personalization: - Purchase-based: "Hey Sarah, your usual [product] is 20% off today." - Behavior-based: "Noticed you browsing our new collection. Here's early access." - Lifecycle-based: "Happy 1-year anniversary as a customer! Here's 10% off." - Geographic: "You're in Chicago. We have local pickup available." ---- (5) Build Two-Way Conversations: Most brands fear replies. But replies are just engagement and feedback that promote relationship building. So you should encourage it: - Ask questions: "What's your biggest skincare challenge?" - Use for support: "Issue with your order? Reply here" - Create polls: "Reply A for [option] or B for [option]" - Actually respond when people text back ---- (6) The Metrics Metrics to track: - Opt-in rate: 10-15% is good - Conversion rate: How many buy after getting SMS - Churn rate: How many unsubscribe - Revenue per subscriber ---- (7) Advanced Tactics - SMS-Exclusive Products: Make subscribers feel special with products they can't get anywhere else - Birthday/Anniversary Campaigns - Pre-Cart Abandonment: If someone viewed a product but didn't add it to the cart, text them. - Cross-Channel Coordination: Let email and SMS work together. ---- Things to avoid: - Treating SMS like email - Bad deliverability setup - Discount addiction - Ignoring replies - No list growth TL;DR SMS is the most personal way to build loyalty with customers who actually want to hear from you. Done right: 40-60% higher LTV than email-only customers.