Customized Messaging Solutions

What if your in-app messaging could adapt to user behavior instantly? Traditional campaigns often require endless templates and manual setup. But now you can deliver real-time, hyper-personalized offers in just a fraction of the time. It’s all about speed, context, and relevance. How this looks in play could be something like: A fitness app that notices you typically log your runs early in the morning. Instead of showing you a one-size-fits-all campaign, a personalized message can instantly serve up a Morning Motivation—with a CTA deep-linked to a custom meal plan or workout routine tailored to your preferences. No separate campaign needed. No extra dev time. This essentially helps with 2 core things: First. Reduced time-to-market: with AI creating and delivering messages at scale, you cut out lengthy development cycles. Secondly, enhanced personalization. Every message, offer, or promotion is tailored to each individual, driving higher engagement and conversions. Multiple consumer brands are now using personalized messaging engines to automatically generate and deliver offers on the fly. Instead of creating dozens of templated campaigns, product & marketing teams can rely on AI to craft dynamic, user-specific messages that reflect each user’s real-time actions, preferences, or history.

Most AI outbound solutions pull from third-party data, grabs job titles, and plugs in generic insights like "I see you're hiring..." or "I noticed your company is scaling..." But is that even helpful? The messaging sounds automated because it is. Sellers send it, buyers ignore it, and everyone moves on. Instead of scraping surface-level data, Actively AI plugs directly into a company’s first-party data—every call, email, CRM note, and prior engagement—to first identify the best accounts/contacts to engage, but then to also generate hyper-personalized outreach that lands. Take Ironclad, for example, a CMS product we support. When sellers from the Ironclad team use our application, Actively taps into years of conversations across legal, procurement, IT, and sales, and learns from that data. It’s then optimized for revenue—identifying who to contact, when to contact them, and why. The final step of automating custom messaging sounds like this: "Hi Michelle, last fall, George Smith mentioned challenges in IT, particularly around accelerating the security process within your organization. Given that you’re hiring now and have previously expressed interest in TPRM solutions, I’d love to reconnect for 10-15 minutes later this week to show you how companies like Plaid and Cisco are leveraging our solutions." More relevance = higher reply rates = more meetings = higher win rates. 

𝗧𝗼𝗼 𝗺𝗮𝗻𝘆 𝗯𝗿𝗮𝗻𝗱𝘀 𝘁𝗿𝗲𝗮𝘁 𝗪𝗵𝗮𝘁𝘀𝗔𝗽𝗽 𝗹𝗶𝗸𝗲 𝗦𝗠𝗦. 𝗜𝘁’𝘀 𝗻𝗼𝘁. That's a criminal misuse of WhatsApp that’s quietly killing retention for both D2C and B2B brands. Brands get access to the WhatsApp API, upload a list, and hit “Send to All.” It feels efficient. But it creates what we call the broadcast trap, a pattern that burns through customer trust fast. 𝗪𝗵𝘆 𝗶𝘁 𝗗𝗼𝗲𝘀𝗻’𝘁 𝗪𝗼𝗿𝗸: Without enough personalization, messages feel generic and irrelevant. Customers start ignoring future messages after 1–2 interactions. Engagement and repeat purchase rates drop significantly. We’ve seen this across hundreds of brands before they changed their strategy to: → 𝗖𝗼𝗻𝘁𝗲𝘅𝘁𝘂𝗮𝗹 𝘁𝗮𝗿𝗴𝗲𝘁𝗶𝗻𝗴: Messages are sent based on user actions, such as abandoned carts, product views, or purchase inactivity. → 𝗦𝗲𝗴𝗺𝗲𝗻𝘁-𝘀𝗽𝗲𝗰𝗶𝗳𝗶𝗰 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻: Returning customers, first-timers, and high-LTV buyers each get a different experience. → 𝗧𝗶𝗺𝗲𝗹𝘆 𝘁𝗿𝗶𝗴𝗴𝗲𝗿𝘀: Instead of one big push, messages are sent at the right moment — like 2 hours after a missed checkout, or 1 day before an offer expires. → 𝗣𝗿𝗼𝗴𝗿𝗲𝘀𝘀𝗶𝘃𝗲 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻𝘀: Each interaction builds on the last instead of restarting from scratch → 𝗖𝗹𝗲𝗮𝗿 𝗼𝗽𝘁-𝗶𝗻𝘀 𝗮𝗻𝗱 𝗽𝗮𝗰𝗶𝗻𝗴: Customers feel in control, not spammed. → 𝟮 -𝘄𝗮𝘆 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻𝘀: Hooking each message with contextual chatbots that continue the conversation. 1-way announcements don’t work, 2-way chats do. Here’s what changes when the 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻 𝗯𝗲𝗰𝗼𝗺𝗲𝘀 𝘁𝗵𝗲 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆: Higher conversion rates Better repeat purchase rates Dramatically fewer unsubscribes and spam reports That’s the power of doing WhatsApp 𝘳𝘪𝘨𝘩𝘵. And for those wondering how brands manage this kind of personalization at scale? They use tools that make it effortless (we built one we’re pretty proud of 😉).

