Personalization Strategy Development

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Over-personalizing in a way that feels intrusive or creepy 🙅🏼 Sending irrelevant recommendations due to inaccurate or outdated data 🙅🏼 Over-segmenting to the point where segments are too small to be effective 🙅🏼 Using templated, robotic language that sounds unnatural The key is finding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.

Attention is easy. Relevance is hard. Our email metrics are teaching us this lesson right now. We're seeing close to 50% open rates on our cold email sequences. This is across multiple campaigns. People are opening multiple times. Scrolling through. Coming back to it. But our response rate is sitting at 1-2%. At first glance, that open rate feels like a win. It's not. High opens with low responses just means you got their attention—but you didn't earn their time. The gap between interest and action is specificity. People are curious enough to open. They might even be intrigued enough to read it twice. But if your message is vague about what you actually do, or how it solves their specific problem, they're not going to respond. Curiosity isn't enough to get someone to take a meeting. We're in the business of helping companies build and expand products through augmented engineering teams. But "we help you build your product" is too generic. What they actually need to know is: What roles are you helping us fill? How fast can we scale? What's the quality bar? Can we test this before committing? The specificity matters. Not just in copy, but in understanding what problem they're trying to solve right now. Are they expanding a team? Replacing someone who left? Building a new function? If we don't know that, our message, no matter how well-written, lands flat. So we're doubling down on personalization based on actual signals. Understanding what roles they're hiring for. Matching our capabilities to their needs. Leading with social proof that's relevant to their situation. And making it dead simple to try our service with zero commitment. The lesson: getting someone to open your email is easy. Getting them to care enough to respond requires you to actually understand what they need, and proof you can deliver it. Attention is cheap. Relevance is what converts.

After months of collaboration with some of the smartest people in advertising, I'm excited to share the IAB AI Personalization Playbook, a practical guide for scaling AI-powered creative personalization. 👉 Here's the thing: many organizations are running pilots. Few are actually scaling those pilots to full enterprise personalization. This playbook is our answer to that gap, a practical, cross-functional guide for moving beyond experiments to repeatable, responsible AI-powered personalization. It's built around three core principles: 1️⃣ Human-centered AI – Because humans still need to be in the driver's seat 2️⃣ Cross-functional integration – Marketing, creative, ops, legal, and data all need to be at the table internally and externally, media and creative teams need to be tightly orchestrated 3️⃣ Risk-tiered governance – Not all content needs the same level of oversight We worked with platforms, brands, agencies, and publishers to build something that's practical and usable, versus simply aspirational. The framework covers everything from strategic briefing to scaled production to measuring what matters. It's designed to help companies figure out where AI fits in your workflow, how to maintain brand integrity at scale, and what good governance actually looks like in practice. Huge thanks to everyone who contributed feedback, challenged assumptions, and helped make this better than any one organization could have built alone. Specifically, Adam Buhler, Executive Vice President, Creative Technology Digitas North America, Adwait Walimbe, Digital Transformation Advisor Adobe, Brian Hull, Head, Global Creative Labs The Weather Company, Graham Wilkinson, EVP, Chief Innovation Officer, and Global Head of AI Acxiom, Kelly O'Brien, Senior Product Manager, NPR, Paul Longo, General Manager, AI in Ads Microsoft, Todd Hassenfelt, EGlobal Digital Commerce Sr. Director, Strategy & Execution Colgate-Palmolive and all the internal teams at IAB. ⭐️ 👉 IAB AI Personalization Playbook: https://lnkd.in/dDqU7p3G #ai #personalization #creative #roi

Personalization is not just about using a prospect's name. To provide a truly personalized experience, you should learn your prospect's language, communication style, and what's important to them right now. Sound complicated? It's really not. Everyone utilizes social media. Learning about your prospects has never been easier. The vast majority of decision-makers, executives, and C-suite members use some form of social media every day. They actively absorb content, watch trends, learn new skills, and find areas of opportunity. You can start right here on LinkedIn. Look at their profile and see what they're posting, commenting on, and liking. Is there a common thread to their messages? Maybe they like data, facts, and figures. They could discuss their vision, the future of their industry, and current concerns. Do they post content or write a blog? Read it. It's the best way to meet them. This is their language. Communicate with them the way they communicate with others. Note the topics they discuss or engage with; these are your lead-ins to having a conversation with them. Join groups related to their industry, learn the hot topics and their jargon and acronyms. Your research should extend beyond the person, the company, and their current role. It's about tailoring your message to them and engaging them like a coworker or trusted partner.

