# Jon Miller

Jon Miller is a B2B marketing technology entrepreneur who founded Phave, an AI-native marketing automation platform. Miller also discusses marketing technology, AI, and B2B marketing leadership through LinkedIn posts and the B2B CMO Project podcast.

- Profile: https://b2binfluencer.marketing/creators/jon-miller/
- LinkedIn: https://www.linkedin.com/in/jonmiller2
- Median of last 5 posts: 50 reactions, 19 comments (checked 2026-11-02)
- Topics: artificial-intelligence, b2b-marketing, marketing-automation
- Based on 9 dated posts, latest 2026-10-07

## Summary

Jon Miller is most useful for explaining AI-native marketing automation and data access to B2B marketing leaders.

- Best for: A B2B marketing technology company seeking a thought-leadership interview or advisory on AI-native automation.
- Not for: A consumer brand seeking a sponsored content package with rates, deliverables, and audience guarantees.
- Check first: Confirm whether they offer paid partnerships and audience composition beyond LinkedIn follower count.

### Takeaways

- Legacy automation is a growing pile of if-this-then-that rules, Miller says.
- AI can use person, account, and buying group information to plan relevant actions.
- Data permissions, not AI skills or org charts, constrain marketing teams, per Lena Waters.

## Main ideas

- **Move from rules to reasoning in marketing automation**: Miller argues that legacy marketing automation platforms are 'glorified if-this-then-that rules engines.' Rules are good at what is allowed but bad at what is best: each rule handles the situation it was written for, and every new exception adds another rule until the system becomes a mess nobody wants to touch. An AI-native system does not need every possibility written in advance; it can work out the right action when the decision comes up. Miller frames this as a shift from rules to reasoning, not as adding AI to existing automation.
- **Decisioning is three different things, and Playlists plan several moves ahead**: In a conversation with Scott Brinker, Miller separates three things commonly called decisioning. Journey optimization picks among journeys a marketer has already mapped by hand. Next-best-action decides one move at a time, which Miller compares to shuffle: each touch may be fine, but nobody in B2B buys because of a single touch. A Playlist plans a sequence of approved actions for each person, looking many steps ahead, about thirty days out, and adjusts as the buyer engages. Miller argues hand-mapped journeys break down combinatorially: three actions can run in six orders, four actions in 24, and each addition multiplies the possible orders until there are more journeys than a team could draw. With Playlists, the team keeps the offers, content, goals, frequency rules, and eligibility constraints, while the AI assembles the order and should show why it chose what it chose. The Playlists idea is also the product Miller is selling through Phave, so the explanation is analysis and positioning at once.
- **The real constraint is data access and context, not AI literacy**: Miller consistently locates the blocker upstream of AI literacy. Summarizing Lena Waters, formerly CMO at Notion and a marketing leader at DocuSign and Grammarly, he endorses her framing that AI adoption in marketing is a permissions problem before it is a talent problem: whether marketers have read and write access to the CRM, how many days and departments it takes to get product usage data, and whether someone can have an idea in the morning and put it into market that afternoon. In his conversation with Scott Brinker, Miller adds the context layer: pulling raw data out of a CRM or data lake is only part of context. The harder part is knowing the facts and memories accumulated about a person, their account, and their buying group. Brinker calls the platform version context-as-a-service; Miller calls the middle layer between model and marketing a 'marketing harness.'
- **Interview practitioners for specific operating moves**: Miller's B2B CMO Project posts follow a recurring method: use a named practitioner's own quotes, pull out a small number of concrete operating details, list additional episode topics, and close with a question aimed at the reader's experience. The priority is what a leader actually does, not a general theme. The guest views are attributed separately from Miller's own arguments.
- **Phave's launch turns the argument into a platform-switch pitch**: The launch post frames Phave as the answer to enterprises that want AI-native capability but cannot afford to lose scalability, security, or integration depth by switching platforms. Miller names Phave's CTO and CPO, Nick Bonfiglio, who the post says was EVP of Global Product at Marketo from 2009 to 2016 and later founded Aptrinsic and Syncari, and cites more than ten enterprise users including SambaNova, SPS Commerce, mabl, Servion, and Hypha. A follow-up post adds customer commentary: Nicole Fuselier, described as VP of Growth and Demand at SambaNova Systems and a Phave development partner, says marketers considering a new platform should start now because waiting widens the gap; Ali Jawin, described as Chief Revenue Officer at Hypha, contrasts a traditional campaign, which specifies who gets what over which channel and when, with Playlists, where the team builds the library and the AI decides who gets what and when inside guidelines. These are launch claims and customer testimonials gathered for the launch, so they evidence how Miller positions the product rather than independent proof that migrations succeed.

