---
author: AI Engineer
date: '2026-05-01'
guest: ''
layout: post.njk
source: https://www.youtube.com/watch?v=CrqPcIZOOXA
speaker: AI Engineer
tags:
- ai-pricing
- hybrid-pricing
- value-based-pricing
- billing-infrastructure
- revenue-growth
title: AI定价策略：Stripe 如何赋能AI公司实现敏捷与灵活的营收增长
summary: 本视频探讨了AI经济的快速增长带来的定价挑战，包括利润波动、用户理解障碍及产品快速迭代。Stripe的Mayank Pant分享了识别客户价值、选择计费指标、采用混合定价模型、设置价格护栏以及持续迭代的关键五步框架。强调了灵活的计费基础设施对企业竞争力的重要性，并介绍了Stripe如何通过其全面的解决方案支持AI公司的营收增长。
insight: ''
draft: true
series: ''
category: ai-application
area: tech-engineering
project: []
people:
- Mayank Pant
companies_orgs:
- Stripe
- OpenAI
- Eleven Labs
- Intercom
- Tropic
- Lovable
- Anthropic
products_models:
- Stripe Billing
- Metronome
media_books: []
status: evergreen
---
### AI经济的爆炸式增长与定价的严峻挑战
Mayank Pant，Stripe的计费解决方案架构师，就AI定价的复杂性展开了深入探讨。他指出，AI经济正以前所未有的速度增长，是传统SaaS的三倍，头部AI公司实现2000万美元ARR的速度是SaaS公司的近三倍。然而，这种爆炸式增长也带来了严峻的挑战。AI公司的规模化速度极快，走向全球和扩展业务的步伐都远超以往，这使得**AI定价**变得异常困难。
传统SaaS定价模式通常拥有稳定且高企的毛利率（80-85%），但AI业务的特点是**利润较低**，且容易受到**算力消耗**和**用户行为**的影响。特别是“能力用户”（power users），他们可能仅占总用户的5-10%，却消耗了80%的计算资源，直接挤压利润空间。此外，**外部成本**如基础设施定价难以预测，可能严重损害利润。
更深层次的挑战在于**用户对定价的理解**。对于产品公司而言，以“tokens”或“API调用次数”为计费单位可能很自然，但对于终端用户来说，这种技术化的度量标准往往难以理解。例如，用户在使用Gamma这类AI工具时，更关心的是能生成多少演示文稿或幻灯片，而不是底层的API调用数量。同时，**产品迭代速度**远超定价更新速度，今天的高级功能可能在几个月后就成为标配，导致定价策略难以跟上产品演进的步伐。Stripe的研究显示，33%的AI公司担心不可预测的计算成本，41%的公司认为定义产品价值是挑战，而84%的公司则指出定价未能跟上产品推出速度。
Original English
>> Hello.
Hi.
I'm
Mayank.
I'm
from
Stripe
and
I'm
the
billing
solution
architect
working
in
Stripe.
And
today
we
want
to
talk
about
AI
pricing.
So
we've
got
a
billing
engine
and
a
lot
of
nowadays
a
lot
of
AI
companies
come
to
us
talk
about
how
they
want
to
do
billing,
how
we
can
help
them
with
their
AI
pricing.
So
based
on
the
research
that
our
Stripe
team
has
done
on
in
the
over
the
last
2
years
and
based
on
our
experience,
we
want
to
share
some
of
the
learnings
with
you
guys.
So
as
we
all
know,
AI
economy
is
growing
at
a
record
pace.
They
they
are
growing
three
x
faster
than
traditional
SaaS
and
based
on
uh
Stripe
data,
this
is
what
we
see,
right?
The
top
100
AI
companies
took
20
months
to
get
to
20
million
ARR
versus
the
top
100
SaaS
companies
which
took
65
months.
So
basically
we
are
growing
at
three
x
faster
rate
than
what
we've
seen
before.
And
though
this
is
great,
this
is
exciting,
but
this
is
bringing
new
challenges.
The
speed
of
movement
is
so
great
that
the
companies
are
now
going
global
faster.
They
are
scaling
up
faster
and
pricing
that
pricing
AI
is
becoming
incredibly
challenging
because
of
the
speed
that
we
see.
So
we
know
that
earlier
it
was
traditional
SaaS
pricing.
Basically
we
had
80
85%
gross
margins.
They
were
not
changing,
right?
But
with
AI
it's
completely
a
different
thing,
right?
The
margins
are
low
and
the
margins
get
impacted
based
on
how
many
users
are
using
your
system.
So
neither
pure
subscription
nor
pure
usage-based
model
offer
us
a
complete
answer,
right?
And
the
simple
reason
is
we
have
margin
risk
from
power
users.
5
to
10%
of
your
users
can
use
80%
of
your
compute.
Uh
external
costs
are
unpredictable,
that
is
your
infrastructure
pricing,
right?
Which
can
really
hurt
your
margins.
Technical
pricing
may
overwhelm
users.
What
we
mean
by
that
is
for
a
product
company
talking
in
terms
of
tokens,
API
calls
might
seem
very
uh
normal,
but
people
on
the
other
side
do
not
understand
that
technical
pricing.
For
me,
for
example,
if
I
go
into
Gamma,
I
don't
really
mind
how
many
API
calls
am
I
using.
I
want
to
see
how
many
slides
or
how
many
decks
did
I
uh
was
I
able
to
get
out
of
the
price
that
I'm
paying,
right?
And
pricing
is
not
able
to
keep
up
with
the
product
velocity.
What
might
be
a
premium
feature
today
in
6
months
maybe
a
standard
feature
across.
So
are
you
able
to
keep
up
with
that
pricing?
Uh
so
what
we
see
at
33%
of
our
AI-powered
business
site
unpredictable
compute
costs
as
their
concern.
41%
say
that
defining
the
value
that
is
being
delivered
is
is
a
concern,
right?
And
84%
of
them
talk
about
that
we
are
rolling
out
products
faster,
but
we
are
pricing
is
not
keeping
up
with
it.
So
that
is
why
what
we
say
in
iteration
is
a
competitive
advantage.
The
first
price
that
you
put
in
is
is
a
hypothesis.
It
is
not
a
commitment
because
you
are
bringing
in
new
features
every
week,
every
month
and
with
those
new
features
and
maybe
the
old
premium
features
are
becoming
standard.
So
the
pricing
has
to
evolve
with
the
feature
that
you
put
in,
right?
So
frequent
pricing
change
is
a
signal
of
growth,
right?
You
build
the
infrast-
infrastructure,
you
put
your
pricing
in
the
infrastructure
that
can
iterate
that
allows
you
to
iterate
rapidly,
right?
So
this
chart
is
one
of
my
favorite.
It
shows
that
hypergrowth
companies
which
are
giving
100%
plus
year
on
year
growth,
they
are
changing
their
pricing
three
plus
times
in
the
last
2
years.
They
are
not
standing
with
their
pricing.
49%
is,
you
know,
high
growth.
They
are
they've
changed
three
plus
and
the
low
growth
companies
are
only
22%
who
have
changed
it.
And
that
means
that
those
low
growth
companies
have
a
static
product,
right?
And
that
is
not
where
you
want
to
be
in
today's
age.
So
now
where
are
these
companies
moving,
right?
If
you
look
at
it,
hybrid
pricing
which
was
only
6%
in
2024
is
41%.
Outcome-based
pricing
is
5%,
right?
And
where
it
has
it
picked
up
from?
Se-
seat-based
pricing,
SaaS
pricing,
subscription
pricing
is
all
declining
because
the
models
are
changing.
So
as
I
said,
hybrid
pricing
seven
x
increase
and
now
56%
of
AI
company
leaders
are
using
hybrid
pricing.
