(upbeat music)
Welcome, everybody. (music ending)
So great to see
so many faces in the audience.
I hope you are all having
an awesome Sessions so far.
(audience applauding)
All right, I’m Sharmeen Browarek Chapp,
and I lead our Revenue
and Finance Automation product team
here at Stripe.
Over my time here,
I have witnessed all types of companies
test and adopt unique
and innovative pricing strategies.
In fact, earlier this year,
one example that drew
the interest of our team
and was also a very lively discussion
in our Slack channels was,
drum roll, please.
Applebee's.
Yes, you heard me right, Applebee's.
It totally took me back
to my college days,
sharing a triple chocolate lava cake
with my friends.
So what they did in this instance was
that they created
a date night pass subscription
that sold out in less than one minute.
And normally
that type of feverish enthusiasm
is made for exclusive drops,
coveted events,
or in my case,
Taylor Swift Eras Tour tickets.
And yes, I did score a pair.
And it's not just restaurants
that are doing this.
We’re seeing all types of companies,
like Instacart,
for example, is offering memberships
that are giving their customers perks
like unlimited free delivery,
lower service fees,
getting credit back, and for all of this,
they’re using Stripe to do so.
And beyond direct-to-consumer,
we’re also seeing businesses
across a variety of segments
and geographies
who are disrupting their industries
with dynamic pricing.
As AI continues to evolve,
B2B companies are also experimenting
with innovative pricing models.
Notably Intercom, who you’re going
to be hearing from later in this session,
recently launched their AI chatbot, Fin,
on a resolution-based pricing model.
That means that they’re charging
customers only
when Fin successfully
resolves a support issue.
So we know that pricing changes
can be difficult,
and that's why we’ve built
our product, Stripe Billing.
We want to provide our customers
with the flexibility
to accommodate usage-based, seat-based,
and subscription-based pricing.
And it goes beyond our
customers at Stripe.
We’re always trying to gather feedback
from our users and our sales teams
to hear how the market
is feeling about pricing.
And we’re thinking about pricing a lot,
but no one thinks about it
more than our next speaker,
Bill Bedsworth.
Bill brings a wealth of experience
in pricing pivots,
and I have the pleasure
of working with him very closely.
Please welcome to the stage,
Bill Bedsworth.
(upbeat music) (audience applauding)
(music ending)
Thank you, Sharmeen.
As Sharmeen mentioned,
I run pricing at Stripe.
It's a little bit dangerous
to give the pricing guy the stage.
I might not give it back,
but I’m here.
I have the pleasure to talk
a little bit about some
of the things I’ve learned
over the years
doing pricing for a number
of different companies.
I’ve worked over 25 years now in pricing-
related fields, starting with
some consulting.
Then Adobe,
I ran the pricing function at Zendesk,
and now at Stripe.
And if there's one key learning
from all those years
doing pricing,
it's that you’re never
actually done with pricing.
I find it's a little bit like
org structure
in that there's not really one answer.
There's a bunch of trade-offs,
a bunch of back and forth.
You know, you can solve one thing,
you create other problems.
And so pricing tends to be iterative
and something that you’re never
quite finished with.
Another theme, though, is that, you know,
we all know that pricing
can drive the bottom line.
We used price increases to drive profits,
but pricing can actually be
an important driver for growth
and can help you stand out in the field.
And that's what I wanted to talk
a little bit about today.
So I’m lucky enough to share,
kind of, a few lessons
that I’ve learned over the years,
and hopefully you'll be able
to apply those to your own business.
The first lesson I want to share
is that you should do your best
to minimize the barrier to entry.
So, this is something that
can be really easy to overlook.
You know, we always think
about, the competitive environment,
our own products,
the market willingness to pay,
but barrier to entry can actually
be a really important aspect to consider.
When I was at Adobe,
we made certainly
the biggest pricing pivot
Adobe's ever made.
Arguably one one of the biggest in history
when we shifted from Creative Suite
to Creative Cloud,
which is a perpetual license model,
moving to subscription.
It seems obvious now,
there are so many subscription models
these days.
As a matter of fact,
they wrote an Harvard Business School
case about this.
I’ve talked to some of the professors,
and they mentioned
it's a completely useless
case for teaching,
because students at this point
are just asking like,
“Why didn't Adobe do this earlier?
This seems so obvious.”
I can assure you it was not
obvious at the time.
As matter of fact,
the first time I pitched this
to one of the key business leaders,
he told me this was the stupidest idea
he'd ever heard.
Obviously we got past that.
And the way we got past that
was actually less about
the transition to subscription
and more about this idea
of barrier to entry.
