Welcome to ChannelWaves, the podcast where channel
leaders share success strategies, best practices, and emerging
trends brought to you by StructuredWeb.
Here's your host, Steven Kellam.
Welcome, everyone, to ChannelWaves, StructuredWeb's
view into everything channel.
And I'm your host, Steven Kellam.
Thanks, everybody, for joining us today.
Very excited to have Gina
Batali-Brooks joining us today.
Hi, Gina. Hey, it's Steven. How are you?
Well, so those of you who don't know Gina, and
you should know Gina if you're in the channel.
Gina is the founder and president at it Is Inspired.
We're going to talk about
integrations today, by the way.
That's where we're going to head in fairly quickly.
And I think I live integrations
on a pretty regular basis.
Gina lives them on a daily basis.
And it's become such a staple of everything that
I'm talking about or we're talking about in every
conversation with all of our clients or our prospects.
And I don't know if I want to say it's getting worse.
It's just getting deeper.
And just the expectations from my perspective is the
bar has been raised so high on integrations that
you just got to have it down today.
And what we're going to talk a little bit today
is why that is what's happening in the world today,
some of the challenges, and we're going to leave you
with some best practices on things you can do.
And maybe we don't even have all the answers,
but hopefully we could have the questions that you
can ask to get those answers right.
But anyways, from my perspective, Gina, and I'll let you
take it from here or start it from here.
The expectations on how fast and what the results
of integrations are, are just through the roof today.
When we get on calls with the IT team, like, if
you're not on all cylinders on how to get that done,
they don't want to have anything to do with you. Okay.
Their patience becomes very slight.
So maybe you could start today with, from your
perspective, maybe tell folks a little bit about what
you do and why you're so involved this.
And maybe we can talk a little bit
about why integrations is so important today. Yeah.
So Is Inspired is a
channel infrastructure consulting company.
So we focus on all things
partnership in the tech stack.
So that's data systems, processes, and the people that
make that all tick so that you can be
successful with your programs and your channel strategy.
And so it's really about, we always say we speak
geek and we speak channel, and we like to combine
those together so that it makes the channel program sing.
And so, obviously, a big piece of any tech stack
is the integrations and how to make those work.
And actually, the core to me is the data. Right.
And so anybody who's worked with me knows that
for years and years since I started, data has
been kind of the foundation to us of what
data needs to be, where to drive what.
And so to me, that's the core of the
integrations and why they need to be there.
And I think one of the things that we're seeing
so much is with whatever you want to call it,
ecosystems, federated partnerships, whatever term you want to call.
But what we're seeing is this ability to meet
the partners and the aspects of the ecosystem where
they're at, and to provide the data that's needed
in a very real time and meaningful way.
And so we're starting to see, not
just within an organization, the integrations being
important, but outside the organizations to make
the full partnerships actually work.
And I think that's kind of an
interesting dynamic that's making the integrations much
more relevant and much more challenging.
Much more challenging.
I personally, since I was a partner,
that's been a long time, I'll always
look at it from a partner perspective.
And I remember when I was running an
MDF company, Gina, this goes back so far.
This is probably before you and I met.
There was a report that the partners wanted
from a very large vendor, and they wanted
to see their MDF, their rebates, their incentive.
They want to see all of these.
And you could probably pull leads into that as well, too, but
they wanted to see all of it in a single place.
And this was back when you had incentives were in
one place, and MDF was one place, and rebates were
in one place, and leads were in one place.
And as a partner, they used to drive me crazy.
And I remember the first time I saw
a partner benefit summary page at this vendor,
and it had all been pulled together.
And to get that data now, it seems pretty easy, right?
Okay, we'll talk about that.
But to get all that data in one place, I remember we
showed it to a partner, and they were like, oh, my word.
And then the vendor was like, can you imagine,
sorry, total aside, can you imagine being a partner
manager, a CAM, and trying to show the benefits
of all the benefits that you're giving to a
partner and trying to pull them together in four
different places and four different slides?
It's just a nightmare for everybody. Yeah.
Obviously, with things like AI
being in the forefront everywhere.
Being able to have real time access to
the data that you need super important, and
quality data is super important to do anything
to realize some of the benefits of AI.