Like
we
talked
to
all
the
all
the
companies
such
as
Intercom,
Lovable,
Eleven
Labs,
OpenAI
and
Tropic,
they
are
all
building
on
Stripe,
billing
on
Stripe
and
all
of
them
are
using
hybrid
pricing
and
I've
also
talked
with
companies
who
were
SaaS
companies
so
far
which
used
to
uh
help
customer
build
workflows
and
they
were
in
SaaS
pricing,
but
now
as
soon
as
they
bring
uh
LLM
AI
into
their
product,
then
they
are
also
planning
to
move
on
to
hybrid
pricing
because
SaaS
pricing
then
starts
eroding
their
margins,
right?
So
to
if
if
this
is
where
we
are
going,
then
how
do
we
start
thinking
about
pricing?
How
do
we
come
to
a
right
price?
How
do
we
define
our
price?
And
how
then
do
we
iterate
it?
So
the
we've
got
a
five-step
uh
a
five-step
framework
for
this
and
the
step
one
of
that
framework
is
you
define
your
value,
right?
So
what
type
of
value
can
my
product
provide?
But
not
what
your
product
is
doing,
but
what
the
what
the
customer
perceives
your
product
to
do.
Like
again,
like
I
took
an
example
of
Gamma.
For
me
as
a
customer,
I
need
that
product
to
give
me
my
presentation,
my
decks.
I
don't
care
underneath
how
many
API
calls
is
it
making,
where
is
it
going.
My
uh
for
the
for
the
customer
it
is
the
quality
of
the
deck
and
the
relevancy
of
that
deck
deck.
So
53%
of
hypergrowth
companies
have
offered
clear
value-based
pricing
that
the
customer
understands
versus
just
26%
of
low
growth
peers.
And
the
way
we
look
at
it
is
uh
there
are
four
broad
frameworks
on
which
the
first
kind
of
these
companies
are
the
company
that
are
providing
automation.
Like
like
I
uh
as
a
company
I'm
helping
them
to
save
time
and
as
a
customer
what
they
are
looking
at
it
is,
okay,
with
the
time
saved
I'm
saving
on
the
cost,
right?
Second
is
augmentation.
The
number
of
people
remain
the
same,
but
the
quality
that
they
come
out
with
is
much
better.
Like
they
can
produce
images
better.
Probably
for
a
campaign
provider
they
can
build
in
better
campaigns
more
quicker.
So
they
uh
those
kind
of
augmentation
the
company
looks
at
it
is,
okay,
I
have
the
same
number
of
people,
but
they
are
more
efficient,
they
can
deliver
more
value,
right?
Third
is
the
enhanced
service.
Maybe
it
gives
you
an
access
to
a
proprietary
software
or
some
new
uh
data
set
that
you
wouldn't
have
access
otherwise,
right?
For
example,
if
you
look
at
it
look
at
Stripe
and
our
payment
infrastructure,
we
can
uh
do
fraud
recognition
much
better
because
of
the
volume
that
flow
through
us,
right?
And
finally,
the
fourth
kind
of
one
is
the
which
gives
you
an
improved
results.
Like
for
example,
company
like
Intercom
who
says,
I
will
price
you
based
on
the
number
of
tickets
that
I
solved
without
human
need.
So
that
is
impacting
the
direct
bottom
line.
So
once
we
realize
how
we
are
helping
the
customers,
how
our
customer
perceive
it,
that
is
when
we
know
the
value
and
we
know
the
price
that
we
can
command
in
the
market.
Once
we've
understood
this
is
the
value
that
we
are
providing,
then
you
define
your
charge
metric.
Like
what
is
the
billable
unit
that
is
best
representing
my
value,
right?
And
then
you
build
features
into
a
currency
that
customers
understand.
For
example,
is
it
consumption-based?
Like
for
an
infrastructure
company,
consumption-based
might
be
the
right
one.
Like
how
many
API
calls
did
I
help
you
to
make,
right?
And
this
aligns
to
the
cost
of
the
company
that
is
providing
that
service.
Second
could
be
the
workflow-based.
Like
how
many
images
that
was
I
able
to
generate?
How
many
documents
was
I
able
to
summarize?
And
this
aligns
to
the
product,
and
the
third
is
the
outcome-based
as
I
said.
How
many
business
results
did
I
generate?
So
if
if
I
am
helping
the
company
to
hire
people,
how
many
uh
candidate
that
I
have
put
forward?
How
many
candidates
were
hired
out
of
those
candidates
resulting
in
saving
time?
Or
how
many
qualified
leads
did
I
generate?
Right?
So,
this
aligns
to
your
customer
ROI.
So,
now
that
you've
understood
the
value
that
you're
providing
and
you've
decided
your
charge
metric
against
it,
we
will
we
will
see
how
they
change
it,
right?
Like
if
you
move
from
consumption-based
to
outcome-based,
it
is
definitely
easier
to
implement
consumption-based
is
much
easier
to
implement.
But,
it
is
harder
to
align
to
value.
Like
if
I
if
some
company
tells
me
and
says,
"I
allowed
you
1,000
API
calls.
I
do
not
know
what
those
1,000
API
calls
mean.
I
want
to
see
how
many
decks
I
generated
as
in
my
previous
example."
But,
if
you
go
from
outcome-based
to
consumption-based,
it
is
easier
to
sell.
Like
I
can
definitely
go
to
a
customer
and
say,
"I
will
increase
your
outcome.
I'll
increase
your
uh
candidate
hired,
but
to
attribute
value
is
difficult."
So,
that
is
where
the
balance
has
to
be
made
and
data
is
required
to
satisfy
and
to
make
your
case.
One
of
the
pro
tip
is
to
translate
value
with
credit.
Like
bundle
the
features
into
credits.
Say
that
"I
am
giving
you
100
credits
for
the
month.
And
then
beneath
under
the
hood
of
the
credits,
you
can
have
your
own
models
how
you
get
to
that."
But,
that
helps
the
customer
to
understand,
"Okay,
100
credits
and
it
will
translate
to
uh
this
particular
ROI."
Once
you've
done
that,
then
that
is
where
you
pick
your
pricing
model.
Now,
is
it
a
subscription
fee?
The
usefulness
of
subscription
fee
or
SaaS
fee
is
predictable
revenue.
It
gives
you
a
committed
customer
relationship.
Right?
How
And
then
the
second
could
be
the
usage
fee,
which
scales
with
customer
with
protects
margins.
But,
the
downside
as
I
said
is
for
the
SaaS
fee,
uh
your
power
users
might
burn
your
margins.
And
for
a
usage
fee,
uh
the
customer
might
be
hesitant
in
experimenting
with
your
product.
Like
going
full
deep
because
they
do
not
know
what
kind
of
a
invoice
will
they
uh
expend
on
this.
So,
pure
subscription,
pure
usage-based
was
a
thing
of
the
past.
Now,
as
we
saw
in
the
previous
slides
as
well,
everybody
is
moving
into
the
hybrid
model.
So,
what
is
the
hybrid
model?
A
hybrid
model
will
have
a
base
fee
and
it
will
have
a
scaling
fee.
The
base
fee
basically
helps
you
to
establish
a
relationship
with
your
customer.
And
the
scaling
fee
or
the
usage
fee
on
top
of
it
will
allow
them
to
experiment
as
much
as
they
want
and
then
to
pay
for
the
value
that
they
derive
out
of
your
platform.
So,
you
are
not
alienating
any
of
the
user
any
category
of
the
users.
Once
you've
established
your
uh
pricing,
then
you
build
in
the
guardrails
because
a
wrong
bill
can
erode
a
lot
of
customer
trust.