Everyone's been sold the same lie: “Spend more time personalizing to get better results.” Here’s what actually happens: Your SDRs waste 5 min per prospect digging through LinkedIn, find nothing useful for 90% of them, and end up defaulting back to generic templates. Personalization is a 1:1 game. You can’t scale it. Relevance is different. Relevance multiplies. One account insight → 10 conversations One company challenge → Every stakeholder One initiative → Entire buying committee The best SDR teams have already made this shift. They’re booking more meetings with less research time. Stop personalizing for people. Start building relevance for accounts using an Account-Based System. What’s an Account System in outbound? Start with company-level insights first, then apply them to the prospects inside the account: Adapt to Above the Line and Below the Line prospects. If your product touches multiple teams, you go both horizontal and vertical inside the account, a multithreaded approach, not just single-thread. With this, it’s faster to spot real initiatives or challenges for each account, then build a strong POV (point of view) around how you can help. That makes your outbound relevant at scale. Example strategy: Identify company strategic initiatives/pain points in under 10 minutes → create a strong POV → reuse insights across multiple prospects in the same account. Here are different approach examples CEO interviewed on a podcast → use it to reach their direct reports. CRO just got hired → leverage with the CEO and front-line sales managers. Bottom-up: talk to end-users about current challenges/tools → use that with front-line managers → Economic buyer. VP of CS just hired 2 CSMs → name-drop. Ask for referrals inside the account. With that, you’ve got (almost) infinite ways to outbound an account. Because if the prospects you’re chasing aren’t active on LinkedIn, you’re just wasting time. And in 2025, with tools like n8n, Clay or AI-driven solutions make this faster and scalable, even if your prospect accounts aren’t active on LinkedIn. "But Elric, does this work in SMB and Mid-Market?” Yes. It works there too Example: Owner sells to single-location restaurants; they only have one contact for most accounts. They adapt the talk track by segment: Restaurant has: A website + uses Uber Eats/DoorDash → focus on the pain of 3rd-party apps (30% revenue cut, no customer data). A website + no delivery → educating them about missed revenue opportunities. They personalize for business maturity, not the owner. -- Follow me 👨🍳 Elric Legloire for daily outbound recipes.

🚀 The Era of One-Size-Fits-All Events Is Over. Stop Doing It. Personalization isn't a single action, it's a series of intentional, strategic choices that come together to make every attendee feel genuinely valued. We’re not just organizing events anymore — we’re crafting journeys. 🧭 In today’s marketplace, attendees expect more than just a badge and a schedule. They want curated content, meaningful connections, and real-time relevance that makes them feel seen. That’s where hyper-personalization comes in. And no, it’s not just using someone’s name in an email. It’s about using data and technology to design experiences that feel custom-built for each person. 🧠📊 As an event marketer, I’m all in on data-driven strategy. This is where we move beyond logistics and design every touchpoint to be personal, memorable, and valuable. Here's some ways that can look like across the attendee journey: Before the Event: 🎯 Targeted Invitations & Content: Use behavioral data to send invites that speak directly to someone's interests. A marketer might get a blog post on campaign strategy, while a developer receives a product case study. 📝 Dynamic Registration: Ask tailored questions based on the attendee’s role or industry to build rich attendee profiles from the start. During the Event: 🤖 AI-Powered Agendas & Recommendations: Event apps can recommend sessions, speakers, and exhibitors based on real-time behavior, interests, and profiles — reducing decision fatigue and maximizing impact. 🤝 Smart Networking: Go beyond job titles. Use AI to match attendees with shared goals, values, or expertise for deeper, more meaningful conversations. 🎉 Personalized On-Site Experiences: Greet attendees by name on welcome screens, print session tracks on badges, or use RFID to tailor in-person interactions. 📽️ Customized Content Delivery: Make booth visits unforgettable. When someone scans their badge, show a video personalized to their company, role, or industry — turning a quick interaction into a memorable moment. 🧢 Personalized Swag: Skip the generic t-shirt. Offer attendees the ability to choose colors, styles, or even print their name on a water bottle or notebook. After the Event 📬 Tailored Follow-Up: Instead of a generic “thanks for coming,” send curated content based on sessions they attended, people they connected with, and their unique interests. 📚 Personalized Content Hubs: Create a portal where attendees can revisit the event — with homepages tailored to their track, interests, or role. 📊 Custom Surveys: Don’t ask vague questions. Personalize post-event feedback forms to reflect their specific journey. 🤔 What's one thing you're doing to add a touch of personalization to your events? Or, as an attendee, what's a personalization strategy that has truly impressed you? Let's share some ideas in the comments! #EventProfs #EventMarketing #HyperPersonalization #EventTech #ExperienceDesign #EventStrategy #PersonalizedExperiences

