>> Hey friends, do you know that we have
data science that proves that you're more likely
to be successful on Azure if you
start at the Azure Quickstart Center.
This insight is one of the reasons that
new users are encouraged to use that center after sign-up.
Lisa Cohen is here to show me how
your feedback and data science drives
this and many other improvements in Azure today on Azure Friday.
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>> Hey friends, I'm Scott Hanselman and it's Azure Friday,
I'm here with Lisa Cohen who's going to teach me all about how
data science can help us use Azure. How are you?
>> I'm great, thanks for having me, Scott.
>> I understand that there's real science
behind how I can be successful on Azure.
I just thought good user interface designers decide where to put
buttons and writers write good documents and then I'm successful.
It's a little more complicated than that though.
>> Well, and they're all part of the puzzle,
all those are certainly all key pieces,
and we design these features
with those end-to-end scenarios in mind.
Then data science is another tool that we get to use
to see what is working,
what's not and so we can continue
to learn and evolve our approaches.
>> I understand that you have a slide that has
an interesting chart that talks about my success,
which I hadn't really thought about before.
>> That's right and so we like to say that
our customer's success is
our success and so that's really what we focus on.
Whether it's tracking those inflection points,
seeing what's having the impact, determining root causes.
As we do that analysis, of course,
as we identify that we want to go
ahead and act on the information we learn.
That can come in the form of product changes,
it can be content that we create to help as well,
or other programs that support the overall user experience.
>> Finding those root causes are really important.
I mean, there's this funnel of success as you move forward.
It's like that button's too small or that wording is not
clear and any one of those thing
could knock me off my path for success.
>> Exactly and so that involves root cause analysis,
sometimes experimentation where you make the change.
We want to see if that was actually truly
what caused the difference.
Also requires having a pretty holistic view of
all the different factors involved so we
can attribute it to them appropriately.
>> That holistic view thing is a really interesting point
because we know that there's all these little individual products,
little silos of Azure,
but they're really just building bricks
that we use to build larger systems,
and when you start building a large system
based on 40 sub-products,
it can get pretty complicated.
>> Absolutely. The data platform that we
built behind this as a key aspect of that experience
and one nice thing is that we
have been able to leverage a number of
Azure technologies through this to use them ourselves as well,
whether that's the data sources that we
bring together, the machine learning models.
We'll get to discuss a bit as well,
where we get to use Azure Data Factory and
Azure Data Lake services
or Data governance.
We get to use purview for our data dictionary and then
further Microsoft technologies in
terms of our distribution channels as well.
>> Interesting building on
Azure to make people successful with Azure.
>> Exactly, you got it.
>> I understand that the Quickstart Center is really important.
We actually did another video about that before
because you want people to be successful early on.
Because if that 0-10 miles an hour isn't successful,
then they're never going to get up to speed.
>> Yeah, let's go ahead and dive into that.
Quickstart Center, fun story behind that is that Aisha,
who had the idea for this feature actually
was originally a data scientist at the time and
she was looking at that challenge that users were
having after they sign up to get going,
and so that's where this idea came to life.
A number of great resources here in terms of templates,
getting started, guides, content.
As we mentioned earlier,
as soon as you finish your sign-up on Azure.com,
you will be directed to this page because we have found that
it does help users with that first step.
Otherwise, if you want to find it at any point in time,
you can just go to the portal,
search for it, or on your homepage,
you'll notice this little link down here.
>> Cool.
>> Great, I know Leon's been on the show as well.
A lot of great experimentation
that's gone on across the portal as it's
been simplified over different iterations.
I was just going to call out the Azure mobile app,
which I think you featured as well.
In terms of what we see in the adoption,
we find that particularly been valuable for
users as they expand the number of subscriptions,
that they're using their workloads.
Super handy to have it right there
on your phone where you can make quick changes on the go.
>> Yeah, I use the Azure mobile app all the time,
particularly recently they added charts,
so I can actually see my website
chart well on the go, which is pretty slick.
>> Awesome. Well, as an Azure user,
another website that you certainly use frequently is Azure.com.
That's another place where we get to do experimentation.
We often talk about the surprising power of online experiments.
Seemingly small changes can make a pretty big impact on example,
there is just aspect.
Wherever you go on this site,
you'll always be able to access this free account linked
to get started here as you navigate around.
The free account link itself brings you
to learn about the Azure free trial services,
and so beyond experimenting with the page,
we've been able to evolve that offer itself over
time to see what's most useful for users.
Whereas we had originally started with
this $200 credit for 30 days,
there's now 12 months of
free services and that's been there for some time.
But the free services,
do continue to evolve as new services become available.
We see what users are leveraging most.
You can always take a look at the current list down here as well.