You
might
be
doing
great
for
the
three,
four,
five
months,
but
if
the
on
the
sixth
month
your
bill
goes
wrong,
bill
goes
very
high,
then
that
those
customers
go
and
then
you
work
so
hard
to
retain
those
customers,
but
then
they
leave
you.
So,
what
safety
feature
do
you
consider?
Like
you
are
giving
them
flexible
pricing.
Now,
you're
building
guardrails
around
it,
right?
As
the
design
principle
is
fair
it's
simple
here.
Build
fair
pricing,
but
then
do
not
surprise.
So,
what
what
we
what
we
advise
people
to
do
is
put
in
usage
caps.
Like
I
paid
$20
and
then
I've
been
given
100
credits.
I
say
that
after
100
credits,
I've
built
in
a
usage
cap.
You
either
pay
more
to
go
ahead
or
we
will
stop
and
you
wait
for
the
next
month.
So,
that
the
it
is
the
customer
that
has
remained
in
control
of
their
uh
usages.
Right?
You
build
an
automated
notification.
You
tell
them
when
they've
used
50%,
70%,
90%
of
uh
of
their
allocated
limits
because
this
is
building
trust
with
the
customer.
We
are
not
trying
to
uh
cheat
them.
We
are
there
trying
to
inform
them
that
this
is
what
you've
used.
These
are
the
uh
thing
that
you
can
go
ahead
with
now.
You
can
top
up.
You
can
do
a
manual
top
up.
You
can
do
an
auto
top
up.
Or
you
can
pause
and
then
start
the
next
month
when
fresh
credits
gets
allocated
to
you.
And
then
you
set
rate
limiting
so
that
no
wrong
code
is
burning
through
the
limits,
right?
So,
this
will
protect
you
and
your
customers
both.
Once
you've
done
these
step
one
to
four,
then
the
step
five
is
you
iterate,
right?
You
keep
iterating.
84%
agree
that
fast
pricing
adaptation
is
a
key
competitive
advantage.
As
I
said,
your
first
model
is
a
hypothesis
and
you
keep
building
on
that
pricing
as
your
product
keeps
evolving.
You
prioritize
speed.
You
do
not
wait
for
the
right
price
right
price
point
and
wait
for
a
year
before
you
put
it.
You
put
a
price
point
there
which
you
think
is
the
right
price
point
and
then
you
iterate.
You
talk
to
your
customers.
Those
guys
who
churn,
you
talk
to
them
and
ask
them
why
they
are
churning.
Is
it
a
product-market
fit?
Which
is
then
you
work
on
your
product.
But,
is
it
high
price?
Then
you
work
on
your
pricing.
Right?
If
they
upgrade,
you
ask
the
same
questions.
You
run
AB
tests
on
pricing
to
find
the
optimum
point,
but
you
prioritize
speed
and
you
keep
iterating.
And
then
you
continuously
realign
to
your
value.
Now,
realigning
to
the
value
means
as
you
are
rolling
out
new
features,
you've
already
given
them
hybrid
pricing.
You've
already
put
in
number
of
credits.
Under
the
hood,
you
can
keep
changing
what
those
credits
means.
Do
do
those
100
credit
that
you've
given
them
means
five
API
calls
of
a
certain
category,
10
image
generation
of
a
certain
category?
Whatever.
So,
under
the
hood
you
can
keep
changing
them.
But,
you
constantly
realign
the
value.
So,
this
is
how
all
the
companies
have
been
thinking
about
pricing.
This
is
how
we've
been
uh
trying
to
help
them.
But,
what
is
most
important
in
all
this
is
what
kind
of
an
infrastructure
do
you
have
for
your
billing,
for
your
pricing
that
is
helping
you
to
do
this?
If
every
change
costs
you
three
months,
four
months,
and
a
lot
of
engineering
effort,
then
it
is
not
worth
it.
So,
that
is
why
it
the
infrastructure
you
choose
determine
how
fast
you
can
iterate.
And
uh
from
our
side,
the
most
flexible
and
complete
billing
solution
in
market
is
we've
got
Stripe
and
it
is
not
us
that
is
saying
it.
78%
of
AI
companies
are
building
on
Stripe,
which
is
a
testimony
in
itself.
Most
of
the
AI
companies
that
you
see
here
are
building
on
Stripe
like
I
said,
Anthropic,
OpenAI,
Lovable,
Eleven
Labs,
Intercom.
They're
all
launching
their
billing
and
pricing.
You
might
have
associated
Stripe
with
payments
only,
but
in
the
last
two,
three
years
we've
uh
we've
invested
a
lot
into
AI
billing.
So,
we've
got
Stripe
Stripe
billing
which
allows
you
to
go
with
subscription
pricing,
usage
pricing,
hybrid
pricing.
And
as
these
companies
are
so
quickly
within
10
to
15
months
now
starting
with
the
retail
PLG
motion
going
to
enterprises,
we've
got
Metronome
that
allows
you
to
build
all
the
all
the
dif-
difficult
and
complicated
contracts
with
the
enterprises
having
minimum
commitments,
uh
pre-commitments,
uh
overage
prices.
So,
we've
got
that
and
we've
got
the
whole
platform
that
allows
you
to
do
uh
payments,
tax,
invoicing,
revenue
recognition
on
this
AI
pricing.
So,
yeah,
this
is
where
we
are
right
now
helping
all
our
AI
companies
in
the
market.
So,
yeah,
this
this
is
me
happy
for
any
questions
that
you
have.
Yes,
please.
This
is
super
interesting.
With
the
advice
around
changing
your
pricing
model
fairly
often,
one
of
the
risks
is
that
that
can
cause
frustration
with
customers
and
then
they
might
churn
because
of
the
sort
of
the
instability
and
it's
less
predictable
for
them
what
their
cost
structure
is
going
to
be.
So,
have
you
got
any
advice
around
like
how
to
Yeah,
so
so
what
what
people
are
doing
and
what
we
also
enable
them
to
do
is
they
sell
credits,
right?
But,
what
do
those
credits
mean?
Like
you
got
in
let's
say
today
in
January
you
had
one
feature
that
was
your
premium
feature.
It
was
not
replicated
anywhere
in
the
market
and
you
had
assigned
five
credits
for
that
feature
under
the
hood,
right?
In
six
months,
that
feature
becomes
standard
feature.
The
pricing
had
dropped
and
in
the
meanwhile
you
brought
in
new
features
because
you
are
also
competing
in
the
market,
right?
So,
for
the
customer,
he
just
see
100
credits.
Under
the
hood,
you
are
changing
these
these
calls
or
permutations
like
what
feature
means
how
many
limits.
So,
the
it
is
remain
transparent
for
the
customer,
it
remains
fair
for
the
customer,
but
based
on
your
product
feature,
you
can
keep
changing
pricing.
Plus,
we
can
we
also
have
features
where
it
allows
you
to
grandfather
pricing
like
you
bring
in
a
new
version.
I
who
have
been
using
it
still
keeps
getting
it
on
the
same
price,
but
the
new
users
have
to
pay
more.
Yes,
please.
At
what
ACV
do
you
start
to
get
better
rates
and
more
of
an
enterprise
management
structure?
Like,
how
how
much
payment
volume
do
I
have
to
do
before
I
can
start
to
get
better
discounts?
So,
again,
more
on
the
sales
side,
but
it
depends
on
the
volume
like
your
payment
volume
and
your
billing
volume.
Basically,
we
like
we
we
have
a
platform.
We
allow
you
to
use
as
much
of
a
platform
as
you
want
or
as
little
of
it
as
you
want,
right?
