Introduction to Digital Analytics Foundation | Simplilearn Video Lecture | Web Analytics: For Beginners - Data & Analytics

welcome to foundations of digital
analytics my name is Stephan amel I'm a
consultant I'm a teacher I'm a speaker
and I've been in the field for several
years so in this training which is part
of digital marketing we're gonna we're
gonna look at what are the essential
components in the essential knowledge
that you should learn about being a good
digital analyst so we're not going to
deep dive into how to use the tools but
we're going to learn a lot about what
are the concepts what are the essential
elements of being a good digital analyst
so stay along with me and we're gonna go
through various sessions addressing each
of the topics that are important in the
field welcome to introduction to digital
analytics so we're gonna start with
basic concepts supporting the role of
the digital analyst so 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 they 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
and 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 and certain needs of
our customers so this in a way is the
essence of what is digital analytics
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've brought in
the scope from a business perspective
because we're thinking about marketing
but we're also expanding 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 broadened 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 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 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 is your own carrier
pad and you can't easily tell other
people you know here's everything I
learned so true digital analytics we can
more easily expand the capabilities of
understanding how things are working
assumptions you you have you can make an
absorption 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's 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 the past
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
field 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 99.9 is the
percentage of successful transaction 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 a
banking environment 99.9 is actually
below the threshold of acceptable
transactions that I should process at
every time so in most environment you
will see targets of being able to
transaction transaction with a very very
little amount of errors so 99 point
maybe 99.95 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 reports
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's 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
analytics 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 analytics 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 realistic decision
informed by data every single word is
important here how an organization might
be a company a private or company 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 we need to
consider so I need to find a balance
between what would be the best solution
and what really I can do and and this
also is key for the digital analysts
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 recommendation that are
both optimal and realistic so we need to
find a balance and inform decision
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 at that
basically what happened is we delegate
that responsibility and we automate the
process but at the beginning they're
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 nee 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 gonna 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 the
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 and 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 realistic
so if we we are good change agents we're
gonna be able to make recommendation
that that get 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 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 this is in in in the future we're
going to see more managers who are more
data savvy and data-driven or data
informed and we're gonna see that they
have both the skills to be really
leveraging data in all contexts of the
business but also make the decisions in
the and
roll 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 the 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 accumulation 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 gonna 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
gonna 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 maturity 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