Build something yourself and you'll value it far more than anyone else does... Harvard students folded origami cranes following simple instructions. Researchers asked how much they'd pay for their own creations. Answer: $0.23 per crane. Then researchers showed those same amateur cranes to different people who hadn't built them. How much would they pay? About $0.05. When those non-builders looked at expert-made cranes, they valued them at $0.23. The students saw their amateur work as equal to expert craftsmanship. Everyone else saw reality clearly. In 2011, Michael Norton, Daniel Mochon, and Dan Ariely at Harvard documented what they called the IKEA Effect. They ran experiments where people assembled IKEA storage boxes, folded origami, and built LEGO sets. Then measured how much builders would pay for their own creations versus non-builders. The pattern held across all experiments. People who assembled IKEA boxes themselves were willing to pay 63% more than people evaluating identical pre-assembled boxes. Builders consistently overvalued their own work and expected others to share their inflated opinions. The mechanism is effort. When you invest labor into creating something, even just following instructions, you develop emotional attachment that dramatically increases perceived value. This has direct implications for product strategy. Nike By You lets customers customize shoe colors and materials. Neuromarketing research shows customers viewing their own customized sneakers exhibit significantly stronger positive emotional responses than standard options. That emotion correlates directly with purchase behavior and premium pricing. Build-a-Bear Workshop charges premium prices for children to assemble their own stuffed animals. M&M's personalization commands multiples of standard pricing. Bain & Company research found customers who customized products online showed higher brand engagement and increased repeat purchases. Dell pioneered build-your-own PC configuration. LEGO Ideas invites customers to submit product concepts. Even modest customization drives the effect. Betty Crocker discovered this in the 1950s when instant cake mixes failed because homemakers found them too easy. The solution? Require adding an egg. That small effort greatly increased baker perceived value. The strategic principle is straightforward. Give customers meaningful input into product creation, even if modest. Monogramming, feature selection, assembly, customization tools. Ensure they can successfully complete their contribution. The emotional attachment and willingness to pay premium prices or repeat purchase follow automatically. Often companies consider some of these ancillary configuration options as extraneous (e.g. minor customization does not change actual product performance or core attributes) but underestimate the emotional attachment and value it can create. When customers build it, they value it highly, even when nobody else does. Cheers!

Marketers claim they want to scale personalization. Most still use the same old playbook. This approach misses key signals. The problem is clear. Most account prioritization models ignore crucial signals that indicate buying intent. These signals come from real-time engagement across digital channels, such as social media interactions, product usage data, and sales touchpoints, where prospects are actively making decisions. A CMO asking for vendor suggestions on a private Slack thread? That’s a high-intent signal. A RevOps leader debating solutions on LinkedIn? That’s critical buying behavior. Traditional CRMs miss these signals, but AI-powered tools like RoomieAI Capture are designed to catch and prioritize these conversations in real time. A champion explaining how they got buy-in for your product? That won’t trigger an MQL. This is why marketers miss high-intent signals. This is why they struggle to scale personalized outreach. A shift is happening. AI is making account research and personalization scalable. But it’s not what most people think. Forward-thinking teams are doing this: ✅  Mining signals from non-traditional sources like social media, job boards, and internal communications to identify in-market accounts before they visit your website. By using AI to uncover buying intent across the web and social platforms, they can reach high-intent prospects earlier in the sales cycle. ✅ Prioritizing accounts based on real engagement. They focus on prospects already in a buying motion, not just random website visitors. ✅ Using AI-generated insights for messaging. They create messages that resonate instead of sending generic sequences and hoping for a response. Here’s how to apply this today: 1️⃣ Audit where your best leads come from. Are they finding you through communities, referrals, or social conversations? If so, your data model is missing key signals. 2️⃣ Stop treating ‘MQLs’ as the only sign of readiness. Shift to engagement-based prioritization. Combine web intent with real conversations. 3️⃣ Experiment with AI-powered research to enrich your outreach. Use AI to gather insights, but keep your messaging human. Making this work at scale used to mean manual research and guesswork. Now, platforms like Common Room make it easier. They automatically surface high-intent signals across social media, web interactions, and internal data to help sales teams prioritize the right accounts and craft messaging that resonates at the right time. Personalization at scale isn’t about more manual research. It’s about building a smarter system. This system automates research while keeping outreach relevant. Think about AI’s role in your GTM strategy next year.