And
then
depending
on
the
volume
that
is
coming
and
we
we
bring
in
all
together.
Let's
say
you
are
using
uh
payment
and
billing
together
but
not
using
tax,
that
is
fine.
You
bring
your
payment
and
billing
and
then
our
sales
people
start
getting
into
it.
The
sticker
price,
of
course,
is
there
for
everybody
to
see.
I'm
not
really
sure
on
what
is
the
threshold
that
you
know,
start
bringing
the
price
down
because
that's
more
on
the
sales
side,
but
do
come
over
to
our
uh
booth.
We've
got
some
sales
people
there.
They'll
be
able
to
give
you
a
better
answer
to
this.
I've
explained
you
the
mechanism,
but
the
threshold
they'll
be
able
to
answer.
Yes,
please.
Your
thoughts
on
the
presentation
was
really
interesting.
Thank
you.
And
one
thing
I'm
wondering,
how
does
for
example
the
pricing
model
of
like
big
AI
labs
relate
to
this
iterative
pricing?
I
feel
like
AI
labs
often
have
like
multiple
plans
which
have
like
very
constant
pricing.
And
then
like
the
roll
out
of
features
always
happen
first
on
the
expensive
plans
and
then
they
trickle
down
to
like
That
is
true.
the
lower
pricing.
And
I
don't
really
see
like
they
don't
really
use
like
iterative
pricing
in
their
pricing.
No,
no,
they
they
use
it
under
the
hood.
So,
for
them,
for
you,
like
even
if
you
go
to
11
Labs,
you'll
see
four
kind
of
plans
there,
right?
Uh
let
me
call
it
good,
better,
best,
and
then
enterprise,
right?
You
will
just
go
for
you
go
for
the
best,
right?
They
will
keep
adding
features
or
removing
features
from
one
plan
to
the
other.
The
pricing
will
They
will
try
to
remain
constant
with
the
pricing
for
you,
but
inside
it
the
features
will
keep
moving
and
that
is
why
they
want
to
give
it
give
you
credits
or
we
advise
that
you
give
credit
to
the
customer
so
that
the
all
these
features
doesn't
start
interacting
with
pricing.
Okay,
like
the
customer
facing
prices
stay
stay
constant
but
linked
to
which
plan?
Yes,
they
they
let
me
say
not
the
pricing
the
customer
facing
plan
remains
constant,
right?
Price
might
change
again,
but
the
features
will
keep
changing
because
it
has
been
abstracted
by
credits
on
the
top.
Okay.
Right,
that's
it.
Yeah,
you
had
a
question,
sorry.
Um
Yes,
sir.
My
question
is
does
your
platform
provide
like
a
way
to
record
every
transaction
in
your
system
like
>> Every
transaction.
Uh
that
costs
something
and
the
user
we
can
track
it.
Yeah,
so
what
what
we
do
is
like
if
the
prompted
like
you
make
a
prompt,
uh
the
customer
is
ingesting
some
uh
calls,
you
will
send
those
calls
to
us.
You
will
tell
us
like
we
have
all
kind
of
pricing
in
there.
Tiered
pricing,
dynamic
pricing,
uh
dimension-based
pricing.
You
tell
us
what
kind
of
pricing
does
it
go
and
then
it
it
comes
in,
we
are
able
to
rate
it
and
price
it
for
you.
And
then
you
can
get
the
whole
report
on
exactly
why
why
the
invoice
is
what
it
is
so
we
can
give
you
all
the
detailed
pricing.
Right?
Thank
you.
All
right,
if
you
have
any
other
question,
then
please
feel
free
to
come
to
our
booth,
floor
three,
right?
Thank
you
so
much.
>> [applause]
[music]
### 拥抱迭代：将定价视为持续进化的竞争优势
面对AI领域的高速发展，Mayank Pant强调**迭代是核心的竞争优势**。最初设定的价格是一个“假设”，而非“承诺”。随着新功能的每周、每月发布，尤其是当过去的高级功能成为标准时，定价必须随之演进。频繁的价格调整应被视为增长的信号。企业需要建立能够快速迭代的**计费基础设施**，而不是依赖僵化的系统。
他通过一个图表展示，年增长率超过100%的“超高速增长”公司，在过去两年内进行了三次或更多次定价调整。相比之下，低增长公司的定价则相对静态。这表明，静态产品和静态定价在当今时代已不再是理想的生存状态。
这种变化体现在市场趋势上：2024年，**混合定价**（hybrid pricing）的采用率从6%激增至41%，而基于座位、SaaS和订阅的传统定价模式则在下滑。目前，56%的AI公司领导者正在采用**混合定价**。许多企业，如Intercom、Lovable、Eleven Labs、OpenAI和Tropic，都选择在Stripe上构建其计费系统，并普遍采用混合定价。即使是过去主要依赖SaaS定价的公司，在引入AI和LLM技术后，也开始转向混合定价，以避免SaaS模式侵蚀利润。
Original English
So
that
is
why
what
we
say
in
iteration
is
a
competitive
advantage.
The
first
price
that
you
put
in
is
is
a
hypothesis.
It
is
not
a
commitment
because
you
are
bringing
in
new
features
every
week,
every
month
and
with
those
new
features
and
maybe
the
old
premium
features
are
becoming
standard.
So
the
pricing
has
to
evolve
with
the
feature
that
you
put
in,
right?
So
frequent
pricing
change
is
a
signal
of
growth,
right?
You
build
the
infrast-
infrastructure,
you
put
your
pricing
in
the
infrastructure
that
can
iterate
that
allows
you
to
iterate
rapidly,
right?
So
this
chart
is
one
of
my
favorite.
It
shows
that
hypergrowth
companies
which
are
giving
100%
plus
year
on
year
growth,
they
are
changing
their
pricing
three
plus
times
in
the
last
2
years.
They
are
not
standing
with
their
pricing.
49%
is,
you
know,
high
growth.
They
are
they've
changed
three
plus
and
the
low
growth
companies
are
only
22%
who
have
changed
it.
And
that
means
that
those
low
growth
companies
have
a
static
product,
right?
And
that
is
not
where
you
want
to
be
in
today's
age.
So
now
where
are
these
companies
moving,
right?
If
you
look
at
it,
hybrid
pricing
which
was
only
6%
in
2024
is
41%.
Outcome-based
pricing
is
5%,
right?
And
where
it
has
it
picked
up
from?
Se-
seat-based
pricing,
SaaS
pricing,
subscription
pricing
is
all
declining
because
the
models
are
changing.
So
as
I
said,
hybrid
pricing
seven
x
increase
and
now
56%
of
AI
company
leaders
are
using
hybrid
pricing.
Like
we
talked
to
all
the
all
the
companies
such
as
Intercom,
Lovable,
Eleven
Labs,
OpenAI
and
Tropic,
they
are
all
building
on
Stripe,
billing
on
Stripe
and
all
of
them
are
using
hybrid
pricing
and
I've
also
talked
with
companies
who
were
SaaS
companies
so
far
which
used
to
uh
help
customer
build
workflows
and
they
were
in
SaaS
pricing,
but
now
as
soon
as
they
bring
uh
LLM
AI
into
their
product,
then
they
are
also
planning
to
move
on
to
hybrid
pricing
because
SaaS
pricing
then
starts
eroding
their
margins,
right?
