Did you hear the one about a snack brand that made assumptions based on focus group data that turned out completely wrong? According to Facebook topic data, we’re snacking with family not friends when watching big sports events. Who knew?! With Facebook on its way to capture 65% of social network ad revenues in 2015, Facebook topic data is uniquely placed to deliver invaluable insights into the opinions of 1.49 billion of Facebook’s monthly users. Brands can now work with one of DataSift’s partners to gain access to this data and test their hypotheses. Join us for our upcoming webinar where you will: See real-life use case examples of how marketers and agencies are leveraging Facebook topic data Learn about our recent updates to PYLON for Facebook topic data and how these new features will make your life easier when analyzing Facebook topic data Have your questions about Facebook topic data answered

1. Get a Clearer Picture of
Your Target Audience
with Facebook Topic Data

2. Jason Rose
SVP Marketing
DataSift
James Ritchie
Agency, Brand and
Data Partnerships (EMEA)
Tim Shea
Agency, Brand and
Data Partnerships (US)

3. Ad Tech Music Festival
AdAgency Snack Brands
Facebook Topic Data Overview
Agenda
1
2
3
4 TV Producer Marketing and Development
5 TV Channel Marketing and Development
6 Q&A

4. Facebook Topic Data
Overview

5. 52
%21%
13%
4%
10%
Facebook is the #1 Social Platform for Marketers
5
Source: 2015 Social Media Marketing Industry Report, May 2015
OTHERS
“THE MOST IMPORTANT
SOCIAL PLATFORM FOR MARKETERS
IS…”

6. SME BUSINESSES
WITH ACTIVE
FACEBOOK PAGES
40M+
Source: Facebook Q2 2015 Earnings Report (1) Facebook, Messenger, Instagram.
2M+
$3.8B Q215
AD REVENUES
GROWING 43% YoY
ACTIVE ADVERTISERSDAILY ACTIVE USERS
1 BILLION
PEOPLE SPEND
46 MINS/DAY
ON FACEBOOK 1
Marketers Are Making Big Investments in Facebook

7. 7
Aggregate and anonymized insights
from across Facebook
Built from Posts + Engagement Data
NEW: ENGAGEMENT ACROSS
FACEBOOK
FACEBOOK PAGES FACEBOOK
ADS
FACEBOOK TOPIC DATA
Insights into your Facebook Pages Insights into your Facebook Ads
Topic Data Unlocks Unique Insights for Marketers
DataSift + Facebook partnershipFacebook APIs being used by analytics companies today

8. Pages vs Topic Data Comparison
Comparison of volumes of engagement relating to
an automotive brand across 7-day period.
FACEBOOK PAGES
~1,000
Posts and Engagement on
your own Facebook Pages
TOPIC DATA
~70,000
Brand-related
Posts and Engagement
across all of Facebook
Content that goes viral on Facebook
about your brand.
What is driving brand recommendation,
purchase, advocacy or churn.
Topic data expands your insights.
The audience that is engaging with
your brand across Facebook.
Audience reaction to multi-channel
marketing campaigns.

9. Expand Your Product with Insights from 1.49 Billion People
WITHOUT FACEBOOK TOPIC DATA + FACEBOOK TOPIC DATA
Analysis across public social data sources
Example: Analysis of automotive brand
6x
Analysis includes Twitter, Tumblr, blogs, forums.

10. 10
Demographics Enables New Opportunities For Analytics and Marketers
Use demographics to develop insight around audience segments
Audience segments that over/under -index in engaging with a brand.
CALIFORNIA
18-24
KENTUCKY
25-34
Insights enable marketers to build and target
creative and campaigns to specific segments
Creative A
Creative B

11. Brand Analytics
How Companies Are Using Topic Data
BRAND • PRODUCT CONTENT • LINKS INDUSTRY • TOPIC AUDIENCE
Content & Media Analysis Industry & Topic Research
Market research to inform creative &
campaigns
Brand Reputation Management
Campaign Analysis
Competitive Analysis
Influential Media Analysis
Topic Analysis
Content Discovery
Industry Benchmarking
Topic-Specific Analysis
Vertical Applications (e.g. TV)
Creative & Campaign Design
Audience Affinity Analysis
Audience Discovery/Expansion

12. Ad Agency
Snack Brands

13. 13
The Problem
An ad agency wanted to improve social engagement and
presence for a snack brand. The agency also wanted to
better understand how consumers engaged with the brand
and the subject of sport in order to drive new creative
approaches.
Previous attempts had struggled with low volumes, which
drove an over-reliance on expensive focus
groups.
Our Approach
๏ DataSift developed filters to capture data about consumer
insights described in the brand brief (events, behaviors, &
emotions associated with the brand). One filter focused
on the brand and its key competitor and a second captured
general engagement around sports.
๏ DataSift used VEDO to classify different product flavors,
events and emotions that aligned to the brand’s strategy.
๏ The brand index captured 180k interactions in 3 weeks,
while the sports index captured 4.4m interactions in 10
days.
Ad Agency Snack Brands

