Research Note 001Reviewed exploratory study

What AI Actually Recommends for Lifecycle Marketing

A reviewed exploratory study of how leading AI models choose lifecycle engagement platforms across realistic buyer situations.

Published August 2, 2026 · Reviewed August 1, 2026

432

Total responses

417 accepted

24

Buyer scenarios

6 market segments

3

Models

Anthropic · OpenAI · Google

$6.82

Model cost

Pilot execution

The headline

Visibility is not the same as fit.

Braze received 44.2% of valid unaided recommendations, more than twice the next platform. It is the study’s strongest spontaneous AI default.

After models saw balanced, neutral profiles for scenario-appropriate candidates, Adobe Journey Optimizer was selected in 52.6% of its eligible opportunities—despite only 6.3% unaided recall.

The gap suggests that AI recommendation visibility contains at least two different signals: whether a platform comes to mind, and whether it looks like the best fit once the buying context is explicit.

Unaided recommendation

What models recall

No vendor names or profiles were shown. Denominator: 206 accepted responses.

01Braze91/206
44.2%
02Salesforce Marketing Cloud40/206
19.4%
03Klaviyo28/206
13.6%
04Customer.io17/206
8.3%
05Adobe Journey Optimizer13/206
6.3%

Equal-exposure preference

What models choose

Rates use eligible scenario-specific opportunities, not a shared denominator.

01Adobe Journey Optimizer60/114
52.6%
02Braze62/185
33.5%
03Customer.io27/88
30.7%
04Klaviyo30/106
28.3%
05Omnisend11/52
21.2%

How to read this note

01

It measures AI behavior

The results describe model recommendations under fixed conditions. They do not measure product quality, market share, or customer outcomes.

02

The modes answer different questions

Open mode measures unaided recall. Controlled mode measures preference after balanced exposure. Their rankings should not be combined.

03

This is a pilot, not a final market ranking

Three repetitions reveal useful patterns, but they are not sufficient for narrow statistical claims or small rank-order differences.