So it started with a pilot,
as all good things do,
in Australia—
apologies to the Australians—
you probably see all kinds
of crazy pricing.
But
what happened in that pilot,
and it wasn't a great pilot, mind you,
but what we did learn was
that 50% of the people
who bought Creative Cloud on this pilot
had never purchased anything
from Adobe before.
Turns out, a couple of thousand dollars
is a pretty big barrier to entry
for a piece of software,
and $50 for our month to try it out
is less so.
And so this was important
at the time for Adobe,
because
we had kind of saturated the market
in terms of the people
who needed Creative Suite,
had Creative Suite,
and in addition,
there were a bunch of new products
coming out that could do a piece
of what Creative Suite could do
far cheaper.
And so Adobe was seeing
a lot more competition
in this area than they had in the past.
And so by introducing this new model
and reducing the barrier to entry,
Adobe was able to get a lot more customers
who they never would have had access
to before.
This is something that
we’re seeing now kind of revisited
when you think about something like AI.
You know, AI is something that is new,
and so if the barrier to entry
is too high,
people aren't going to adopt it
or give it a try.
And Darragh, who's going to come up
and talk in a little bit,
has done some interesting things
with their pricing of AI
and pricing it in a way that it
has extremely low barrier to entry
and really anybody can give it a try.
So, you know, coming back to this idea,
minimizing barrier to entry
is a really important point.
And it doesn't have to be
a huge move like Adobe did.
This can be something as simple
as laddering your products,
so that there is a kind of low entry point
as well as further points.
You know, things like that
that help people kind of
get into the product.
Second lesson,
opt for simplicity.
I’m here to tell you, nobody thinks
about your product as much as you do.
It's just kind of the way it is.
And so when a customer comes to you,
they need you to tell them
how to configure their product
and what they should be buying
and you should help them.
So for example here, when I came to Zendesk,
Zendesk was employing
what I would have called
an atomized pricing model,
very customizable.
There were a number of different products.
Each of those products
had three or four tiers.
There were probably 20 something add-ons.
So you could create
whatever customer service platform you
needed, which is great.
The problem is our customers didn't know
what customer service
platform they needed.
And so when they came to the website
and saw all these choices,
they got overwhelmed.
There were 4,000 different combinations
of the product that you could configure.
Yikes, right?
And so in addition to being overwhelming,
we would consistently hear from customers,
“Oh, we had to leave Zendesk,
because you didn't have this feature.”
When in actuality
we did have that feature.
They had just configured the product
in such a way that they
didn't have that feature.
So in addition to overwhelming them,
we were actually preventing them
from getting the customer service
solution they needed.
So, in an effort to be
more customer friendly
and more competitive,
we decided to simplify.
So it took a lot of collaboration,
a lot of product work,
a lot of work with our sales teams.
But we went from
4,000 different product combinations
to 5.
Go to the website at Zendesk,
now there are five solutions,
five suites.
And this was hard, right?
Like I said, it took a lot of analytics
trying to fit 4,000 different combinations
of existing customers into these 5.
You know, it involved
a lot of understanding
of our customers
and involved some faith.
As a matter of fact,
when we went live with this,
we turned it on on a Friday,
and I spent most of my weekend
texting back
and forth with our COO,
who was fairly convinced
I'd broken the business.
Luckily that wasn't true
for me and for Zendesk.
As it turns out, customers loved it.
The number one thing
that we heard from them is,
it's so much easier to figure out
what product I need to buy from you.
Deal cycles got shorter.
Volume on the website went up.
It was a huge success.
So much so that one of our key competitors
copied it probably about six months
after we introduced it.
So, keep in mind this idea of simplicity,
less can be more.
Try to help your customers
figure out what they need.
I will say in perfect
transparency and honesty,
this is somewhere at Stripe,
we’re still working on it, right?
You know the idea,
you’re always working on pricing.
This is an area where
we’re trying to improve.
Lesson three,
sometimes you have to go low to go high.
I keep saying this is hard,
this is really hard.
So how often do you go
into a pricing discussion
with the idea that,
you know what?
I think we should reduce the price.
Just doesn't happen, right?
We’re always trying to increase the price.
Think about how to
increase those numbers a little bit.
And so early in my career,
I worked at a
high-tech equipment manufacturer.
They had kind of a twofold
business model, right?
They sold the equipment
and they serviced the equipment,
kind of like a car dealership.
And so, the service was
a little bit more expensive,
but you had the brand name behind you.
And so you know, this was the model.
In trying to grow,
the service team had been
increasing prices a little bit,
trying to drive up that growth.
