WSI - September 29, 2026 Look at deal count, deal value, timing, stage conversion, sales capacity, and customer mix in sequence to find where the result changed. Summary When new-business revenue falls short of plan, several metrics may look concerning at once. Inquiry volume, stage conversion, proposal age, win rate, and average deal value describe different parts of the result. The best starting point is to identify which measure changed first, for which group of opportunit

WSI - September 28 2026 When customer data and conversion tracking are already shaky, another layer of automation makes both the experience and the reporting harder to trust. Summary A growing share of B2B go-to-market teams let AI agents act on customer records without a clear view of what those agents are doing. When agents work from inconsistent data and unreliable conversion tracking, prospects get duplicate outreach and reports lose their link to revenue. Teams that sett

WSI - August 7, 2026 Summary: Google shipped a new Search Console report on June 3 that finally shows how often your brand shows up in AI Overviews. It still doesn't show clicks or sales, and neither does any other AI platform for citations you didn't pay for. Two low-lift methods close part of that gap right now: capturing the hidden link marker Google sometimes attaches to AI Overview clicks, and adding an AI option to your existing "how did you hear about us" question. Nei

New McKinsey research across nearly 4,000 B2B buyers and sellers in 13 countries points to the same infrastructure gap already showing up in CRM adoption numbers. Summary: McKinsey's 2026 B2B Pulse Survey found that fewer than 10 percent of organizations have scaled AI in any function, even though almost every B2B company is already using some form of it. The companies pulling ahead redesigned the workflow the tool sits inside, backed by a data structure where someone actual

Lead Management Architecture - AI Readiness Clean CRM data isn't the same as AI-ready CRM data The numbers below are some of the most important data to come out in 2026 on this subject. For the first time, there's hard, public evidence behind an argument that's mostly been made on pattern recognition until now. Summary: Salesforce's stalled Agentforce rollout is a preview of a much bigger problem sitting inside most enterprise CRMs. Most CRMs were never built to force real ag

Summary A cluster of 2026 research from Iterable, BCG, Grant Thornton, McKinsey, and PwC points to the same underlying issue across marketing organizations: the barrier to using AI more fully isn't the technology, it's ownership. Most teams have the tools to move faster, personalize more precisely, and act on data in real time. What's missing is a clear answer to who's accountable when a decision goes live. Closing that gap, one named owner per decision, is what separates org

A closer look at the structured data, protocols, and payment rails building the two sides of the agentic web, and why both run deeper than a single file or standard. This one runs more technical than most of what I write. That's deliberate. The shift underway here touches how trust and transactions get built into the web itself, and it's still early. Every protocol named below is a draft, a trial, or a first-year rollout. None of this is settled, and the map will keep changin

Marketing teams have solved the visibility problem. Most now agree on which metrics matter. What's still unresolved is what happens the moment a number arrives, because without an agreement made in advance, every result becomes a fresh argument. Two real client engagements, a luxury vacation rental company and a home organization systems company, show what changes when a number has to earn trust before it gets acted on, rather than after.

WSI June 23 2026 Most Companies Measure Search. The Best Ones Use It To Drive Growth. Every mid-market business I work with is sitting on top of more buyer intelligence than any market research firm could produce on demand. Search data. Query trends. Content gaps. Competitive visibility shifts. Real signals from real people actively trying to solve real problems, collected in real time, at scale, for free. And almost none of it makes it into a decision to drive growth. Not be

Search has always been reactive. Someone had a need, they typed it, you showed up or you didn't. That model isn't dead. But it's no longer the whole game, and for a growing slice of buyers, it's not even where the game starts. Google is building a profile of each user before they open a search bar. This is what the industry is starting to call pre-query personalization, and it changes the problem marketers are solving for. It connects Gemini to Gmail, Google Calendar, Google

Before you adopt AI, do sales and marketing agree on what a customer looks like? Don't go into the executive team meeting if you don't! Your company has invested in AI. Probably more than once. Marketing bought a tool. Sales bought a tool. Maybe the CEO approved a platform that was supposed to connect them. You ran the demos. You onboarded the teams. You told the board you were moving fast on AI. Here's the question nobody asked in that meeting: do sales and marketing agree o

The tracking is live. The attribution is catching up. I've written before about zero-click search, about AI intercepting the buyer journey before anyone reaches a website, and about what that's doing to paid search performance. This is the next part of that conversation. Our engineering team started seeing a pattern across client accounts that didn't have a clean explanation. Organic rankings were solid. Nothing had shifted in terms of position. But traffic from specific quer

While Everyone Is Still Debating AI A few months ago I wrote about how AI was intercepting buyers before they ever clicked an ad, how CPCs were rising, CTRs were falling, and the real problem wasn't your campaigns. It was where the decision was already being made. That holds. But the story moved faster than most people expected. Three things happened between January and April of this year that changed the day-to-day reality for anyone running paid search. ChatGPT ads launched

Everyone's talking about AI. Not everyone's talking about the same thing. That distinction is becoming expensive for businesses that assume all AI is interchangeable. GenAI tools, AI agents, and agentic AI aren't three names for the same technology. They're three fundamentally different operating models with different capabilities, different limitations, and very different requirements to deploy well. Understanding where each one starts and stops is the difference between usi

The voluntary migration window is open but closes when automatic upgrades begin in September This isn't a Google product update. It's a structural shift in how paid search works, and both major platforms are executing it on roughly the same timeline. Google announced this week that starting in September, it will stop allowing advertisers to create new Dynamic Search Ad campaigns. Existing DSA, automatically created asset, and campaign-level broad match campaigns will be autom

Here's the Road From Here to There Sundar Pichai was asked last week whether search would exist in ten years. His answer: "Search would be an agent manager, in which you're doing a lot of things." That's not just a prediction, it's pretty much a product roadmap. If you're running marketing for a mid-market business, the question worth asking isn't whether that future arrives, it's what your business needs to look like at each stop along the way. Because there are stops. This

AI access is no longer the issue Most organizations are already there. Tools are in place. Teams are experimenting. Research shows that 78% of organizations are using AI in at least one business function, and 75% of knowledge workers report using AI at work. That sounds like progress. But when you look at how the business actually operates, something doesn’t line up. Because despite that level of adoption, more than 80% of organizations are not seeing a meaningful financial i

There's a new evaluation happening before your prospect ever lands on your website. An AI tool has already compared you to three competitors, noted that your product descriptions lack specificity, and flagged that you don't show up in structured data feeds. And it may have recommended someone else. That's not a future scenario. That's what's happening right now, and the research is catching up to what a lot of us in performance marketing have been watching build for over a ye

Google just released research that confirms what most mid-market companies are getting wrong about paid media measurement. The answer isn't more data. It's better causality. There's a conversation that happens in boardrooms across North America every quarter. Marketing presents a stack of dashboard screenshots. The CFO looks at the numbers, nods, and then quietly redirects budget somewhere else. Not because the marketing isn't working. Because no one can prove that it is. Tha

The gap isn’t AI adoption. It’s the quality of guidance behind it. AI has moved from experiment to operational reality for most businesses. The question for owners and executives is no longer whether to engage with it. It's whether the person you're paying to guide you actually knows what they're doing. That distinction is where a lot of organizations are getting into trouble. The Competitive Gap Is Already Opening The numbers on this are not subtle: 71% of C-suite executives