2. Need advice? The Social@ team is at your service, but we need: Involvement early in the process A clear brief Sufficient time to respond Email: thomas.crampton@ogilvy.com john.stauffer@ogilvy.com
3. Social Digest: Week of August 29 “Like” and “+1” Extensions Facebook and Google have rolled out Chrome extensions, which allow users to Like or +1 a site regardless of whether page owners have incorporated the plugins into their site or not. The Like extension takes it a step further by allowing you to leave a comment along with your Like. Reference:http://techcrunch.com/2011/09/01/facebook-chrome-like-button/ Wildfire’s New App Wildfire has launched a Facebook app, named the Wildfire Storyteller App, which focuses on creating better content for Facebook’s Sponsored Stories. The app’s focus is to generate engaging Sponsored Stories ads from user responses. By asking the right question, brands can create for more engaging social ads. Reference: http://mashable.com/2011/09/01/storyteller-app-wildfire/ Foursquare Adds 5 New Languages As Foursquare focuses on their global expansion efforts, the check-in social platform has added five new languages: Bahasa Indonesia, Korean, Thai, Portuguese, and Russian. According to the Foursquare blog, use of the app in countries where those languages are spoken has since exploded. Reference: http://mashable.com/2011/09/01/foursquare-adds-5-new-languages/
7. Shifts in Search Filtered Search With social networks becoming the top source for news, search results have shifted from being filtered by rank to relying on shared items from individual user networks. Content Finds Us Rather than needing to seek out information, users encounter content while on various social networks; or in essence, the content finds users where they hang out. Social Click Through Rate (CTR) The ease of content sharing via social networks is impacting click through rates as users are more likely to click on items shared from those within their personal network.
8. Filtered Search Content Finds Us Social CTR Brand Impact Before: Rank Filtering Previously, top ranking links surfaced to the first page of results
9. Filtered Search Content Finds Us Social CTR Brand Impact Before: Rank Filtering Search engines ranked results based on keyword relevancy and links
10. Filtered Search Content Finds Us Social CTR Brand Impact Before: Rank Filtering Brand websites optimized content designed to outrank competitors
11. Filtered Search Content Finds Us Social CTR Brand Impact Before: Rank Filtering Product reviews from “strangers with expertise” drove purchases
12. Filtered Search Content Finds Us Social CTR Brand Impact Now: Network Filtering Search engines have integrated social connections with search results
14. Filtered Search Content Finds Us Social CTR Brand Impact Facebook Search Engine? Level of connection – Results might be shown from people you are directly connected to first, then from indirect connections, then random users of the network, possibly followed up by third party content published outside of the social networking system. Reputation of Users – Posts from users who have low reputations, possibly spammers or malicious users, may appear lower in results than posts from users with higher reputations. Popularity – A popularity score for individual posters, based upon having more interactions than other users, may cause posts returned in a search to rank more highly than posts from less popular users. Real Time Content Searching in Social NetworkInvented by AkhilWable, Hong Yan, Spencer Ahrens, Yofay Kari Lee, and GuizhenYangAssigned to Facebook US Patent Application 20110196855 Published August 11, 2011Filed: February 11, 2010
15. Filtered Search Content Finds Us Social CTR Brand Impact Facebook Search Engine? Similarity – A similarity score between the post’s author and the searching user could be based upon demographic information such as age, gender, location, interests, or other similarity measure, and that similarity could also boosts results from similar posters. Affinity with other users – if you interact with certain people more frequently than others, their relevant posts would rank more higly in Facebook’s search results. Affinity with shared applications – for example, if you frequently participate in social online puzzle games, the posts from other people who participate in the same kind of puzzle games (on the social network itself, or possibly on the Web) may be boosted in search results. Real Time Content Searching in Social NetworkInvented by AkhilWable, Hong Yan, Spencer Ahrens, Yofay Kari Lee, and GuizhenYangAssigned to Facebook US Patent Application 20110196855 Published August 11, 2011Filed: February 11, 2010
16. Filtered Search Content Finds Us Social CTR Brand Impact Now: Network Filtering Search engines return social media content – not just corporate websites
17. Filtered Search Content Finds Us Social CTR Brand Impact Now: Network Filtering Searchers can filter results based on their own unique social network
18. Filtered Search Content Finds Us Social CTR Brand Impact Now: Network Filtering Your personal network travels with you as you search and browse the web
