Leveraging Social Media
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1 Leveraging Social Media Social data mining and retargeting Online Marketing Strategies for Travel June 2, 2014
2 Session Agenda 1) Get to grips with social data mining and intelligently split your segments to communicate more effectively across your marketing channels 2) Learn how to harness social media data and better divide your marketing segments 3) Personalize and retarget effectively: How to leverage social data to reach the right consumer at the right time with the right message (without being creepy) 4) What information are you legally allowed to collect, use and store from social data sources?
3 Presentation Agenda 1) Mining social data a) Definitions b) Uses and challenges c) Execution: DIY vs. vendors 2) Retargeting a) Definitions b) Customer intent c) Campaign execution d) Segmentation and Throttling 3) Social retargeting
4 Definitions: Data Mining The computational process of discovering patterns in large data sets the automatic or semi-automatic analysis of large quantities of data to extract previously unknown interesting patterns such as: groups of data records (cluster analysis), and; dependencies (association rule mining).
5 Data mining by Clustering: flower categorization Fisher s iris data
6 Data mining by Association Rules: politics v. beers
7 Presentation Agenda 1) Mining social data a) Definitions b) Uses and challenges c) Execution: DIY vs. vendors 2) Retargeting a) Definitions b) Customer intent c) Campaign execution d) Segmentation and Throttling 3) Social retargeting
8 Social data mining uses Companies are mining the social web to build dossiers on you. Information posted publicly on blogs, Facebook, Twitter, forums and other sites is fair game. Leah Bettancourt, Mashable contributor Purposes include: credit judgment, fraud detection, product customization, new customer acquisition, influencer identification/targeting.
9 Social data mining uses [Twitter s] constant stream of experiences, opinions and sentiments has spawned a vast commercial ecosystem, serving up putative insights to: Product developers, Hollywood studios, major retailers and potentially most profitably hedge funds and other investors.. - Elizabeth Dwoskin, WSJ
10 Social data mining challenges: record sifting Companies face the issue of identifying their customers among the millions in any given online community. Chris Boorman, CMO of Informatica Dealing with data sets measured in petabytes is a challenge in itself, and there is a serious problem with the signal-tonoise ratio we estimate that at best, only 20% of the social media data stream contains relevant information.
11 Social data mining challenges: record matching Methods include: Company participation: On Facebook businesses can gain access to the profiles of anyone who clicks the Like button on the company s business site Mining + Algorithms: If a company has one or two key pieces of information about its customers address is often the most important that company can accurately identify them on a social site and extract a substantial amount of data
12 Presentation Agenda 1) Mining social data a) Definitions b) Uses and challenges c) Execution: DIY vs. vendors 2) Retargeting a) Definitions b) Customer intent c) Campaign execution d) Segmentation and Throttling 3) Social retargeting
13 How you can mine social data: DIY Hands-on data mining text, using (free) Python Introduces social sites Describes the sites uniqueness and unique data Explains how to pull and analyze
14 Social data mining DIY: Twitter Teaches you how to: Discover trending topics Identify retweeters of a status Identify all followers of a Twitter user Analyze a user s friends and followers Perform tweet frequency analyses Find the most popular tweets Search for individual tweets Harvest a user s tweets Crawl a Friendship Graph Analyze a user s favorite tweets.
15 Social data mining DIY: Facebook Teaches you how to: Analyze social graph connections. Analyze Facebook pages Analyze things your company s friends like Analyze mutual friendships Visualize directed graphs of mutual relationships.
16 Social data mining: Vendors Certified data resellers: 1) Gnip the world s largest and most trusted provider. a) Very comprehensive set of social media sources 2) Data Sift the leading social data platform a) Advanced filters b) SQL-like query language 3) Topsy Labs, Inc. charts Twitter and Google trends
17 Twitter volume queries using Topsy
18 Presentation Agenda 1) Mining social data a) Definitions b) Uses and challenges c) Execution: DIY vs. vendors 2) Retargeting a) Definitions b) Customer intent c) Campaign execution d) Segmentation and Throttling 3) Social retargeting
19 Resources: The Retargeting Playbook Articulates complete retargeting strategy and set of tactics: Setting up your campaign Segmenting your customers Optimizing your ads Meeting specific objectives Optimizing for Social and Mobile Adhering to privacy laws
