Boosting Your Brand Marketing with Facebook Topic Data Insights
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You have a new market entrant. You would like to know how it’s impacting your brand. So the first thing you do is to find out your share of voice in the market. What now? Indeed, knowing your brand’s share of voice is important for monitoring your brand health, but wouldn’t it be even better if you know how it varies among different demographic groups, how audiences are engaging with your brand and what features or products are driving your top engagements? We believe so. It is in the details that makes the difference and can truly impact your brand marketing. The share of voice use case is but one of the many Facebook topic data insights that can help you turn a good first start into a full fledged brand marketing strategy. Join us for our upcoming webinar and learn: About the different ways your brand can apply Facebook topic data to achieve the brand marketing results you’ve always wanted Explore the brand health use case and three other examples of how Facebook topic data insights can help you discover the undiscoverable Have your questions about Facebook topic data answered Sign up to save your seat today!
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Boosting Your Brand Marketing with Facebook Topic Data Insights
- 1. Boosting Your Brand Marketing with Facebook Topic Data Insights
- 2. Kester Ford Director of Product Marketing DATASIFT Dary Hsu Product Marketing Manager DATASIFT
- 3. 1. Facebook Topic Data Insights 2. Brand Health 3. Product Development 4. Understanding Viral Content 5. Campaign Analysis 6. Q&A Agenda
- 4. Facebook Topic Data Insights1
- 5. For years, companies struggled to get a complete view of their audience on Facebook and turn that information into useful insights until….
- 6. DATASIFT + FACEBOOK Partnership ENGAGEMENT ACROSS FACEBOOK FACEBOOK TOPIC DATA Topic Data Unlocks Unique Insights for Marketers
- 7. What is Facebook Topic Data? 7 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.
- 8. Not a Data Feed. Topic Data is Aggregated and Anonymized 8 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.
- 9. 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 6xAnalysis includes Twitter, Tumblr, blogs, forums.9
- 10. Brand Health2
- 11. Brand Health 11 A measurement of consumer opinion towards a brand. It can be quantitative, such as a share of of voice versus competitors or qualitative, such as consumer sentiment. It is multi-faceted and can be understood differently through different factors.
- 12. The setup 12 “Cars”, “Automotive”, “Ford”, “BMW”, “Honda” • Identify interactions for automotive industry and brands. • Identify features to compare performance across brands. “Style”, “Practicality”, “Purchase price”, “Environment”, “Reliability” Classification rulesInteraction filter
- 13. Identify share of voice and over time 13 Discover: ๏ Share of voice for brands - snapshot or over time
- 14. Identify sentiment 14 Discover: ๏ Sentiment expressed toward brands by gender
- 15. Identify brand health by location 15 Discover: ๏ Share of voice by region (US states)
- 16. Identify brand health by feature 16 Discover: ๏ Brand performance by feature
- 17. Identify brand health by demographic group 17 Discover: ๏ Share of voice by each demographic segment ๏ Outlier by baselining - ex. BMW over-indexes among younger male audiences
- 18. How does Facebook topic data help? 18 Easily answer the below questions: • How much share of voice a brand achieves? • How share of voice varies over time? • How the brand performs within each demographic group? • How the brand performs in different geographies? • What features, products or services drive engagement for a brand?
- 20. Product Development 20 A key component of product development is doing market research to understand what your customers really want, allowing you to tailor your product offering to meet demand and giving you a real competitive edge. Evaluate new product ideas Monitor product performance Identify key features Refine marketing campaigns
- 21. How do people do it now? 21 Market research on products can either be carried out in primary or secondary research. Secondary research Published industry reports, competitive research Primary research Survey, interviews, questionnaires
- 22. The setup 22 “galaxy”, “tab”, “tablet”, “tabpro” • Identify interactions which mention existing products in the market. • Identify and normalize mentions of brands, models and features. “Samsung”, “Audio”, “Connectivity”, “Display” Classification rulesInteraction filter
- 23. Identify model share of voice 23 Discover: ๏ Most popular model among your audience
- 24. Identify the most popular features 24 Discover: ๏ Most engaged feature
- 25. Breakdown feature by demographic groups 25 Discover: ๏ Most popular feature by gender and age ๏ Outlier by baselining - younger segments care about style but brand under performing
- 26. Measure sentiments 26 Discover: ๏ Sentiment by feature
- 27. How does Facebook topic data help? 27 Easily answer the below questions: • which brands are being discussed most. • which existing models are being discussed most. • which features of models are driving engagement. • how brands and models perform within each demographic group and geography. • how features vary by demographic group and geography. • sentiment and opinion towards brands, models and features
- 29. Why Viral Content 29 Understanding what content has organically been picked up and spread by an audience is a key insight to inform future creative campaigns.