19. Filtered Search Content Finds Us Brand Impact Social CTR Content Finds Us How does this impact users?
20. Filtered Search Content Finds Us Social CTR Brand Impact Content Finds Us Users are heading to social networks more than search engines Internet Visits to Social Networks & Search Engines Source: Hitwise, Oct 2010
21. Filtered Search Content Finds Us Social CTR Brand Impact Content Finds Us This means we first encounter information via social networks …then we head to search engines for a deeper look
22. Filtered Search Content Finds Us Social CTR Brand Impact Content Finds Us Essentially, content finds us on social networks before we know to look for it
23. Search is no longer a list of website links…25% of search results for the top 20 largest brands are links to user generatedcontent Source: Media Agility, 2010
24. How are people responding to the increased volume of social content?
25. Filtered Search Content Finds Us Social CTR Brand Impact User-Generated Content in Search Etao.com ties product information, reviews, and social media content Q&A discussions on first page of results for “iPhone4” “Questions: What are the new features of iPhone4? When can I buy iPhone4 in China? What’s your guess of the price of iPhone4?
26. Filtered Search Content Finds Us Social CTR Brand Impact User-Generated Content in Search Social brand messages are nearly twice as effective as email Click Through Rates on Shared Content SocialTwist, 2010 Source: SocialTwist, 2010
27. Filtered Search Content Finds Us Social CTR Brand Impact User-Generated Content in Search Of social media shares, Facebook and Twitter are most effective for CTRs 287% Click Through Rate 1904% Click Through Rate Source: SocialTwist, 2010
28. Filtered Search Content Finds Us Social CTR Brand Impact User-Generated Content in Search These social shares are linked to users’ own social pages, the same pages becoming more relevant to search engines
30. Filtered Search Content Finds Us Social CTR Brand Impact Social Search: Brand Impact With millions using Like and +1 buttons, social searches will appear regularly
31. Filtered Search Content Finds Us Social CTR Brand Impact Social Search: Brand Impact Success on Facebook and other networks will spill over to search results
32. Filtered Search Content Finds Us Social CTR Brand Impact Social Search: Brand Impact Brands not engaged in social will encounter a two-sided business risk: Angelo Bosco (Flickr) 2. Declining search rankings 1. Missed opportunity for fans
Hinweis der Redaktion
Welcome to the weekly Social Media training episode. This week we’re looking at the concept of social search with a focus on what’s been floating around the social media news.
Welcome to the weekly Social Media training episode. This week we’re looking at the concept of social search with a focus on what’s been floating around the social media news.
Welcome to the weekly Social Media training episode. This week we’re looking at the concept of social search with a focus on what’s been floating around the social media news.
There are three major trends or shifts we’ll focus on today.A movement from Rank Filtering to Friend Filtering.A look at how content finds us, before we even know to look.And how Social CTRs (Click Through Rates) can help guide our social media planning on behalf of clients.
Top ranking links surfaced to the first pages of results. Searchers found brands that popped to the surface, clicked on those top links, found “strangers with experience” – product reviews from people with a relevant point of view. “Excellent Choice for Beginners.”New bike!
Top ranking links surfaced to the first pages of results. Searchers found brands that popped to the surface, clicked on those top links, found “strangers with experience” – product reviews from people with a relevant point of view. “Excellent Choice for Beginners.”New bike!
Top ranking links surfaced to the first pages of results. Searchers found brands that popped to the surface, clicked on those top links, found “strangers with experience” – product reviews from people with a relevant point of view. “Excellent Choice for Beginners.”New bike!
