Utilizing Dynamic Content

Most Workday admins use document templates for offer letters. But very few unlock their true power. Because Workday Docs isn't just a replacement for BIRT or static PDFs It’s a fully dynamic, token-driven engine that can automate contracts, policy letters, NDAs, promotions, and more with personalization, localization, and conditional logic. Let’s unpack what’s really possible: ->Start with Tokens: -Tokens are live merge fields like ${Worker.FirstName} or ${Offer.SalaryAmount} that pull real-time data into your documents. -You can insert them directly into templates via the Workday Docs editor, and they’re sourced from: --Related business objects (Job, Candidate, Compensation, etc.) --Custom calculated fields --Report fields if you're using an Advanced Report as the data source -Whether it’s a promotion letter or an onboarding checklist, your HR team never has to manually edit names, dates, or salaries again. ->Design Once, Personalize Infinitely: -Inside the Workday Docs editor, you can: --Format headers/footers with company branding --Add tables, page breaks, or signature blocks --Build templates for multi-language usage in a single file --Store & manage versions via Workday Drive It’s drag-and-drop, secure, and governed just like any other business object. ->Conditional Paragraphs (2025 R1 Update): -Before 2025 R1, you could only show/hide content using Boolean fields. -Now, you can conditionally display sections based on any data field, like: -- Country = “India” -- Compensation.Amount > 100,000 -- WorkerType = “Contingent” -This means: --One offer letter can contain India clauses, U.S. at-will disclaimers, and contractor disclaimers,all toggled based on dynamic data. --Bonus section appears only if there’s a bonus. --Relocation paragraphs disappear for in-office hires. All with a clean interface and no need for multiple templates. ->Where It’s Used: -Document generation can now be embedded directly into: --Offer business processes --Onboarding flows (NDAs, policy agreements) --Promotions and compensation changes --Compliance letters (e.g. Wage Theft Prevention notices) --Internal communications like Code of Conduct acknowledgments And thanks to 2025 R1, onboarding documents can now be auto-generated at hire, filled with tokens, routed for e-signature, and stored all natively within Workday. Best Practices Workday Recommend: -Use calculated fields for reusable, readable tokens (like full entity name or salary band) -Design one global template with language variants + conditional clauses to reduce sprawl -Use naming conventions and Drive folders to manage versions -Always test with preview + real worker data to validate -Limit editing access, your documents are legally binding assets Love this workday bite? For more such info , follow Kalyani Ghule img src: 3plusconsulting

Using Dynamic Creative Optimization (DCO) to Personalize Programmatic Ads: In programmatic advertising, standing out means delivering the right message to the right person at the right time. Dynamic Creative Optimization (DCO) makes this possible by tailoring ads in real time for different audience segments within a single campaign. Leveraging data and automation, DCO boosts relevance and engagement. Here’s how to use it effectively. Step 1: Define Your Segments Start by identifying audience segments based on first-party data—think demographics (age, gender), behavior (cart abandoners, frequent buyers), or context (location, device). For example, a retailer might target “urban millennials” versus “suburban parents.” Upload these segments to a DSP like Google DV360 or The Trade Desk, ensuring data is anonymized for privacy compliance. Step 2: Build Modular Creative Assets DCO thrives on flexibility. Create a library of interchangeable ad components—headlines, images, CTAs, and colors. For instance, pair a “20% Off” headline with a sneaker image for young shoppers or a “Free Shipping” offer with a stroller for parents. Use a DCO platform (e.g., Celtra or Ad-Lib.io) to assemble these into templates that adapt dynamically. Step 3: Set Up Decision Rules Link segments to creative variations via rules in your DCO tool. Example: If “user = cart abandoner,” show “Complete Your Purchase Now” with their abandoned item’s image. AI can refine these rules over time, learning which combos drive clicks or conversions, making the process smarter without manual tweaks. Step 4: Integrate with Programmatic Buying Sync your DCO setup with your DSP. As the platform bids on impressions, it pulls the tailored creative matched to the user’s segment in milliseconds. Test this on a small scale first—say, a single ad placement—to ensure rendering works across devices and channels like display or video. Step 5: Measure and Optimize Track performance by segment using metrics like CTR, conversion rate, or ROAS. If “urban millennials” respond better to bold visuals, double down there. Adjust underperforming variations—like swapping a weak CTA—based on real-time DSP analytics. The Payoff DCO transforms a single campaign into a personalized powerhouse, cutting creative waste and lifting engagement. A travel brand, for instance, could show beach ads to sun-seekers and ski deals to snow-lovers—all from one buy. In a crowded market, DCO’s precision is your competitive edge.