- 30. The setup 30 “Movie”, “Film”, “TV/Movie Award” • Identify interactions from the audience who have engaged with your campaign. • Identify topics, sources and personalities which influence content sharing. “Online News”, “Video”, “Review”, “Gossip” Classification rulesInteraction filter
- 31. Monitor audience activity 31 Discover: ๏ Peak audience engagement for viral content
- 32. Breakdown engagement by demographic groups 32 Discover: ๏ Content engagement by gender and age ๏ Outlier by baselining - F18-24 engages relatively less with the topic
- 33. Identify popular links 33 Discover: ๏ Which links were engaged with most
- 34. Identify popular links 34 Discover: ๏ Popular links shared by country
- 35. Identify popular links 35 Discover: ๏ Popular links shared by gender and age
- 36. Analyze source of content 36 Discover: ๏ Popular source of content
- 37. How does Facebook topic data help? 37 Easily answer the below questions: • When has there been a peak in sharing activity by your audience? • Which are the most popular pieces of content being shared? • Which are the key sources from which people are sharing content? • How does the content shared and source vary by demographic group? • How quickly has each piece of content spread? • Which celebrities and topics are driving sharing?
- 39. Campaign Analysis 39 It is always important understand how a marketing campaign has performed so that you can optimize your next campaign. Typical objectives for campaign analysis include: • Identify best marketing channel• Identify best materials• Monitor traffic
- 40. How do people do it now? 40 Monitoring campaign performance requires advanced setup. • Manual - Ask people lots and lots of questions in your own forms (where are you from, who are you) • Third party tools - Insert UTM codes everywhere (links, landing pages, etc),
- 41. The setup 41 “walking,dead:4”, “amc.com/shows/the- walking-dead” • Identify interactions from the audience who have engaged with your campaign. • Identify topics, sources and personalities which influence content sharing. “social networks”, “video”, “news”, “gossips” Classification rulesInteraction filter
- 42. Monitor audience engagement 42 Discover: ๏ Peak audience engagement
- 43. 43 Identify most active demographic group Discover: ๏ Content engagement by demographic group ๏ Outlier by baselining - F25-34 outperforms wider Facebook audience
- 44. Identify most popular content by age group 44 Discover: ๏ Content engagement by age group
- 45. 45 Discover: ๏ Content engagement by demographic group ๏ Outlier by baselining - older audience Analyze content source performance
- 46. Identify topics driving engagement 46 Discover: ๏ Popular topics driving engagement
- 47. How does Facebook topic data help? 47 Easily answer the below questions: • when your audience engaged with your campaign. • which pieces of content drove most engagement. • which sources (or publishers) generated the most engagement. • which demographic groups engaged most with the campaign. • how engagement varies by location. • which personalities proved influential.
- 48. 48 Self-declared demographics that other networks don’t (and can’t) provide give deep insights into audience opinion and allow comparisons Not only is the total number of people more representative of society, but usage is more evenly spread across all demographic groups. Sharing with friends and family, not just for self- promotion. Posts are more authentic and insights more representative of public opinion. Audiences can be defined, understood and explored Significant representation in all demographic groups Not Just Bigger. Better! Authentic representation of audience opinion
- 49. Q&A
- 50. THANK YOU
Hinweis der Redaktion
- Thank you Molly. Hi everyone, my name is Dary Hsu, I’m a product marketing manager here at DataSift. Thank you all for joining our webinar today. Before we dive into the main topic of the day, the use cases of Facebook topic data, I just want to make sure everyone is on the same page on what is Facebook topic data.
