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 Hey Marketing Bestie, Dream sporting events I want to attend
There are more, but I would love to go to these. What is something you are dying to attend? It doesn't have to be sports. And, if you're at the Indy 500 this weekend, send me pics. Was this email forwarded to you? Sponsored by Insense You know UGC works. It's making it that's the problem. Garbage in, garbage out.Your AI is only as smart as the data you feed it. I talk a lot about AI in Marketing. The tools, the automations, the ad optimizations. But the unsexy thing sitting underneath all of it: Dirty Data. </3 Bad data doesn't just slow you down. It actively breaks things.
That's tech debt, and it compounds. Congrats, you built a mess and now you're paying rent on it. Don't worry, we'll fix. Why it matters right nowIn CRM, messy data means bad routing, broken lead scoring, and sales following up on the wrong people with the wrong message. In advertising, it means your 1st-party audiences and conversion signals are garbage inputs into Google and Meta and both platforms optimize against whatever you give them. You're basically paying to train the algorithm on your own chaos. Wait long enough and you have 5 tools, 3 ops people manually fixing the same problem, and half your automations misfiring. Clean data is EVERYTHING for anything AI-adjacent to actually work. Clean the data that powers your most important decisions 1st. The fields that drive revenue, automation, and targeting like email, company, name, lifecycle stage, source, consent, attribution. Start there. <3 What to clean firstStart with your CRM. If it feeds your ad platforms and AI workflows, it's the source of truth and right now it's probably lying. Duplicate contacts, invalid emails, stale phone numbers, bad lifecycle stages, broken UTM tags, outdated consent. Clean that first. Every downstream system inherits whatever mess lives there. A simple playbook1️⃣. Audit the data you actually use for Marketing and AI, not all of it, just what matters. Look at what fields are powering your automations, your lead scoring, your ad audiences. That's your priority list. 2️⃣. Define standards: format, naming conventions, required fields. Write it down and make sure the whole team is working from the same rules. "I thought we were doing it this way" is not a data strategy. 3️⃣. Deduplicate and merge matched records. 1 contact, 1 source of truth. Duplicates corrupt scoring, waste outreach, and break attribution. 4️⃣. Validate emails, domains, phone numbers, and consent. If you can't reach them or you don't have permission, the record is dead weight. 5️⃣. Enrich missing firmographic or behavioral fields where you can. Incomplete records limit segmentation, personalization, and AI performance. 6️⃣. Add guardrails at entry points so bad data stops coming in the front door. Form validation, required fields, integration hygiene. Fix the source, not just the symptom. 7️⃣. Automate profiling and monitoring so quality doesn't slip back after cleanup. Set alerts, run regular audits, make it part of how the team operates. Not a quarterly panic, a system. Treat data quality like an operating system, something you run continuously, not something you fix once and forget. Before you buy another AI tool, before you launch another automation, before you scale another campaign, check what it's running on. The ROI of clean data compounds the same way dirty data does. Just in the right direction. MEME OF THE WEEK  Sponsored by Markup AI AI grammar tools can make copy that sounds......."good." 🎙 TUNE IN Podcast to listen to this week: How to measure the ROI of AI with Christine Royston, CMO of Wrike What you will learn: 🎙: The workflow mistake that makes AI slower and more expensive🎙: Why AI budgets don't work like SaaS budgets JUST FOR FUN 🤩: Brand of the week: Net-a-Porter My friend is at the Indy 500 this weekend for a Bachelor Party and some of his friends are camping near it. I've never felt older. Your friend, | ||||||||||||
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