𝐀𝐫𝐞 𝐲𝐨𝐮 𝐬𝐮𝐫𝐞 𝐲𝐨𝐮𝐫 𝐦𝐞𝐬𝐬𝐚𝐠𝐢𝐧𝐠 𝐢𝐬 𝐫𝐞𝐬𝐨𝐧𝐚𝐭𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐭𝐨𝐝𝐚𝐲’𝐬 𝐁𝟐𝐁 𝐛𝐮𝐲𝐞𝐫𝐬?   NEW RESEARCH published today highlights how emerging B2B message testing software and services enable organizations to boost buyer engagement and conversion by validating #messaging *before* investing into costly content and campaigns.   I'm pleased to author Gartner's first 𝐌𝐚𝐫𝐤𝐞𝐭 𝐆𝐮𝐢𝐝𝐞 𝐟𝐨𝐫 𝐁𝟐𝐁 𝐌𝐞𝐬𝐬𝐚𝐠𝐞 𝐓𝐞𝐬𝐭𝐢𝐧𝐠 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬. Discover the differences between self-serve software and service-based delivery models, understand key capabilities for effective message testing, and see how AI is rapidly evolving capabilities from data analysis to intelligent customer simulation. This guide includes 𝟏𝟎 𝐫𝐞𝐩𝐫𝐞𝐬𝐞𝐧𝐭𝐚𝐭𝐢𝐯𝐞 𝐯𝐞𝐧𝐝𝐨𝐫𝐬 and offers actionable recommendations for evaluating solutions and embedding #messagetesting into your marketing workflows.   🔗 #Gartner clients can access the market guide here: https://lnkd.in/e3RJfJcE   🔗 Not a client? Explore sample Gartner resources: https://lnkd.in/g75YKcvQ   Special thanks to my co-authors, Jess Walker and David Yockelson, for their invaluable contributions!   #B2BMarketing #ProductMarketing #DemandGeneration #GTM #MarketResearch

I built a Clay workflow that automated 100% of manual prospecting AND turned raw account data into hyper-personalized messages with specific buying signals. Watch the video to see it in action. Here's how it works: 1. FINDING THE RIGHT ACCOUNTS We pull tech companies from Apollo, Crunchbase, and Clay's native company finder. Then Claygent visits each company's website to verify if they're actually B2B SaaS. Once confirmed, Claygent enriches them with funding data, job postings, headcount growth, and restructuring news. We even scrape Glassdoor reviews to analyze employee sentiment for potential pain points. 2. IDENTIFYING DECISION MAKERS We find prospects with validated work emails and mobile numbers using Clay's waterfall enrichments. Then, we use SureConnect to check if their phone numbers are likely to result in a pickup, saving hours of wasted calling time. We then analyze their LinkedIn activity to find posts relevant to our solution for personalized outreach angles. This gives us data points that normally take hours to research manually. 3. SEGMENTING BY SENIORITY LEVEL We split prospects into three segments: - C-suite - VP/Director - Manager level Each level gets completely different messaging because their priorities and pain points differ. C-level gets strategic messaging while managers get tactical messaging. This segmentation significantly improves response rates compared to one-size-fits-all messaging. 4. CREATING PERSONALIZED MESSAGES All account and prospect data are fed into multiple Claude prompts, which write custom messages for each prospect. These messages look better than what most could write manually, as all relevant data points are fed to finely tuned Claude prompts. We create both email copies and LinkedIn messages formatted for each channel. 5. AUTOMATING THE DISTRIBUTION We distribute prospects evenly among all SDRs through a round-robin system. Each prospect gets pushed to specific sequences in Outreach.io (email) and HeyReach.io (LinkedIn). The system also checks if they exist on these platforms to prevent any duplicates. Everything also syncs to the CRM Salesforce/HubSpot, so the sales team can access all data points we gathered. ___________ This workflow now requires no manual work, allowing the sales team to focus on conversations instead of research or manual list building. If you have any questions about the workflow, let me know in the comments.

