Hey! 👋 Hope you’re having a great summer! ☀️ 

I once had a previous consulting client who reached out, saying that she “needed help fixing her reporting in HubSpot.” So we met to do an audit and figure out what all was going on.

It became apparent, very quickly, that the issue wasn’t the configuration of their reports…it was their underlying data. See, they had let go of their 1 marketing ops person 6 months prior…and the VP of Marketing had been trying to manage HubSpot as a side hustle. That’s already a bit problematic, but then layer on that there was no transition period, so the VP of Marketing was flying blind and had little to no understanding as to what had already been built in HubSpot Workflows.

So here’s what was happening -- her previous ops person had 1 set of lead lifecycle definitions and the VP had another. The previous ops person had set up their own definitions from before, and the VP tried to create their own automation to align with their own definitions. You know what’s coming..tons of redundant and contradictory automations that are incorrectly overwriting stages and other data, causing mass confusion with sales + marketing.

And there's a particular kind of dread in opening your funnel report and knowing, in your gut, that the numbers are lying -- that there are MQLs sales never works and a "disqualified" pile you suspect is full of warm pipeline. If people can’t understand the data on even a basic level, it is just a distraction.

About a year ago I broke down the lifecycle stages here and handed you a cheat sheet to map your own. At the end, I asked one question: did you want the technical version…how to really build this in HubSpot or Salesforce? Sure enough, many of you have reached out since, asking for a guide on how to set up your lifecycles in your MAP or CRM.

Most lifecycle advice doesn't help because it's either too conceptual -- a pretty diagram with no build behind it -- or so platform-specific that it doesn’t help you figure out the strategy (and not every model is one-size-fits-all). But the logic of a lifecycle is universal. The stages, the data model, the automation rules, the SLAs, the recycling -- those are the same no matter which MAP you run.

But first, a quick word from the partner keeping this one free 👇

This section is sponsored by Knak, a partner who supports this newsletter. 💌

🤔 Lots of talk about the future of campaign ops in AI, but what’s the reality for most teams right now?

Knak surveyed 333 enterprise marketing decision-makers on how campaigns move from idea to launch, and the numbers are fascinating:

• 82% of teams spend at least half their time on production -- building, reviewing, approving, sending -- instead of strategy.

• 70% have deployed AI somewhere in the workflow, but only 29% call their adoption advanced.

• 85% missed at least one launch date in the past year because of workflow constraints, with approvals as the top culprit.

The teams pulling ahead have moved AI past drafting and into the production layer itself -- and they're 85% more likely to ship a single email in under an hour. The report is amazing and full of insights that you’d be well served to check out!

🔗 Get the State of Marketing Production report (free)

Okay -- now the lifecycle build, logic first. 👇

Design the data model before you automate anything.

This is honestly the hardest part. It’s so easy to want to move right into execution, but if you don’t have shared definitions of stages and activities surrounding them, they won’t serve you very well and may even cause more distraction than benefit. Get your GTM leads in a room and work through the definitions, and only build once you have alignment.

Build the acceptance loop, or your MQLs are a suggestion.

The MQL score is the easy part…usually. In great lifecycle design, when a lead becomes an MQL, sales accepts or rejects it against an SLA -- and a rejected lead recycles with a reason instead of vanishing. If sales can ignore an MQL with no SLA and no report, this is all basically useless. Make sure you have sales buy-in on actioning throughout the lifecycle.

Don't dead-end your recycled leads.

We’ve all heard the phrase “expanding existing customers is x times more cost efficient than going after new logos” and it’s true, even for disqualified or closed-lost deals. The disqualified/closed-lost pile is usually your warmest future pipeline, and most teams let it rot while they pour all of their efforts into net-new. Give rejected and gone-cold leads a real path back -- a recycle stage with a reason, and a plan to continue to nurture them over time. Count the loops so you can tell the bad-fit leads from the slow-burn ones.

Get your stage definitions and processes right before layering in AI.

I KNOW, I KNOW -- everyone wants to use AI everywhere to be as efficient as possible. But I’m a big believer in starting small and manual to “get the reps in” before automating or increasing complexity. Make sure the team understands the processes, definitions, SLAs, rules of engagement, all that good stuff before you consider automating. If you want to test small, you could look to automate deal progression as a first step, since deals have their own little lifecycle through their stages. Just make sure you test responsibly, and I would not automate anything that you’d want a human to validate before you take action, like marking something as closed won and kicking off onboarding without a human-in-the-loop.