14. With topic data we found that many of the assumptions
around audiences and engagement were incorrect:
๏ Assumed 18 to 24 year old men. It actually turned out 35
- 66 year old women were engaging.
๏ Expected pre-game excitement to peak just before game
time. It really peaked almost 6 hours earlier.
๏ Thought most games were watched with friends. Turns
out most are watched with families.
Recommended Actions
๏ Use accurate knowledge of audience engagement to create more relevant messaging and campaigns.
๏ Target messages to audiences with better timing, to match true engagement patterns prior to game.
18-24
MALE
35-66
FEMALE
ASSUMPTIONS Vs. DATA
FRIENDS FAMILY
Ad Agency Snack Brands

15. Ad Tech
Music Festival

16. 16
The Problem
An ad tech partner wanted to improve performance for a
campaign on Facebook for a national music festival. Data
from non-Facebook sources was resulting in outdated
creative, overly simplistic advertising strategies.
Our Approach
๏ DataSift developed a filter that identified Facebook
engagement with the music genre as well as the key
artists scheduled to perform at the festival.
๏ DataSift used VEDO to tag performers and sponsors
already associated with the music festival.
๏ The index captured 5.7m interactions in 8 days.
Ad Tech Music Festival

17. Topic data identified audiences that were more and less
likely to engage with content and help target promotion:
๏ Identified that Women 25-34 from Kentucky, Indiana,
Michigan & other states over-indexed in music genre
engagement.
๏ Identified that Men 18-24 from California under-indexed in
the music genre engagement.
๏ Identified a range of related interests, websites, retailers
and broadcasters that could be used for targeting.
Recommended Actions
๏ Diverted spend from under-indexing to over-indexing demographic groups improving engagement rates and driving a 17%
increase in video completion rates.
๏ Identified artists and potential co-marketing partners to inform future campaigns and tailor content.
CALIFORNIA
18-24
KENTUCKY
35-44
AVERAGE ENGAGEMENT
Ad Tech Music Festival

18. TV Producer
Marketing & Development

19. 19
The Problem
A TV show producer was struggling to understand how
different audiences engaged on Facebook around the
episodes, storylines, and characters of a major show. They
needed to make more informed decisions around
advertising, social content, as well as casting decisions for
future seasons.
Our Approach
๏ DataSift developed a filter that identified Facebook
engagement with existing characters and storylines. A
second filter measured engagement with breakout
actors from recent film festivals and actors from top
TV shows.
๏ DataSift used VEDO to tag references to key
episodes, storylines, quotes, memes and characters.
๏ The index captured 1.5m interactions in 10 days.
TV Producer Marketing and Development

20. Based on topic data producers were able to better
target content and inform casting decisions:
๏ Identified the characters gaining the most
engagement on Facebook and then identified variations
by gender, age and state.
๏ Identified the scenes & storylines that drove most
engagement over the season.
๏ Identified potential actors for an upcoming season that
resonated with their core target demographic.
Recommended Actions
๏ Tailor sponsored updates to feature an image of the most engaging character for each demographic group.
๏ Casting was also able to evaluate new actors that already resonate most with the TV show’s core demographics.
SCENE A SCENE B SCENE C SCENE D
TV Producer Marketing and Development

21. TV Channel
Marketing & Development

22. 22
The Problem
A major TV Channel wanted to understand if they were
reaching their target audience with the right programming
and content, how that content could be improved, and if
they could have better control over the feedback loop
between engagement on Facebook and tune-in on
television.
Our Approach
๏ DataSift developed a filter that identified Facebook
engagement with all of the programming & supporting
marketing assets associated with the series.
๏ DataSift used VEDO to tag references to characters,
celebrity & marketing partners, and all of their
Facebook fan page posts.
๏ The index captured 7m interactions in 8 days.
TV Channel Marketing and Development

23. Gained a better understanding of audience interest
and engagement with content:
๏ Identified the shows, themes, characters, and
social posts with the most engagement on
Facebook, on a minute-by-minute basis, broken down
by gender, age and state.
๏ Identified content that would likely resonate, and
which audiences it would likely resonate with.
๏ Quantified movement of audiences from TV to
social (and back) to identify more efficient times to
engage with them, and specifically who to engage
with.
Recommended Actions
๏ Adjust advertising and calls-to-action on TV to follow the audiences as they naturally move between TV and social.
๏ Leverage demographic insights to optimize advertising and programming.
TV Channel Marketing and Development

24. Seize the Opportunity
1 Facebook is the #1 social platform for marketers.
For the first time, topic data enables companies to build insights from sharing and
engagement across Facebook.
Supports a wide set of use cases such as: creative, PR, and analytics
2
3

25. Take the next Step
Contact a DataSift Partner Contact DataSift
Visit our Partner Portal
Visit our Contact Us Page

26. Q&A

27. THANK YOU!