Performics top 3 trends to drive participation and performance in 2013: (1) AUTOMATED INTUITION: Advertisers activate Big Data to customize ads at scale, by intent, across devices, in real- time to better Connect with participants, (2) THE HUMAN ALGORITHM: Participants move beyond traditional search results to Discover alternative (human!) authority for crowd-sourced decision making, (3) SEARCH APP+IFICATION: Search engines seek to Empower participants by giving them niche content—e.g. integrated vertical search portals directly in the results.
Advertisers will be better able to engage Facebook users to complete lower-funnel activities—like booking a flight after searching, buying a product after filling a cart or subscribing to a service after browsing.
20 13PARTICIPATION ACTIVATED: A Trends Report by Performics @Performics
Par•tic•i•pa•tion Acti•vat•ed: The Process of Turning Engagement into Action We’re creating over 2.5 quintillion bytes of data each day. For years, search engines, search management platforms, advertisers and agencies have been collecting this data, coining it “Big Data” – but it has only been actionable to marketers on a small scale. “This is the year of breaking data out of the cloud.” 2013 is when marketers will activate participant data across screens, at scale, in real-time, setting in motion a spiral of shares, likes, comments, clicks, leads and sales. This is traceable, individual, optimized data that feeds back into (and out of) the cloud. Performics’ Participation Activated Report sets out the major themes to watch. By embracing these themes, marketers can better drive participation in 2013.
THEMES AUTOMATED THE HUMAN SEARCH APP- INTUITION ALGORITHM IFICATION Participants move Search engines Advertisers activate beyond traditional seek to EmpowerBig Data to customize search results to participants by givingads at scale, by intent, Discover alternative them niche content—across devices, in real- (human!) authority e.g. integrated vertical time to better for crowd-sourced search portals directly Connect with decision making in the results participants
AUTOMATED INTUITIONAdvertisers Leverage Big Datato Customize Ads by Intent, MICRO-TRENDSat Scale, across Devices toConnect with Participants Remember the scene in Minority Report where Tom Cruise walked into a mall and a Gap ad scanned his retina, Real-Time Search by Data / personalizing a custom message: “Hey Intent Analytics Tom, how’d those assorted tank tops Bidding work out for you?” This is the Retargeting Teams application of Big Data for retail. In Mass many ways, this future is here. SEM Personalization Platforms Social Expanding e-commerce platform Profiling advances, robust analytics tools and attribution modeling allow unprecedented application of Big Data. Marketers are beginning to deliver highly customized Minority Report- type ads, at scale in a completely automated way. We’re calling this trend Automated Intuition.
AUTOMATED INTUITIONMicro-Trend 1: Search by IntentFor years, marketers have been managing campaigns separately by device: (1) desktop, (2) tablet, (3)smartphone. Meanwhile, participants have been moving across devices, fluidly consuming content.Because participants think of devices as fluidly connected, Google Enhanced Campaigns (rolling out inlate Q1 and Q2) enable marketers to manage devices as fluidly connected . AdWords will now bedesigned to manage hybrid desktop and mobile campaigns per context (intent), not per device. Location: 41.85˚ N, 87.65˚ W With Google Enhanced Campaigns, marketers can Time: 8:30AM deliver search ads based on user intent. What intent does a user have when he searches for “coffee?” Well, that depends on where he is, what time it is and what device he’s on. He may want a coffee shop or home coffee delivery. Enhanced Campaigns enable marketers to make cross-device, automated inferences based on participant data , at scale Location: 42.01˚ N, 87.45˚ W Time: 9:07PM
AUTOMATED INTUITION Micro-Trend 2: Retargeting Through retargeting, marketers can make automated inferences to engage specific participants that have already engaged with them. Emerging search capabilities soon coming out of beta enable advertisers to customize bids, copy and landing pages for searchers cookied on the advertiser’s site. In social, Facebook Ad Exchange (FBX) enables advertisers to reach users based on their browsing histories (via cookies). Advertisers will be better able to engage Facebook users to complete lower- funnel activities—like booking a flight after searching, buying a product after filling a cart or subscribing to a service after browsing.Search FacebookEx: If a marketer knows that a searcher has engaged with that Ex: A user who places products in her shopping cart on a retailer’smarketer on its site, that marketer can bid up for that searcher site but doesn’t purchase later sees a Facebook ad promoting 10%and serve her customized copy: off the products in her cart: User Later Searches User Later on FacebookUser on Your Native Site User on Your Native Site
THE HUMAN ALGORITHMCustomers Increasingly Seekto Discover Alternative MICRO-TRENDSAuthority for Crowd-SourcedDecision Making People are moving beyond the traditional algorithms of Bing and Google to places like Amazon, Data Ubiquitous “Answer” TripAdvisor, Quora or Facebook to Management Search Platforms get search results influenced by People- their friends or peers. Powered Established Accuracy User- What these people see and say Search Collective Generated has significant impact on your Portals Relevancy Content brand. Search marketers must think less about pleasing algorithms and more about pleasing participants. We’re calling this trend The Human Algorithm.
