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Every product leader has to make them: the high-stakes decisions that define outcomes, shape careers, and don't come with easy answers.
The Hard Calls podcast, hosted by Trisha Price, features candid conversations with product and tech leaders about the pivotal decisions that drive great products and the pressure that comes with it. From conflicting priorities and unclear success metrics to aligning teams and navigating executive expectations, you will hear compelling stories and best practices that drive business outcomes and help you make the Hard Calls.
Real decisions. Real stakes. Real leadership.
Presented by Pendo
Learn more at pendo.io/
Follow Trisha Price on LinkedIn: https://www.linkedin.com/in/trisha-price-3063081/
Trisha Price: How do you do that?
How do you help your product teams
as they move through that maturity
matrix to make sure that what they are
measuring aligns to sort of the bigger
OKR business outcomes of the company?
Noa Ginsberg: Yeah, this is such
a tough one because at the end
of the day, it's top line and
margin and EPS growth that matter.
I would say that our headline metrics
approach has been a, our best stab
at that, which is providing this
portfolio of metrics that you could
view for any product to see how
it's impacting on the user side.
So it doesn't really directly
impact but it helps you to gauge
the quality of your revenue.
And I think that's a big piece.
Trisha Price: If you build
software or lead people who do,
then you're in the right place.
This.
Is hard calls, real decisions,
real leaders, real outcomes.
Hi everyone.
I am Trisha Price, and welcome back to
Hard Calls, the podcast where we bring on
the best product leaders from across the
globe to talk about those moments, the
decisions that matter, the hard calls.
On today's show, we have Noa Ginsberg,
who leads the Product Management
Center of Excellence at FactSet.
Noa and I have known each other for about
four years now, since I joined Pendo.
When I met Noa.
She was starting up a product
analytics and product center of
excellence function for FactSet.
I really, right from the start, admired
Noa's approach to the role, her commitment
to excellence, and her ability to
build strong teams and relationships.
In addition to Noa sharing a hard call
that's made a big impact on her career,
we're also gonna dive into what does
it take to create a product center of
excellence and the benefits that the
team has on being a product-led company.
Noa's gonna share her insights on why
product operations is the glue that binds
all of the pieces of the org together.
Her learnings on how to keep product
teams close to the customer and how
AI is changing the product landscape.
This is a truly knowledge rich
conversation, and I can't wait for
you to hear it and to jump into it.
Welcome to the show, Noa.
Thank you so much, Trisha.
It's great to be here.
So, Noa, you know that the
show is called Hard Calls, so
looking back over your career.
Or even just in the past year, can you
share a hard call that you've had to make?
What made it so challenging?
What considerations or process did
you follow to make the decision
and what'd you learn from it?
Noa Ginsberg: I'll start off by saying,
first of all, I'm thrilled to be here.
I saw the list of other guests
and I was super flattered.
So really appreciate the opportunity
and I love chatting with you and talking
shop and the opportunity to do that.
It's awesome.
So thanks for having me.
Hard calls are pretty much
what we do in product.
I think there are very few easy calls,
especially as you know, mature in your
career, you start seeing only hard calls.
and I've noticed that for me, the
hardest calls tend to be at the
intersection of people and priorities.
And each of those are hard.
And those are kind of
what we do in product.
Again, people, the people on our
team, the people we hire, the people
we work with as our stakeholders,
our clients, importantly.
and then the priorities we set as a
product team are pretty much our bread
and butter, and that's how we master all
our resources together and deliver value
for our clients to, to be successful.
and.
The intersection of those are when
I think it's the hardest call.
So I can think back to a time about
four years ago when we really wanted
to double down on our ability to run
a real true product organization, as
you might see at any tech company,
and we've been around a long time.
So we've been around since the late
seventies before the internet, before ai.
so we've had a lot of different ways of
doing things, but we had the opportunity
to really double down on product thinking,
a product mindset, the product toolkit
that you need, the skillset that you need.
but that was a major transformation
and a huge undertaking, and we did
it so that we could deliver on our
strategy, and we did it so that we
could deliver for our customers.
and make them more successful,
which is what we're here to do.
but that was a tough thing to go through
because it was a real shift for a lot
of people in their, their daily roles.
mostly very positively received,
and we've come a long way.