Bing + Facebook http://www.youtube.com/watch?v=OE3h7xabHjoLevel of connection – Results might be shown from people you are directly connected to first, then from indirect connections, then random users of the network, possibly followed up by third party content published outside of the social networking system.Reputation of Users – Posts from users who have low reputations, possibly spammers or malicious users, may appear lower in results than posts from users with higher reputations.Popularity – A popularity score for individual posters, based upon having more interactions than other users, may cause posts returned in a search to rank more highly than posts from less popular users.Similarity – A similarity score between the post’s author and the searching user could be based upon demographic information such as age, gender, location, interests, or other similarity measure, and that similarity could also boosts results from similar posters.Affinity with other users – if you interact with certain people more frequently than others, their relevant posts would rank more higly in Facebook’s search results.Affinity with shared applications – for example, if you frequently participate in social online puzzle games, the posts from other people who participate in the same kind of puzzle games (on the social network itself, or possibly on the Web) may be boosted in search results. The patent filing considers this kind of shared affinity to be a “personalization” approach because it takes advantage of interests that are uncovered based upon your use of the social network or even on the Web, to personalize your results by ranking higher posts from other people who may share interests with you.
Bing + Facebook http://www.youtube.com/watch?v=OE3h7xabHjoLevel of connection – Results might be shown from people you are directly connected to first, then from indirect connections, then random users of the network, possibly followed up by third party content published outside of the social networking system.Reputation of Users – Posts from users who have low reputations, possibly spammers or malicious users, may appear lower in results than posts from users with higher reputations.Popularity – A popularity score for individual posters, based upon having more interactions than other users, may cause posts returned in a search to rank more highly than posts from less popular users.Similarity – A similarity score between the post’s author and the searching user could be based upon demographic information such as age, gender, location, interests, or other similarity measure, and that similarity could also boosts results from similar posters.Affinity with other users – if you interact with certain people more frequently than others, their relevant posts would rank more higly in Facebook’s search results.Affinity with shared applications – for example, if you frequently participate in social online puzzle games, the posts from other people who participate in the same kind of puzzle games (on the social network itself, or possibly on the Web) may be boosted in search results. The patent filing considers this kind of shared affinity to be a “personalization” approach because it takes advantage of interests that are uncovered based upon your use of the social network or even on the Web, to personalize your results by ranking higher posts from other people who may share interests with you.
Bing + Facebook http://www.youtube.com/watch?v=OE3h7xabHjoLevel of connection – Results might be shown from people you are directly connected to first, then from indirect connections, then random users of the network, possibly followed up by third party content published outside of the social networking system.Reputation of Users – Posts from users who have low reputations, possibly spammers or malicious users, may appear lower in results than posts from users with higher reputations.Popularity – A popularity score for individual posters, based upon having more interactions than other users, may cause posts returned in a search to rank more highly than posts from less popular users.Similarity – A similarity score between the post’s author and the searching user could be based upon demographic information such as age, gender, location, interests, or other similarity measure, and that similarity could also boosts results from similar posters.Affinity with other users – if you interact with certain people more frequently than others, their relevant posts would rank more higly in Facebook’s search results.Affinity with shared applications – for example, if you frequently participate in social online puzzle games, the posts from other people who participate in the same kind of puzzle games (on the social network itself, or possibly on the Web) may be boosted in search results. The patent filing considers this kind of shared affinity to be a “personalization” approach because it takes advantage of interests that are uncovered based upon your use of the social network or even on the Web, to personalize your results by ranking higher posts from other people who may share interests with you.
Social search returns content from people I know. Not from corporate websites. This means word of mouth from fans, customers (even detractors) will continue to outrank owned assets (microsite, retail hubs, corporate web pages).Hmmm, let’s see who has some thoughts on a new pair of Nike shoes.
I filter the results based on my own network. Looks like some really smart bloggers I know have written about Nike shoes. That’d be great if I was looking for a case study, but right now I need a pair of shoes. Let’s see, someone in my Ogilvy network also wrote about Nike. Our own Asia Digital Map blog (shameless plug: http://www.asiadigitalmap.com/) has some content on Nike shoes.Ah, here we go, two hits: one from a marathon runner I know (he’s faster than me) and a running store I really like (they have a test track inside the store). These are the two links I care about.Network filtering in action.
Your network has a greater influence on which links you clicks and which products you buy. Bing now includes Facebook content in product pages results.
The results are powered by Microsoft's Bing and feature products from China’s largest online retailer, Taobao.
A CTR above 100%? How? For every single link shared, 2.87 people click through on the Facebook wall, and 19.04 people click on a link in a tweet.