A VP of Marketing at a $25M sales training firm runs a $800,000/y ABM program. 500 accounts ($250M+ software co's). Great engagement. Zero form fills. Her exact words: "They just aren't filling out the forms" "These CROs & CFOs aren't surfing the web downloading PDFs. And if I'm being honest, I'm not surprised." A playbook written 10-15 years ago. Gate content, run ads to it, generate MQLs, email/call them. The buyers have moved on a long time ago, but 90% of B2B marketing campaigns still follow this broken model. This VP has seen its ineffectiveness first hand and decided to do something about it. We spent 45 minutes talking how Peel's AI Demos could fix her problems by turning passive content into active conversations with the exact buyers she's trying to reach: 1) Replace gated content with an AI Demo An AI Demo does something a PDF never can: it asks questions back. Instead of a prospect skimming a whitepaper and disappearing, Peel learns what they care about, surfacing relevant content dynamically, and qualifying them in real time. By the end of the session, you know their role, their pain, their buying stage, and what resonated most. 2) Turn ABM outreach into a personalized experience Her SDRs are sending the same decks and follow-ups to 500 accounts and hoping something sticks. With Peel, each outbound link is tailored: load in the contact's LinkedIn profile, add special instructions ("focus on pipeline velocity for this CFO"), and customize the opening message. The AI Demo greets them by name and picks up exactly where the relationship left off. It stops feeling like marketing. It starts feeling like a conversation. 3) Make every piece of content work harder As a sales training firm, they produce A TON of great content: frameworks, case studies, webinars and training content. Right now, that content sits on a page collecting dust. Peel turns all these content assets into an AI SDR/SE that qualifies, discovers and demoes 24/7 while everyone sleeps. 4) Replace MQLs with AALs MQLs are responsible for billions in wasted ad spend behind gated content campaigns, for billions of hours of reps’ time wasted on trying to talk to ‘leads’, for billions of those ‘leads’ who got a 'buy our stuff' email just because they downloaded a report, for ruined email delivery rates. Most of all, for the broken Marketing <> Sales relationship. Once AI Demos are in place (in ABM campaigns, website content assets, etc), she can start generating AALs (agent-activated leads). who have been qualified, discovered, demoed & enticed by AI. Instead of sending MQLs (ICP-fit + content engagement) to the Sales team, she'll be sending leads who have been qualified, discovered, demoed & enticed by AI. ------- There's never been a better time to kill the gated content campaigns and MQLs. Every marketer I know has wanted to do that for a long time, we just didn't have the right alternative. But with AI, now finally do.

#PowerPlatformTip 128 – 'Dynamic Data Retrieval' 💡 Challenge We often face the challenge of handling dynamic data in Power Automate without resorting to complex conditional structures like Switch or If statements. Whether it's language variations, user roles, or specific message types, a flexible and scalable solution is needed. ✅ Solution Using the Parse JSON action and dynamic keys, you can retrieve various information directly from a JSON structure. This allows you to pull different content (like greetings, settings, or user data) based on need, without additional effort. 🎉 Result Instead of complex conditions, you now have an agile, scalable solution that dynamically retrieves and processes data in real-time. 🌟 Key Advantages 🔸 No need for complex conditions 🔸 Quick adjustments for new data variations 🔸 Flexible for multiple applications Use Case Examples: 1️⃣ Language-Specific Greetings Use dynamic retrieval to automatically provide the appropriate greeting in the customer’s language, ideal for multilingual email communication. 2️⃣ Role-Based User Permissions Create JSON structures for different user roles. With dynamic querying, the correct role data is accessed automatically to tailor permissions or content. 3️⃣ Managing Message Types Set up a JSON structure with various message types (e.g., "Warning," "Info," "Confirmation"). This allows your app to retrieve and display the correct text or style based on the selected type. 4️⃣ Loading Product Settings or Variants Dynamically Have a JSON structure with product variants or settings? Use dynamic querying to load the correct data based on user input or selection in an app. This approach makes your workflows more agile, organized, and saves time on future modifications. #PowerPlatform #PowerAutomate #Flexibility #JSONParse #DynamicData