### AI定价的五步框架：从价值定义到持续迭代
为了应对AI定价的复杂性，Stripe提出了一个五步框架，指导企业如何科学地制定和演进其定价策略。
**第一步：定义你的价值 (Define Your Value)**
核心在于理解客户如何感知你的产品所提供的价值，而非仅仅描述产品功能。例如，用户使用Gamma工具是为了获得演示文稿，而不是关心其背后的API调用。**价值定义**应关注客户能获得的实际结果，如**自动化**（节省成本）、**增强**（提高效率和质量）、**增强服务**（访问专有数据或软件）或**改进结果**（直接影响底线，如Intercom解决的工单数量）。研究表明，提供清晰、客户易于理解的价值定价是**超高速增长**公司的关键。
**第二步：定义计费指标 (Define Your Charge Metric)**
选择一个能最佳代表产品价值的可计费单位。这可以是**基于消耗的 (consumption-based)**（如API调用次数，与公司成本挂钩，易于实施但难与价值对齐），**基于工作流的 (workflow-based)**（如生成的图片数量，与产品产出挂钩），或是**基于结果的 (outcome-based)**（如带来的业务成果、招聘数量、合格线索，与客户ROI直接关联，易于销售但难精确归因）。一个重要的技巧是将价值**翻译成客户理解的“积分”或“信用”**，使客户能够掌握其花费并预估ROI。
**第三步：选择定价模型 (Pick Your Pricing Model)**
模型选择需平衡公司收益和客户体验。**订阅费/SaaS费**提供可预测收入和客户承诺，但可能被“能力用户”侵蚀利润。**使用费**可随客户使用量扩展并保护利润，但可能让客户因账单不确定性而犹豫尝试。因此，**混合模型 (hybrid model)**成为主流，它结合了**基础费用**（建立客户关系）和**可扩展/使用费用**（鼓励尝试，按实际价值付费），从而不疏远任何类别的用户。
**第四步：构建价格护栏 (Build Guardrails)**
确保计费的公平性和可预测性，避免因意外高额账单损害客户信任。关键措施包括：
* **使用上限 (Usage Caps)**：设定明确的消费额度，超出部分需额外付费或暂停服务，让客户掌控消费。
* **自动化通知 (Automated Notifications)**：在用户达到50%、70%、90%的额度时发送提醒，建立信任。
* **速率限制 (Rate Limiting)**：防止错误代码或异常流量消耗过多的资源，保护双方。
**第五步：持续迭代与价值对齐 (Iterate and Realign to Value)**
定价是一个持续演进的过程。初始定价是假设，需要不断根据产品发展和客户反馈进行调整。**优先考虑速度**，快速推出定价并根据客户反馈（如流失原因、产品-市场契合度）进行迭代。通过AB测试优化定价点。同时，即便采用混合定价和积分模式，也可在“幕后”调整积分的实际含义，使定价始终与客户感知到的核心价值保持一致。
Original English
So
to
if
if
this
is
where
we
are
going,
then
how
do
we
start
thinking
about
pricing?
How
do
we
come
to
a
right
price?
How
do
we
define
our
price?
And
how
then
do
we
iterate
it?
So
the
we've
got
a
five-step
uh
a
five-step
framework
for
this
and
the
step
one
of
that
framework
is
you
define
your
value,
right?
So
what
type
of
value
can
my
product
provide?
But
not
what
your
product
is
doing,
but
what
the
what
the
customer
perceives
your
product
to
do.
Like
again,
like
I
took
an
example
of
Gamma.
For
me
as
a
customer,
I
need
that
product
to
give
me
my
presentation,
my
decks.
I
don't
care
underneath
how
many
API
calls
is
it
making,
where
is
it
going.
My
uh
for
the
for
the
customer
it
is
the
quality
of
the
deck
and
the
relevancy
of
that
deck
deck.
So
53%
of
hypergrowth
companies
have
offered
clear
value-based
pricing
that
the
customer
understands
versus
just
26%
of
low
growth
peers.
And
the
way
we
look
at
it
is
uh
there
are
four
broad
frameworks
on
which
the
first
kind
of
these
companies
are
the
company
that
are
providing
automation.
Like
like
I
uh
as
a
company
I'm
helping
them
to
save
time
and
as
a
customer
what
they
are
looking
at
it
is,
okay,
with
the
time
saved
I'm
saving
on
the
cost,
right?
Second
is
augmentation.
The
number
of
people
remain
the
same,
but
the
quality
that
they
come
out
with
is
much
better.
Like
they
can
produce
images
better.
Probably
for
a
campaign
provider
they
can
build
in
better
campaigns
more
quicker.
So
they
uh
those
kind
of
augmentation
the
company
looks
at
it
is,
okay,
I
have
the
same
number
of
people,
but
they
are
more
efficient,
they
can
deliver
more
value,
right?
Third
is
the
enhanced
service.
Maybe
it
gives
you
an
access
to
a
proprietary
software
or
some
new
uh
data
set
that
you
wouldn't
have
access
otherwise,
right?
For
example,
if
you
look
at
it
look
at
Stripe
and
our
payment
infrastructure,
we
can
uh
do
fraud
recognition
much
better
because
of
the
volume
that
flow
through
us,
right?
And
finally,
the
fourth
kind
of
one
is
the
which
gives
you
an
improved
results.
Like
for
example,
company
like
Intercom
who
says,
I
will
price
you
based
on
the
number
of
tickets
that
I
solved
without
human
need.
So
that
is
impacting
the
direct
bottom
line.
So
once
we
realize
how
we
are
helping
the
customers,
how
our
customer
perceive
it,
that
is
when
we
know
the
value
and
we
know
the
price
that
we
can
command
in
the
market.
Once
we've
understood
this
is
the
value
that
we
are
providing,
then
you
define
your
charge
metric.
Like
what
is
the
billable
unit
that
is
best
representing
my
value,
right?
And
then
you
build
features
into
a
currency
that
customers
understand.
For
example,
is
it
consumption-based?
Like
for
an
infrastructure
company,
consumption-based
might
be
the
right
one.
Like
how
many
API
calls
did
I
help
you
to
make,
right?
And
this
aligns
to
the
cost
of
the
company
that
is
providing
that
service.
Second
could
be
the
workflow-based.
Like
how
many
images
that
was
I
able
to
generate?
How
many
documents
was
I
able
to
summarize?
And
this
aligns
to
the
product,
and
the
third
is
the
outcome-based
as
I
said.
How
many
business
results
did
I
generate?
So
if
if
I
am
helping
the
company
to
hire
people,
how
many
uh
candidate
that
I
have
put
forward?
How
many
candidates
were
hired
out
of
those
candidates
resulting
in
saving
time?
Or
how
many
qualified
leads
did
I
generate?
Right?
So,
this
aligns
to
your
customer
ROI.
So,
now
that
you've
understood
the
value
that
you're
providing
and
you've
decided
your
charge
metric
against
it,
we
will
we
will
see
how
they
change
it,
right?
Like
if
you
move
from
consumption-based
to
outcome-based,
it
is
definitely
easier
to
implement
consumption-based
is
much
easier
to
implement.
But,
it
is
harder
to
align
to
value.
Like
if
I
if
some
company
tells
me
and
says,
"I
allowed
you
1,000
API
calls.
I
do
not
know
what
those
1,000
API
calls
mean.
I
want
to
see
how
many
decks
I
generated
as
in
my
previous
example."
But,
if
you
go
from
outcome-based
to
consumption-based,
it
is
easier
to
sell.
Like
I
can
definitely
go
to
a
customer
and
say,
"I
will
increase
your
outcome.
I'll
increase
your
uh
candidate
hired,
but
to
attribute
value
is
difficult."
So,
that
is
where
the
balance
has
to
be
made
and
data
is
required
to
satisfy
and
to
make
your
case.
One
of
the
pro
tip
is
to
translate
value
with
credit.
Like
bundle
the
features
into
credits.
Say
that
"I
am
giving
you
100
credits
for
the
month.