What they found was
it was driving that short term growth,
but they were getting
some diminishing returns.
So each individual price increase
bought us less.
And so, we were trying to figure out
why is this happening?
What's the answer?
And it turns out,
every time we raised the price,
our competitors would raise their price too,
but not as much as we did.
And so the gap between us and our
competitors was growing,
and it was growing to the point
where the brand umbrella couldn't support
that anymore for some of these customers.
And so, the answer in this case was not
to have more price increases.
It was actually to do
a price decrease in certain segments,
in certain geos,
that actually allowed us
to be more competitive.
It allows us to balance this accessibility
with the premium status.
We were able to look at which
of the products were more complex
that would actually support more
of our premium versus less,
which geos had more competition.
And so we were actually successful in
in driving growth
by decreasing price.
Kind of counterintuitive.
Again, a lot of analytics,
a lot of market intel,
and understanding the dynamics
in all of these different areas.
And again, a little bit of faith.
All right, lesson four,
understand your customer's expectations.
It's always important
to remember your customer expectations,
right?
If you are pricing in a way
that is different
from the way your customer
expects to be priced,
you can expect a lot of questions
and probably a lot of pushback,
because this isn't what
they’re expecting in the market.
And so it's important to research,
to understand,
and to price in a way that aligns
with those expectations.
This probably is the first
and foremost rule of pricing
in terms of understanding your customer.
But there's a reason
that I’ve saved this one for last,
and it's because this is
a lesson that we are,
again, learning at Stripe.
And so I wanted to talk
a little bit about some
of what we’re doing here.
And so at this point,
I'd like to invite Sharmeen back up
to share some of our
own experiences with this idea
of meeting customer expectations.
Thanks, Bill.
So this is a topic
that has been top of mind
since I joined Stripe.
The thing that I hear
the most from our customers
is that they want us to
rethink our pricing
for our billing product.
Today, it's based on how
we charge for payments,
which is a percentage of volume.
And that's not how our customers expect
to pay for billing software
given the market.
80% of you have told us that you prefer
to pay with a monthly or annual fee.
We heard you, you all are the first
to hear in this room right now
that we will be offering a subscription
based pricing plan
for Stripe Billing and Stripe Tax
later this summer.
And we’ve made this transition
to offer a pricing model
that better meets your expectations.
(audience applauding)
Like I said, this is a great example
of where we at Stripe
are learning the lessons
that I’m talking about, right?
This is us kind of listening
to customers, understanding,
and making that change.
It also goes back to this idea,
like I said,
you’re never done with pricing.
So it's a constant iterative process.
So, to sum up,
I talked about a few different lessons,
minimizing the barrier to entry,
making sure that your customers have a way
to get in at a lower price
and try your product,
simplification, making sure
that you are helping
your customers figure out
what the product configuration is
that they need from you,
going low to go high,
sometimes a price increase
is not the answer.
And this last one, customer expectations.
Making sure that you are in fact
meeting the expectations
that your customers have in the market.
But you know, it's one thing
for me to stand up here
and kind of talk about these lessons.
I know all of you probably prefer
to hear from somebody
who's actually doing this
out in the field.
Sharmeen, I think you’ve brought
somebody today to talk about that.
Yeah, we're going to talk to one of our users
who has recently made a big
transformation in pricing.
Please welcome Darragh,
the CTO at Intercom.
(audience applauding and cheering)
(upbeat music)
(music ending)
Welcome, Darragh, thank you
for making the trip from Ireland.
How was it?
It was great. Yeah, smooth.
So, you know, our partnership
with Intercom is actually the inspiration
of this talk today.
And you know,
we're going to get into the details,
but before we do that,
we'd love to talk about how we got here.
Can you walk us through how
pricing at Intercom has changed
with each phase of growth?
Sure, yeah, so to start with,
for people who might not know,
Intercom's an AI-first
customer service platform.
We are fighting hard to be the best.
And our customers will typically tell us
that when they switch to
Intercom from incumbents,
they deliver better support faster,
especially when they embrace AI.
Our pricing journey has been colorful.
Our company's about 10+ years old,
and we started really simple.
We were beautifully simple.
And then, you know,
over the following decade,
a combination of our product strategy
came quite diffuse.
And we were trying to do
all things for all people,
and our pricing
and way of selling our product got,
you know, insane and,
I think it's fair to say.
And the combination of those things
I think just
resulted in us suffering
pretty real brand damage,
relating to pricing, and hurt our business.
And I’m pretty certain
that there's some people in this room here
for whom you’re familiar with this saga,
and I’m deeply sorry. (audience laughing softly)
But I’m,
you know, determined to fix it.