But we had Pendo was a part of that
as we stood up product analytics, to
give a, a single platform for people
to be able to monitor things rather
than having to stand up their own.
It was, it was, it was a hard call to
move forward with that versus being
successful as we are for so long.
Making that shift, getting everyone on
board, getting the tools and processes
in place to support that from a product
excellence perspective is definitely.
A very hard call, one that I think we
are now seeing the fruit of because
we have positioned ourselves so well
to take advantage of this new wave of
technology with AI in the last few years.
if we hadn't had the foresight to
really position ourselves for that,
I think we wouldn't be where we are.
And we are pretty far along and
ahead of the curve, especially in,
in a space that can tend to lag that
adoption of, of these types of things.
So it was.
Risk.
But, it's always good
to have a balanced risk.
So I think that's a key
part of hard, a hard call.
And we use Pendo, we use a lot of other
tools to help us make like de-risked
decisions, but there's always some element
of risk in any call, or we wouldn't be
making it, it wouldn't be a hard call.
So, yeah,
Trisha Price: I I love that you
brought that up because hard calls
are a little bit of our experience.
And our gut feel combined with data
and tools and bringing our stakeholders
together, all of those have to come
together, to make those hard calls.
But I always like to tell my team
too, no decision is also a decision.
And so like, while a hard call might be
difficult, not making a decision is just
as impactful and a lot of times worse.
Noa Ginsberg: Yes, absolutely.
We try to bring more speed
to decision making here.
But yeah, you have to pull it forward.
You have to make the hard call,
you have to make it clear to
people too, what the call is.
And I think recognizing where you are,
whether it's a people call or if it's a
priorities call, I think knowing where
you are is always important in order to.
Get where you wanna go, you have
to know where you're starting.
And that's something that
we've, we think about a lot.
We have a lot of good, tooling in place.
And you mentioned instinct versus data.
I really think our gut feel as you
gain experience is a bunch of data
that's just sort of in your own LLM,
in your mind of what you should do,
what you've seen this before, you
start to have some pattern recognition.
Always relying on gut checking that
not only with the data, but with
other experts, other stakeholders
with our customers within our own
teams, always validating that.
So like, trust your gut, but verify
I think is very important and using
all those tools at your disposal.
So you do make the best decision.
Trisha Price: That is great advice.
I wanna dive into some of the things
you mentioned in your hard call a bit
in the Product Center of Excellence.
But before we do, Noa, maybe you could
just tell us a little bit about FactSet
and what you do, and particularly your
role and your team before we jump.
Noa Ginsberg: Yeah, definitely.
So FactSet is a financial
data and analytics provider.
So we have workstation tools that
you might use, to monitor the
markets, to make trades, to research
companies, to catch up on earnings.
And it's used by over 8,000 of the
largest financial institutions over
200,000 users, and with 95% retention.
So we've been around for 46 years.
I've been public for 30.
I actually used FactSet in
my first job out of school.
I was a user of FactSet for a
couple years when I started out in
investment banking, and I'd always been
interested in finance and technology,
so I went to a bank and worked in
the technology group at the bank.
Used FactSet, loved the tool,
loved the people, loved the
client focus that they had.
The real obsession with the user
was clear to me as a client.
So I came to work for FactSet and
I've been here for 23 years now in
a bunch of different roles, but I
started out supporting our clients
as a consultant on the help desk.
We would answer the phones here
in New York, from the bankers
calling at 2:00 AM who needed help.
So you gain a lot of empathy for
the role of our clients, and that's
inherent in everyone who works here.
A lot of people come up through,
right outta college, answering
phones and things like that.
So, FactSet's a pretty indispensable
tool to the investing community.
So anyone you know who works at a wealth
advisor or a hedge fund or an asset
manager or an investment bank definitely
uses FactSet or has in the past.
So it's really part of the fabric of.
Of how the investment community
operates and we are known for our
service and our client obsession.
