The document discusses optimizing marketing strategies using Facebook Topic Data, highlighting its ability to provide marketers with insights from a vast array of user interactions while maintaining privacy. It presents various use cases across different industries, emphasizing how brands can analyze consumer behavior, engagement patterns, and competitive positioning. Recommendations are provided on tailoring advertising strategies based on demographic insights and engagement metrics derived from the data.

1. How to Optimize Your
Marketing Strategy Using
Facebook Topic Data
February 25th • 2016
Live Webinar with Q&A

2. Tim Shea
Agency, Brand and Data Partnerships (US)
DATASIFT
James Ritchie
Agency, Brand and Data Partnerships (EMEA)
DATASIFT
Dary Hsu
Product Marketing Manager
DATASIFT
SPEAKERS

3. What is Facebook Topic Data?
Agenda
1
Use Cases2
Q&A3

4. What is Facebook Topic
Data?

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. For years, companies struggled to get a complete view of their
audience on Facebook and turn that information into useful insights
until….

7. DATASIFT + FACEBOOK Partnership
ENGAGEMENT ACROSS FACEBOOK
FACEBOOK TOPIC DATA
Topic Data Unlocks Unique Insights for Marketers

8. What is Facebook Topic Data?
8
What’s on your mind?
CONTENT DEMOGRAPHICS LIKES and SHARES
Anonymized and aggregate topic data
• Posts
• Pages Posts
Plus engagement data
• Likes on Posts
• Shares on Posts
• Comments (no text) on Posts
Data enriched with
• Demographics
• Topics
• Sentiment
• Real-time access to the entire newsfeed with over 4.75 billion pieces of content shared a day.
• Gain anonymous & aggregated insights about specific activities, events, brand names, and other
subjects that people are sharing on Facebook.

9. Not a Data Feed. Topic Data is Aggregated and
Anonymized
9
New approach to provide privacy-first insights:
Facebook is not a public social network.
User identity is removed from posts and engagement data
processing.
Text and meta data from anonymized posts are indexed
within Facebook’s infrastructure for analysis.
Developers query data collected in real-time to perform
analysis. Data is aggregated at query time to provide
aggregate results.
Privacy controls ensure results only provided if audience size
thresholds are met.

10. Insights From a Network of 1.59 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

11. 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
Cross-shopping For Car
Brands

13. 13
The Problem
The agency struggled to quantify how & when
consumers were “cross-shopping” between
competitors' vehicles, what motivated them to do
so, and where they were in the purchase funnel.
They also lacked the ability to measure cultural
differences and care-abouts between Spanish &
English speaking audiences.
Our Approach
๏ DataSift developed 1 filter focused on the brand, its
models & competitors, as well as car features. The
second filter focused on understanding cross-
shopping behavior.
๏ DataSift used VEDO to classify 10 automobile
features across 6 different languages, as well as
purchase intent into consideration, rejection, or
ownership.
๏ The brand index captured 180k interactions in 3
weeks.
Ad Agency Car Brands

14. Using topic data the agency was able to
uncover multiple audience insights for their
client:
๏ Significant differences between Spanish &
English-speaking audiences for various
automobile features. For example, style & price
barely showed up within Spanish conversation.
๏ How often the client brand was mentioned together
with a competitor brand as an indication of cross-
shopping. We also enabled them to quantify what
features were being compared as well as what was
motivating the comparison.
๏ Client brand had the lowest level of brand
consideration, whereas another competitor
enjoyed zero brand rejection.
Recommended Actions
๏ Emphasize different features and vernacular when advertising in Spanish versus English.
๏ Understand how to position against competition and quantify changes in risk to market share.
Ad Agency Car Brands
CROSS
SHOPPING
Competitor
C
5%
3%
10%
TOP 3 FEATURES ENGLISH VS. SPANISH
ESPECIFICACIÓN MECÁNICA
AMBIENTE
COSTO DE FUNCIONAMENTO
STYLE
PRACTICALITY
PERFORMANCE

15. Global Brand
Crisis Management

16. 16
The Problem
The global brand was subject to a protest
campaign driven by a small number of protest
groups, whose campaign video was “going viral”.
The brand could measure engagement on other
social networks but they lacked demographic
insight and the ability to measure the scale of the
backlash on Facebook.
Our Approach
๏ DataSift developed 1 filter focused on the crisis -
tracking engagement with the protest video,
references to the crisis and links to the global
brands’ websites.
๏ DataSift used VEDO to classify interactions which
linked to stories already identified as influential.
Another classifier tagged the key consumer brands.
๏ The index captured 40k interactions in 8 days.
Global Brand - Crisis Management

17. Through analysis of topic data the brand was
able to uncover the following insights:
๏ The brand could see how different demographic
groups engaged in the issue, with women over
65 over-indexing massively.
๏ The brand had been focused on stories with
some traction on other social networks but was
unaware of stories in France & Germany which
were driving much larger engagement on
Facebook.
๏ They could identify which product brands were
being most targeted for boycott.
Recommended Actions
๏ By understanding the demographics of people actually engaging in the crisis the brand could develop better targeted messaging.
๏ Identify specific product brands needing additional defence / support.
CPG Brand - Crisis
Management
MISSING THE BIGGER PICTURE
AVERAGE ENGAGEMENT
FEMALE
65 +