20 The re- is important, or else it s just targeting It was already blue before.
21 Definitions: Site Retargeting is Someone arrives at your site (often from search) then leaves without buying (or buying enough). The Retargeting Playbook, Berke
22 Definitions: various Retargetings Term Search retargeting retargeting Social retargeting Actually describes Targeting display ads based on Google search terms Sending to people who visit your site, or Using in-message retargeting pixel to dynamically adjust Targeting a consumer based on Facebook like, or Targeting site visitors on Facebook Exchange. The Retargeting Playbook, Berke
23 Presentation Agenda 1) Mining social data a) Definitions b) Uses and challenges c) Execution: DIY vs. vendors 2) Retargeting a) Definitions b) Customer intent c) Campaign execution d) Segmentation and Throttling 3) Social retargeting
24 Intent: why retargeting is successful 1) Search engines capture intent to purchase 2) Site behaviors also signal intent, but: a) Shoppers are more connected/distracted b) 71% of the 97% break off before purchasing because: 44%: shipping and handling were too expensive 41%: wasn t ready to purchase 27%: wanted to compare prices on other sites 25%: product price was higher than I was willing to pay 24%: just wanted to save product in cart for later consideration The Retargeting Playbook, Berke
25 Presentation Agenda 1) Mining social data a) Definitions b) Uses and challenges c) Execution: DIY vs. vendors 2) Retargeting a) Definitions b) Customer intent c) Campaign execution d) Segmentation and Throttling 3) Social retargeting
26 Campaign Setup 1) Post your privacy policy on all data-collection pages. 2) Tag your website to start building lists a) Each ad marketplace has a JavaScript tag for each page header b) Verify that the tags are working c) Accumulate at least 500 visitors before impressions start serving. 3) Create and upload ads a) There are ten total ad types used in retargeting b) Five major types (300x250, 160x600, 728x90, 100x72, 200x200) 4) Launch your campaign 5) Segment The Retargeting Playbook, Berke
27 Presentation Agenda 1) Mining social data a) Definitions b) Uses and challenges c) Execution: DIY vs. vendors 2) Retargeting a) Definitions b) Customer intent c) Campaign execution d) Segmentation and Throttling 3) Social retargeting
28 Segmentation: Basic Basic retargeting segmentation is driven by intent signals. 1) Funnel-based segmentation a) Number of visits to the site b) Time on site c) # of pages viewed (and funnel depth) d) Items added to cart 2) Possible segmentation scheme a) All site visitors b) Viewers of at least one product page c) Shopping cart users d) Purchasers The Retargeting Playbook, Berke
29 Throttling 1) Use Conversion charts to determine: a) Frequency cap: max impressions a user can see/day b) Audience duration: how long to keep targeting? (30 days?) 2) Cadence modification: bidding less on successive impressions 3) Segment prioritization: e.g. exclude purchasers 4) Inventory management: drop out of non-performing spaces The Retargeting Playbook, Berke
30 Presentation Agenda 1) Mining social data a) Definitions b) Uses and challenges c) Execution: DIY vs. vendors 2) Retargeting a) Definitions b) Customer intent c) Campaign execution d) Segmentation and Throttling 3) Social retargeting
31 Facebook targeting parameters 1) Location (Country, State, City, Zip) 2) Age (13-65 or 65+) 3) Gender and relationship status 4) Precise interests (liked The Biggest Loser ) 5) Broad categories (e.g. small biz owners, Hispanics) 6) Connections (target/exclude fans) 7) Friends of connections 8) Education level 9) Likes and Shares
32 Retargeting on Facebook using social data mining 1) Perform social (or non-social) data mining 2) In Ads Manager: input your targeted Custom Audience: a) Acceptable key fields: address, phone numbers, Facebook user IDs or mobile advertiser IDs. b) Minimum recommended size: 1K targeted customers c) Format:.csv, single column, no heading 3) Specify Facebook ad targeting criteria 4) Observe performance and continually refine
33 Appendix
34 Retargeting vendor considerations Reputation: ethical and successful Reach: participates on all major exchanges Technology: owns and operates its own Flexibility: insertion-order-based and no contracts/minimums Transparency: discloses campaign performance Service: responsiveness Pricing: dynamic CPMs The Retargeting Playbook, Berke
35 Ad exchanges 1) Google s AdX 2) Yahoo! 3) Appnexus 4) AOL 5) FBX (news feed and right-hand side) The Retargeting Playbook, Berke
36 Sample Privacy Policy As you browse [company site], advertising cookies will be placed on your computer so that we can understand what you are interested in. Our display advertising partner, AdRoll, then enables us to present you with retargeting advertising on other sites based on your previous interaction with [company site]. The techniques our partners employ do not collect personal information such as your name, e- mail address, postal address or telephone number. You can visit to opt out of AdRoll and their partners targeted advertising. The Retargeting Playbook, Berke
37 Segmentation 1) Basic (intent-signal based) 2) Category-based 3) Product-based 4) Advanced The Retargeting Playbook, Berke
38 First-party data: you have access to 1) Pages people visited 2) Time on site 3) Products viewed 4) Purchase history The Retargeting Playbook, Berke
39 Segmentation Cart abandoners Viewers of specific: Products Product lines Repeat buyers
40 Facebook Marketplace vs. Exchange Tool Marketplace Exchange Funnel focus Demand Generation (upper) Demand Fulfillment (lower) Bought through Facebook or partners ( preferred marketing developers ) Facebook-qualified partners Sold on Impression basis Insertion basis Uses data from Facebook (profiles, interests and other actions on-platform) Your website only (onsite intent data, 3 rd party data) For retargeting? Eventually added Yes Ad units Almost every type (including sponsored stories, page-post ads: links, videos, photos, events) News Feed (static & dynamic) Right-hand-side (static & dynamic) Page-post link ads only on desktop The Retargeting Playbook, Berke
41 Data analysis, Old School Fitting a line approximating x vs. y relationship
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