Really, that's a big differentiator
for us and something that I think
is only continuing as we're seeing
the pace of change increase so much.
So it wasn't surprising to me when
we made this shift to have a product
management excellence group because it
really does help enable the whole company
to have that client obsession, which we
already inherently have as fact setters,
but it really helps to bring scale and
consistency to that so that everybody
can do things and maybe there are even
fewer hard calls for others to make.
If we in the center of excellence
are kind of providing what's,
what tooling should we use?
How do I do user research?
What design systems should I use?
Trying to solve a lot of those
issues at scale, for people so they
don't have to make those hard calls.
We've already made them.
That's, I think, a huge
benefit to the team as well.
Trisha Price: Wow.
You know, first of all, incredible,
longstanding successful company with
a incredible reputation and what.
An interesting career for you to
come, have joined them so long ago and
done so many different roles there.
And now to be leading this product
center of excellence, which I know
the entire product team at Factset
really leans on you for best
practices, for insights to really make
sure that you can execute on that.
Client obsession or as we call
it at Pendo, our core values,
maniacal focus on the customer.
So we have that in common.
And I think that that's I think a big
part of not just our love of product,
which I know we'll talk about today,
but our obsession with customers has
definitely brought you and I together
over the four years as we've talked.
So, really excited to dive in.
You know, I get the question a lot, Noa.
When I'm out talking to customers or just
product managers and product teams and
product leaders is product operations,
center of excellence for product overall.
How do I do it?
What does it look like?
So I'm really excited to spend this time
today with you who is truly a leader in
setting up a center of excellence and
has done just an incredible job with
it for, for people to learn from you.
So maybe like, tell me, do you think,
because I get asked this a lot, do you
think every company should have a product
management center of excellence or if not,
is there a time or a level of maturity
when you think it's time to establish one?
Noa Ginsberg: Yeah, great question.
I wish I had a book to read, to tell
me about every specific situation.
There are a few out there on this
topic and I've, but I've found that
we, nothing really it's great to take
those as inputs, but you kind of have
to do your own instinct, combination
with data to decide what works for you.
So I think certainly a large company
FactSet has 13,000 employees globally.
It's a big company, hard to
keep everything coordinated.
So sometimes that can be sort of a warning
or like a, maybe a light going off on the
dashboard to say, "Hey, maybe you should
think about this?" So there are a few
things that I think you could think about.
One is probably coordination.
So if you're starting to feel
like things might not be.
As smooth as they could be.
Or you're seeing a lot of Conway's law,
maybe if you're big enough where you're
seeing multiple kind of conveyor belts
coming outta the company and to the
consumer or the end user, it's like,
looks like a bunch of different companies.
That's obviously a red flag, that
would say like, Hey, maybe we should
benefit some from some less duplication
of effort, from more coordination.
That's one thing that I think any kind
of centralized team can help with.
And another one is related
to that probably stakeholder.
Confusion.
So does product marketing know how to
work with each team in the same way?
Is the process in one team totally
different and then when another central
team tries to work with that product
team, it takes too long because it's
learning a new way of doing things.
same thing with support or sales.
Like, do we have a well-oiled machine?
Does everybody know what to do?
You don't always need
people to set that up.
You can just be clear of how things should
go with existing personnel and staff.
But beyond a certain scale, I think it's
very helpful to have a central team like
this that operates almost like a platform
team would, like a platform product
team, but for the product of building
products, which is a little bit meta,
but we do think about it as a product.
What we do, what we put out from
our team is a product and what.
The people using it internally
at the company are our users,
and we are very careful to always
stay connected to our users.
It's very important for what we're doing.
And then I think the last thing I would
say is if you find that the language
you're speaking is not the same as
another product team, there might be
some differences that are necessary
depending on the kind of product you have.
But if you're all talking about
adoption and you have a different
denominator for adoption.
It's very hard to compare the success
of one product versus another.
And when you have a large product
portfolio, it's very important to
be able to have an apples to apples
comparison on the success of that product.
So those are kind of three areas, I
guess I would say where you might wanna
think about it if you don't already.
