How to Collect and Use Training Data Effectively

AI is only as smart as the data you feed it. Most HR teams already have the data. But it’s buried in the wrong formats. At Fig Learning, we help HR leaders unlock it. Here’s how to make your data AI-ready. Structured vs. Unstructured: What’s the difference? Structured = ready to use. Labeled, searchable, clean data in tools like LMSs. Unstructured = hidden value. Think emails, transcripts, PDFs, and feedback notes. Structured data is plug-and-play. Unstructured data needs work - but holds gold. Step 1: Audit your data sources Where does learning actually live right now? Start by mapping your tools, folders, and files: - LMS reports? - Post-training surveys? - Feedback forms? - Meeting notes? Inventory what you touch often but never analyze. Step 2: Prioritize what to work on Not all messy data is worth it. Start with content that’s high-volume and high-impact. Focus on: - Post-training feedback - Coaching and 1:1 notes - Workshop or debrief transcripts - Policy docs in unreadable formats This is where insights are hiding. Step 3: Structure the unstructured Use lightweight AI tools to make it usable. Try: - ChatGPT Enterprise to tag and summarize - Otter.ai / TLDV to transcribe and recap - Guidde to turn steps into searchable guides And tag docs with topic, team, and timestamp. Step 4: Train AI on what matters Once structured, your data becomes leverage. Use it to power SOPs, checklists, or internal bots. Let AI write based on your real examples. It will save time and multiply your reach. Good AI starts with good prep. Don’t feed it chaos. Feed it clarity. P.S. Want my free L&D strategy guide? 1. Scroll to the top 2. Click “Visit my website” 3. Download your free guide.

𝗠𝗲𝗮𝘀𝘂𝗿𝗶𝗻𝗴 𝘁𝗵𝗲 𝗜𝗺𝗽𝗮𝗰𝘁 𝗼𝗳 𝗬𝗼𝘂𝗿 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗣𝗿𝗼𝗴𝗿𝗮𝗺 📚 Creating a training program is just the beginning—measuring its effectiveness is what drives real business value. Whether you’re training employees, customers, or partners, tracking key performance indicators (KPIs) ensures your efforts deliver tangible results. Here’s how to evaluate and improve your training initiatives: 1️⃣ Define Clear Training Goals 🎯 Before measuring, ask: ✅ What is the expected outcome? (Increased productivity, higher retention, reduced support tickets?) ✅ How does training align with business objectives? ✅ Who are you training, and what impact should it have on them? 2️⃣ Track Key Training Metrics 📈 ✔️ Employee Performance Improvements Are employees applying new skills? Has productivity or accuracy increased? Compare pre- and post-training performance reviews. ✔️ Customer Satisfaction & Engagement Are customers using your product more effectively? Measure support ticket volume—a drop indicates better self-sufficiency. Use Net Promoter Score (NPS) and Customer Satisfaction Score (CSAT) to gauge satisfaction. ✔️ Training Completion & Engagement Rates Track how many learners start and finish courses. Identify drop-off points to refine content. Analyze engagement with interactive elements (quizzes, discussions). ✔️ Retention & Revenue Impact 💰 Higher engagement often leads to lower churn rates. Measure whether trained customers renew subscriptions or buy additional products. Compare team retention rates before and after implementing training programs. 3️⃣ Use AI & Analytics for Deeper Insights 🤖 ✅ AI-driven learning platforms can track learner behavior and recommend improvements. ✅ Dashboards with real-time analytics help pinpoint what’s working (and what’s not). ✅ Personalized adaptive training keeps learners engaged based on their progress. 4️⃣ Continuously Optimize & Iterate 🔄 Regularly collect feedback through surveys and learner assessments. Conduct A/B testing on different training formats. Update content based on business and industry changes. 🚀 A data-driven approach to training leads to better learning experiences, higher engagement, and stronger business impact. 💡 How do you measure your training program’s success? Let’s discuss! #TrainingAnalytics #AI #BusinessGrowth #LupoAI #LearningandDevelopment #Innovation