A marketing team huddles around a conference room, debating the results of an A/B test. The lifecycle CRM marketer is exhausted at the thought of babysitting another test. The data has been trickling in for weeks, and the insights are random at best.

The A/B Testing Chaos

In the last few months, we talked to 100+ CRM and Lifecycle leaders to understand what's chaotic in the marketing workflows, and the world they envision.

The Problem with Traditional A/B Testing

With the emergence of AI, tasks that once took months—like developing and running A/B tests—can now be completed in hours. In our conversations with executives from Etsy, Thumbtack, Notion, Equity Multiple, and Lemonade, AI seems to be reshaping the marketing paradigm.

One key takeaway? Traditional A/B testing is riddled with inefficiencies. As one lifecycle marketer admitted, by the time a messaging change ships, the user base has often either forgotten the trend or lost interest in the new product or feature.

A senior leader at Thumbtack, stated: “The biggest bottleneck on Growth is knowing what works. And so your ability to run tests faster and test more things and test smarter things is the biggest capability that will lead to success.”

The Octopus in Lifecycle Journeys

The process of setting up personalized journeys can spiral out of control. The lifecycle marketing lead at Notion described the phenomenon as an "octopus". Each cohort or segment adds another tentacle in their CRM tool, with more A/B tests to set up, but without a clear way to audit or share findings across teams. The result? Teams are buried under a growing mountain of data with no efficient way to act on it. The reporting becomes unmanageable. Personalization fails to scale.

Lemonade’s Lifecycle Director shared a similar frustration: “We’ve been focused on optimizing A/B testing workflows, but inefficiencies persist when testing multiple variations. It’s difficult to scale without the right tools.”

A typical journey setup

A New Era of Marketing Experimentation

These octopuses indicate an obvious aspiration - marketers envision a system where every campaign is heavily personalized, optimized for timing, and backed by robust data insights. Yet, the operational effort required to achieve this is immense, with agility being the key challenge. AI is making this vision a reality.

With new AI capabilities, we're seeing a paradigm where marketers can unlock -

• [Mechanics] Rapid experimentation: Test dozens of variations simultaneously, shrinking 4-6 years of testing in one month.

• [Messaging] Hyperpersonalize at scale: Instead of setting up hard-coded rules in journeys, AI can dynamically pull the right messaging for different cohorts.

• [Measurement] Reporting: Gain actionable reporting through a centralized platform across channels, user segments, and campaigns.

Lauren Guillory at Modern Health described this as the 3Ms framework, and how every marketer needs to optimize for at least one of the 3 Ms at all times.

Moving Beyond Vibes-Based Testing

The days of building A/B tests based on intuition and limited data are numbered. Marketing leaders across the industry believe, that teams should move beyond "vibes-based" testing and embrace a data-driven, AI-powered approach. This isn’t just about efficiency—it’s about staying competitive in a fast-moving landscape. AI offers the ability to test, iterate, and optimize campaigns at a speed and scale previously unimaginable.

For companies like Thumbtack, Notion, and Lemonade, it’s the difference between lagging behind and leading the charge.

Personalization: More Than Just a Buzzword

Personalization has become something of a buzzword. Every time you open LinkedIn, there’s another martech influencer claiming that every syllable in your messaging needs to be based on data from your user base. But realistically, how do you achieve that at scale? Should each lifecycle marketer on your team research individual users and write one-off emails? Or worse, rely on overly vague personas that don’t accurately reflect your audience, only to bombard them with thousands of irrelevant, unsolicited emails that fail to convert?

When working with marketing leaders at BiggerPockets, this approach seemed all too common. Without data that prioritized the individual user first and broader trends second, launching retention campaigns often felt futile. However, with the emergence of AI tools capable of compiling data and delivering hyper-targeted messages to each unique user, personalization is no longer just a silly buzzword but an actual superpower built to scale.

How AI is Redefining Campaign Testing and Execution

As marketing leaders adopt AI into their workflows, they’re not just keeping up—they’re thinking ahead on how campaigns are built, tested, and launched. AI empowers marketing teams to move from reactive to proactive strategies by enabling faster testing, deeper personalization, and smarter decision-making.

As enterprises gradually adopt the AI tools of the future, they do so under rigorous quality control processes. The real challenge now lies in how quickly teams can embrace these tools to transform their processes and stay ahead of the curve. The smartest players have mastered the art of balancing the agility of AI with appropriate controls and guardrails.