- So we all know Facebook is the largest social network and most engaged network by far. With over half of the world’s internet users on Facebook, Facebook is the key advertising platform for brand marketers and also continually growing in importance. However, for years companies struggled to get a complete view of their audiences on Facebook. There are some access to Facebook data today including the Page API or the Ads API. With Page API you get access only to posts shared on your company pages while Ads API give you access to how your ads are performing on Facebook. You really don’t see the full picture of what what people are sharing on ALL of Facebook. That is until…
- Facebook topic data. Through our unique partnership with Facebook, DataSift’s technology gives you access to unprecedented amount of audience insights for the first time with our privacy first approach. For the first time you can see what people are posting about their life events, activities they are doing, events they are going, brands they love and more. It gives you a complete picture of what people are engaging across Facebook.
- So what exactly is in Facebook topic data? Essentially it is everything that you would see in the Facebook News Feed. DataSift is connected to the real-time feed of posts and engagement data with over 4.75 billion pieces of content shared a day on all of Facebook. You gain anonymous and aggregated insights, I will go over this in a minute, about specific activities, events, brand names and other stories that people are sharing on Facebook and engagement data such as likes, shares, and comments. The data is also rich with demographics information such as age, gender, and location details of the author, topics identified through Facebook Open Graph, links shared, and sentiment of the post as well.
- I mentioned aggregated and anonymized data. Since Facebook is not a public network, our technology ensure you get all the actionable insights you can get but in a privacy safe way for the people on Facebook. First, user identity is removed form posts sand engagement data and the text and metadata from anonymized posts are indexed and stored within Facebook’s firewall for analysis, then you can query the index to perform analysis but only aggregated results are returned. Our privacy controls make sure only results with over 100 interactions are returned.
- To put thing in context, here is an example of before and after Facebook topic data. Using an automotive example, you can see on the left hand side, this is the amount of interactions you can get from public data sources such as Twitter, Tumblr, blogs and forums mentioning car brands in their posts. On the right hand side, you see over 6x spike in interactions. That’s simply amazing. So now I’ll turn it over to Kester to go over how brands can use Facebook topic data to inform their marketing strategies.
- add pie chart for share of voice
- Thank you Kester, let me show you how companies can apply Facebook topic data insights to product development.
- So a key component of product development is doing market research to understand what your customers want, to see if your product offering has the product-market fit. Market research is part of every phases of product development. You want to evaluate new product ideas during the concept phase, monitor product performance once the product is introduced, identify key features to improve upon during growth phase, and finally refine your marketing campaigns for wider adoption.
- So how do people do market research now? They rely on primary research such as survey, interviews, and questionnaires or secondary research using published industry reports and competitive research. The pros of primary research is that you get tailored insights that no one else has, you get to access the psychology of the customers. The con is that it’s expensive, takes a long time, and has limited sample size and hence biased. For secondary research, the pro is that it’s lower cost, gives a good overview for market level insights, and easy to obtain. The con is that it’s not tailored, lack of detail/actionable insights, and they are often slow to update. With Facebook topic data insights, you can combine the best of both worlds. Let me show you how it’s done in this use case.
- For demo purpose, we created an example around the Samsung Galaxy tablet series. To start analyzing, we need to create a filter based on existing products. Then we can create custom tags to categorize models and features such as display, connectivity, audio, and etc. Once we have this setup we can start analyzing. Let me show you some samples of Facebook topic data insights you can get for product development.
- Using the model classification rules we added to our filter, we can analyze the breakdown of the models and see how each model is racking up engagement on Facebook. In this example, we can see that Galaxy Tab 4 has the largest model share of voice.
- Now that we’ve found out which model receive the most attention, we can look at which features are being discussed and engaged with the most. Using the classification rules we added to our filter, we can analyze the breakdown of the features. In this example, we see style is the most discussed “feature.”
- We can further breakdown a feature by demographic segments to find out how that feature performs for different age groups. For example, style was the most engaged feature, but does it matter to everyone? We can see here that style is most important to females between age 25-34 and 45-54. We can add another layer of analysis by using baselining to find out how engagement in each demographic group compares with a wider Facebook audience in that age group. In this example, you can see style is in general important to male age 18-34 in the gray bar but the brand is underperforming there.
- Facebook topic data also provides generic sentiment scores from Facebook. We can analyze sentiment of the stories being engaged for features by brand. In this example, we focused on Samsung and you can see that the display features of Samsung tablets are relatively less well received by the audience.
- As you can see, FTD insights is great for providing product development insights. It easily answer questions such as which brands or models are being discussed the most, which features are driving engagement, how models or features are performing within different demographics group and geography, and overall sentiment and opinions toward brands, models and features. FTD gives you detail audience insights without resorting to generic industry reports and the expense and time investment on conducting focus group programs while getting insights from the largest focus group ever. Kester will go over how people can identify viral content with Facebook topic data next.