And so, again, the integrations and some of the
things we're starting to see around, and not that
these are new terms, but I'm actually starting to
see them being implemented, and implemented well, in some
cases around things like data mesh and data fabric,
and looking for ways to unify, to come and
look at data, regardless of which systems they're in.
And that enables you to be able to get
rid of some of the point-to-point integrations
that have been going on, which are fragile, especially
when you get outside of an organization.
One side changes something, and all
of a sudden it breaks everything.
And so we were working with a customer who
had done that and done a great job of
integrating with some of their partners, some of their
big partners, and they said just the maintenance of
trying to keep the integrations up was so hard.
And so I think some of the new structures coming
out and seeing people, I talked to somebody the other
day who's got a data fabric implemented, and they said,
literally, they're getting ready to change out their CRM, and
it's no problem because the data fabric is there.
And it's not a point-
to-point integration with anything.
It's one integration they have to
write into the data fabric.
And so, to me, that was just, like, kind
of mind blowing, because you hear, I'm not to
cut you off, but I haven't heard that yet. I have yet.
To be in a situation where someone
has said that, that's actually pretty cool.
And I would think that most of our
listeners and viewers have not experienced, you know,
like I said, data fabric is a term.
NetApp has been talking about it for years.
I mean, it's a term that's been around there.
And in concept, it's always interesting.
And I know Forrester's got a lot of stuff
around it, but to hear a customer talk about
it actually being implemented and the fact that they
can switch things in and out is just.
I mean, it was pretty cool.
I think the opposite side, I was on a call
the other day, and it was an hour long call.
Someone's replacing their PRM and their TCMA, and the
nightmare in dealing with the CRM and the nightmare
of that call, you could see the trepidation.
It was interesting.
And you might relate to this because you're in
the middle of this, more than I am.
I was sitting back and listening to it.
And normally I think about, okay, what's the effort
level on my side at a TCMA, or my
partner at the PRM or the MDF?
I literally was thinking, Gina, what's the effort level of
the client that they're having to go through this?
Because it's very opposite of what you're talking
about with all the point-to-point integrations.
That's right.
And I think the other thing I was reading that
was kind of interesting is Accenture said that 90% of
the data has been produced in the last ten years.
And then Forrester came out with a report saying
that 32% of the people they interviewed are not
getting any value out of the data.
It's 90%.
But how much is relevant? Yeah.
And I think it was 27 or
28% are saying that there's no actionable.
Only 27 or 28% say they can
actually take action on the data.
And so if you think about that and think
about what we're trying to do in the partnership
world where you're using, ideally you can be able
to say, hey, based on a transaction that's happening,
what's the right contact content and the immediate recommended
next action for somebody to take in order to
have the best chance of closing that deal?
That data is coming from multiple places.
Some of that might be in your data warehouse,
some of that might be in your content library,
some of that might be in your CRM.
And so how do you get all of
that together to start really making that happen?
It's exciting, and I think there's a lot of
movement in this space, but people need to really
start thinking about what that data architecture looks like
and how they want to have these integrations that
can be maintainable over time. Right.
Because the other thing that's happening, as you know
all too well, is the amount of the functionality
that's coming out in systems and the system availability
in the partnership space, and how new things are
coming out all the time.
And you want to be able to take advantage of
those little point things that make your life easier.
And how do you then integrate that all in together?
I mean, this is exactly what you had me thinking about.
And if one lags behind the other, you just
minimizing the effectiveness, for instance, as well as I
do that some of the functionality is, well, what
if we could, in a deal registration, have that
content lined up from an AI perspective to automatically,
as you say, go to that, right, partner? Based on what?
But it's the base, on what side?
So the functionality is there in the
tech stack to get that there.
But then you have to figure out who is
that right partner, where in that buyer's journey.
And I feel like we're a smidgen away from that.
I think the tech stack is actually
caught up in some of that functionality.
And we just need to get that
data to be able to get that. Right, partner.
That's right.
And not rely on the partner to tell you that.
I had to laugh because I was the partner. Yeah.
And they don't have time.
The whole point I was like, hey, we got
this really cool thing for you, and it's really
automated and AI is going to make this beautiful.
Oh, but wait, here's the missing part.
You now have to tell us stuff versus just going in and.
Yeah.
Being able to learn it from what's
in your environment and the deal past
experiences and all those kinds of things.
