1. Social media analytics involves gathering data from social media channels to support business decisions and measure the performance of actions. 2. It uses specifically designed software to retrieve and analyze keywords, topics, and other data across social media platforms through search and web crawling. 3. Social media analytics provides insights into trends, conversations, customer sentiment, and competitors that can be used to make strategic business decisions regarding product development, customer experience, branding, and more.

1. What is social media
analytics?

2. Social media analytics is the ability to gather and find
meaning in data gathered from social channels to support
business decisions — and measure the performance of
actions based on those decisions through social media.
Social media analytics is broader than metrics such as likes,
follows, retweets, previews, clicks, and impressions
gathered from individual channels. It also differs from
reporting offered by services that support marketing
campaigns such as LinkedIn or Google Analytics.

3. Social media analytics uses specifically designed software
platforms that work similarly to web search tools (Hubspot,
Buzzumo, Semrush etc). Data about keywords or topics is
retrieved through search queries or web ‘crawlers’ that span
channels.
Social media analytics includes the concept of social
listening. Listening is monitoring social channels for
problems and opportunities. Social media analytics tools
typically incorporate listening into more comprehensive
reporting that involves listening and performance analysis.

4. Why is social media analytics important?
IBM points out that with the prevalence of social media: “News
of a great product can spread like wildfire. And news about a
bad product — or a bad experience with a customer service rep
— can spread just as quickly. Consumers are now holding
organizations to account for their brand promises and sharing
their experiences with friends, co-workers and the public at
large.”
Social media analytics helps companies address these experiences and use
them to:
• Spot trends related to offerings and brands
• Understand conversations — what is being said and how it is being
received
• Derive customer sentiment towards products and services
• Gauge response to social media and other communications
• Identify high-value features for a product or service
• Uncover what competitors are saying and its effectiveness
• Map how third-party partners and channels may affect performance

5. These insights can be used to not only make tactical adjustments, like
addressing an angry tweet, they can help drive strategic decisions. In
fact, IBM finds social media analytics is now “being brought into the core
discussions about how businesses develop their strategies.”
These strategies affect a range of business activity:
• Product development - Analyzing an aggregate of Facebook posts,
tweets and Amazon product reviews can deliver a clearer picture of
customer pain points, shifting needs and desired features. Trends can
be identified and tracked to shape the management of existing product
lines as well as guide new product development.
• Customer experience - An IBM study discovered “organizations are
evolving from product-led to experience-led businesses.” Behavioral
analysis can be applied across social channels to capitalize on micro-
moments to delight customers and increase loyalty and lifetime value.
• Branding - Social media may be the world’s largest focus group.
Sentiment analysis can continually monitor positive or negative
expectations to maintain brand health, refine positioning and develop
new brand attributes.

6. • Competitive Analysis - Understanding what competitors are
doing and how customers are responding is always critical.
For example, a competitor may indicate that they are
foregoing a niche market, creating an opportunity. Or a spike
in positive mentions for a new product can alert organisations
to market disruptors.
• Operational efficiency – Deep analysis of social media can
help organisations improve how they gauge demand. Retailers
and others can use that information to manage inventory and
suppliers, reduce costs and optimise resources.

7. Reasons why social media analytics is essential
1. Measure and prove ROI and marketing impact
The bottom line to analytics is that they give you instant feedback about how
your company is performing across social media channels and whether the
strategy your teams are executing is effective. Overviewing performance KPIs is
essential to the success of your social media campaigns.
If strategy isn’t working, then your data analysis will point you in exactly the
right direction so you can make effective strategy tweaks before performance
dips or becomes a real problem. Catch any downward turns fast and remedy
them right away.
Clear overviews also allow CMOs, or anyone across the organization, to quickly
and easily see the most important metrics and evaluate marketing performance,
so everyone’s working from the latest data.
It’s logical to seek to understand if the resources you’re investing in social media
(for example, paid content promotion) are bringing in revenue – directly or
indirectly. A full 61% of marketers still struggle to prove ROI from their marketing
efforts.