And I would say even if you can see a
little bit ahead and anticipate those
things, you'd be even better off.
Because once you have a certain
scale, I think it really helps to
have some central coordination.
Trisha Price: I am so glad you
brought up the stakeholders piece.
I am such a firm believer, and I know
you are too, that the only reason we
do product investments or technology
investments, depending on the kind
of kind of company you are, is to
drive business outcomes, right?
It's either to drive revenue, to
cut costs, to reduce risk, and the.
Leaders of our companies, teams,
investors, they expect a return for
this investment that we're making.
And you know, I think it's easy in product
to get too focused on the feature you're
building or the product you're shipping
and not the outcome you're driving.
And without that really strong stakeholder
communication and coordination, you
won't get those business outcomes
that you need from your product.
So it's great that you talked about how
you operate and the processes with your
stakeholders being such an important
part of A COE and when you need a COE
is to standardize that because without
those relationships and without the
processes to partner, if sales isn't
selling it and support doesn't know how
to support the new features and products
that you're putting out, and you don't
have a convenient way to work with those
people 'cause they have day jobs too.
It's kind of like, why are you
building what you're building?
Noa Ginsberg: Totally.
We've tried to really
provide data around that too.
So we, on our agile teams, we have
stakeholder assessments that some of
the teams can do to see assess how well
the team is meeting the stakeholder's
expectations on things like communications
or value delivery, or timing.
So those things are all
really important to monitor.
And then we also have a portfolio
of headline metrics that is
visible to everyone at the company,
across the product portfolio.
And those are the headlines that
we want people to be talking about.
And that can be used to
compare across products.
So a key one for support
would be supportability,
some of these sort of hidden.
Costs, trying to bring them to
light so people really understand
the full implication of a product.
It's not just who paid for it and
how much they paid, but how much
it costs to support the product.
And that's something we've
tried to bring forward.
So stakeholders have more
realization of that too.
Trisha Price: Yeah.
Noa Ginsberg: And even within the product
teams to be able to have that visibility.
Trisha Price: Yeah.
It's good that you brought up
supportability, because we often, as
product managers get pretty good at
Voice of Customer and whether that
comes through our sales teams or through
customers directly or customer success
teams really understanding what it is
that our customers are looking for, but
indirectly it does impact our customers.
And if we're gonna be customer
obsessed, if a product's difficult
to support and support's not educated
on it, not only does that drive
costs up of your overall product, but
it does impact customer happiness.
And you know, it may be okay for a
period of time where your support team
can cover up for you, but in the end,
if your product's not easy to support
or there's a lot of support tickets
coming out of a particular part of your
product, that's equally important to
fix than like direct voice of customer.
Noa Ginsberg: We try to monitor, some
buddy metrics along with supportability,
so we're not just looking at does
support go down And then because people
don't like it and stopped using it,
that's one reason it could go down.
So we always pair it up with NPS, which
we do get from Pendo, and we track
NPS versus year over year change in
supportability for cases per active user.
And we have tracked that for years
now since we've had Pendo and NPS in
place, and it's been really helpful
to see that validation that we are
improving and we're not not at the
expense of our customer satisfaction.
So that's something that's really
important to us in terms of
supportability and voice of the customer.
And we've also gotten so much
more data in the last four years
since standing up this team.
We really didn't have a centralized place.
We have a lot, again, a lot of
connectivity with our customers,
super focused on them and really at
the core of everything we do, but a
systematic way of sharing that, making
sure it's available to everyone.
You know, it didn't exist.
You had to know someone or know
who had it or find it somewhere.
but we've.
We've kind of brought that together
into an inventory so we know what we're
getting, what streams of VOC data we have,
who owns it, what the follow up is that's
expected and that's a work in progress.
Like we still wanna expand that.
We wanna do more there, but we've
come a really long way, and I think it
shows in how we develop our products
and ultimately what we deliver.
Trisha Price: So we kind of dove in
a little bit into some of the things
your teams, your team does and focuses
on around analytics and voice of
customer and stakeholder management.
