I used to end a lot of my Slack messages and emails the same way: "Reach out if you need me." It felt generous. Mostly it let me check a box and move on with my day without doing anything.
The problem is nobody reaches out. The ask puts the responsibility on the person who's already struggling to carry it. You don't raise your hand when you're burned out or too deep in it to know what to ask for. Which means the people who need help most are the last ones who'll ask.
Real relationships are opt-in. Leaving a door open and hoping someone walks through it isn't the same as walking through first.
Opting in looks like calling someone and saying, hey, what's going on, how can I help. It's noticing something specific — a bad week, a rough call, a quiet Slack channel — and naming it instead of waiting to be asked. That's the real difference between being available and being present.
It's the same instinct behind some of the best work I've seen this year, bringing top clients into Pittsburgh alongside Google, LinkedIn, Meta, and Reddit. In higher ed, these organizations compete for the same students. That day, nobody defended territory. Everyone had already opted in, which made the rest easy.
This works in marketing, too. The cold "get in touch" CTA is our industry's version of "reach out if you need me." Individual outreach to a prospect or client you've spent time getting to know works for the same reason.
So here's what I'd try this week: skip "let me know if you need anything." Pick one person, call out the specific thing you noticed, and ask what would actually help.
Patrick Patterson
CEO at Level Agency
What's interesting this week
Google Display is migrating to Demand Gen by January 2027 Google announced in May that standalone Display campaigns will be absorbed into Demand Gen, with the ability to create new Display campaigns disappearing in January. The GDN itself isn't going away, but the buying path is. WordStream has a practical breakdown of what changes, what carries over, and the five steps to take before the deadline.
Key takeaway: If you're running Display, the time to start testing Demand Gen isn't next quarter.
Yelp just piped 330 million reviews into ChatGPT Yelp licensed its full review database, 330 million cumulative reviews and more than 8 million business listings, to OpenAI for use in ChatGPT local recommendations. Yelp's Request a Quote feature is coming to ChatGPT soon, meaning users will be able to contact local service providers directly from an AI response. The deal is non-exclusive, so Yelp can strike similar agreements with other AI companies.
Key takeaway: For any marketer in home services, healthcare, or local services, the surface where "best plumber near me" gets answered just expanded significantly.
Your CRM data is probably not AI-ready HubSpot published a thorough breakdown of what a CRM data model actually is and why most teams don't have one. The stat worth holding: according to Validity's State of CRM Data report, 37% of CRM users have directly lost revenue from poor data quality, and only 9% trust their data enough for confident reporting.
Key takeaway: As AI features inside CRMs grow, the teams with clean, well-structured data get faster results.
Virtual insider session: Can you automate human taste?
Tomorrow | Thursday, July 30 | 1 PM EDT | 30 min + live Q&A
Most marketing teams aren't resistant to AI in creative. What looks like pushback is usually taste, and taste can't be automated.
Tomorrow, Level's Carly Fridhandler and Mike Rubino walk through where AI belongs in the creative process, where it actively makes creative worse, and what the performance data is starting to show about AI-generated ads versus human-made work. Level just published a look at the eight-step process behind AI creative that actually holds up (versus the one-prompt slop that's crowding every feed), and this session is the live version of that conversation.
Carly has led creative for Adidas, Walmart, and Lululemon, and is a Forbes-recognized AI artist exhibited from Tokyo to Paris. Mike brings the strategic layer that connects creative to business outcomes. The live Q&A is where this session earns its place over just watching the recording.
Awesome at Boring: The Unglamorous Habits That Fund Real Growth Ft. Jon Morris, Founder of Rise Interactive and CEO of Fiscal Advocate
Jon Morris turned a $10,000 business plan prize into Rise Interactive, one of the largest independent digital marketing agencies in the world, nearly $40 million in revenue, 250 people, and nine consecutive Inc. 5000 appearances before its acquisition. He came on the show to hand over the financial framework most marketing leaders are missing.
The core argument is uncomfortable in a productive way: you will not grow faster than your competition if you spend less on sales and marketing as a percentage of revenue than they do.
Jon lays out the benchmarks he coaches to, roughly 20% organic growth, 20% EBITDA, and around 8% of revenue on sales and marketing, and explains why the leaders who grow fastest almost always sit on the "spend more" side of that line. He also shares a two-question test that exposes whether your "we're data driven" positioning means anything at all.
Process discipline and data-driven management compound quietly over years. That's the unglamorous engine behind durable growth, and it's exactly the kind of thing that doesn't show up in a case study but shows up everywhere in a P&L.
Alex Moss, Principal SEO at Yoast, published a piece in Search Engine Journal that reframes what technical SEO actually means in 2026. The short version: rankings were the success metric of the old web. Trust, accuracy, and machine readability are the metrics of the new one.
The argument starts with a fact worth sitting with: Google has dropped support for nine ItemTypes from its rich result search gallery since ChatGPT's launch. Schema isn't dying, Moss argues. One display feature it benefited from is diminishing. The underlying function, identifying entities and their relationships so that agents can read your content without guessing, is more important than it has ever been.
Moss lays out five layers of data integrity (entities, relationships, format, actions, and perception) and maps them to a growing stack of protocols, from llms.txt and JSON-LD to WebMCP and OKF, none of which have a shared standard yet. His honest take: no consortium is coming to agree on one the way Google, Microsoft, and Yahoo agreed on sitemaps in 2006. The practical advice is to hedge: stabilize your entity IDs and sameAs links first because everything else stands on them, then test how you're actually interpreted before assuming the graph reads the way you intended.
The piece is dense and worth the full read for anyone running technical strategy.
The CMO's guide to building an AI-first marketing team
MarTech published a practical playbook from Margaret Lee, CMO of Devart, on what it actually takes to turn AI adoption into changed behavior across a marketing team. The hard-won observation that opens it: the most difficult part isn't choosing the model or buying the seats. It's changing how a team thinks, briefs, reviews, and ships work.
A few things from the piece that are worth the read. Lee's rule: every training session is paired with a real project that starts the same week. Knowledge without a deliverable disappears within days. She also flags a structural problem McKinsey's State of AI research surfaced: adoption is growing, but most companies are still experimenting without changing how work actually gets done. The fix isn't more training. It's cleaning up messy processes before applying AI to them, because AI amplifies existing process problems, it doesn't resolve them.
The scorecard at the end is the most useful part. It includes KPIs most teams aren't measuring, including a 60% reduction in time on top three routine tasks, 70% active weekly usage in the pilot team, and a target of 80% of AI-assisted outputs accepted with minor edits. A useful benchmark set for anyone trying to measure AI transformation past "we ran some training."
Granola is an AI notepad for people in back-to-back meetings. It transcribes in the background using your computer's audio, no meeting bot, no notification to the room, and when the call ends it enhances your notes using the full transcript and whatever you jotted down yourself.
It syncs with your calendar and preps a brief before every external meeting, pulling context from past conversations so you're not scrambling through five tabs before you click in. There's an MCP connector that feeds your meeting notes directly into Claude and other AI tools without copy-pasting. Free for unlimited notes on conversations under 30 days.
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