8. The right tools are as important as the right method of calculation when it comes to
ROI on social media. To make things easier:
• Add a Facebook tracking pixel to your site’s key pages, and any page linked to
from your social channel. This allows you to accurately attribute conversions and
actions to specific content or campaigns, even if the user converts days or weeks
after first reading your content. If users don’t convert, the Facebook pixel allows
you to conduct remarketing campaigns, targeting users who have already visited
specific pages before but failed to take action.
• Add Google Analytics UTM parameters to your social ads’ URL to understand how
much traffic and how many conversions your social media marketing activities are
driving.
• Ads Benchmarks help you measure your social media ROI in context by
understanding how the return on Facebook ads (or Instagram ads) evolves across
regions and industries over the course of a campaign, or any period of time you
choose.
• Paid Analytics allows you to quickly track all your campaigns and ads in one place
so there’s no confusion around advertising campaign performance. Analyze entire
campaigns, or individual ads, to save time and optimize budget. There are so many
moving parts within paid campaigns but this solution gives you maximum
transparency and actionable insights.

9. 2. Make better strategic and business decisions
Strong social media analytics will obviously provide marketing teams
with data and insight that help them identify what’s working and what’s
not when it comes to social media and content strategy. However,
social analytics also provide vital insights that help inform strategic
decisions outside of marketing.
This holds more and more true every year, as the amount of data being
posted to social media is steadily increasing, as is our ability to extract
useful insights from this data as technology improves. Here are some
examples of how social media analytics can help improve key
decision-making both inside and outside of marketing:
Respond to trends in a timely manner – Access real-time data so that
you can rapidly act upon bigger trends and get the jump on
competitors.
Minimize business risk – Data is there to signpost your strategic path
and show you the right direction, so let data guide your decisions and
help you make the best use of your resources and be led by your
performance KPIs.

10. 3. Compare your social media performance against competitors
What is the point in celebrating good performance if you have no idea
whether it’s better than your competitors' performance or how it looks
set against average industry performances? It’s pure vanity to do so,
and metrics that stand alone have no bearing on real success.
Context is so crucial, so to measure real success companies must
compare themselves to competitors, and also to industry and regional
performance averages.
Benchmarking always provides key insights and allows you to see
how you stack up against the competition, or see how your
performance looks against your industry or region averages.

11. The Phenomenology of
Social Media

12. Social media provides people with an incredible opportunity to express
their opinions on an array of important, meaningful life topics. In turn,
they experience a wide variety of opinions from other people to which
they react and respond accordingly. However, there is mixed
consensus in the literature about the nature of social media in relation
to how people psychologically handle the multitude of opinions
expressed there about personal and relevant topics.
Social media has become a mainstay of interpersonal communication in
our postmodern society. It transformed the means, the frequency, and
the intensity with which we express our ideas with one another. It gives
us another form of access to other people, whether it be a genuine,
intimate, calculated, or limited gateway into their personal lives, with
anyone anywhere in the world. It also provides an online platform for
different individuals, groups, organizations, and institutions to convey
their messages to either the general masses or to specific target
audiences in a quick and simple manner.

13. One of the ways through which people communicate with each other on
social media is through opinion expression – the sharing of opinions by an
individual, group, organization, or institution. Throughout the course of a day,
people have countless opportunities to share their values and beliefs to
others by expressing their personal and/or professional opinions on a variety
of topics, as well as arguing against other people’s differing opinions on
those topics.

14. SOCIAL MEDIA
ANALYSIS BASICS

15. Why social network analysis?
Enables us to segment data based on user behaviour.
Understand natural groups that have been formed:
1. Topics
2. 2. Personal Characteristics
Data collection methods:
• Surveys
• Interviews
• Observations
Analysis:
• Computational analysis of metrics

16. THANK-YOU