But for those just getting started
with a product center of excellence
and maybe just establishing them.
How do you get started?
What are the things to consider?
Like do you jump right to some of
the mature processes you're talking
about with NPS and data collection
and standard analytics and adoption?
Or are there more simple
places for people to start?
What are the considerations
for folks to think about?
Noa Ginsberg: Yeah, I think it's
important to know what good looks like.
As I said, sort of where you wanna
go and where you are and try a,
try to chart a path to get there.
But obviously you can't start with
everything and like good product
people we know we have to prioritize.
So I would look at what is the
biggest pain point for your product
managers or for the business?
Like what visibility is missing?
In the KPIs we're using to track
our investments or to track how
the company's doing as a whole.
What are the blind spots?
Maybe you don't have them.
Maybe that's really well oiled
machine and you don't need to
focus on the metrics piece.
I think there are some companies
that probably are there just.
Starting off.
But if, if you have that, great,
you can move on to something else.
But I think, having a centralized
qualitative and quantitative
view is very helpful and those
things inform each other.
So that's another one.
So if you don't have a user research
function that is central, I think
that's another place that could be a
kind of high leverage place to start.
As well as a system to store the
user research you're doing so you
can share that knowledge broadly.
that's really important because
product people can conduct user
research and do it very well, but
they're not laser focused on that.
They don't know all of the methodologies
that are available necessarily, right?
So having a centralized, really skilled
user research team can be very helpful.
And again, bring leverage
to the product teams.
I think there's also some, some
goodness in centralizing how
we communicate with clients.
So in app, whether it's a homegrown thing
or Pendo, we use a combination, how are we
communicating to clients with our voice?
And then how do we get information
from customers in the app or
in email or in other channels.
So those are some sort
of good ideas to start.
I think even when you have started,
we actually, we work on this
maturity assessment for ourselves.
We made an acronym out of it
so that we could remember it.
'cause we like acronyms
in finance and at FactSet.
So it's FACT is our own internal maturity
model specifically for product analytics.
But it's foundational, aspirational,
competitive, and then transformative.
And we use that to assess.
Ourselves, but also how well our
product teams are using and leveraging
the data that we are providing.
And that helps us see, okay,
let's think about where we are.
We've come back to it when we're
setting goals for the year.
You know, what do we wanna do
to level up the whole function?
And look what's, well, if we're
in column A, we wanna move to
column C, what do we need to do?
Or what are the things we could
try or consider doing next
year to just move us forward?
So I think that's, whether you're at a
zero or you're on your way, I think that's
just a good outlook and way to frame it.
Trisha Price: Yeah.
It forces us all to constantly get
better and mature and see a path
to that no matter where we are.
Noa, when you're, when you're moving
through your maturity matrix or
aligning on which metrics matter
for a particular product group.
How do you align what your product
teams are measuring to what your
leadership is accountable too, right?
Because I see this is really hard.
I think in product, I think this is one
of the hardest things that's hard for me.
And I mean, we at Pendo are an analytics
company and it's still really hard to go
from, "Hey, we're trying to drive revenue.
Hey, we're trying to improve cross sell.
Hey, we're trying to reduce support
cost," to this is the particular
part of the product I'm gonna
focus on and I'm gonna measure.
You know, time to value or
retention, like how do you do that?
How do you help your product teams
as they move through that maturity
matrix to make sure that what they are
measuring aligns to sort of the bigger
OKR business outcomes of the company?
Noa Ginsberg: Yeah, this is such
a tough one because at the end
of the day, it's top line and
margin and EPS growth that matter.
so I would say that our
headline metrics approach has.
Been our best stab at that, which is
providing this portfolio of metrics that
you could view for any product to see
how it's impacting on the user side.
So it doesn't really directly
impact, but it, it helps you to
gauge the quality of your revenue.
And I think that's a big piece.
So whereas a SV, what we call
annual subscription value,
because we're a subscription
business, is a lagging indicator.
We want more leading indicators.
We wanna be able to assess the
health of our customers better.
So the more data we have on how the system
is being used, what tools they're using,
what data they're using, the better we
can understand the quality, maybe better
address at risk, and build that success
profile based on the data we have.