And
then
beneath
under
the
hood
of
the
credits,
you
can
have
your
own
models
how
you
get
to
that."
But,
that
helps
the
customer
to
understand,
"Okay,
100
credits
and
it
will
translate
to
uh
this
particular
ROI."
Once
you've
done
that,
then
that
is
where
you
pick
your
pricing
model.
Now,
is
it
a
subscription
fee?
The
usefulness
of
subscription
fee
or
SaaS
fee
is
predictable
revenue.
It
gives
you
a
committed
customer
relationship.
Right?
How
And
then
the
second
could
be
the
usage
fee,
which
scales
with
customer
with
protects
margins.
But,
the
downside
as
I
said
is
for
the
SaaS
fee,
uh
your
power
users
might
burn
your
margins.
And
for
a
usage
fee,
uh
the
customer
might
be
hesitant
in
experimenting
with
your
product.
Like
going
full
deep
because
they
do
not
know
what
kind
of
a
invoice
will
they
uh
expend
on
this.
So,
pure
subscription,
pure
usage-based
was
a
thing
of
the
past.
Now,
as
we
saw
in
the
previous
slides
as
well,
everybody
is
moving
into
the
hybrid
model.
So,
what
is
the
hybrid
model?
A
hybrid
model
will
have
a
base
fee
and
it
will
have
a
scaling
fee.
The
base
fee
basically
helps
you
to
establish
a
relationship
with
your
customer.
And
the
scaling
fee
or
the
usage
fee
on
top
of
it
will
allow
them
to
experiment
as
much
as
they
want
and
then
to
pay
for
the
value
that
they
derive
out
of
your
platform.
So,
you
are
not
alienating
any
of
the
user
any
category
of
the
users.
Once
you've
established
your
uh
pricing,
then
you
build
in
the
guardrails
because
a
wrong
bill
can
erode
a
lot
of
customer
trust.
You
might
be
doing
great
for
the
three,
four,
five
months,
but
if
the
on
the
sixth
month
your
bill
goes
wrong,
bill
goes
very
high,
then
that
those
customers
go
and
then
you
work
so
hard
to
retain
those
customers,
but
then
they
leave
you.
So,
what
safety
feature
do
you
consider?
Like
you
are
giving
them
flexible
pricing.
Now,
you're
building
guardrails
around
it,
right?
As
the
design
principle
is
fair
it's
simple
here.
Build
fair
pricing,
but
then
do
not
surprise.
So,
what
what
we
what
we
advise
people
to
do
is
put
in
usage
caps.
Like
I
paid
$20
and
then
I've
been
given
100
credits.
I
say
that
after
100
credits,
I've
built
in
a
usage
cap.
You
either
pay
more
to
go
ahead
or
we
will
stop
and
you
wait
for
the
next
month.
So,
that
the
it
is
the
customer
that
has
remained
in
control
of
their
uh
usages.
Right?
You
build
an
automated
notification.
You
tell
them
when
they've
used
50%,
70%,
90%
of
uh
of
their
allocated
limits
because
this
is
building
trust
with
the
customer.
We
are
not
trying
to
uh
cheat
them.
We
are
there
trying
to
inform
them
that
this
is
what
you've
used.
These
are
the
uh
thing
that
you
can
go
ahead
with
now.
You
can
top
up.
You
can
do
a
manual
top
up.
You
can
do
an
auto
top
up.
Or
you
can
pause
and
then
start
the
next
month
when
fresh
credits
gets
allocated
to
you.
And
then
you
set
rate
limiting
so
that
no
wrong
code
is
burning
through
the
limits,
right?
So,
this
will
protect
you
and
your
customers
both.
Once
you've
done
these
step
one
to
four,
then
the
step
five
is
you
iterate,
right?
You
keep
iterating.
84%
agree
that
fast
pricing
adaptation
is
a
key
competitive
advantage.
As
I
said,
your
first
model
is
a
hypothesis
and
you
keep
building
on
that
pricing
as
your
product
keeps
evolving.
You
prioritize
speed.
You
do
not
wait
for
the
right
price
right
price
point
and
wait
for
a
year
before
you
put
it.
You
put
a
price
point
there
which
you
think
is
the
right
price
point
and
then
you
iterate.
You
talk
to
your
customers.
Those
guys
who
churn,
you
talk
to
them
and
ask
them
why
they
are
churning.
Is
it
a
product-market
fit?
Which
is
then
you
work
on
your
product.
But,
is
it
high
price?
Then
you
work
on
your
pricing.
Right?
If
they
upgrade,
you
ask
the
same
questions.
You
run
AB
tests
on
pricing
to
find
the
optimum
point,
but
you
prioritize
speed
and
you
keep
iterating.
And
then
you
continuously
realign
to
your
value.
Now,
realigning
to
the
value
means
as
you
are
rolling
out
new
features,
you've
already
given
them
hybrid
pricing.
You've
already
put
in
number
of
credits.
Under
the
hood,
you
can
keep
changing
what
those
credits
means.
Do
do
those
100
credit
that
you've
given
them
means
five
API
calls
of
a
certain
category,
10
image
generation
of
a
certain
category?
Whatever.
So,
under
the
hood
you
can
keep
changing
them.
But,
you
constantly
realign
the
value.
So,
this
is
how
all
the
companies
have
been
thinking
about
pricing.
This
is
how
we've
been
uh
trying
to
help
them.
But,
what
is
most
important
in
all
this
is
what
kind
of
an
infrastructure
do
you
have
for
your
billing,
for
your
pricing
that
is
helping
you
to
do
this?
If
every
change
costs
you
three
months,
four
months,
and
a
lot
of
engineering
effort,
then
it
is
not
worth
it.
So,
that
is
why
it
the
infrastructure
you
choose
determine
how
fast
you
can
iterate.
And
uh
from
our
side,
the
most
flexible
and
complete
billing
solution
in
market
is
we've
got
Stripe
and
it
is
not
us
that
is
saying
it.
78%
of
AI
companies
are
building
on
Stripe,
which
is
a
testimony
in
itself.
Most
of
the
AI
companies
that
you
see
here
are
building
on
Stripe
like
I
said,
Anthropic,
OpenAI,
Lovable,
Eleven
Labs,
Intercom.
They're
all
launching
their
billing
and
pricing.
You
might
have
associated
Stripe
with
payments
only,
but
in
the
last
two,
three
years
we've
uh
we've
invested
a
lot
into
AI
billing.
So,
we've
got
Stripe
Stripe
billing
which
allows
you
to
go
with
subscription
pricing,
usage
pricing,
hybrid
pricing.
And
as
these
companies
are
so
quickly
within
10
to
15
months
now
starting
with
the
retail
PLG
motion
going
to
enterprises,
we've
got
Metronome
that
allows
you
to
build
all
the
all
the
dif-
difficult
and
complicated
contracts
with
the
enterprises
having
minimum
commitments,
uh
pre-commitments,
uh
overage
prices.
So,
we've
got
that
and
we've
got
the
whole
platform
that
allows
you
to
do
uh
payments,
tax,
invoicing,
revenue
recognition
on
this
AI
pricing.
So,
yeah,
this
is
where
we
are
right
now
helping
all
our
AI
companies
in
the
market.
So,
yeah,
this
this
is
me
happy
for
any
questions
that
you
have.
Yes,
please.
This
is
super
interesting.
With
the
advice
around
changing
your
pricing
model
fairly
often,
one
of
the
risks
is
that
that
can
cause
frustration
with
customers
and
then
they
might
churn
because
of
the
sort
of
the
instability
and
it's
less
predictable
for
them
what
their
cost
structure
is
going
to
be.