I recently revamped my personal website after realizing how 𝗶𝗻𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁 𝗶𝘁 𝗳𝗲𝗹𝘁 𝘁𝗼 𝘂𝗽𝗱𝗮𝘁𝗲 𝗰𝗼𝗻𝘁𝗲𝗻𝘁. Every small change required touching the codebase. Instead of hardcoding blogs and content or integrating a database, I 𝗺𝗼𝘃𝗲𝗱 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 𝘁𝗼 𝗡𝗼𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝘂𝘁𝗶𝗹𝗶𝘇𝗲𝗱 𝗶𝘁𝘀 𝗔𝗣𝗜𝘀 𝗮𝘀 𝘁𝗵𝗲 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗹𝗮𝘆𝗲𝗿. Titles, paragraphs, images, and blog posts are all fetched dynamically and rendered on the site. This made me rethink how personal websites should be built. 𝗦𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗻𝗴 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗨𝗜 made the system cleaner and much easier to maintain. Now, I write in Notion, refresh the site, and the updates are live. 𝗡𝗼 𝗰𝗼𝗱𝗲 𝗲𝗱𝗶𝘁𝘀. 𝗡𝗼 𝗿𝗲𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁𝘀. If you’re building a portfolio and plan to create content consistently, I believe 𝘁𝗿𝗲𝗮𝘁𝗶𝗻𝗴 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝘀 𝗱𝗮𝘁𝗮 𝗿𝗮𝘁𝗵𝗲𝗿 𝘁𝗵𝗮𝗻 𝘀𝘁𝗮𝘁𝗶𝗰 𝗺𝗮𝗿𝗸𝘂𝗽 changes the workflow entirely. I am still refining the design and performance, but the foundation feels much stronger. If you are curious about the implementation, I’ve outlined 𝗵𝗼𝘄 𝘁𝗼 𝘂𝘀𝗲 𝘁𝗵𝗲 𝗡𝗼𝘁𝗶𝗼𝗻 𝗔𝗣𝗜 in the GitHub README (https://lnkd.in/gvze9Qhg). I might also write a more detailed breakdown soon. Here’s the link to the site: https://lnkd.in/g8tD5kSC Would be interested in how others are structuring their personal sites.

Most companies are sitting on a goldmine of content they'll never use. It's a paradox. We're tasked with creating learning experiences, but we're already drowning in a sea of existing content: webinars, PDFs, videos, and knowledge bases. Your team isn't looking for more content. They're looking for the right content. The good news? If your organization has already invested in a Content Management System (CMS), Digital Asset Management (DAM), or a single-source publishing system, you are miles ahead of the competition. You've already done the hard work of creating structured repositories with rich metadata. This structure is rocket fuel for Generative AI, making it dramatically easier to transform those assets into personalized learning experiences. The old model of manually creating static, one-size-fits-all courses is broken. The future isn't about being a content creator. It's about being a content architect, and AI is the new toolkit. It’s a two-part system: 1. AI-Powered Curation This is about finding the right content at the right time. Instead of manually searching, AI can instantly: ▪️Discover relevant assets from across your entire organization. ▪️Organize them into logical paths. ▪️Deliver the precise answer a learner needs, exactly when they need it. 2. AI-Powered Adaptation This is about transforming that content to meet diverse needs. Once AI finds the right asset, it can instantly: ▪️Translate it into dozens of different languages for a global team. ▪️Convert its format—turning a dense document into a summary, an audio file for a commute, or a short instructional video. ▪️Personalize the information to an individual’s specific role, skill gaps, and career goals. Our role is shifting from building courses to designing intelligent systems. Systems that leverage existing assets to create truly personalized, on-demand learning experiences. How is your organization preparing to shift from static content libraries to dynamic, AI-powered learning environments?