So I think without a basic set of metrics,
and we only have a handful, right?
It's five metrics working on six,
but, Adoption sentiment, which is from
Pendo NPS, engagement supportability.
Those are the main areas
that we are providing for
everyone else to monitor that.
So I think then beyond that, beyond sort
of equipping people with the basics, it's
also fostering some experimentation and
being okay to experiment because, we
might say that we think this is a leading
indicator, but it may not turn out to be.
You can't argue that
adoption is a good thing.
So you want higher adoption.
Yes, you wanna build something.
It's like everyone's worst nightmare.
Every engineer's worst nightmare.
Every product person, you build
something and no one uses it.
No one uses it.
And it could be a marketing
problem, it could be a, a good
market problem or a sales problem.
Like it doesn't it radiates
out from the product though.
If it's not a good product, it doesn't
matter if you have a world class.
Trisha Price: I always say that,
you know, if you have an adoption
problem, it's the product.
Now, those other groups could be
making it better or can cover up
really well to make it less bad.
But at the end of the day, if we have
an adoption problem, we have to look
ourselves in the eye as product team
and ask ourselves what's going wrong?
Noa Ginsberg: Yes, a hundred percent.
And if, and so we wanna
always in increase adoption.
And we work very closely
with go to market.
Like we've actually, we as the
Center for Product Excellence, we
redefined our product lifecycle.
So that, again, everyone's
speaking the same language.
Everyone knows what we mean when we say
the ideate or validate or build phases.
And we work with product marketing to
be very close throughout the lifecycle,
especially at the earliest stages.
Yeah.
So that they're involved.
And it isn't a handoff where it's
like finger pointing happening.
But we've got, we've gotten a
lot of runway out of that and
it's, it's really improved,
especially over the last few years.
Trisha Price: Well, Noa, your team is
so important at setting these standards
of facts, your maturity matrix and
how to work with stakeholders and
really ensuring you get business
outcomes from your investment.
But they're not the ones.
Accountable or owning the actual
individual products, right?
They're that messy, middle, supporting
all of the other teams around them.
With that I know you've talked
about being customer obsessed
is so important at FactSet.
How do you motivate your team, make
them feel connected to the customer
and accountable to outcomes when you
are sort of the messy middle and one
step removed from the end product.
Noa Ginsberg: Yeah.
Yeah.
I mean, we do work really directly and
as one with these teams, especially
the pillars in my team are UX client
help and communication enterprise,
business agility, and product analytics.
So those teams are working
closely with the product teams.
So they're part of the team
and they're invested and they.
Understand as well as
the others on the team.
What we're trying to drive and
understanding the user is always
something we are seeking to do.
But we also have another set of
users, which is our internal users.
So I've tried, and I think most of the
team has always seen it as what we do
as a product for internal consumers and
we are very closely connected to them.
We run cabs, we do annual surveys.
We check engagement with the tools
that we build and the products,
quote unquote, that we release.
And some of those products are,
are events, things like we run this
annual idea, hon, which is a pretty
unique innovation tournament that
precedes our hackathon and it seeds
the hackathon with business validated
ideas coming from, it can come from
engineering, but it often comes from
outside of product engineering design.
It comes from sales, it comes from
finance, it comes from hr. So it's
really the whole company putting forth
innovation ideas and then people can
take those forward to the hackathon.
And so we try to foster that innovation
and that feeling of a product
mindset, even within our internal
clients and our internal teams.
And I think that's really important.
But when you're setting
goals, it is hard to.
Especially OKRs, right?
They're supposed to be within your
line of influence and something
too far beyond it can be difficult.
So the we, we are challenged by that, but
I think we try to focus more on the direct
impact we're having and then sort of the
second order things we do follow also.
Trisha Price: Yeah, that's great.
It is such a critical role, and it is
critical to keep people feeling connected
and tied to the business outcomes,
and I know you do a great job of that.
A few minutes ago you mentioned your
product development lifecycle and
even changing it up and standardizing
it to make sure that everyone,
even your stakeholders knew it.