But kind of reflecting on it,
you know,
when I think back,
and I wasn't responsible
for a bunch of these,
but I was present,
almost all the changes appeared rational.
You know, there were
good arguments for them,
there was conventional wisdom,
but they certainly were
all in the direction
of complexity and opaqueness,
and they hurt us in the long term.
So when Bill was talking
through his lessons,
I was kind of nodding along thinking,
yep, we did the opposite,
and it sucked.
So listen to Bill.
Yeah, so the first step is
identifying the problem.
Yeah. Always.
And once you recognized
that a change needed to be made,
what action did Intercom take next?
I mean, quite simply,
we went back to basics.
We did a whole bunch of research
and looked at the customer's perspective
of pricing all the problems.
You know, it wasn't just pricing,
it was billing experience, all of that.
And we just delivered something
that was much simpler,
much closer to customer expectations,
far more transparent,
and aim to reduce friction.
You know, it was a big delta
between where we'd been
and it required a lot of
courage and conviction
and a willingness to take a bet,
because, you know,
there was no sensible way to... like,
so much was changing.
You couldn't really model it.
You had to make a bunch
of assumptions, but,
and you know, it was hard
to iterate to that point.
So, it was a big bet.
But, you know, early days,
it's been really great for us.
You know, people are,
turns out when you make it easier
and fair and simpler,
people buy more and stick around more.
So, you know,
strong lesson on just being
more customer-centric there.
So, Darragh, we mentioned this earlier,
but Intercom launched its
AI customer service agent
last year and it's gotten
some great attention
for its results driven pricing model.
Can you tell us more about that?
Sure, yeah, so to start with,
Fin was the little thing you saw
animating at the start.
It's the pointy end of our
AI customer service platform.
It will automatically and near instantly
resolve on average
42% of the query set that hit it,
which has an incredible impact for a business.
Alongside it we've got Copilot,
which helps humans be more effective.
And then working on analysts.
So Fin's part of that system
and, you know,
it's been our most successful
product launch yet.
There's tremendous value
and people are loving it.
And the cliche
I think was something, like, you know,
better, faster, cheaper, pick two.
But with Fin, people
see all those benefits,
they pick all three.
So tell us a little more about
how resolution-based pricing works.
How did Intercom decide
on that for the pricing model?
Right, so for the resolution-based pricing,
we price when the bot actually
solves the problem for the customer.
So it's based on, you know,
really strongly aligned incentives
between what our customer wants
and what their customers care about.
They just want their issue solved.
So when Fin does that,
they pay and they’re happy to,
and when it doesn't, they don't pay.
But Fin has helped disambiguate the issue
and give humans a headstart
when they get involved.
You know, how do we get here?
We, you know,
we didn't know where to go
with pricing when it started.
We considered a lot of things,
and this approach made a lot
of sense from, you know,
aligning incentives,
but it wasn't obvious.
And there was a lot of pushback,
a lot of pressure internally,
a lot of others maybe looking
at a cost, like LLM cost-based model,
you know, like we do for things like SMS.
But I think that meaningfully
underserved the kind of value
that's being delivered here.
And an interesting
reflection here is, like,
you know, one of the things we considered
was a version of that,
but it really fell down
in our assessment when,
you know, you price on volume
but kind of disconnected from results.
So an example of that really is,
had we exposed our pricing in that way,
the reality is the product isn't
just a wrapper around, like,
you know, an easy to reason about call.
There's lots of things going on,
and as we try to improve it,
we change the internal.
So, pricing on that LLM cost
would have forced us
to constantly
resurface a change in price to customers,
and it would have slowed down
our innovation.
So I don't think we really anticipated
this ahead of time,
but upon reflection
that's been a big win.
That's the best type of win.
The one that wasn't intended,
but ended up being a big one. Yeah.
So what type of feedback
have you gotten from customers,
and how did you gather
that feedback and act on it?
Yeah, so the nice
signal for feedback is
around usage and retention,
and like Bill mentioned,
how it's a very low barrier for entry.
Like it, you buy Fin,
you don't pay unless you actually use it,
you know, so you can use 1 for $1
or 1,000 for $1,000.
And the, you know,
general signals we’ve seen
is, like, people stick
and expand their
usage pretty significantly.
The reaction is they want to spend more,
because they see the value,
they want to spend more.
So, you know, from that point of view,
I’ve really appreciated
the purity of the model.
You can't hide
from failure or success.
There's no such thing as zombie revenue.
It's either delivering value
and paying you or not.
So that's one thing.
