Digital Analytics Introduction | Digital Marketing Tutorial For Beginners | Simplilearn Video Lecture | Web Analytics: For Beginners - Data & Analytics

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imagine in the offline world imagine you
have a store where you are able to look
at people you know walking on the street
looking at the window of your shop and
looking at you know what are the
characteristics of those people why are
some people coming in the store and some
people not coming in why are how people
interact in the store what we are
looking at how they walk in the always
in the looking at different products
maybe picking something looking at it
and putting it back on the shelf even
putting stuff in their cart and
eventually abandoning the cart and not
purchasing anything so in the offline
world doing something like this would be
you know fairly difficult it expensive
and would be time-consuming in the
online world we have the we're lucky
because we have a constant environment
where we can watch learn and adjust and
improve our business to better answer
the needs of our customers so this in a
way is the essence of what is digital
analytics is to understand where people
are coming from what are their
characteristics what are they doing on
our website and whether it works for
them and it works for us because we want
to have a successful business so in the
past just as a side note in the past we
were talking about web analytics
because it was very very focused on
websites and it was heavily geared
toward marketing and now we're talking
about digital analytics so we've
broadened the scope and when we talk
about digital analytics we talk about
websites of course but we also talk
about mobile application we talk about
the Internet of Things where we can
measure any type of device and collect
data about whether it's working or it's
not working and we broaden the scope
from a business perspective because
we're thinking about marketing but we're
also expand
to every business function we're looking
at sales we're looking at customer
support we're even looking at HR because
most websites have a way of contacting
to apply for a job for example so we've
brought in the scope from web analytics
to digital analytics so what do we want
to learn we want to have some some very
important understanding of what it is to
be an analyst what it is to do digital
analytics we want to understand what is
the context of the business and how
being creative is also an important part
of the analyst role we want to
understand how we evolved from looking
at simple reports up to today where the
landscape is very complex very rich and
there's virtually no limit to what we
can do so why digital analytics so I
just alert to the physical store but one
of the element is the despite all of the
experience that you might have it is
very useful it is valuable but it
doesn't scale so your experience is your
own carrier path and you can't easily
tell other people you know here's
everything I've learned so through
digital analytics we can more easily
expand the capabilities of understanding
how things are working assumptions you
you have you can make an assumption and
it might be very very valuable it might
be very plausible that yes I think doing
this on the website would be better for
our customers and and better for our
business but until you you actually test
it until you actually make the change
there's no way to be sure that
effectively better than the other
alternative so assumptions are good but
we want to go in
at a pace where things are moving so
quickly that we have to adapt and we
have to evolve very quickly and last is
faith faith is yeah we can believe that
something is so good we can believe that
the latest technology and latest trend
is so awesome but at the same time we
have our own bias we are biased in so
many ways because of our experience
because of our culture because of the
previous jobs that we had in a path and
and so many reasons so true digital
analytics we remove in a way this bias
that we have so those are you know three
aspects of why you should go for digital
analytics experience that doesn't scale
assumptions that can't be proven on
fields you actually do it and and faith
and bias that we have that we want to
get put that aside and go with something
that really works so continuing on why
do we want to do digital analytics in in
today's environment we have a tremendous
amount of data data is coming from
everywhere it's coming from your website
it's coming from your mobile application
it's coming from your own business
systems like customer relationship
management CRM systems it's coming from
sales it's coming from competitors it's
coming from all over the place so the
problem is not having a large amount of
data because we usually have more than
we need but we want to extract
information out of it information is
being able to understand the meaning of
the data but once we have information
what do we do with it
we want to transform it into knowledge
knowledge is understanding the context
of the data and the context of the
information we have so we know that for
example if we if I have a piece of data
that says 99.9 that's a piece of data
that I have but what does it mean
information might be that ninety-nine
point nine is the percentage of
successful transactions so there's a
little
number of transaction that actually
doesn't go through through my systems
and there are errors and stuff knowledge
might be that understanding that because
I'm in the banking environment
ninety-nine point nine is actually below
the threshold of acceptable transactions
that I should process that every time so
in most environment you will see a
target of being able to try to process
every transaction transaction with a
very very little amount of errors so
ninety-nine point maybe ninety nine
point nine five so I mean just a little
bit below my threshold this is knowledge
I know because of the environment that
I'm in I know because of the target that
I have that I need to do something and
wisdom is actually being able to act on
that information now that I know what
can I do with it I need to investigate I
need to find where the problem is I need
to be creative and find different
alternatives to try to go from 99.9
success to my target of 99.95% of
success okay so going from data up to
acting on the data this is critical in
the role the analyst is going to play so
it's if you don't want to we sometimes
we hear the term reporting monkey
reporting monkey is is pretty negative
you know it basically means that yes you
are able to extract the data you might
be able to turn it into information in
the form of your part but you don't
bring the knowledge so you don't want to
be reporting monkey right so you know
being a teacher and being in the field
for so many years I looked at how people
define what is analytics and you know it
simply put analytics is the science of
analysis okay what is analysis analysis