HubSpot just quietly handed Pro users an Enterprise-level feature called Custom Events. The ugly truth about most CRMs is that they are full of noise because teams track traffic instead of behavior. Custom Events let you track the actual psychology of your buyers in real time. Now Pro users can stop guessing and start knowing. Look at your SaaS motion. Stop praying a prospect replies to an automated drip campaign and track exact product activation. When a free trial user invites a teammate or runs three reports, your app fires a payload to HubSpot. You then use a simple workflow trigger to instantly create a task for the sales owner and bump the lead score. You strike when the intent is real, not three days later. Look at e-commerce and marketplaces. Generic abandoned cart emails are table stakes now. Instead, track when a user spends ten minutes reading a specific legal agreement using Custom JavaScript events inserted into your tracking script to monitor that specific element. Or track winning auction bids by passing the exact dollar amount directly into the CRM, since the API lets you push up to 50 custom properties per event. You segment them based on verified buying intent, not assumed demographics. Look at your content strategy. Vanity page views tell you nothing. Capture the exact timestamp where a prospect paused your demo video. You push that video player data into a Custom Event using JavaScript, which triggers a workflow that drops them into a highly specific Active List. Your website's Smart Content is then rules-based to display customized messaging to anyone in that specific list on their next visit. Even customer success changes completely. Your software logs an error code, and you use the Events API to push that payload directly to the customer's CRM timeline. A workflow catches the event trigger and instantly generates a high-priority ticket in Service Hub for their account manager. Your support rep reaches out with a fix before the customer even realizes there is a problem. You just killed churn before it started. When you track actual human behavior, your CRM stops being a static database. It becomes the real-time central nervous system of your revenue engine. Have you used custom events? What are your favorite use cases?

I was speaking with someone a few days ago about FAB (Features, Advantages, Benefits), and then it struck me—how often we skip straight to features and wonder why sometimes our pitches don’t resonate with the customers. The truth? Features might inform, but it’s the benefits that sell. Here’s the breakdown: Features are the specs, processes, or tools behind the service—important for credibility, but not what convinces a client. Advantages start to show why our approach or tools stand out compared to alternatives. This is good, but it often doesn’t spark that client “aha” moment. Benefits? That’s where we connect to the client’s needs, aspirations, and goals. Benefits say, “Here’s how our service makes a real impact on your business.” Take, for example, a supply chain visibility solution: - Feature: Real-time, end-to-end visibility across the supply chain. - Advantage: Enables faster response to disruptions than standard reporting. - Benefit: Reduce stockouts, improve customer satisfaction, and build a resilient brand that’s prepared for the unexpected. So, how do you implement FAB effectively? 1. Customize for Each Client: Benefits vary depending on the client’s priorities. For a premium brand, it might be about “ensuring product availability for demanding customers.” For a value-oriented brand, it could be “optimizing costs through efficient inventory management.” Speak to each client’s unique goals. 2. Tell a Story: Clients remember scenarios, not specs. Frame FAB through real-world examples that show how your service addresses their specific challenges. Example: For a client struggling with fluctuating product availability, share a story about another brand that used real-time visibility to catch bottlenecks before they happened, keeping shelves stocked even during a sudden demand spike. Relate how this enhanced customer loyalty and built trust in the brand’s reliability. By crafting a vivid scenario around FAB, you help the client picture your solution working for them, making the benefits tangible and memorable. 3. Balance in Messaging: FAB is perfect for deep dives like presentations or proposals, but in shorter interactions, focus on benefits and let features and advantages subtly support. Example: In a short pitch, instead of listing “real-time visibility” (feature) or “faster response times” (advantage), highlight how “our solution ensures shelves stay stocked and customers keep coming back” (benefit). You might briefly mention the underlying feature (“using real-time data”), but let the benefit drive the message. This way, you’re speaking directly to the client’s goals, catching their attention with what matters to them most, and making a memorable impact, even in a short touchpoint. When talking about services, lean heavily into benefits. Clients want to see how your services drive tangible impact—not just what’s under the hood. How have you used FAB in your pitches? #cpg #cpgindustry #consumerproducts

