facebook topic data meets the power of insightpool
TRANSCRIPT
Title Area
The Social Relationship Intelligence Platform
#FBdata
Insightpool x Datasift Webinar
FACEBOOK TOPIC DATA Meets the Power of
INSIGHTPOOL
#TopicData
Devon WijesingheCEO of Insightpool
@DevonWijesinghe
Speaker
Co-founded Insightpool in 2012, and has led the company from two to 60+ employees, acquired a Silicon Valley start-up, Next Principles, and is currently revolutionizing marketing and sales across social.
#TopicData
Tim BarkerCPO at Datasift
@timbarker
Speaker
Joined DataSift after serving as VP EMEA Marketing atSalesforce, leading a world-class marketing team to create the social enterprise and cloud-computing industries. Tim has entrepreneur DNA, having founded 3 successful startups.
#TopicData
What data are we analysing
Facebook Page
Topic Data
Posts, Likes and Comments on brand-owned page globally
Posts, Likes and Comments on Facebook
#TopicData
What’s on your mind?
Content and Behaviours
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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
#TopicData
Topic/Entity Data from the Facebook Open Graph
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Entity/Topic Detection is applied to every post Leverages Facebook’s massive Open Graph data set to identify topics and events. The same technology is used to surface Public Trends on Facebook. Enable exploration of topics related to a brand Topics enable exploration of the data without access to raw posts. For example - cluster the topics related to a product or event. Topics can be used within filters to remove noise. Create a CSDL filter for posts for the movie “The Interview”.
fb.topics.category == “Movie" and
fb.topics.name contains “The Interview"
CONTENT
TOPICS
Sony (Organization) The Interview (Movie)
Kudos to Sony for distributing The Interview
#TopicData
Demographics and Engagement
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Gender Age Range Location
Male Female
18-24 25-34 35-44 45-54 55-64 65+
Country State / Region
Self-declared, not
derived.
Enables exploration of audience segments Demographics for every post, comment and like. Understand the audience engaging with your brand.
#TopicData
Privacy-First Data Management Controls
Social data never leaves Facebook Social data is processed by DataSift technology running inside Facebook’s network. User identity is removed before processing User identity is removed from social data before processing by DataSift technology. Results provided in aggregate, anonymized Only summary results containing insights from 100 or more people are delivered by DataSift. 30-day retention period for underlying social data Data deleted from DataSift’s technology after 30 days. Prevents analysis of minors Minimum age applies for data collected for analysis.
#TopicData
Facebook Topic Data is a Killer App for Research
Demographic Context
38M people in UK, 210M
people in North America
Share with friends
Gender, Age, Location,
Education, Relationship
Status
Data Structured for Standardized
Analysis
Representativity Lack of demographics Unstructured data Self-promotion bias
#TopicData
How it Works
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DataSift platform connects to the real-time feed of Posts, Comments, Likes.
2 • CATEGORIZE
Filtered data can be classified with customer-specific rules.
4 • QUERY
The Index is sub-queried and further processed using CSDL against 60+ attributes.
5 • ANALYTICS
Aggregated and anonymized data returned for developers to create applications, analysis and visualizations.
Each customer defines their specific filter based on their criteria.
1 • FILTER
Filtered and categorized data is indexed into a real-time analysis engine.
3 • INDEX 6 • MINING AND VISUALISATION The data is then mined and visualised by using a range filters, classifiers and interactive visualisations to help you craft insights.
#TopicData
Why PYLON for Facebook Topic Data?
Data science via PYLON for Facebook topic data is at the center. Information fuels Insightpool’s targeting, messaging, and activation flow.
#TopicData
Client Objective
Major auto parts retailer is interested in partnering with NASCAR. Major auto parts retailer needs to find out what makes NASCAR fans tick -Who are they? -What topics spark influencer engagement?
Insightpool creates a PYLON for Facebook topic data filter to find Facebook posts relevant to NASCAR
FIL
TE
R
Include Tags of “NHRA, NASCAR, Motocross, drag racing, top fuel, funny car, PEAK racing” And NOT Tags of “racing, race driver, ski, bicycle, professional, pro, BMX, obstacle, spartan, champion, champ, bike, raced”
#TopicData
Data Analysis
Peak: Wednesday, August 26
All sharing and engaging on Facebook is uncovered when a filter is applied. We discovered a peak and further investigated.
#TopicData
Deeper Dive
We focused in on the specific peak to uncover topics/demographics that sparked increase in social sharing and engagement.
PYLON can bring detailed breakdowns on:
Sentiment
Post’s author’s region Age
Country of Origin
Top Link Shared
Gender
Language
Hashtags
Media Type (Posts/Links)
Facebook Type (Comments, Likes, Stories,)
Topics
#TopicData
Topics and Data Analysis
A multitude of anonymised and aggregated data can be drawn out from the overall NASCAR discussion, or from any specific demographic or tag. PYLON has the capability to create customizable tags to further filter the sharing and engagement around NASCAR based off of phrasing, tone and sentiment. For example, PYLON can filter out only the negative sentiment posts, to compare to the positive sentiment posts. We can then determine the topics that are frequent in positive posts as well as negative posts.
#TopicData
Sentiment Example
Positive Sentiment
Negative Sentiment
Tag.sentiment of fb content contains any: “love, obsessed, can’t wait, excited, pumped, awesome, great, amazing, excitement, exciting”
Tag.sentiment of fb content contains any: “hate, stupid, dumb, don’t like, lame, bad”
Sentiment of the overall filter Negative sentiment of towards a specific topic
#TopicData
More Insights
With PYLON for Facebook topic data, you can visualize:
Post author’s region Post’s author’s gender
Post author’s gender
#TopicData
Key Insights
Top 3 links shared
• The top 3 links being shared revolving the topic of NASCAR are all on FoxSports URLs.
• This can be used to inform ad buys, or content to be pushed by the brand
Takeaway: The most amount of sharing and engagement was coming from Fox Sports around a tribute to a driver.
#TopicData
Conclusion
• This information informs major auto parts retailer to be empathetic towards NASCAR fans and also create more sharing and engagement around tribute content.
• This also informs them to place media buys on Fox Sports where a large percentage of traffic is coming from.
http://foxs.pt/1NAb2pX
#TopicData
PYLON Benefits
The major auto parts retailer can now amplify it’s targeting, messaging, and activations around the tribute story. Valuable Hidden Insight: The top traffic drivers were coming from Fox Sports and the content was a tribute to a specific driver. Client also knows where to spend media dollars and put their brand in front of the Fox Sports audience to drive greater conversions
#TopicData