You also just mentioned your idea
on, and your hackathon right now.
All of us, our product development
lifecycle is in flux and the tools that
we're using and the pace at which we're
ideating and validating is changing.
And even things like
ideathons to hackathon.
It used to be probably two years ago
or a year ago, if you did an ideathon,
they probably ended up in some sort of
slides or maybe a document outlining
the idea, and now I'm guessing
you have a full blown prototype
even without engineering involved.
So tell me about how you think about
that and how the roles are blurring
and just how are you responding
and changing in this sort of a
new era of product development.
Noa Ginsberg: Yeah.
I mean, everyone's head is spinning,
but in a really exciting way.
I mean, I first entered the workforce
around the.com time and that was also
super exciting, that feels the same to me.
We are really forward thinking on
this and from the very early stages
we had our own internal AI tooling.
So everyone at FactSet has been
able to play around and get good at
these technologies for years now.
Of course that has different
implications, but we are a
pretty creative group of people.
We're like high agency.
It's a very entrepreneurial kind
of environment for a large company.
And so we've seen a lot
of that happening already.
We've got the builders coming
in no matter what their role is.
Everyone's now a builder it sounds like.
So whether you're a product
person or a designer.
Or an engineer who didn't know front
end development, like now everyone can
do that, of course, not in production,
but it really has facilitated the
speed because instead of talking about
doing something, we're just doing it.
So the early stages of the lifecycle,
I think, are the most exciting and
ripe for disruption and acceleration
by these tools, even though it sort
of started off in the development.
Side with the code completion or code
automation and we're seeing great, great
results there, but it's more incremental.
I would say, when you think about
the build phase, like obviously
execution's very important and, but
we're really good at it already and
so it's hard to sort of 10 x that.
But I think when you think about all
the communication that happens, the
long documents that we would write like.
I just don't think that's the future.
And that cuts not hours off of developing
something, but months off of deciding
whether something's a good idea or not.
Trisha Price: Yeah.
Noa Ginsberg: And that's
super high leverage.
Trisha Price: I totally agree with you.
It's the confidence factor
when we actually put.
Engineering effort at something is wildly
different now than it was a year ago.
you know, it used to be, "Hey, we've
got this idea. We've talked to a few
customers." We've done some discovery.
Let's get V zero into some
sort of design partner's hands.
And then iterate, iterate, iterate,
and kind of constantly examine
whether we're gonna kill something.
But now what we can, what our builders,
as you said, can build even without
engineering support, can get us to a
point where we can iterate, iterate
so much faster that by the time we're.
Building for real at the confidence level,
we've gone through so much iteration and
levels of discovery and it's so fast.
It's mind boggling.
Noa Ginsberg: Yeah.
We're hearing teams canceling
meetings because they don't need
to sync up on something like the
prototype kind of helps them do that.
We're seeing people show a prototype
to a client in the morning and then
15 minutes later show it again, and
so the number of iterations is just
skyrocketing because anyone can iterate.
You don't need to go have a meeting,
you don't need to ask the designer
to redo the Figma prototype.
You know, there's some downside to
that and we we're gonna work through
a lot of the issues it raises of
like, who's, whose job is whose.
And you know, but I think we're an
open-minded place and so I think we'll
work through those things, but there are
real things to consider, like how do our
processes get impacted by these changes.
But overall, it's super exciting
and most people are really excited
about it because again, we're a
place where people just wanna get
stuff done and want the best outcome.
So I think that's gonna
have a huge impact.
We're piloting a few different
tools here for product and design.
For the AI prototyping piece, we're
working on an agent backlog for
accelerating the product lifecycle.
And obviously our developers
have been at this for a while.
When tools like GitHub, copilot
and others came out in cursor.
So there's a lot of exploration
happening and we don't want people to
have to go do it on the side of the
desk or you know, in their spare time.
Like, we wanna provide these tools,
we wanna change the way we're working
and be at the cutting edge here.
Because, it's a huge opportunity.
Trisha Price: So you talked about
utilizing all kinds of different
tools that give you productivity.
