Web analytics involves analyzing data from websites and web pages. It can identify areas of risk, fraud, or ineffectiveness and influence business decisions. Web 2.0 analytics analyzes quantitative and qualitative data from websites to improve customers' online experiences and achieve expected results. Metrics like bounce rate, traffic sources, and abandonment rate are important to analyze. Popular web analytics tools include Google Analytics, True Social Metrics, and Kissmetrics. Mobile analytics differs from web analytics due to differences in how users interact with mobile apps versus websites.

1. Web Analytics 2.0
KEVIN SANTIAGO JIMÉNEZ CORTÉS
UNIVERSIDAD COLEGIO MAYOR DE CUNDINAMARCA
2019

2. introduction
web analytics is a branch or discipline of data analytics
or business analytics.
It focuses on the analysis of the data that flows through
sites and web pages.

3. The analysis of data on the web is more analysis of web
traffic.
The web has offered data more data to large volumes of
data. However, it is about finding the most significant
data and the task is difficult.

4. data analytics
it involves the processes and activities designed to obtain
and evaluate data to extract useful information.
can identify key areas of risk, fraud, errors or misuse,
improve business processes, verify the effectiveness of the
processes and influence the decisions of a business.

5. web 2.0 analytics
is the analysis of quantitative and qualitative data
from your website and the skills to drive an
improvement to the online experience that both
regular and regular customers have and translates
some expected results

6. web analytics approachesWeb Analytics:
technologies and web analysis tools, used in laptops servers that have formed systems systems of traditional
imformation, base of operation of the discipline.
Social Analytics:When social media starts to implant in organizations there is a need to analyze and manage the
app's data.
Mobile Analíticas:
You can spend less time in applications than on the web, but the application sessions are more concentrated.
Big data analytics: Big Data is much more than taking into account an application or an Internet tool. It is a discipline that
has been able to evolve enough to analyze and process millions of data through powerful servers and specific tools. In this
analysis we must take into account, in addition to the volume of data generated, its speed of creation and the fact that they
are unstructured.

7. Metric`s
1 ) Rebound rate:
This statistic is important both on websites
and landing pages, because if the user enters
and leaves without doing any action within it,
the visit will not have served us at all because
we will not have fulfilled our objective.

8. 2)Traffic sources:
If you only look at the visits you
will not know where they came
from, but if you analyze the
sources of traffic you can see if
that work in social networks is
working or not because you will
know how many visits have
arrived exactly from there.

9. 3)Abandonment of the user:
This metric is very important in an e-commerce, because if we
analyze the purchase process and we see that many people
leave the web at a certain point of the shopping cart we
should improve it to get increase the conversion rate.

10. web analytics tools
1) Analytics :
2)True Social Metric's:
3)Kissmetrics:

11. Mobile web analytics
The criteria universally marked to measure and
analyze the data of a web page have not been
transferred in the same way when analyzing a
mobile environment or an app. Mobile and Web
have big differences when you start to analyze user
data. Users use mobile apps in a different way