So, yeah, the vision that I've had for years
about where this could be going, it's so exciting
because you can start to see it happening.
We've got a ways to go, but it's pretty cool, right?
It's pretty cool. Okay.
We could talk about AI.
We could talk about this forever, but we're going
to wrap this up and let you reach out
to Gina or you can reach out to me.
If you want to get deeper on this, you can go online.
But I thought I would wrap it up
with what's the biggest challenge that you see
out there and what's the biggest opportunity?
Yeah.
So I think the biggest challenge comes to really
having a strategy about how you want to do
your integrations moving forward and having that be making
decisions on, are you going to have centralized processes
for it, decentralized processes for it, how are you
going to govern it and make sure there's security
around all of it right.
As you're reaching outside of walls.
And so to me, that aspect of figuring out the
approach that you want to take for that, what's the
biggest opportunity that you see out of this, right.
And who's going to win by taking advantage of this.
So who are going to be the
winners and what's the biggest opportunity?
Yeah, so I think the biggest opportunity is to
harness the value of the data, to drive processes,
actionable insight, AI, and to be able then to
use that across all of your systems. Right.
And so I think that's the biggest opportunity.
I think, as it relates to who's going to win,
it's the people that figure that out and really understand
now that they have to get the strategy in place
for that so that as things mature around AI and
the integrations and systems and all of that, as that
all starts to mature more and more and take advantage,
they'll be able to take advantage of that functionality.
Okay, I know I said that was a wrap up, but I've got
one more question for you on this, and I can't help it.
This promise, the last thing, because we were
trying to keep these things short and sweet.
Who's owning this?
And the reason I bring this up
is because my stakeholder has changed.
We're in the through channel marketing automation, but
we tie into everyone else there, right.
Integrations are 100% key for us.
But I'm looking at who owns the big project
and it used to be point based, right.
The marketing individuals or owners would do one.
You had the MDF and you have PRM.
I'm personally seeing people in the IT department
owning the whole project and the whole landscape.
I'm seeing a shift towards the
person who owns those integrations.
And it's interesting, they're having to take this all up
a level and pull in all of these business owners.
It's been fascinating to me to watch how that goes.
I'm curious what you're seeing is what I'm seeing just
kind of a one off on some of my opportunities,
or is it moving more towards this direction in general?
Yeah.
So I think it all depends on the strategy.
So obviously the data and IT organizations are
from a data strategy and integration strategy are
going to drive a lot of this. Right.
The question comes down to of
which type of strategy you choose.
Do you choose more of a decentralized, like a
data mesh type of an approach where you have
products from a data perspective and you have organizations
that are the data owners and they're publishing products
that other people can use?
Or do you have more like a data
fabric perspective where it's more centralized and governed?
More centralized.
The systems still are in their relative areas,
but how the data is looked at is
more central still allowing you more flexibility than
all the data being in one place.
I think it's going to really depend on, and there's
pros and cons to both of them as start talking
to people and I was talking to somebody else who's
done, who's implementing data mesh right now, and to take
advantage of some of the AI and they feel like
they can move faster because they can provide that to
different departments but still have an overall.
It just, I think it really depends from an
ownership perspective how it lays out down the road.
All right, Gina, thank you for joining us today.
It's been a pleasure. Steven.
Always a pleasure.
It's great.
And what's the best way for people to
reach out to, to talk to you offline?
Yeah.
So you can always reach out to me via LinkedIn.
Gina@isinspired.com is my email.
Love to talk to.
I love this stuff is so interesting to me.
If you have thoughts, I'd love to hear them.
Fascinating.
So here's my last plug for Gina.
This was several years ago, before we met, and I
was asking someone in my space of friends who's the
most unbiased technology person I could talk to.
That's no BS, is just going to tell me
exactly what they see and exactly what they work,
what works, and treat me like an adult.
Not to the left, not to the right.
Just give me the facts.
And they recommended that I reach out to you.
So that was a pretty big
compliment for someone to say that.
And I have to say, I believe they were correct.
It's what we believe in, right?
There's different answers for different problems.
And the most important thing is to understand the
problem first and then figure out the solution.
So that's what we're all about. Okay. All right.
Once again, Gina, thanks for joining us. Listeners.
Thanks for joining us.
Have a great day. Bye.