## Work to read

- [Phave comes out of stealth: the post behind the name](https://www.linkedin.com/posts/jonmiller2_its-been-20-years-between-these-two-shirts-activity-7508514108279820290-tw8x)
- ["The 7 Ways AI Changes Marketing Automation" keynote post](https://www.linkedin.com/posts/jonmiller2_how-is-marketing-automation-is-changing-in-activity-7521567660325797888-88eX)
- [Context-as-a-service and the "marketing harness"](https://www.linkedin.com/posts/jonmiller2_scott-brinker-and-i-recently-talked-about-activity-7523057507657818112-z_8J)
- [Journey optimization, next-best-action, and Playlists](https://www.linkedin.com/posts/jonmiller2_a-journey-optimizer-picks-the-best-path-a-activity-7519065904094023680-Qw0v)
- [Practitioner advice on switching marketing automation platforms](https://www.linkedin.com/posts/jonmiller2_advice-for-marketers-consider-a-new-marketing-activity-7516566689287847936-4fG7)
- [Snowflake's Denise Persson on why soft quarters cannot be fixed late](https://www.linkedin.com/posts/jonmiller2_snowflakes-cmo-denise-persson-says-theres-activity-7521250515654004736-dGSf)
- [Lena Waters on data access as the real AI constraint](https://www.linkedin.com/posts/jonmiller2_cmos-keep-asking-what-an-ai-native-org-chart-activity-7508164868890595328-3hXN)

## Brand relationships

- **Phave** (owned_business)
- **SambaNova Systems** (client)
- **Hypha** (client)
- **Telarus** (mention)
- **B2B CMO Project** (disclosed_partnership)
- **Marketo** (mention)

## Partnerships

Nothing in the material reviewed documents a partnership or sponsorship offer from Jon Miller. His visible commercial activity is as founder of Phave, an AI-native marketing automation platform: the posts promote the product's launch, cite named development partners and early customers (SambaNova, SPS Commerce, mabl, Servion, Hypha), and thank marketers who gave feedback. He also co-hosts or appears on the B2B CMO Project podcast, where guests have included Snowflake CMO Denise Persson and former Notion CMO Lena Waters. Those are business and editorial relationships, not purchasable placements: no media kit, rate card, audience specification, deliverable list, or sponsorship terms appear anywhere in the reviewed posts. A brand cannot plan a paid placement with Jon Miller from this evidence, because no format, price, or booking route is stated. What the record does support is a conversation: an interview or advisory approach tied to AI-native marketing automation, legacy platform migration, and marketing operations data access, which is where his posts concentrate. Treat the absence of a documented offer as exactly that. The reviewed material shows no sponsorship package; it does not show that Jon Miller never accepts sponsorships, and it should not be read that way.

## Alternatives

- Björn Radde: Choose Radde when the same interview or advisory slot needs to answer a demand-capture question rather than a platform question. The reviewed posts cover two things a marketing technology vendor's audience asks about directly: identifying the companies behind anonymous B2B website traffic and enriching them with company and intent data so sales can prioritise on real behaviour, and splitting AI search spend between paid placement inside ChatGPT and longer-term generative engine optimisation so a brand is mentioned inside AI answers rather than only clicked past. If the vendor wants an episode that ends with a channel plan its audience can act on, Radde's material is closer to that than Miller's platform-architecture argument.
- Dev Basu: Basu is the stronger alternative when the audience is a newly appointed or struggling CMO and the goal is an operational playbook. The reviewed posts supply a 100-day sequence — audit closed-won deals, map channels against pipeline produced, check the real MQL-to-SQL rate, audit attribution, interview the last five losses, then align on ICP and a single North Star pipeline metric — and a breakdown of how six buying stakeholders (champion, executive, finance, IT and security, operations, legal) each need different content, with deals stalling because teams build for only one of them. Those are usable in a workshop or an advisory session within the same week.
- Scott Wueschinski: Wueschinski fits when the same slot is aimed higher in the organisation or at the product-data side of AI buying. The reviewed posts argue that agents now decide on structured inputs rather than browsing, that an audit found 70 percent of leading brands' product pages fall short of that standard, and that structured product data should be treated as a revenue line with an owner, a budget, and a board metric. The second post makes a governance argument for AI agents in the revenue engine — one named owner per agent, one workflow per agent, a business metric set before launch, and an exportable rollback path — using the gap between AI scaling and reported EBIT impact as the hook.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/