Hey there, Ever looked at your WhatsApp messages and thought, “𝘞𝘩𝘺 𝘤𝘢𝘯’𝘵 𝘵𝘩𝘦𝘴𝘦 𝘫𝘶𝘴𝘵 𝘭𝘢𝘯𝘥 𝘪𝘯 𝘮𝘺 𝘵𝘦𝘢𝘮 𝘤𝘩𝘢𝘵 𝘢𝘭𝘳𝘦𝘢𝘥𝘺?” Well... I made it happen. 😎 I just completed a fun side project that connects 𝗪𝗵𝗮𝘁𝘀𝗔𝗽𝗽 with 𝗠𝗮𝘁𝘁𝗲𝗿𝗺𝗼𝘀𝘁 using a custom Node.js bot powered by the 𝗕𝗮𝗶𝗹𝗲𝘆𝘀 𝗹𝗶𝗯𝗿𝗮𝗿𝘆, all containerized using Docker Compose. This setup enables bi-directional messaging where WhatsApp messages get relayed into Mattermost channels, and Mattermost users can reply directly to WhatsApp. Here’s a quick rundown: 𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸 🔸WhatsApp – via Baileys 🔸Mattermost – Open-source team collaboration platform 🔸Docker Compose – Orchestrating services 🔸Node.js – Handling the logic 🔸PostgreSQL – Backend database for Mattermost 🔸n8n (Optional) – For future workflow automation 𝗦𝘁𝗲𝗽-𝗯𝘆-𝗦𝘁𝗲𝗽 𝗦𝗲𝘁𝘂𝗽 𝟭. 𝗖𝗿𝗲𝗮𝘁𝗲𝗱 𝗮 𝗗𝗼𝗰𝗸𝗲𝗿𝗶𝘇𝗲𝗱 𝗘𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁 🔸Set up a custom docker-compose.yml to spin up:    • PostgreSQL    • Mattermost (team edition)    • n8n for future automation 🔸All services use the same internal Docker network for seamless communication. 𝟮. 𝗕𝘂𝗶𝗹𝘁 𝘁𝗵𝗲 𝗪𝗵𝗮𝘁𝘀𝗔𝗽𝗽 𝗕𝗼𝘁 𝘄𝗶𝘁𝗵 𝗕𝗮𝗶𝗹𝗲𝘆𝘀 🔸Used the Baileys library to connect to WhatsApp Web via QR login 🔸Created an Express server listening for incoming Mattermost payloads 🔸Messages from WhatsApp are received, formatted, and relayed 𝟯. 𝗖𝗼𝗻𝗻𝗲𝗰𝘁𝗲𝗱 𝗠𝗮𝘁𝘁𝗲𝗿𝗺𝗼𝘀𝘁 𝘂𝘀𝗶𝗻𝗴 𝗜𝗻𝗰𝗼𝗺𝗶𝗻𝗴 𝗪𝗲𝗯𝗵𝗼𝗼𝗸𝘀 🔸Configured a Mattermost channel with a custom webhook 🔸When a WhatsApp message is received, it's POSTed to the webhook URL 𝗘𝗻𝗮𝗯𝗹𝗲𝗱 𝗠𝗲𝘀𝘀𝗮𝗴𝗶𝗻𝗴 𝗳𝗿𝗼𝗺 𝗠𝗮𝘁𝘁𝗲𝗿𝗺𝗼𝘀𝘁 𝘁𝗼 𝗪𝗵𝗮𝘁𝘀𝗔𝗽𝗽 🔸Mattermost users can send messages using a simple format like:    @2547𝘟𝘟𝘟𝘟𝘟𝘟𝘟𝘟 𝘏𝘦𝘭𝘭𝘰! 🔸The bot parses this and sends it back to WhatsApp using Baileys 𝗙𝘂𝘁𝘂𝗿𝗲-𝗣𝗿𝗼𝗼𝗳𝗲𝗱 𝘁𝗵𝗲 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 🔸Spun up 𝗻𝟴𝗻 as part of the Docker network 🔸Will soon connect the bot to n8n for advanced automations like:     • Logging WhatsApp chats to Airtable/Google Sheets     • Auto-replies or escalations based on message content 𝗪𝗵𝘆 𝗜 𝗕𝘂𝗶𝗹𝘁 𝗧𝗵𝗶𝘀 This integration is perfect for teams using Mattermost internally who also need to: 🔸Interact with clients on WhatsApp 🔸Centralize communication 🔸Maintain a proper audit trail  𝗪𝗵𝗮𝘁’𝘀 𝗡𝗲𝘅𝘁? 🔸Add NLP to understand messages and auto-reply 🔸Build n8n flows to trigger Mattermost alerts from WhatsApp 🔸Create Dockerized monitoring and retry mechanisms #WhatsApp #Mattermost #Automation #NodeJS #Docker #Baileys #DevOps #Integration #OpenSource