So,
have
you
got
any
advice
around
like
how
to
Yeah,
so
so
what
what
people
are
doing
and
what
we
also
enable
them
to
do
is
they
sell
credits,
right?
But,
what
do
those
credits
mean?
Like
you
got
in
let's
say
today
in
January
you
had
one
feature
that
was
your
premium
feature.
It
was
not
replicated
anywhere
in
the
market
and
you
had
assigned
five
credits
for
that
feature
under
the
hood,
right?
In
six
months,
that
feature
becomes
standard
feature.
The
pricing
had
dropped
and
in
the
meanwhile
you
brought
in
new
features
because
you
are
also
competing
in
the
market,
right?
So,
for
the
customer,
he
just
see
100
credits.
Under
the
hood,
you
are
changing
these
these
calls
or
permutations
like
what
feature
means
how
many
limits.
So,
the
it
is
remain
transparent
for
the
customer,
it
remains
fair
for
the
customer,
but
based
on
your
product
feature,
you
can
keep
changing
pricing.
Plus,
we
can
we
also
have
features
where
it
allows
you
to
grandfather
pricing
like
you
bring
in
a
new
version.
I
who
have
been
using
it
still
keeps
getting
it
on
the
same
price,
but
the
new
users
have
to
pay
more.
Yes,
please.
At
what
ACV
do
you
start
to
get
better
rates
and
more
of
an
enterprise
management
structure?
Like,
how
how
much
payment
volume
do
I
have
to
do
before
I
can
start
to
get
better
discounts?
So,
again,
more
on
the
sales
side,
but
it
depends
on
the
volume
like
your
payment
volume
and
your
billing
volume.
Basically,
we
like
we
we
have
a
platform.
We
allow
you
to
use
as
much
of
a
platform
as
you
want
or
as
little
of
it
as
you
want,
right?
And
then
depending
on
the
volume
that
is
coming
and
we
we
bring
in
all
together.
Let's
say
you
are
using
uh
payment
and
billing
together
but
not
using
tax,
that
is
fine.
You
bring
your
payment
and
billing
and
then
our
sales
people
start
getting
into
it.
The
sticker
price,
of
course,
is
there
for
everybody
to
see.
I'm
not
really
sure
on
what
is
the
threshold
that
you
know,
start
bringing
the
price
down
because
that's
more
on
the
sales
side,
but
do
come
over
to
our
uh
booth.
We've
got
some
sales
people
there.
They'll
be
able
to
give
you
a
better
answer
to
this.
I've
explained
you
the
mechanism,
but
the
threshold
they'll
be
able
to
answer.
Yes,
please.
Your
thoughts
on
the
presentation
was
really
interesting.
Thank
you.
And
one
thing
I'm
wondering,
how
does
for
example
the
pricing
model
of
like
big
AI
labs
relate
to
this
iterative
pricing?
I
feel
like
AI
labs
often
have
like
multiple
plans
which
have
like
very
constant
pricing.
And
then
like
the
roll
out
of
features
always
happen
first
on
the
expensive
plans
and
then
they
trickle
down
to
like
That
is
true.
the
lower
pricing.
And
I
don't
really
see
like
they
don't
really
use
like
iterative
pricing
in
their
pricing.
No,
no,
they
they
use
it
under
the
hood.
So,
for
them,
for
you,
like
even
if
you
go
to
11
Labs,
you'll
see
four
kind
of
plans
there,
right?
Uh
let
me
call
it
good,
better,
best,
and
then
enterprise,
right?
You
will
just
go
for
you
go
for
the
best,
right?
They
will
keep
adding
features
or
removing
features
from
one
plan
to
the
other.
The
pricing
will
They
will
try
to
remain
constant
with
the
pricing
for
you,
but
inside
it
the
features
will
keep
moving
and
that
is
why
they
want
to
give
it
give
you
credits
or
we
advise
that
you
give
credit
to
the
customer
so
that
the
all
these
features
doesn't
start
interacting
with
pricing.
Okay,
like
the
customer
facing
prices
stay
stay
constant
but
linked
to
which
plan?
Yes,
they
they
let
me
say
not
the
pricing
the
customer
facing
plan
remains
constant,
right?
Price
might
change
again,
but
the
features
will
keep
changing
because
it
has
been
abstracted
by
credits
on
the
top.
Okay.
Right,
that's
it.
Yeah,
you
had
a
question,
sorry.
Um
Yes,
sir.
My
question
is
does
your
platform
provide
like
a
way
to
record
every
transaction
in
your
system
like
>> Every
transaction.
Uh
that
costs
something
and
the
user
we
can
track
it.
Yeah,
so
what
what
we
do
is
like
if
the
prompted
like
you
make
a
prompt,
uh
the
customer
is
ingesting
some
uh
calls,
you
will
send
those
calls
to
us.
You
will
tell
us
like
we
have
all
kind
of
pricing
in
there.
Tiered
pricing,
dynamic
pricing,
uh
dimension-based
pricing.
You
tell
us
what
kind
of
pricing
does
it
go
and
then
it
it
comes
in,
we
are
able
to
rate
it
and
price
it
for
you.
And
then
you
can
get
the
whole
report
on
exactly
why
why
the
invoice
is
what
it
is
so
we
can
give
you
all
the
detailed
pricing.
Right?
Thank
you.
All
right,
if
you
have
any
other
question,
then
please
feel
free
to
come
to
our
booth,
floor
three,
right?
Thank
you
so
much.
>> [applause]
[music]
### Stripe的解决方案：构建灵活且完整的AI计费基础设施
Mayank Pant在回答关于定价模型演进和客户担忧时，着重强调了**灵活的计费基础设施**的重要性。他指出，如果每一次定价调整都需要数月甚至大量工程投入，那么这种模式将难以持续。因此，选择正确的计费基础设施是实现快速迭代和保持竞争力的关键。
Stripe凭借其在支付领域的深厚积累，已大力投资于**AI计费**领域，提供了一个“最灵活和完整的解决方案”。目前，78%的AI公司选择在Stripe上构建其计费系统，这本身就是一项有力的证明。众多知名AI公司，如Anthropic、OpenAI、Lovable、Eleven Labs和Intercom，都在使用Stripe进行计费和定价。
Stripe提供的解决方案包括：
* **Stripe Billing**：支持订阅、使用量和混合定价模型。
* **Metronome**：为企业提供复杂的合同管理能力，包括最低承诺、预付款和超额价格等。
* **全面的平台**：支持支付、税务、发票和收入确认等一站式服务。
在Q&A环节，当被问及如何缓解频繁价格调整给客户带来的不确定性时，Mayank Pant解释说，公司通过**销售积分（credits）**来实现客户体验的稳定。客户看到的“100个积分”在内部可以代表不同的功能组合或API调用量，允许企业在不改变客户界面价格的情况下，根据产品迭代和价值变化调整后台的“积分含义”。这种方式确保了对客户的**透明和公平**。此外，Stripe还支持“**保留旧定价（grandfather pricing）**”策略，允许老用户继续享受原有价格，而新用户则采用新定价。
关于企业客户的**ACV（年合同价值）和折扣**，Mayank Pant表示这更多取决于**支付和账单的总体量**。Stripe平台本身允许客户按需使用，其销售团队可以根据具体情况提供更详细的折扣阈值信息。
对于大型AI实验室的定价模式，Mayank Pant解释说，它们同样在使用**迭代定价**，只是将其“置于幕后”。例如，Eleven Labs提供不同层级的套餐（Good, Better, Best, Enterprise），客户看到的是固定的套餐价格，但套餐内的**功能会随着产品演进而调整**，并通过积分系统进行抽象，以保持客户面前价格的稳定性。
最后，当被问及平台是否支持记录和追踪每一笔产生费用的交易时，Mayank Pant确认Stripe可以做到。无论是用户输入的提示（prompt）、API调用，还是其他计费动作，Stripe都能将其转化为**分级、动态或基于维度的定价**，并提供详细的**账单报告**，清晰展示每一笔费用的构成。
Original English
And
uh
from
our
side,
the
most
flexible
and
complete
billing
solution
in
market
is
we've
got
Stripe
and
it
is
not
us
that
is
saying
it.
