What’s New inFacebook Topic Data

Jason RoseSVP Marketing

DataSift

Jay KrallDirector of Product Management

Datasift

Facebook topic data in action

What’s new in Facebook topic data

Facebook topic data Overview

Agenda1

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4 Q&A

Facebook Topic Data Overview

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SME BUSINESSES

WITH ACTIVE FACEBOOK PAGES

40M+

Source: Facebook Q2 2015 Earnings Report

2M+$3.8B Q215

AD REVENUES GROWING 43% YoY

ACTIVE ADVERTISERSDAILY ACTIVE USERS1 Billion

PEOPLE SPEND 46 MINS/DAY ON FACEBOOK

(1) Facebook, Messenger, Instagram.

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Marketers Are Making Big Investments in Facebook

Surfacing Insights across Facebook

Facebook Page

Topic Data

Posts, Likes and Comments on brand-owned page globally

Posts, Likes and Comments on Facebook

Not a data feed. Topic Data is ‘Aggregate and Anonymised’

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New approach to provide privacy-first insights

1.User identity is removed from posts and engagement data processing.

2.Text from anonymised posts is stored within Facebook’s Infrastructure for analysis.

3.Customers query data collected to perform analysis.

4.Results are provided if audience-size exceeds a minimum size.

Facebook is not a public social network

Topic Data is Multi-Dimensional. Build Insights into Content, Engagement, Audiences

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CONTENT

Privacy-safe analysis of text within posts

CONTENTAutomatic classification of related topics eg. Star Wars VII (Film)

CONTENT

Gender: MaleAge-Range: 35-44Region: California, USA

CONTENT

Positive

TEXT ANALYSIS

TOPIC ANALYSISDEMOGRAPHICS

SENTIMENTCONTENT

URLs

Analyze URLs shared across Facebook relating to your brand

Analyze Engagement and Demographics around likes, comments and shares

ENGAGEMENT

Can’t wait to take the kids to watch Star Wars VII

Anon

Privacy Controls Unlock Deep Insights

Privacy-first data management controls allow highly detailed demographic information on audiences to be revealed

• Interaction data is stored behind Facebook’s firewall

• Ask any question of the underlying data• Aggregated results are returned• Only way to reveal highly detailed demographic

data

What’s new in Facebook topic data?2

What’s New in Facebook Topic Data

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3 major new enhancements to topic data1. New Countries - Facebook topic data now contains

insights from over 50 countries.2. Super Public Content - to help validate results and

quickly iterate filters a sample of Super Public data is provided.

3. Nested Queries - To increase the effectiveness of analysis topic data now incorporates nested queries.

PYLON for Facebook Topic Data Release Schedule

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PYLON 1.2May 15 2015

• First Generally Available Release

• Account Management Endpoints & Token-Based Authentication

PYLON 1.3July 1 2015

• Nested Analysis Queries

• Improved Scoring Algorithm Handling

PYLON 1.6September 29 2015

• New Countries added

• Super Public Text Samples

• Better Usage Reporting

PYLON 1.5August 17 2015

• Common Target Mapping

• Capacity Notifications

• Improved Time Zone Handling

PYLON 1.7October 2015

• Filter Swapping

Topic Data Available in Over 50 Countries

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Facebook topic data is being made available for countries in Europe, the Middle East and Africa๏ Topic data is now available for 57 countries

including the North America, Europe, Middle East and Africa

๏ Topic extraction is available in 11 languages and sentiment is available in 7 languages.

๏ Additional countries are being added in a priority order with more to follow

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Facebook topic data contains a sample of Super Public posts providing:

Easy iteration of filters

Data/Insight verification

Create training sets for classifiers and machine learning algorithms

Definition: Super Public is defined as: 1) Published by people who have a “Follow” setting enabled

in their profile.2) and Story is posted with privacy setting set as

public.3) and Post is not on the timeline of another person.

Going for a drive in my Ford

Anon

Love my Ford

Anon

Can’t wait to see Harrison Ford

Anon

Super Public Content Sample

Working with Super Public Content

๏ Receive a limit of 100 posts per recording per hour (no engagements available)

๏ Use the count parameter to specify a number of posts between 10 and 100 for each request

๏ Use start/end parameters to restrict posts retrieved to a time range in the past. You can perform repeated requests against the same time range. If you don't specify a time range, the most recent available posts are delivered

๏ Use the filter parameter to use query filtering (secondary CSDL) to retrieve results relevant to the specific aspect of your filter that you're trying to validate

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What’s on your mind?

Ways to use Super Public Data๏ Find false positive terms to add to your filters๏ Expand the lists of words and phrases you use for

filtering to reflect the way people really talk about brands & products

๏ Collect steady stream of 100 posts per hour over time to understand how brand-related engagements change

๏ Drill deep into a specific event or time period with multiple requests over time

๏ Train a scoring-based VEDO classifier (recommended minimum 2K posts per class)

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My car is way too expensive and uses too much gas!!

Example of a Nested Query

Create a single query that will return all results that meet the minimum unique author gate provided the total audience is >1,000๏ Create an analysis of 3 brands in the automotive industry.๏ Analyze how important certain features of the vehicle are to people on Facebook๏ Analyze regional differences by Geo๏ We can now create a single “nested query” with each of these attributes defined to

build our dashboard.

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Nested analysis query: Age and Gender Breakdown

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{ "start": 1432120326, "end": 1434712326, "hash": "c63bb577b68e33777351cc0d4d82f075", "parameters": { "analysis_type": "freqDist", "parameters": { "threshold": 2, "target": "fb.author.gender" }, "child": { "analysis_type": "freqDist", "parameters": { "threshold": 2, "target": "fb.author.age" } } }}

Gender

Age-Breakdown

Facebook topic data in action4

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Brand Analytics

How companies are using Topic DataBrand / Product Content / Links Industry / Topic Audience

Content & Media Analysis

Industry & Topic Research

Market Research to inform creative & campaigns

Brand Reputation MgmtCampaign AnalysisCompetitive Analysis

Influential Media Analysis Earned Media Analysis Content Discovery

Industry BenchmarkingTopic-specific analysisVertical Applications (eg TV)

Creative & Campaign Design Audience Affinity AnalysisAudience Discovery/Expansion

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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.

Industry Research

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.

CALIFORNIA18-24

KENTUCKY35-44

AVERAGE ENGAGEMENT

Industry Research for Music Festival

Q&A5

THANK YOU