Real-time personalization is killing your conversion rates. Everyone's obsessing over "hyper-personalized experiences." Dynamic content. AI recommendations. Real-time everything. But they're making a fatal mistake: They're optimizing for relevance while destroying speed. And speed ALWAYS wins. After auditing 300+ high-traffic sites, here's what I discovered... 🔍 The Personalization Paradox The Promise: 20-30% engagement lifts through real-time customization The Reality: Every second of load delay = 32% bounce rate increase Most sites are trading 15% conversion gains for 40% traffic losses. That's not optimization. That's self-sabotage. Here's the systematic approach that actually works... 🔍 The Zero-Latency Personalization Framework Layer 1: Predictive Preloading Stop reacting. Start predicting. → Chrome's Speculation Rules API: Prerenders likely pages → AI Navigation Prediction: 85% load time reduction → User Journey Mapping: Anticipate next actions Example: Amazon preloads product pages based on cart behavior. Result: Sub-second "personalized" experiences that feel instant. Layer 2: Edge-Side Intelligence Move computation closer to users: → CDN-Level Personalization at edge nodes → Sub-100ms response times globally The Math: Traditional: Server → Processing → Response (800ms) Edge-Optimized: Cache → Instant Delivery (50ms) Layer 3: Asynchronous Architecture Never block the main thread: Base page renders (0.8s) Personalization layers load (background) Content updates seamlessly User never sees delay 🔍 The Fatal Implementation Errors Error 1: JavaScript-Heavy Personalization Loading 500KB of scripts for 50KB of custom content. Error 2: Synchronous API Calls Blocking page render for recommendation queries. Error 3: Over-Personalization Customizing elements that don't impact conversion. Error 4: Ignoring Core Web Vitals Optimizing engagement while destroying SEO rankings. The Fix: Performance-first personalization architecture. 🔍 My Advanced Optimization Stack Data Layer: → IndexedDB for instant preference retrieval → Server-Sent Events for real-time updates → Intersection Observer for lazy personalization Delivery Layer: → Feature flags for gradual rollouts → Minified, bundled assets → Progressive image loading Results Across Portfolio: → Sub-2-second loads maintained → 25% retention improvements → 20% revenue lifts → 40% better SEO performance Because here's what most miss: Personalization without speed optimization isn't user experience. It's user punishment. The companies winning in 2025? They've cracked the code on invisible personalization. Users get exactly what they want, exactly when they want it. And they never realize the system is working. === 👉 What's your biggest challenge: delivering relevant content fast enough, or measuring the true impact of personalization on business metrics? ♻️ Kindly repost to share with your network

Its no longer about Email Personalization, you need Contextual intelligence. When your outreach references real challenges at the right moment, you’re not just getting attention. You’re sparking conversations that matter. And those conversations can turn into real pipeline. So, what’s the difference? Personalization is what you see—job titles, company size, recent posts. Contextual intelligence is understanding what’s happening in your prospect’s world right now—market shifts, company triggers, strategic hurdles. The problem with surface-level personalization? It can come off as fake. It’s often disconnected from what actually drives business value. Here’s what true contextual intelligence sounds like: "Donna, with ABC’s 40% growth quarter, I imagine managing the complexity that comes with scaling is top of mind. How are you handling the increased demand for pipeline visibility?" Why does this work? Because prospects feel safe when they don’t feel “sold to” or manipulated. They feel understood. Contextual intelligence creates that safety—by addressing real business challenges. What outreach approach are you leaning into right now?