A few months ago, we introduced our “Dynamic Login Wall” across our sites. We developed this proprietary technology after realizing that we were missing out on hundreds of thousands of sessions and page views on content that had very minimal conversions. Why? Google Discover, which is now one of the most important sources of traffic for a wide majority of publishers, has an algorithm that uses user signals like Bounce Rate and CTR to rank content. The higher the bounce rate, the less you get promoted. We’ve noticed this on hundreds of occasions and we knew this was a ranking factor on Facebook as well. This severely affects publishers with static login walls (or paywalls) because your bounce rate is naturally way higher. The solution: What you want to do is actually create a “Dynamic Login Wall” that automatically deactivates the login wall across content that has below average conversion rates (we identified that as 3%) and keeps it active on content that performs above average (closer to 5%). This allows you to maximize revenue and traffic on lower converting content, while maximizing conversions and loyal reader growth on higher converting content. Win win. Publishers who don’t have any login wall on their websites for fear of losing revenue and traffic should seriously consider setting something up like this soon. The more you wait to build your first party data strategy, the more f*cked you will be when platforms stop sending you visitors for free.

Dynamic Personalisation is now live for Sponsored Content. As everyone is talking about it, here's my take... I’d start testing it now, as while it will improve initial results, it won't last forever. For a long time, we've been able to use macros like {firstName}, {companyName}, {jobTitle} in formats such as Message Ads, Conversation Ads and Spotlight Ads. Now, LinkedIn is allowing the same with Sponsored Content - meaning your in-feed ads can now dynamically pull in a user’s name, company, or title directly in the introductory text copy. Great or weird? Honestly, both. Personalisation generally increases CTR and engagement, and you'll stand out while others catch up. But being realistic, I predict it will become the norm and once every advertiser starts using it, the novelty (and impact) will fade fast and over time, most will revert back. My advice on it is: →Test it early → Measure initial performance uplift → But keep an eye on it over time, as it may drop off As with any new feature, it's a short-term advantage. Use it while it works. But don’t rely on it forever.

In Episode #11 of the Claude Marketing Automation Series, we move beyond blogs and FAQs and begin creating one of the most valuable content assets for AI search visibility: dynamic service pages. While many marketers focus exclusively on blogging, AI search engines like ChatGPT, Gemini, Claude, Perplexity, and Google AI frequently cite service pages because they clearly explain what a business does, who it helps, and where it provides services. (In previous episodes I showed you how I get this data automatically from CallRail and by interviewing the customer) In this episode, I show how we use Claude, Duda MCP, Airtable, dynamic pages, and customer conversations to automatically create service pages at scale. You'll learn how to: ✅ Create dynamic service pages using Claude ✅ Use customer call data to generate service page ideas ✅ Build pages directly into Duda collections ✅ Connect Duda collections with Airtable ✅ Generate SEO-ready content automatically ✅ Create title tags, meta descriptions, and URL slugs ✅ Scale service page creation without rebuilding layouts ✅ Refresh collection data inside Duda ✅ Publish pages directly into your sitemap ✅ Submit new pages to Google Search Console / Bing Webmaster Tools Most importantly, you'll learn why dynamic pages are one of the most scalable ways to grow Answer Engine Optimization (AEO) visibility. Instead of manually building hundreds of pages, you create a structure once and allow AI to continuously populate it with highly relevant content based on real customer interactions. This is one of the most powerful workflows for agencies, marketers, and local businesses that want to scale content creation without scaling workload. Topics Covered: ✅ Claude MCP ✅ Duda Dynamic Pages ✅ Airtable Collections ✅ Service Pages ✅ Local SEO ✅ Answer Engine Optimization (AEO) ✅ Dynamic Content ✅ Google Search Console ✅ AI Search Visibility ✅ Automated Content Creation ✅ Programmatic SEO ✅ Service Area Pages This series is designed for: ✅ Agency owners ✅ SEO professionals ✅ AEO specialists ✅ Digital marketers ✅ Website builders ✅ Duda users ✅ AI workflow builders ✅ Automation engineers #ClaudeAI #Duda #AEO #SEO #ProgrammaticSEO #AISEO #MarketingAutomation #AnswerEngineOptimization #Airtable #ClaudeMCP #LocalSEO #DigitalMarketing #AIWorkflows