But of course we also
talk to our customers a lot,
very product-oriented company.
And the Fin product was in the hands
of many beta customers before
we'd even figured out pricing.
So that was a great opportunity to talk
to people who'd really felt
and seen the value of the product
and get their kind of feedback
at that point.
And then, of course, we later,
as it became publicly available,
we would do a bunch of research
and talk to people who either bought
or didn't buy or who
were happy or who churned, etc.
So, you know, you'd never go wrong talking
to your customers.
In terms of actual feedback,
A whole range of things.
But kind of two themes that jumped out,
like one relating to usage
pricing in general.
And I think there are elements
to this in the announcement
around subscription pricing.
Like, it's hard to predict
the usage pricing.
And people are worried,
particularly in a customer service org,
where they’re maybe quite tight
around their ability to spend,
they’re worried about
predicting their spend,
they have to budget very carefully.
So, you know, one partial
thing to help with that is,
you know, building a lot of transparency
and control so they can see
what's going on
and they can limit it.
And that's been quite helpful.
The other one is around
scrutiny of the metric itself.
So there's an element of
subjectivity here.
Not all resolutions are as hard
or perceived as high quality or as,
and as a result you have people
who will interrogate
and say, “Hey, over here it feels great.
I'll happily pay $1 all day.
But over here this feels not great”,
and that's just a hard one
and one of the kind of accepted trade-offs
of the simplicity of the model.
But we definitely made an intentional effort
to try to reduce
The bias against creating situations
where delivering lower-value resolutions.
So, this next question I have to ask,
right?
We all know that a brand new
pricing strategy
can be extremely difficult to execute,
and I'd love to hear how Stripe
helped you do this more effectively.
Sure, so to kind of give a little bit more
background here, you know,
we’re as well as our pricing
being quite messy.
And I gather this is not uncommon too...
the systems that underpinned are,
you know,
billing and a go-to-market machine
in general
was pretty awful and unloved.
And the consequence of that was that
it was actually very hard for us to move
and iterate and build new models
or try things
or even deliver a quality of service
that was in any way acceptable.
So we effectively declared bankruptcy
on the part we'd been on,
we wanted to do
too much change that we felt,
you know, we could
afford to bet on that part.
So we instead
chose Stripe as our future platform there,
made a triple bet
on a system change, a model change,
on this new AI product.
I don't recommend that necessarily,
but we had insane time pressure
and so we optimized for speed.
We didn't test our way into this,
we just wanted to move
as fast as we could to the end state.
And you know, I think as evident
by all this stuff
you'll hear in this event,
Stripe has a super high bar,
very ambitious,
move fast, and we strive for the same.
So we bet on that kind of trajectory
and that mindset and it's paid off.
But I do look forward
to being able to do some
of the more methodical,
targeted, you know,
testing with the Australian market,
for example,
when we get to sort of more calm,
stable base.
So Darragh, do you have any
closing thoughts
on AI pricing for the folks in the room?
Sure, so first off,
I think, accept it's a new world
and how you might have thought about
or auto-completed
on pricing decisions in the past
are likely not right.
AI has a potential
to deliver insane value,
like the products you build become
way more than a tool,
they do work too.
And you should think about
the value of that work
and then kind of, you know,
the answer will be different
from every kind
of different variety of things
people are building here.
But some general questions
I think are relevant are like,
you know, how much will this
define your product or business?
Is it like the thing
or a little bit on the side,
how differentiated it is versus you know,
what is easy for others to do,
what usage level you
might expect and how
that changes over time?
And of course cost as well.
Like I know that's all pretty high-level,
but they’re the dimensions
to poke on there.
Absolutely, so we are at time,
so I’m going to wrap this up super quickly.
Based on everything you’ve heard today
from both Bill's expertise
and Darragh's firsthand experience,
there are three main takeaways
that we want you all to have.
The first one is to get creative
and experiment with your pricing models.
The second one is that good pricing
is a strategic business
lever when simplified.
And the third one is
to determine your trade-offs
based on what is most fair to your users.
And in the words of Bill:
“Don't forget that you are never done
with pricing.”
And I’m just going to jump up
and say if you’re interested
in learning more
about Stripe Billing,
we have a Billing booth
in the expo hall,
and there are also tons of
folks from our team
who are in the room right now.
So just come find us, talk to us,
and if you want to see
what we are building next,
stick around right here in this room.
In 15 minutes,
we’re going to have our Revenue
and Finance Automation
product roadmap talk.
So please hang out
and we hope to see you very soon.
Thank you all for coming.
(audience applauding) (upbeat music)
(music ending)