We're killing the DM at @Zapier. Starting with the executive team. We've long held Default to Transparency as a value. That value has largely encouraged communication in public channels. But as the company grew, DMs are a hard habit to resist and break. But every DM is a gap in our Shared Brain. It's context that is lost for humans and AIs. As a result the cost of DMs keeps going up. So earlier this year I posted about our exec transparency leaderboard. The leaderboard has become quite the competition internally… I'm 3rd today. My co-founder @BryanHelmig has held the top spot as long as I can remember… It sets a standard for the rest of the company. In fact, since last year we’ve seen the % of Slack messages in public channels go from 33% to 46%. What the leaderboard measures Transparency is a team sport, and a disinfectant. Every month we track what percentage of our execs' Slack messages happen in public channels versus private DMs. When your CEO debates strategy in a DM, that decision is invisible to every agent and every team that needs to know what was decided and why. The decision happens but the reasoning vanishes. When that conversation happens in a channel, it stays. New hires can search it, agents can read and verify it, etc. Your Shared Brain knows what's true now: ask it a question and the answer reflects the latest reality. Taking It to the Next Level Reducing DMs are one way to increase transparency and open up context for humans and AI, but there are other mechanisms that help too. Three things beyond the leaderboard: 1. Meetings get recorded, transcribed, and become queryable 2. We run a shared skills library. Anyone on the team can encode a workflow they've figured out into a skill and share with the team 3. And we keep score. It's a silly scoreboard, but it subtly drives positive behaviors Raising Your Ambition In order to get the most of AI in your company, the AIs need context. So making your context queryable is one of the most practical moves you can make to improve the effectiveness of your AI agents. P.S. I’m coming for #1, Bryan...

You don't need a $2K/month attribution platform. Just ask AI to write 2 Google Tag Manager tags. Tag 1 fires on all pages. It reads your URL parameters — UTMs, gclid, fbclid, whatever you're tracking — plus the referrer, and stores everything in first-party cookies. First touch gets locked in on the initial visit. Last touch gets updated every time someone comes back through a new campaign. Cookie sits on your root domain so it works across subdomains. Tag 2 fires on your conversion page. Thank you page, order confirmation, whatever yours is. It reads those cookies, grabs the order ID and revenue from your dataLayer, and sends the whole thing to a webhook. What you do with the webhook is your call. Zapier, Google Sheet, Supabase, your own database. Doesn't matter. To get AI to write both tags, give it: → The URL parameters you want to capture → Screenshots of your dataLayer from GTM Preview mode on your conversion page → Where you want the data sent Takes about 10 minutes. Paste both tags into GTM as Custom HTML, set your triggers, done. Now every order or lead has first-touch and last-touch attribution tied to actual revenue. Not GA4 session data. Not platform-reported conversions. Real money matched to the campaign that drove it. No dev team. No Shopify requirement. No monthly fee. Works on any site that has GTM installed. Happy to help if you have questions.

Most marketing attribution tools assume you're on Shopify. But what about companies that built their own app? Your marketing site is on WordPress. Your app is on a separate domain. Someone clicks an ad → lands on your site → clicks through to your app → makes a purchase. GA4 stitches the session. But your order database has zero idea where that customer came from. The tools that exist (Attributer, Triple Whale, Northbeam) either require Shopify or only work with form submissions into CRMs. If your conversion is a purchase in a custom app? You're on your own. I built a system that solves this using only GTM and first-party cookies. No backend dev needed. Sharing the full breakdown this week. Architecture, code, everything — free. Who else is dealing with this?

Google Ads update! Advertisers can now see performance data for each RSA headline. No more guessing what works. Use this to make smarter, data-backed copy decisions and boost your ad results. searchengineland.com/google-… #PPC #GoogleAds

This is extremely helpful for measuring the impact of YouTube Ads and YouTube Select ads.

My guess, @GoogleAds will transition from keywords to search themes (like in pMax). For larger advertisers, it'll work great. They have the tech and first party data to direct the AI with high quality signals. Small advertisers will struggle. May have to rely more on marketplaces for leads. The Van Halen fan knows what's up 👇

Looks like Zapier is working on an API builder: api-builder-alpha.zapier.app… @AutomationAce_ , curious your thoughts on this? This could be a killer combo with tables, canvas, and interfaces.

Hey @TallyForms , can you make Google Ads enhanced conversions easy to setup? P.s. Meta, Google, and Bing do not like passing PII in URL parameters.

Hey @GoogleAds pros — is anyone offering a “Redesign My Campaign Structure” service? Not audits. Not optimization tips. A real overhaul based on deep historical search term analysis + intent-based segmentation. The dream deliverable: 1. Search term mining at scale 2. Intent-driven campaign restructuring 3. Match type & negative keyword guardrails Feels like the highest ROI project a PPC pro can sell. #ppcchat

In Reddit Ads, you can target exact match keywords by unchecking "Feed" in your Placements. You can add negative keywords too.

Prediction: The best Google Ads pros will be leaning into Search Max within 2 years. Get your measurement right and redesign your website to take advantage.