You walk into a restaurant with no menu, no signage, and the waiter says, “Welcome! We offer… food. It’s good for hunger, great for energy, and improves overall satisfaction. Shall we get started?” You’d pause, right? What kind of food? How much does it cost? Is it a quick bite or a sit-down dinner? Am I even in the right place? Now, think of your homepage as the front door of your business. If your messaging is vague or overly focused on high-level outcomes like “boosting ROI” or “enhancing efficiency,” you’re leaving your potential clients in the same state of confusion as that restaurant waiter. What happens when your homepage lacks clarity: 1️⃣ Your audience feels lost. If visitors can’t immediately understand what you offer, they’ll bounce faster than a millennial at a chain restaurant. 2️⃣ The wrong people inquire. Generic messaging attracts everyone… and no one. You’ll waste time chasing leads that were never a fit to begin with. 3️⃣ Champions can’t advocate for you. If the people tasked with comparing vendors can’t explain why you’re the better choice, your deal dies before it gets to the decision-maker. Your homepage is the start of a trust-building conversation. It should instantly answer: What problem do you solve? Be specific. Instead of “boosting productivity,” say, “reduce manual data entry by 70%.” Who do you solve it for? Call out your ideal audience. For example: “For mid-sized SaaS companies struggling with churn.” How are you different? What’s your unfair advantage? A feature, a process, or even your approach? Don’t hide it. Own it. Great homepage messaging = clarity. When your messaging feels customised, visitors know they’re in the right place. And instead of wondering, “Should I reach out?” they’re thinking, “How fast can I book a demo?” Your audience doesn’t need “food.” They need to know if you’re serving sushi, steak, or salad and if it’s exactly what they’re craving. Make it easy for them to choose you. 

The days of "I noticed you like Guinness!" personalization are dead. Here's how top sales teams are identifying specific pain points their solution can uniquely solve. After building Apollo's AI research agent from zero to thousands of users, I've seen what separates good prospecting from great - and it's not what most people think. The Old Way: Generic Filters & Surface-Level Personalization - Start with basic filters: job titles, industry, company size - Download list, manually research each prospect - Find something generic to mention ("saw you went to Stanford!") - Send bland outreach with superficial personalization - Hope for 1-2% response rates while burning through your TAM The New Way: AI-Powered Pain Point Identification 1. Multi-source data enrichment: Configure multiple data sources in one place to maximize contact accuracy. For example, set up a waterfall enrichment that tries several email and phone providers in sequence to find valid contact information before your first touchpoint. This significantly increases your reach rate without wasting time on bounces. 2. AI qualification for genuine pain points: Create natural language prompts that identify prospects with problems you can solve. For a localization company, this means scanning websites for translation gaps. One prospect had a product supporting 30+ languages but maintained an English-only website – a perfect opportunity to start a value-driven conversation about expanding their web presence. 3. Signal stacking for personalized outreach: Combine multiple signals in priority order to craft messages that address specific pain points. Look for companies showing international expansion signals alongside their existing language limitations. One prospect was expanding overseas but only offered English language support – a clear opportunity to help them scale localization for customer acquisition in new markets. The result? Instead of "Hope this email finds you well," you can send: "We noticed you support 14+ languages in your product, but your website is only in English. Are you looking to expand your website to better service your international users?" The best part? You can do all of this inside Apollo.io - from initial prospect search to multi-source enrichment to AI custom research to signal stacking to AI messaging - in just a few clicks. Check out the demo to see how easily you can transform your outreach from generic to genuinely valuable.