Pro tip: once you’re ready, you can build this today with Claude and a custom HubSpot MCP. The MCP lets Claude read data across all of your GTM systems -- then proposes the stage move when a record's behavior has outrun its stage. Let it write the low-stakes moves on its own, like nudging an Inquiry to Engaged, and route anything near an open deal or customer to Slack for you to confirm. Every change is logged, so you always see what moved and why.

Okay, that was a quick overview -- here's the full thing to steal. 👇

Steal the build

This is the guide the old cheat sheet only pointed at. It's the full system -- the data model to set up first, the automation rules that transfer to any platform, the sales-acceptance SLA loop, the recycling paths, and the reporting -- with a build-step translation for each major MAP, so you're never stuck reading someone else's platform.

👉 Steal the Lead Lifecycle Build here.

It's platform-agnostic on purpose. Learn the logic once, then build it wherever you live (or are forced to live 🙄 ).

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What I’m up to/what I’m studying 💭

Fitting for this edition, I've been deep in our own lead and account lifecycle at Vector. We've gone from one product to several, with add-ons and partnerships on top, so the model I built a year ago has to grow up with the business. Same "design before you automate" work I'm preaching here, on my own instance. 😅

My team has also been working on setting up outbound systems for sales, and it sure is an interesting space right now. Where so many orgs are working on ultra-automated mass emails, we are moving in the other direction, focusing on ultra-personalized warm touch 1:1 or 1:few emails. Which brings me to a question: what’s your favorite sales outbound tool right now?

Finally, I’m working on updating a RevOps Data repo where we house all of our Stripe data, so we can format it and send it into HubSpot. I do not wish the Stripe API upon my worst enemy… 😅 

Finally, I just checked out a new women’s sports bar that opened down the street, and I must recommend it if you’re ever in San Diego! It’s been unusually hot in San Diego lately, so I’ve been spending a little more time indoors, rewatching old Vanderpump Rules episodes. 😆 

P.S. If you want to follow along with our wider GTM strategy and tactics, follow the Vector blog! You can subscribe to our newsletter too! 👻

Dear Sara ✍️

New to marketing operations? On a team of one at your company? Shy/introverted? Wish you could ask a question to an experienced marketing operations professional, without them knowing who you are? Here’s your chance! Submit an anonymous question to me here and I’ll answer a new question in every issue.

Here’s my answer to a question from last week:

Great question, and good news -- HubSpot handles most of this out of the box, with one caveat for the third-party stuff.

The Pardot equivalent you want is the activity timeline in the middle column of the contact record in HubSpot. Open a contact, click the Activities tab, and you get a chronological feed of everything HubSpot tracks natively: marketing and sales emails (including opens and clicks), form submissions, page views and website visits (as long as your tracking code is installed and the contact is known), calls, meetings, and notes. You can filter that feed by type with the toggles at the top, so you can isolate just emails or just web activity when you want. Here's HubSpot's doc on filtering the timeline.

If you want it to feel more like Pardot's everything-at-a-glance, you can customize the record layout -- add a Website Activity card and rearrange the middle column, or on Pro/Enterprise add dedicated tabs and team-specific views so the history sits right on the overview. You'll need Customize record page layout or Super Admin permissions to do it. Here's the how-to.

Now the caveat, so you don't hit a wall: anything HubSpot tracks itself is native, but social and most third-party platform engagement are not fully out of the box. Native social tracking on the contact record is…thin. 😅 For an outside tool to show up in that timeline, one of two things has to be true -- either a native HubSpot marketplace integration writes activities back to the record, or someone builds a custom integration using HubSpot's Timeline Events API to push those events onto the contact timeline. The first is a quick install if the integration already exists; the second is a developer build.

Short version: the unified timeline you had in Pardot exists natively for HubSpot-tracked and integrated sources, and you shape how it looks with record customization. The "every third-party engagement in one view" piece is where you'll lean on a marketplace integration or a custom Timeline Events build. Coming from Pardot, the shift is that HubSpot's timeline is broader -- sales and marketing together -- but leans on integrations for anything outside its own tracking. Ultimately, it depends on what exact activities you want to track! Where there’s a will, there is typically a way. 🙂 

News of the week 🗞️

Scott Brinker's State of Martech 2026 report is out and ungated. It's the annual read on where the stack and the profession are heading, and this year leans hard on the gap between teams operationalizing AI across their workflows and teams bolting it on as a productivity toy.

