Brad Batesole

When you dig into attribution, you realize how tough it is. So I asked a friend for help... - Matt Bahr's Fairing analyzed 20 million post-purchase surveys and found the attribution mistakes most Shopify brands make. - Turns out we're missing tons of hidden channels like AppLovin and CTV. - He breaks down which survey questions actually work and how to cut Meta dependency. Link in comments

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Your PMM role is changing: How to build human+AI workflows that define what's next That's what I'll cover on April 1 at Product Marketing Alliance's Product Marketing Summit in Denver. I will show HOW I guide AI live using various AI platforms. Your launch campaign workflow could connect positioning, messaging, content, and sales enablement in one flow. Your sales enablement workflow could build pitch decks, dynamic sales prep dashboards, and interactive ROI calculators. This becomes possible when you move from using AI to building with it. The PMM's job is changing. Trailblazing PMMs are building AI teammates trained on their expertise, connecting them into workflows across functions, and deciding how humans and AI work together. They're writing the new job description themselves. You'll see real workflows for product launches and sales enablement, and a tool that helps you identify which workflows to build and which AI teammates to connect. You'll learn: ► How to find workflow ideas and decide which are worth building for PMM work ► How to design workflows that create new value, not just speed up existing processes ► How to evolve your role from AI user to builder and orchestrator Looking forward to learning from an insightful line-up of speakers on April 1-2. Come join us. See link in comments for more info and to register.

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Your sales team shouldn’t have to translate your marketing. If your deck, site, or campaigns require a 20-minute walkthrough just to make sense, that’s a GTM disconnect, not a sales enablement issue.

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Melanie Smith's SDRs book 70% of their meetings via cold call. But WHO they call surprised me: Melanie's team calls below-the-line end users. Not to book meetings, but to gain intel. Once they get intel, THEN they'll reach out to Execs with hyper-targeted messaging using what they learned. --- If you're having trouble breaking into large accounts, consider running a groundswell motion as a way to figure out what the VP actually cares about. Bonus: If you do a good job with the groundswell call, they might even be willing to refer you to the Exec. --- Loved getting to learn from Melanie Smith from Nooks this week on 30 Minutes to President's Club. Highly recommend the episode if you want to learn how to run a world-class outbound team. 

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In 2026, ABO is no longer the best way to test creatives. I didn’t want to believe it either. But after testing CBO since September across five different accounts, the data was very clear. CBO was ~27% more efficient on average. Here’s the CBO testing structure I’m running now: - Exclude all existing customers (Klaviyo + Pixel) - 100% Broad targeting - Set a minimum spend per ad set to force learning - Use Flexible Ads when I’m testing very similar creative variations What happens next is key 👇 Winners move into CBO Scaling Top performers also get pushed into Whitelisting & Partnership campaigns That said… I still see ABO outperform CBO in some accounts, especially smaller ones. So make sure to test both and see what works best for your account.

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Ummm can we pleaseeeee stop calling transactional $$s ARR?! 😑 As someone who has operated in both worlds, they require completely different approaches to GTM 🔑 But it starts with being honest about what type of revenue it is 🤷🏽‍♀️ 1️⃣ Recurring rev is much harder to land but typically easier to expand. On the flip side, transactional revenue is easier to land (experimental budgets, multiple vendors winning $$s) but much harder to retain and showcase long term value ✔️ 2️⃣ Recurring revenue is much easier from a planning perspective. Setting quotas / quarterly planning with transactional revenue is a different type of hell 😅 3️⃣ A generalist GTM persona (full stack AEs that prospect, close, expand and renew) may work better in the transactional rev world given the risks of retention. Vs a specialized set up may be better in the annual recurring revenue model for efficiency 🙌 Ofcourse buyer persona, implementation ease and product complexity also play a role in each company’s unique set up. But let’s start with NOT calling GMV / transactional $$s as ARR 🙄 🎤 Thanks for coming to my TED talk #revenuerecognition #cro #revenue #startups #sales

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WARNING: this is long and a good read IMO. I talk to hundreds of partners about the future of agencies and how to pivot into AI. If I was an agency, here is what I would be focusing on right this second. How to help companies complete the buying loop, not the marketing loop Buying loop: How people find, buy, use and expand with companies What you HAVE to solve for to do this: 1: What are the expectations we HAVE to hold employees to in order to get a good out come? Marketing: - how many channels are they using weekly - volume hitting these channels - is the messaging consistent with the plan - channel metrics so we can tweak Sales: - what is the end state of each meeting or convo our team has based on stage in process (lead process, selling process and hand- off process) - did the rep meet the end state - expectations of rep between calls Service: - how we pick up the ball (closed won deal from sales) - end state for each call - did rep meet the end state - cadence of meetings (do they own the exp or are they being owned) 2: How can we see if those expectations are being met? "A good plan violently executed now is better than a perfect plan executed at some indefinite time in the future" If you cannot see the teams behaviors (what they are ACTUALLY doing) then you will be stuck in the loop of changing processes to try to get better results just to never get the results. You need an OK process/plan that is VIOLENTLY executed on by the teams. 3: How can we see if these expectations are leading to better outcomes? This is how you can compare past results to current once the new process, platform and people systems are rolled out. To do this, you will need a slick combo of: - Ability to design process - Ability to train on this process - Reporting on behavior (are they really doing it, this likely needs AI and something like Supered⚡'s process boards) - Reporting on business metrics - Framework on how to tie this all together I am a 9.8/10 that this is how the next gen of agencies are going to win. By making an operating system of process AND behavior. Not just "solving" for the process and leaving the people side up to the company that paid you to build it. Disagree?