AI really supercharging and
giving you productivity.
You just mentioned an agent.
Is that an agent?
You guys are actually thinking about
building that's particular and has context
about your processes and your products.
That helps your product
managers be more efficient.
Noa Ginsberg: Yeah, we're not sure
yet what it looks like, but we've
put the call out to build up our
backlog by the end of the year.
And then on our internal agent platform,
which we're developing, we will be
building out those tools that are
gonna help us to get that productivity.
So it could be something more
rules-based, maybe it's not an agent.
There's a lot of opportunity
to improve and get speed out
of a process that isn't AI.
So we're open to that too.
But there, the agentic piece is.
I think going to be very important.
Imagine you have an agent that updates
your documentation for you automatically
based on the release notes or just
constantly trolls your documentation
to say, Hey, like these pages, and then
our writers can then document so much
more or they can work on other things.
It's a really exciting area.
Our quality would be better, because it's
just hard for us to manage everything,
even though we have great people.
It's just a lot to cover.
Trisha Price: No, I know we
haven't talked about this before,
but imagine it'll be really cool.
And, and this is what we're
planning for at Pendo too.
If, when you're building that agent, that
agent would have access to your Pendo data
and you could ask it even this is your
agent, not the one we're building, but one
you have configured and built on your own.
But through our MCP server, you'd
be able to ask adoption numbers,
et cetera, through your own agent.
And that's, I think, an
exciting thing because I do
think everyone Yeah, of course.
All software companies, you're doing it.
We're doing it, are building these
agentic interfaces and agentic automation.
But we also know you're gonna have
your own and your own's gonna have
special context about things that
is only relevant to FactSet and
FactSet group of product managers.
And we wanna make sure that kind of data
is available to those agents as well.
Noa Ginsberg: It's totally, exactly
the same for us with our clients.
So we definitely would want to be involved
in that design partner program for MCP.
And it's the same way we're thinking
about both internally for ourselves,
enabling that with the protocol and
the agent platform, and agent re
registry so that we know what's out
there and can permission appropriately.
There's so much to consider, but we
are doing that for our clients as well.
So we're totally on the same page.
Although that page keeps
moving, keeps moving.
Trisha Price: Keeps turning.
Well, I think there's no, no
better time in my career of
building software than now.
And I think it allows us to focus on
the things that are important, like
business outcomes and customer happiness
and customer outcomes, versus a lot of
the more mundane tasks that have to get
done 'cause they're a part of the job.
But allowing these tools to
automate more and more of those.
And I think that's just such an
exciting time and I think it'll
help us get back to the part of
our job that is the most rewarding,
but also the most difficult, which.
Is really the hard call and you
know, how we opened it and how we can
finish today, which is all around.
What makes product hard is that
everybody thinks they know the right
answer and has an opinion, right?
One particular customer.
One particular sales person, but at
the end of the day, we are the ones
who have to make the hard calls in our
jobs and you know, is this interesting?
Sort of balance between gut
instincts that we talked about
earlier, which I agree with you.
I love your analogy that gut instincts.
Is really data.
It's just our own LLM, human
processing, all of that data and
pattern recognition to make decisions.
And you can, you can use other
people and you can use systems
and other pieces of data, but your
gut instincts is really data too.
And I love that.
and I love.
You know, learning from you today
about your product center of excellence
and how that enables not just you
to make decisions, but all of your
product managers to make more informed
and faster and better decisions
and how you have been able to.
Continue to evolve with AI and new tools
that are out there, but yet still remained
business outcome, analytics focused, and
most of all, customer success focused.
So, I just really appreciate you,
Noa, been a long time partner for us
at Pendo, but also for me, and I always
learn something from you every time
we have a conversation and impressed
with you and what Factset has done.
So truly appreciate you coming on today
and sharing your knowledge and wisdom
with, our listeners and with me, and
look forward to future conversations.
Noa Ginsberg: Likewise, thank you so
much and I learned so much from you
as well and from the podcast, so it's
a great thing you've started here.
Trisha Price: Thank you.
Appreciate it Noa.
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