>> It is a lot more simple than I remember it being in the past.
I can admit even though I
work for the company that I had been a little bit overwhelmed.
But things are getting more, I don't know,
like less overwhelming, more welcoming,
and I feel like I'm being led along a path to success.
>> Great. There's three different key ways
we think of in terms of getting Azure,
whether that's through the subscriptions
available on Azure.com itself,
working with a partner or working as larger corporation,
getting Enterprise Agreement and working with the Microsoft field.
While we use data science across all those today,
we're focusing on things that you,
and the end-user, directly access yourself.
There are a number of these offers here
for specific types of scenarios.
As a developer, startup, etc.
One that I do want to call out for
our users if there are any students tuning in,
is Azure for students offer,
which has been great to have this $100 credit over 12 months
with no credit card required to make
it particularly accessible to students.
The team has been able to
leverage data throughout the evolution of this offer to streamline
that sign-up process for the students and just knowing
the student usage patterns throughout
the academic year has also been able to add a renewal.
Folks may not be aware of it typically.
A student for more than one year so that
you can actually renew that at the end of your first year as well.
>> Sleek.
>> Well, finally beyond the Azure subscriptions itself,
another part of the overall Azure portfolio you want
to download is a number of
the VMs services available through the Azure marketplace,
whether offered from Microsoft or from our partners.
You can access this on azuremarketplace.com,
or ultimately as you transact
you'll come through the portal or you
can also search for marketplace up hear in the search tab.
Team here uses data to evolve the flow and layout categories here.
Also, we saw that when people get these offers,
there's a funnel there in terms of your acquisition
and those would have the best experience,
are typically using offers that have great documentation upfront,
plan details upfront,
and so continue to update those,
let you have all the information you need to get started.
Then I often think about support is really
a key aspect of that overall experience.
Support of course is a general term,
includes even things like Azure Friday,
helping learn about the services available,
as well as a number of other community forums,
documentation, learn.
There are support plans that you can
access as well different levels here.
We do use data science with our support team to be able to predict
with those cases which are blocking urgent issues for users.
That can help prioritize and create
quick actions for the support engineers
to engage and maximize
those communications that they have with you as well.
Then we also take a look at
the support cases through
natural language processing and identify what are
those top topics that keep
emerging so that we can actually solve that problem
more upstream and make changes in the user experience.
We certainly prioritize many issues that we
might see that come through there and
that we can solve once and for all.
>> That's a really great point if someone has to call support,
but you could fix it by changing something,
like you said, way upstream,
whether it be in docs or in the portal itself,
it saves every one time.
>> Absolutely. Great, and then we also mentioned tools here that
you can use yourself
to unblock and use data with your own solution.
There was a show on Advisor
showing the different cost recommendations,
security policies to implement.
Of course, there's cost management
through the portal where you can actually forecast
the cost for your subscription and make changes to optimize there.
Then before you even get started here and
azure.com using the pricing calculators.
Those are a few key features available where
you can use data on your subscriptions too.
Then lastly, I wanted to end with documentation.
I think we just continue to find
that throughout the user experience,
whether it's signing up, first getting started,
or as you expand the depth and breadth of Azure services,
you engage with the users that use documentation consistently,
achieve greater success with
their migration and expansion in the Cloud.
Of course, definitely advocate using myths wherever possible,
and on the data science side,
we've been trying to make it more accessible
as there is millions of
documents across a wide variety of products levels.
Here in Azure, in the search,
we actually use Azure Search,
which you have available through cognitive services as well.
Then here at the bottom,
you'll start to notice there is related content.
This is powered through machine learning as well to identify
related topics that often get visited with this topic.
Lastly, another scenario,
we love all the feedback that comes through
here definitely a great volume,
and so we use clustering techniques in order to categorize these.
For example, if there's
a broken link category sample code that needs to be updated,
localization that could be improved,
so that helps us just rapidly route that
to the appropriate team that can act on it must quickly.
>> Very cool. You know what we need to do, you and I Lisa,
is we need to have a follow-up to find
out how much more
successful you can be when you watch Azure Friday.
>> Love that.
>> Fantastic. Well, it's really good that you're
using data science to make me more successful.
I know that we're going to include links in
the show notes because you-all
at data science at Microsoft have a blog on Medium.
We can learn more about
all the different work that's being done holistically
throughout all of the Azure product line to make folk successful.
>> Sounds great, Yeah, join us
there to learn more about the techniques,
the code, everything that we use behind the scenes.
>> I am learning today all about how data science could help make
me and you successful today on Azure Friday.
Hey, thanks for watching this episode of Azure Friday.
Now I need you to like it.
Comment on it, tell your friends, retweet it.
Watch more Azure Friday.
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