SOLUTION · AI REFERRAL FUNNEL

AI assistants shape the purchase. Your storefront still treats every click the same.

ClickMint uses source and first-party behavioral data to identify how AI-referred shoppers behave, diagnose where revenue is lost, and generate and deploy higher-converting experiments—without adding work to your team.

Request Free AI Traffic Audit
Context Handoff · Live Session
AI Assistant
i need running shoes for marathon training
budget's under $150 — and i overpronate
how do these compare to the Pegasus?
Use caseMarathon training
BudgetUnder $150
ConstraintOverpronation
ComparisonPegasus
Private conversation context is not passed to the storefront.
Referral / campaign sourcewhere available
Entry page/product-detail
On-site behaviorscroll · dwell · exit
Reading observable signals
90+
Ecommerce brands analyzed
$315M+
Ecommerce revenue analyzed
Source-level
AI traffic visibility
Control-tested
Incremental revenue lift
The problem

The decision happens before the click. The storefront starts over.

Intent formed upstream

AI visitors often arrive after researching a category, comparing alternatives and narrowing their requirements. A generic homepage or PDP makes them restart a decision they have already begun.
drop-off

cause-1

AI traffic disappears into the blend

AI referrals are fragmented across platforms and frequently buried inside referral or direct traffic. Most brands cannot clearly see the channel’s conversion rate, revenue per user or economic value.
drop-off

cause-1

No experience is optimized for it

Brands send AI-referred visitors into the same storefront as everyone else and measure the result in aggregate. That makes it impossible to know which post-click experience actually increases revenue.
drop-off

cause-2
Where AI sits

Search captures demand. Social creates it. AI assistants shape the decision.

Most DTC brands lose 40–60% of their branded search revenue to a generic landing experience. Run the number.
SEARCHKeyword-led intent and active demand
SOCIALDiscovery, creative and demand creation
AI ASSISTANTSResearch, comparison and decision support
Blended referral traffic AI-source measurement
Generic storefront Channel-adapted experiments
Aggregate reporting Control-tested RPU and GMV lift
measured vs control
EARLY ACCESS · QUALIFIED DTC BRANDS
The channel is new. The revenue discipline isn’t.
ClickMint is opening early access to qualified DTC brands that want to understand and improve the value of their AI-referred traffic. We first baseline its volume, behavior and revenue contribution, then determine whether the channel supports a dedicated experiment program.
Request AI Traffic Diagnostic
THE solution

How ClickMint turns AI-referred traffic into measurable revenue.

01

Baseline and diagnose

ClickMint segments identifiable AI-referred sessions using referral, campaign, landing-page and first-party behavioral data. Our AI then identifies where those visitors stall and prioritizes the issues carrying the greatest revenue cost.
Baseline & Diagnose
AI-referred sessions · sample
Identified sessionSourceRevenue cost
sess_9f2a · /pdp/pro-xAI referralHIGH
sess_71c8 · /homeAI campaignMED
sess_3d40 · /collectionsAI referralMED
sess_b6e1 · /pdp/pro-xAI referralLOW
AI segments the sessions, then prioritizes the friction carrying the greatest revenue cost.
02

Generate and deploy

Where traffic volume supports testing, ClickMint’s AI generates the UX, copy, design and production-ready experiment code for channel-adapted experiences, then manages deployment and iteration without requiring work from the brand’s design or engineering teams.
Generate & Deploy
channel-adapted experiment
UX & layout for AI-referred visitors
Copy matched to the channel
Production-ready experiment code
experiment.variant.jsxgenerated by ClickMint AI
Deploy variant →
03

Prove and compound the lift

Every experience is tested against control. ClickMint measures CVR, revenue per user and incremental GMV, learns from the result and determines what should be tested next.
Prove & Compound
variant vs control
Control
baseline
Variant
+ lift
CVR
measured vs control
RPU
revenue per user
GMV
incremental lift
learns from the result → determines the next test
case study

Proven System - New Channel

Context
A post-click experiment created a clearer path from discovery to purchase, generating more revenue from existing traffic without increasing acquisition spend.
BLVCK · PREMIUM APPAREL
Revenue per session
+183%
Incremental revenue
+$33K
Additional media spend
0$
Request Diagnostic

What’s included in every engagement. AI-driven end to end.

AI traffic baseline

Visibility into identifiable AI-referred sessions, conversion behavior and revenue yield.

Funnel diagnostics

AI detection and prioritization of the issues costing the channel revenue.

AI-generated experiment roadmap

The highest-value opportunities selected using behavioral data, benchmarks and prior learnings.

Experience generation

UX, copy, design and production-ready experiment code created by ClickMint’s AI.

Deployment and QA

Experiments launched through the ClickMint platform without requiring a storefront rebuild.

Incremental revenue reporting

CVR, RPU and GMV lift measured against control, followed by continuous AI-led iteration.

AI discovery is already shaping purchases. Make every measurable visit worth more.

ClickMint will show you how AI-referred visitors behave, where the storefront loses them and which experiments offer the clearest revenue opportunity—in under two weeks.