is it really relates to a science it's
how we break something complex into
small parts
little chunks so that we can understand
how they work individually and if we
understand how they work individually we
can measure them and we can optimize
them so this is really what is analysis
breaking something complex into smaller
parts so that we can understand it and
therefore we can optimize so again what
is the narrative the science of analysis
that's a very simple definition right
but after asking you know fellow
colleagues and other consultants and
practitioners and a lot of people
basically I realized that there were no
good definition of what is analysis so I
decided to come up with a definition I
think can old water very easily so I
define analytics as being how an
organization arrives at an optimal and
reality decision informed by data every
single word is important here
how an organization organization might
be a company a private organ it might be
you know publicly traded might be
government nonprofit so it's an
organization so it applies to any type
of environment how you do something
implies there's a process there's a way
to do it there's some kind of recipe
that you can follow to get to a success
the optimal in realistic is really
important because it plays on the
ability of the digital analyst to be to
be creative to find the balance between
what would be the best solution if there
were no constraints if there if there
were no limits to what I can do no
constraints of budgets no constraints of
politics maybe no constraints of the
legal and ethical environment and I
could do anything so this would be the
optimal but realistically there are a
number of things that I need to consider
so I need to find a balance between what
would be the best solution and what
reactively I can do and and this also is
key for the digital analyst because
often time analysts will make
recommendations that don't go anywhere
and the reason for that you very often
the reason is simply that analysts are
not able to make recommendations that
are both optimal and realistic so we
need to find a balance and inform this
vision implies action and informed by
data implies that there still we still
leave room for the human brain to make a
decision to leverage their own expertise
experience and other other elements that
come into play when you have to make a
decision so that's why we say it's
informed it's not automatically done
with the data later on we're going to
talk about automations and stuff like
that basically what happened is we
delegate that responsibility and we
automate the process but at the
beginning there's still an informed
decision to do it right there are three
essential elements that we need I
mentioned the banking environment the
financial environment so we need to
understand the context of the business
we need to have data right and on top of
that we need to be creative so there's a
lot of room for creativity in what we do
being creative creative is is the
ability to go beyond the obvious it's
the ability to go beyond the here's the
top 10 things that you should do and be
and go beyond that be much better than
that being creative is being able to do
better than your competitor because it's
easy to look at a competitor and say oh
we're going to do the same no you don't
want to do the same you want to do
better than that so context data and
creativity are three important elements
that will allow us to do our analytics
at the core of the analyst role when you
think of it we are essentially change
agents we bring change to the
organization and that's why we make
recommendations we push for change
sometimes yes it might be difficult but
again going back to the definition of
what is analytics we need to balance the
optimal in the reality so if we we are
good change agents we're going to be
able to make recommendation that that
gets acted on right and being a change
agent means that sometimes it won't work
it will take time it will imply you know
facing you know changes about status quo
we want things to change we want to
improve things we want to take risks if
we don't take any risk nothing is going
to change the big difference that I've
seen between an analyst and a manager is
essentially that the analyst has a power
of recommendation but the manager has a
power of decision so that is in the
future we're going to see more managers
who are more data savvy and data-driven
or data informed and we're going to see
that they have both the skills to be
really leveraging data in all contexts
of the business but also make the
decisions as in the analyst role do you
make recommendation but you typically
don't make the decision except in the
scope of what you are responsible for so
for example if you are responsible to
optimize AdWords campaigns on Google on
Google search you've been delegated that
responsibility and you are you you make
the improvement you make measurement and
you make the decision to reallocate the
budgets and optimize those campaigns
because that power of decision has been
delegated to you but typically when we
go beyond those boundaries we have a
power of recommendation no power of
decision so is it harder easy that has
been a debate for the past ten years I
would say you know it's it's really easy
to start it's really affordable to start
there are free solutions that
you can use and get going very easily
the key to make it easier is to work on
the thing that you can manage that you
can control and that you can influence
and we're going to talk more about those
things manage control and influence this
is how you're going to keep your work
interesting and easy and in the next
lesson we're going to talk about the
concept of maturity so we're finding out
what are our strengths and weaknesses
and based on that develop a road map
that will be optimal and realistic so
that we can do better digital and
outtakes so in this lesson we've looked
at some very important aspects to get
going and we're going to deep dive into
each of those aspects a little more in
the upcoming lessons we need context we
need data and we need to be creative we
need to understand how we can break
something complex into smaller parts so
that we can understand it and we can
optimize it we need to understand also
that we went from web analytics web
focus and marketing centric to digital
analytics where we can leverage any data
we have and we can basically optimize
any aspect of the business given we
understand the context and we can
leverage the data we also want to
emphasize the importance of working
especially when you're starting in the
field work on the things that you can
control manage and influence and lastly
doing a match with the assessment will
allow you to identify your strengths and
weaknesses and develop a roadmap that
will work for you over the next six
month year and then repeat the process
of assessing your maturity and adjusting
the roadmap accordingly
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