18. Ad Agency
Audience Research

19. Ad Agency For Drinks Brand
The Problem
Ad agency wanted to understand how women
engaged with their client’s brand and with hot
drinks. They also wanted to get a deeper
understand of the media consumption / magazine
stories which most engaged their target consumers
Our Approach
๏ DataSift developed 2 filters focused around the
campaign. The first filter focused on the brand, its
key competitors and on hot drinks. The 2nd index
focused on engagement with links to 10 top female
magazines
๏ DataSift used VEDO to categorize hot drinks
(across multiple languages) and to tag magazines
based on URLs
๏ The 1st index captured 2.5m interactions in 12
days. The 2nd index captured 950k interactions in
16 days

20. Under 35s, as a % of brand’s total
engagement
47%
The brand was able to derive multiple
actionable creative insights using topic data:
๏ There are clear variations in preferences for
hot drinks across nations and demographic
groups
๏ The brand found that they suffered with the
lowest relative engagement amongst
millennials
๏ We could see the publications, stories &
celebrities which drove most engagement
amongst the target demographic
Recommended Actions
๏ Look at featuring different hot drinks when advertising in different markets and to different demographic groups
๏ Use story insight for media placement as well as for identifying potential influencers
CPG Brand
1st
2nd
3rd
LATTE
HOT CHOCOLATE
ESPRESSO
HOT CHOCOLATE
LATTE
CAPPUCINO
CAPPUCINO
LATTE
ESPRESSO
USA UK GERMANY
Client Brand Competitor A Competitor B
31%
58%
18-24
25-34
35-44
45-54
55-
64
65+
JENNIFER LAWRENCE
SHARON STONE
TAYLOR SWIFT
KYLIE JENNER
JUSTIN TIMBERLAKE
Celebrity stories driving most engagement
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000 6500 7000 7500 8000 8500 9000 9500 1000 10500 11000 11500 12000 12500 13000 13500 14000 14500

21. CPG Brand
Audience Research

22. CPG Brand
The Problem
A CPG brand was running a 2nd iteration of
their flagship campaign. They wanted new
ways to understand how people engaged with
the campaign and its underlying theme on
Facebook. They also wanted to develop
creative insight to support future campaigns.
Our Approach
๏ DataSift developed 2 filters focused around
the campaign. The first filter focused on the
campaign itself: the underlying theme as well
as hashtags and urls. The second filter
focused on how the campaign tag line was
used in normal discussions
๏ DataSift used VEDO to categorize themes and
phrases
๏ The 1st index captured 6.9m interactions in 7
days. The 2nd index captured 461k
interactions in 14 days.

23. The brand was able to derive audience and
creative insights using topic data:
๏ The campaign had targeted a theme which
had much less engagement than the
themes of pride or determination.
๏ When people engage with these more
popular themes, the majority of links they
share are for charity runs or causes.
๏ We could track the volume (and
demographics) of engagement in phrases
the brand had previously featured and
identify new phrases which should
resonate with their target audience.
Recommended Actions
๏ Look at targeting different themes and phrases, which are proven to resonate with target audience
๏ Consider sponsoring charity runs / events as part of future marketing mix
CPG Brand
2,481.900
299,000
Campaign theme
Determination
Pride
Top websites linked when sharing emotional
state
CHARITY RUNS
CHARITY RAISING FOR INDIVIDUALS
OTHER
11,300

24. CPG Brand
Audience Research

25. CPG Brand
The Problem
A CPG company believed that Millennials are
fundamentally different to older consumers in
their attitudes to food. They wanted to use
Facebook to measure and understand these
differences so they could develop new
creative campaigns to better engage
Millennial consumers.
Our Approach
๏ DataSift developed 2 filters focused around
the campaign. The first filter focused on
general engagement with food as a topic. The
2nd filter focused on the specific food trends
the company had already identified
๏ DataSift used VEDO to categorize themes,
trends, consumption locations and meals
๏ The 1st index captured 13.2m interactions in
6 days. The 2nd index captured 11m
interactions in 32 days.

26. The brand was able to derive multiple
actionable creative insights using topic data:
๏ We could see very significant different levels
of engagement in most food trends between
young millennials (18-24) and older millennials
(25-34) but little distinction between
millennials versus older consumers
๏ Small differences in the media types
millennials post (more photos) but a negligible
difference in the content they engage with
when discussing food
๏ Identified a range of national difference in
engagement with food themes and meals
Recommended Actions
๏ Don’t treat Millennials as a homogenous group - in many ways they are like the rest of us!
๏ Optimize campaign messaging to reflect national engagement in different food trends
CPG Brand
Media type when posting about
food
Engagement on media type
about food
American Males engagement
in Reduced Meat
British Females engagement
in Natural Food

27. Q&A

28. THANK YOU!