Marketing automation platforms have run on the same logic for two decades: if a lead does X, do Y. That rules engine scaled email in the 2000s and lead scoring in the 2010s, but it was built for a buying process that moved in a straight line. B2B buying does not move in a straight line anymore, and a wave of new entrants is betting that the platforms built to run it need to reason about ambiguity, not just execute rules against it.
The bellwether: Marketo’s own co-founder says the category he built has stalled
Jon Miller, who co-founded Marketo in 2006 and later Engagio, has launched Phave, an AI-native marketing automation platform aimed squarely at the enterprise accounts that Marketo, Pardot, Eloqua and HubSpot have held for years. Phave came out of stealth after two years of development and reached general availability in August 2026, according to the company’s own launch release. It is already running inside enterprise marketing teams including SambaNova, SPS Commerce, mabl, Servion and Hypha, and is backed by FirstMark, Ridge Ventures and Costanoa Ventures.
Miller’s critique is not about features. It is about architecture. “Rules are good at what is allowed, but bad at deciding what is best,” he said in the launch release. Traditional automation platforms encode decisions as if-then logic: if a contact opens three emails, then move them to a nurture track. That works when the buying group is one person following one path. It breaks down against the buying committees that now define enterprise B2B, where a single account can involve stakeholders across IT, finance and operations, each moving at a different pace and none of them behaving like the linear lead the rules engine was written for.
What Phave does differently
Instead of if-then branches, Phave uses what the company calls “playlists”: the system computes, for each individual person, account and buying group, the sequence of touches most likely to move that specific relationship forward, then adjusts as new signals arrive. Marketers describe the outcome they want; the platform works out the path, rather than a campaign builder pre-defining every branch in advance. Phave treats contacts, accounts and multi-person buying groups as distinct objects, each with its own journey, instead of collapsing them into a single contact record the way legacy platforms do.
Bruce Eidsvik, chief growth officer at Servion Global Solutions, one of Phave’s early customers, described the practical difference in the same release: “With a traditional platform, going after a single account with four global sites and buyers across IT, finance and service operations is practically impossible… Phave’s playlists work out when and how to reach each person.” That is the argument in miniature: not faster execution of the old model, but a different unit of decision-making, built around the account and the buying group rather than the individual contact.
Pricing signals where the bet is placed
Phave starts at $36,000 a year, priced on the number of people who receive something in a given month rather than on database size, the metric legacy platforms have billed against for years. That is a small detail with a real implication: database-size pricing rewards hoarding contacts, engaged or not, while engagement-based pricing rewards a system that can tell the difference between a contact worth touching this month and one that is not. It is a pricing model that only makes sense if the underlying system can actually make that judgment call reliably, which is the same claim Miller is making about the product itself.
What it means for the marketing leader
Phave is one company, but the reasoning-over-rules argument is not confined to marketing automation. Vendors across the martech stack are making a version of the same bet: that pattern-matching against predefined logic is the wrong architecture for how B2B buying and consumer behavior actually work now, and that judgment-capable AI belongs closer to the execution layer, not just the reporting layer on top of it. For a CMO evaluating a platform switch, the question this raises is not whether the new system is faster than the old one. It is whether the vendor can show, with a real account like the one Eidsvik described, that the system’s judgment holds up when the buying group gets messy, and whether that judgment is auditable enough to defend to a CFO when a deal stalls. A rules engine is at least explainable: you can point to the exact branch that fired. A reasoning engine has to earn that same trust with evidence, not architecture diagrams.
The practical test for any team considering this category shift is narrow and specific: ask the vendor to run one real multi-stakeholder account through the system in a pilot, then ask what the system did differently than a rules-based sequence would have, and why. If the answer is a general description of “personalization at scale,” that is marketing language. If the answer is a specific, traceable decision, the reasoning claim is real.
There is a governance question underneath the reasoning pitch that vendors in this category tend to skip past. A rules engine fails loudly and predictably: a branch either fires or it does not, and a marketing ops team can trace exactly why an account received a given touch. A system that decides “what is best” rather than “what is allowed” needs its own audit trail, or the marketing leader adopting it is trading a system they can explain to legal and compliance for one they have to trust. Enterprise buyers evaluating Phave or any reasoning-based competitor should ask specifically how the system logs and surfaces the “why” behind each decision, not just the decision itself, before treating auditability as a solved problem.
Marketing automation has consolidated around the same handful of platforms for a decade. A credible challenger with the original Marketo pedigree, real enterprise logos and a pricing model built around engagement rather than database size is a signal that the category is genuinely contestable again, not just adding another point solution to an already crowded stack. Related coverage: Marketing Automation Is Merging Into One Shared Layer and Marketing’s New Agents Don’t Just Suggest, They Act.
Source: PR Newswire