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Ever wonder why hitting your pipeline targets feels like rolling the dice? Most SaaS teams track surface metrics:  → Demos booked  → MQL volume  → Lead response times Those are inputs. They don’t guarantee revenue. The real predictors live in three places: 1️⃣ Quality Pipeline Certainty (QPC) – Are the right buyers showing up to demos, moving quickly to qualified opportunities, and converting at consistent rates month after month? 2️⃣ Cost to Acquire a Customer (CAC) – How much are you actually spending to win each deal? Lower isn’t always better if it means you’re chasing cheap leads that churn. 3️⃣ Lifetime Value (LTV) – Are those customers sticking around and expanding? High-value, long-term accounts turn marketing from an expense into a growth engine. When QPC, CAC, and LTV are aligned, growth stops being a gamble. That’s when 30 high-intent demos can produce more revenue than 100 “anyone with a pulse” leads. At Powered by Search, we’ve seen clients triple their pipeline with fewer demos — because the right mix of QPC, CAC, and LTV compounds over time. That’s the power of measuring what actually matters.

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The creator economy is now valued at ~$250B+ and set to scale rapidly (thanks G2 for the stat). So now more than ever amid all the automation tools, generative-AI content, and omni-channel creator noise, people with true subject-matter expertise need a way to cut through. The new Udemy Production Hub helps creators, subject matter experts and learning design leaders transform their domain expertise into impactful dare I say authentic content (I did, I said it) that bridges the gap between passion and tangible impact. Shout out to Ava Plasse and Gaby Araujo Z. for leading this project and sharing their expertise with the community. It’s only the start. Link in comments. #content #learning #AI

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How we added $9.6M in annual revenue for Dr. Squatch—without A/B testing Most CRO agencies go straight to A/B testing. (We didn’t, and it cost an additional $800k MRR for our client.) Dr. Squatch was already successful, but they wanted to scale from $5M to $100M+ in revenue in under 2 years. Most agencies would’ve started testing. We started with deep customer research: • Implemented heatmaps • Monitored social feedback • Analyzed purchase patterns • Conducted customer surveys We found that customers were already buying multiple soap bars... but the product pages weren’t optimized for this behavior. Here’s what we did: • Added quantity selectors to product pages • Set default quantity to 2 bars • Redesigned the checkout flow • Enhanced product collections • Improved subscription offers The results? ✅ 54% increase in revenue per soap purchaser ✅ $800k+ additional monthly revenue ✅ $9.6M+ annualized revenue impact The biggest wins don’t come from random A/B tests. They come from understanding customer behavior and optimizing for existing purchase patterns. Want to see how we approach CRO? Dr. Squatch Case Study: https://lnkd.in/dacPvF9V ♻️ Share this with a founder who could benefit 🔔 Follow for more CRO and growth insights

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Asana’s Secret to scaling pipeline? Agentic marketing with Piper the AI SDR Agent. Facing challenges like inconsistent follow-ups, stretched SDR teams, and missed opportunities during off-hours, Asana struggled with things most marketer teams worry about. They turned to Qualified and Piper the AI SDR agent to help them scale their pipeline motion without scaling their sales teams. Piper operates around the clock, engaging with high-intent inbound visitors, qualifying leads, and booking meetings directly into AEs’ calendars. This 24/7 coverage ensures that no opportunity slips through the cracks, even during peak times or after hours. The results? A remarkable 22% increase in pipeline without the need to scale headcount. Piper's ability to handle lead qualification and engagement autonomously has allowed Asana's human reps to focus on high-value conversations, enhancing overall efficiency. As Shannon Duffy, CMO of Asana, put it: “Agents like Piper are transforming how CMOs operate. This is what Agentic Marketing looks like in action: scalable, intelligent, and revenue-driven.” For a deeper dive into how Asana scaled their pipeline with Piper, check out the full case study here: https://ow.ly/XC9e50W2PHJ

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B2B commerce is 2-3x the size of B2C and growing twice as fast. Yet most e-commerce platforms aren't built for it. I listened to the latest episode with Jason Nuss from Shopware on Always Off Brand Podcast with Scott Oshman and Summer Jubelirer. The conversation highlighted why B2B commerce remains a sleeping giant. The core problem: ERPs run B2B businesses. They're the heartbeat - handling revenue, resource planning, and costs. When a $750M company generates only $20M through e-commerce, they can't conform to platforms designed for consumer transactions. Sales reps spend 70% of their time on bureaucracy instead of selling. They chase invoices, manage pricing against competitors, and file activity reports. Agentic AI changes this by automating the inefficient 70% so reps focus on relationships and closing deals. Shopware dominates 20% of e-commerce in Germany, Austria, and Switzerland - nearly 2x Shopify's US market share. Their North American strategy targets complex commerce: regulated industries (alcohol, firearms, healthcare), massive catalogs, and B2B operations where ERP integration determines execution. The B2B difference matters. Average distributors make 5-7 points of margin. Traditional SaaS pricing at 300 basis points consumes 60% of those margins. B2B needs different economics. Most interesting insight: For the first time, some merchants see more traffic from LLMs than Google. The next generation learns different search behaviors. The opportunity exists for companies solving genuine B2B complexity rather than forcing consumer patterns onto business transactions. What challenges are you seeing in B2B commerce that don't fit the traditional e-commerce playbook?

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