- when there has been a peak in sharing activity by your audience. which are the most popular pieces of content being shared. which are the key sources which people are sharing content from. how does the content shared and source vary by demographic group. how quickly has each piece of content spread. which are the personalities and topics driving sharing
- Thank you Kester, let me show you how companies can apply Facebook topic data insights to measure campaign success.
- Campaign analysis is a big part of what marketers do to measure their success and optimize for better campaign performance. Some of the typical objectives include monitoring traffic, identifying key audiences, figuring out which of your content performs best, and also identifying what is the best channel to reach your audience.
- So how do people do it now? Marketers can create super long forms to ask lots of questions on their forms for audience info or they can insert UTM codes everywhere. All of these require a lot of advanced setup and most of them are very top of the funnel measurements without knowing demographics of your audience. With Facebook topic data insights, you can gain both market and audience level insights into every step of the funnel without requiring you to set up everything right in the beginning. Let me show you how it’s done in this use case.
- For demo purpose, we created an example to capture all the interactions related to a campaign for the popular TV show “The Walking Dead.” To start analyzing, we defined a filter to capture all the interaction from audiences that are engaging with content relating to the campaign. Then we created custom tags to categorize different publication sources so we can tell which channel is the most effective. Once we have this setup we can start analyzing and let me show you some samples of Facebook topic data insights you can get for campaign analysis.
- Using the filters we created, we can monitor all the interactions specifically tied to the show. We can use a time series analysis to focus on the period of our campaign to investigate when our audience has been most active.
- We can also identify the most active demographic group by breaking down the engagement by age group. In this example, we have amazing engagement from female 25-34 and they actually do over-index engagement from a broader baseline audience. This confirms that as a group female 25-34 is a great target demographic for the brand.
- Facebook topic data lets us inspect links shared by our audience. We can analyze which content is being shared the most and also break it down by age group.
- We can also use the tags we created for content sources such as Anime, Manga,Comic, Videos, and social networks, news to see how the content performance varies by source. In this case, you can see Anima, Manga, Comic, Fun source scored really well, probably all coming from stories around Walking Dead comic con events.
- Aside from actual content engagement, we can also look at what topic categories and topics are discussed the most based on the stories shared. Not surprisingly, for the Walking Dead, topics relating to the actors and directors are being shared the most. And of the actors, Lauren Cohan is the most talked about actress.
- As you can see, FTD insights is great for providing campaign performance insights. It can easily answers questions such as when your audience engages with your campaign, which pieces of content drive most engagement, which sources generate the most engagement, what demographic groups engage the most with the campaign, how engagement varies by location, and what topics are driving engagement. FTD not only gives you a more complete understanding of campaign performance but also demographic insights of your audiences so that you can fine tune your campaigns. So these are the use cases we want to share today. Kester will share now how FTD is not just bigger and better before we start our Q&A.
- More representative: closer to total population, plus more evenly spread across demographic groups More authentic: people are posting for their friends and family about their real lives Better demographics: self-declared, privacy safe So how is Facebook different from other social networks in terms of finding and understanding your audience? Traditionally consumer research via social data has a few challenges that makes it difficult for businesses to gain meaningful insights. The first challenge is dealing with relatively small sample size compared to the market out there. The second challenge is that public networks have a “self-promotion bias”, in which a lot of people on networks that are more open than Facebook are not there just to be social with their friends and family, but they are there to sell, to promote their artistic works or to promote their political agenda. A third challenge is that the target audiences don’t have enough demographic information to allow you to focus and draw useful consumer insights. This all changes with Facebook topic data. When we talk about representative data - over 1.55 billion people worldwide are on Facebook and this represents a sample size that no other type of market research has ever come close to. Not only that, but a much wider demographic spread is represented on Facebook than on the social networks marketers are used to getting data from. People on Facebook are more often sharing because they want to share with their friends and family, not just for self-promotion. This makes their posts more authentic and insights derived from them more representative of public opinion. Facebook topic data has self-declared demographic data that allows us to focus on the audience that we are interested in, to discover which audiences we should be interested in and also to normalise our findings so that we get a real understanding of the audience that is engaged, not just that they are most active on social media.