Why you should care: Scott is the GOAT of martech industry insights, and his passion comes through in the quality of his reports. What I found most interesting about this year’s report:

• Context is king: I’ve been calling context our GTM data layer, but it’s basically the same thing -- we need structured, trustworthy, valuable data in order to drive campaigns, whether they are Agent-led or human-led.

• For the first time in 15 years, the martech landscape got smaller. We’re seeing this out in the wild -- tons of smaller martech orgs closing shop or getting acquired by larger platform-based companies. I anticipate this will continue, and those with high value proprietary data will be the winners (whereas feature houses will quickly get eaten up by orgs who can just move faster with AI, or be left behind for internal vibe-coded custom apps).

• “In the last era, martech platforms competed to be where marketers worked. In the next era, they’ll compete to be what agents can work with.” ← this is critical -- if things continue has they have, I anticipate many of our marketers and salespeople will want to primarily work out of Claude or ChatGPT, not CRM or MAP.

• I also think that they are correct in their theory that context engineering is going to be the real value focus of ops in the next few years -- pulling the data together in the right places and in the right way for humans and Agents to activate as efficiently as possible.

• Let me know if you want me to dedicate an edition to a full write up on this report!

HubSpot opened Agent Hub and Agent Builder in public beta on July 23. Pro and Enterprise portals get one console to see every AI Agent and track its live status, plus a no-code builder to assemble new Agents from your prompts and CRM data.

Why you should care: Our job is shifting from building just one clever Agent to governing a roomful of them, and every one acts on your CRM. That makes the unglamorous work in this edition -- clean stages and field authority an agent won't misread -- the thing that decides whether the tooling helps you or just degrades your data faster.

The CMO Council's 2026 Marketing Transformation audit landed on July 22, and it doesn’t surprise me but certainly validates many of our thoughts in ops. Only 1 in 4 chief marketers rate themselves as advanced and adaptable with their martech and AI, while 37% admit they're challenged and lagging at integrating and deploying the tools they've already bought.

Why you should care: Teams keep buying capability faster than they can operationalize it, which is the whole argument for this edition -- the unglamorous plumbing underneath is what turns a martech investment into something the business can measure. Basically, we have a big opportunity here!

Two GTM-signal platforms got scooped up this month. Zoom is acquiring Common Room (announced July 2), folding its person-level buyer intelligence into Zoom's push to become an AI revenue platform, not just a video tool. And Clarify acquired Seam AI (July 21), rolling Seam's web-signal monitoring -- funding rounds, hiring, website activity, and exec job moves -- into a new "Clarify Signals" product.

Why you should care: Standalone signal tools keep getting absorbed into bigger revenue platforms, the same consolidation story Scott’s report points out. If you run a point tool whose whole job is surfacing signals, it's worth asking how long it stays standalone -- and making sure what it feeds you lands in a data model you control, not just in someone else's UI.

What else have you heard about recently? Reply back to this email to send me any other word on the street. 👂

Community poll of the week 🎟️

I ran a poll on LinkedIn that hit a nerve: "How many AI tools in your GTM stack are paying off right now?"

Here's how 118 of you voted:

My reaction: nearly half of you get value from one or two tools, and another quarter are still waiting on pilots to prove out. So three in four GTM teams are seeing payoff from two tools at most, and plenty from none yet -- after two years of buying everything that demoed well. Only 19% feel most of the stack is earning its keep, and 7% owned up to shelfware (I respect the honesty 😅).

It lines up with the research I flagged in that post: fewer than 10% of GTM teams are seeing broad AI payoff.

Want in on the next one? I post these on LinkedIn -- come vote. 👀

Meme of the week ⚙️

“Just fix it!!!” 🫠 

If you have a moment, will you let me know if you enjoyed this edition of the newsletter? Thank you!

Thanks for reading,

❤️ Sara

P.S. Special thank you to our sponsors for supporting the creation of this newsletter. 🫶