78%
of
AI
companies
are
building
on
Stripe,
which
is
a
testimony
in
itself.
Most
of
the
AI
companies
that
you
see
here
are
building
on
Stripe
like
I
said,
Anthropic,
OpenAI,
Lovable,
Eleven
Labs,
Intercom.
They're
all
launching
their
billing
and
pricing.
You
might
have
associated
Stripe
with
payments
only,
but
in
the
last
two,
three
years
we've
uh
we've
invested
a
lot
into
AI
billing.
So,
we've
got
Stripe
Stripe
billing
which
allows
you
to
go
with
subscription
pricing,
usage
pricing,
hybrid
pricing.
And
as
these
companies
are
so
quickly
within
10
to
15
months
now
starting
with
the
retail
PLG
motion
going
to
enterprises,
we've
got
Metronome
that
allows
you
to
build
all
the
all
the
dif-
difficult
and
complicated
contracts
with
the
enterprises
having
minimum
commitments,
uh
pre-commitments,
uh
overage
prices.
So,
we've
got
that
and
we've
got
the
whole
platform
that
allows
you
to
do
uh
payments,
tax,
invoicing,
revenue
recognition
on
this
AI
pricing.
So,
yeah,
this
is
where
we
are
right
now
helping
all
our
AI
companies
in
the
market.
So,
yeah,
this
this
is
me
happy
for
any
questions
that
you
have.
Yes,
please.
This
is
super
interesting.
With
the
advice
around
changing
your
pricing
model
fairly
often,
one
of
the
risks
is
that
that
can
cause
frustration
with
customers
and
then
they
might
churn
because
of
the
sort
of
the
instability
and
it's
less
predictable
for
them
what
their
cost
structure
is
going
to
be.
So,
have
you
got
any
advice
around
like
how
to
Yeah,
so
so
what
what
people
are
doing
and
what
we
also
enable
them
to
do
is
they
sell
credits,
right?
But,
what
do
those
credits
mean?
Like
you
got
in
let's
say
today
in
January
you
had
one
feature
that
was
your
premium
feature.
It
was
not
replicated
anywhere
in
the
market
and
you
had
assigned
five
credits
for
that
feature
under
the
hood,
right?
In
six
months,
that
feature
becomes
standard
feature.
The
pricing
had
dropped
and
in
the
meanwhile
you
brought
in
new
features
because
you
are
also
competing
in
the
market,
right?
So,
for
the
customer,
he
just
see
100
credits.
Under
the
hood,
you
are
changing
these
these
calls
or
permutations
like
what
feature
means
how
many
limits.
So,
the
it
is
remain
transparent
for
the
customer,
it
remains
fair
for
the
customer,
but
based
on
your
product
feature,
you
can
keep
changing
pricing.
Plus,
we
can
we
also
have
features
where
it
allows
you
to
grandfather
pricing
like
you
bring
in
a
new
version.
I
who
have
been
using
it
still
keeps
getting
it
on
the
same
price,
but
the
new
users
have
to
pay
more.
Yes,
please.
At
what
ACV
do
you
start
to
get
better
rates
and
more
of
an
enterprise
management
structure?
Like,
how
how
much
payment
volume
do
I
have
to
do
before
I
can
start
to
get
better
discounts?
So,
again,
more
on
the
sales
side,
but
it
depends
on
the
volume
like
your
payment
volume
and
your
billing
volume.
Basically,
we
like
we
we
have
a
platform.
We
allow
you
to
use
as
much
of
a
platform
as
you
want
or
as
little
of
it
as
you
want,
right?
And
then
depending
on
the
volume
that
is
coming
and
we
we
bring
in
all
together.
Let's
say
you
are
using
uh
payment
and
billing
together
but
not
using
tax,
that
is
fine.
You
bring
your
payment
and
billing
and
then
our
sales
people
start
getting
into
it.
The
sticker
price,
of
course,
is
there
for
everybody
to
see.
I'm
not
really
sure
on
what
is
the
threshold
that
you
know,
start
bringing
the
price
down
because
that's
more
on
the
sales
side,
but
do
come
over
to
our
uh
booth.
We've
got
some
sales
people
there.
They'll
be
able
to
give
you
a
better
answer
to
this.
I've
explained
you
the
mechanism,
but
the
threshold
they'll
be
able
to
answer.
Yes,
please.
Your
thoughts
on
the
presentation
was
really
interesting.
Thank
you.
And
one
thing
I'm
wondering,
how
does
for
example
the
pricing
model
of
like
big
AI
labs
relate
to
this
iterative
pricing?
I
feel
like
AI
labs
often
have
like
multiple
plans
which
have
like
very
constant
pricing.
And
then
like
the
roll
out
of
features
always
happen
first
on
the
expensive
plans
and
then
they
trickle
down
to
like
That
is
true.
the
lower
pricing.
And
I
don't
really
see
like
they
don't
really
use
like
iterative
pricing
in
their
pricing.
No,
no,
they
they
use
it
under
the
hood.
So,
for
them,
for
you,
like
even
if
you
go
to
11
Labs,
you'll
see
four
kind
of
plans
there,
right?
Uh
let
me
call
it
good,
better,
best,
and
then
enterprise,
right?
You
will
just
go
for
you
go
for
the
best,
right?
They
will
keep
adding
features
or
removing
features
from
one
plan
to
the
other.
The
pricing
will
They
will
try
to
remain
constant
with
the
pricing
for
you,
but
inside
it
the
features
will
keep
moving
and
that
is
why
they
want
to
give
it
give
you
credits
or
we
advise
that
you
give
credit
to
the
customer
so
that
the
all
these
features
doesn't
start
interacting
with
pricing.
Okay,
like
the
customer
facing
prices
stay
stay
constant
but
linked
to
which
plan?
Yes,
they
they
let
me
say
not
the
pricing
the
customer
facing
plan
remains
constant,
right?
Price
might
change
again,
but
the
features
will
keep
changing
because
it
has
been
abstracted
by
credits
on
the
top.
Okay.
Right,
that's
it.
Yeah,
you
had
a
question,
sorry.
Um
Yes,
sir.
My
question
is
does
your
platform
provide
like
a
way
to
record
every
transaction
in
your
system
like
>> Every
transaction.
Uh
that
costs
something
and
the
user
we
can
track
it.
Yeah,
so
what
what
we
do
is
like
if
the
prompted
like
you
make
a
prompt,
uh
the
customer
is
ingesting
some
uh
calls,
you
will
send
those
calls
to
us.
You
will
tell
us
like
we
have
all
kind
of
pricing
in
there.
Tiered
pricing,
dynamic
pricing,
uh
dimension-based
pricing.
You
tell
us
what
kind
of
pricing
does
it
go
and
then
it
it
comes
in,
we
are
able
to
rate
it
and
price
it
for
you.
And
then
you
can
get
the
whole
report
on
exactly
why
why
the
invoice
is
what
it
is
so
we
can
give
you
all
the
detailed
pricing.
Right?
Thank
you.
All
right,
if
you
have
any
other
question,
then
please
feel
free
to
come
to
our
booth,
floor
three,
right?
Thank
you
so
much.
>> [applause]
[music]