THE HUMAN ALGORITHMMicro-Trend 1: Ubiquitous SearchSearch is ubiquitous; it’s everywhere. When participants turn to sites like Amazon for reviews fromreal humans, they may not call it “searching.” But, in fact, they are searching. And as a searchengine, Amazon is as important as Google. To illustrate, a bike shorts brand could rank #1 organicallyon Google for “bike shorts.” It could have a perfectly optimized paid search program. It could deliverthe right messages at the right time in display, social and email. It could have poor Amazon reviewsand not sell any bike shorts.Participants are increasingly dependent on answers from sites like Amazon, Quora and TripAdvisorfrom context-rich human opinions. Success in the age of The Human Algorithm hinges on activatingparticipation—reviews, comments, likes, shares to engage participants across the path-to-purchase.
THE HUMAN ALGORITHMMicro-Trend 2: People-Powered Accuracy Social networks are clearly capitalizing on The Human Algorithm trend. In January 2013, Facebook rolled out Graph Search. Graph Search results are influenced by humans; they include information that the searcher’s friends have shared (people, photos, interests, places, “Likes”). To illustrate, a user can search “NY restaurants my friends like” to see results for restaurants in NY liked by their Facebook friends. Additionally, Twitter rolled out the Twitter Human Computation Engine in January 2013, which puts a human layer on Twitter search to increase accuracy. Contributors look at trending queries and evaluate them for relevancy, effectively annotating Twitter’s search algorithm. Facebook Graph Search (Jan. 2013) Twitter Human Computation Engine (Jan. 2013) Twitter: “How would you know that #bindersfullofwomen refers to politics, and not office accessories? . . . [W]e need to teach our systems what these queries mean as quickly as we can [by sending them] to real humans to be judged.”
THE HUMAN ALGORITHMMicro-Trend 3: Collective Relevancy How will traditional engines embrace The Human Algorithm ? They’ll continue to expand social integrations to bring more human into their algorithms. Bing revealed major social integration in 2012—the right-hand “sidebar” column that displays recommendations/advice related to the searcher’s query from friends, experts and enthusiasts—with emphasis on Facebook and Twitter. Sidebar also features a box for searchers to pose questions to their Facebook friends. In January 2013, Bing also announced a five-fold increase in Facebook-influenced results. Bing Social Search The challenge for the traditional engines is that Facebook, Amazon and Twitter “own” most of the participant data that enables The Human Algorithm. However, Microsoft has the Facebook partnership, and Google will continue to build social data of its own through Google+.
SEARCH APP-IFICATIONAs Users Move to Niche Sites,Engines Adjust w/ Vertical MICRO-TRENDSSearch App-ification Participants are increasingly moving to vertical sites for product discovery. 33% of shoppers now start their searches Listings Generic “Niche” on Amazon vs. 18% on a search Integration Irrelevance Discovery engine (Forrester). This is Feed reminiscent of the old days when Evolution people used vertical-specific Vertical- Utility- Vertical portals to search. Specific Data Gardens Based Search Google is well aware that this participant trend is a threat to its “one-stop shop” status. Thus, Google is working on a series of “apps” within the search page for vertical queries. We’re calling this trend Search App-ification.
SEARCH APP-IFICATIONMicro-Trend 1: Generic Irrelevance Can you imagine a world without Google? A world where people ditch mass search engines for niche engines? A world where people use restaurant search engines to find restaurants, hotel search engines to find hotels, skinny tie search engines to find skinny ties? It’s not that crazy. We know the importance of vertical search result relevancy. The biggest threat to Google isn’t Bing. It’s a million little niche engines—Citysearch, TripAdvisor, RetailMeNot (coupons), SkyScanner (flights), TinEye (images), Pipl (people), MixTurtle (songs) and SlideFinder (Powerpoint slides). Participants who have specialized needs are, in a way, finding the established engines irrelevant —and looking elsewhere for “better” results.
SEARCH APP-IFICATIONMicro-Trend 2: Feed Evolution In Search App-ification, the “apps” push down traditional results. In the below example, the Google-controlled Shopping Ads (PLAs) draw searchers’ eyes from the top-ranked Amazon organic listing. If you’re a retailer trying to make it solely in traditional SEO, what do you do? Because traditional organic results are increasingly losing real estate, you’ll have to insure your presence in these continuously evolving “apps” and product feeds: • Google Local/Maps listings (local SEO) AdWords Ad • Google+ Business Pages (social SEO) Shopping Ads (PLAs) • YouTube videos (video SEO) • Google Shopping (PLAs) (feeds/CSE): App-ification accelerated in Feb. 2013 when Google purchased Channel Intelligence (product feeds optimization) to bolster Google Shopping • Travel/hotel sponsored content Organic Listing • Top-sponsored ads to trump “app” results
SEARCH APP-IFICATIONMicro-Trend 3: Vertical Gardens Of course, innovation often encounters legal barriers. In a ten-month investigation ending in January 2013, the FTC explored allegations that Google “manipulated its search algorithms to harm vertical websites and unfairly promote its own competing vertical properties.” For example, in the below screenshot, the Google hotels “app” pushes all the organic listings below the fold. However, the FTC eventually determined that this practice could be “justified as innovation that improved Google’s product and the experience of its users.” The FTC gave Google the green light to continue to prominently feature its own properties. App-ification is already happening in verticals like shopping, travel, hotels, weather, local and coupons. Is your vertical next?