Social Search BlackFin360 - Innovation To Reality

One of the questions I receive a lot is the relation between Google+ and search. I commonly hear “of course Google+ impacts search”, but when pressed most don’t fully understand to what extent. Google+ is one of the more misunderstood properties when it comes to mapping it’s value for a social strategy. The key is not to look at Google+ from just a social lens.

Google provides an incredibly powerful ecosystem for a brand but when it comes to strategy Google is often a secondary area of consideration because of the separation of traditional SEO and the entities that manage social properties or the disconnect between paid & owned strategy.

Think about the three primary points of entry, Google, YouTube & Google+. Google is the primary search engine for a majority of the world, YouTube is the #2 search engine and a key point of distribution for video content and the Google+ represents the future of where Google is building the intersection of search & social via contextual search driven by engagement.

You can see more emphasis on the ecosystem via Google’s new authentication Messaging

So I thought it would be interesting to test the impact of Google+ content on search and the impact of content discoverability. I continue to be impressed by how timely Google is mapping newly created content into search results.

You can see that a Google+ post that I added is already associated with the topic in a search query for a broader topic “5 Reasons to Consider Flipboard”. I wanted to understand the point of differentiation from a contextual placement vs. standard.

I enlisted the help of various team members to test the contextual mapping of the post:

Step 1: Please google a recent Google+ post topic such as “5 Reasons to Consider Flipboard”
Step 2: Try this while logged into Google+
Step 3: Try this while logged out to see if you get the same result.
Step 4: If I don’t appear in your results please follow me on Google+ and see if that changes your results.
Step 5: Please send me a quick note directly to me that outlines at which step the content appeared to you if at all.

Why the experiment? One of the key elements we need to constantly consider from a content strategy standpoint is the impact that posting through Google+ can have from a search perspective vs. engagement. If the domain is verified and the author is mapped as a contributor via their personal Google+ profile, content created will associate elements of the authors Google+ profile in search results (You can see my Google+ profile pic is shown in conjunction with the post). Understanding the reach of the end result of Google authorship and if this is purely contextual vs. standard is of interest.

The Results: For those who were not following me prior to the experiment my social content did not have any association with their Google results either logged into Google+ or logged out.

Here are the results without any contextual association

The association did not become apparent until the user had added me to their circle, then 100% of the users saw the content within the next 24 hours.

Here is what users who added me to their circles saw upon searching for the topic

Content that is optimized for contextural search, including correct usage of hashtags, keywords, etc… will show in search results within minutes of posting to Google+. If a user is following you via a circle and happens to search on the topic you just posted about in the traditional google+ ecosystem, they will see your post towards the top of the 1st SERP (Search Engine Results Page).

As a brand, topical content shows towards the bottom of the 1st SERP for those that in your circles. I am a follower of Callaway Golf, and their Google+ topical content now displays in my SERP.

The final signal to Google is via engagement. If the content gets a significant amount of engagement (Threshold TBD) then the content has a higher probability of the content shifting from contextual to standard, meaning the content is now discoverable outside of those in immediate circles. This is one of the driving factors behind driving circle growth within Google+. It is less about Google+ as a social platform, and more about mapping social content into a more traditional point of consumer discovery.

Google will continue to be a key ecosystem to consider in mapping larger integrated digital campaigns. Especially with the increased focus on content creation, discovery & distribution, understanding how to amplify the content and create contextual associations between socially created content and search will be a key point to consider as contextual search moves to the center of the Google ecosystem.

Follow Tom Edwards @BlackFin360

Recently Facebook announced one of the biggest changes to their search feature to date with the limited beta release of Graph Search. Mark Zuckerberg stated Graph Search would become the third pillar of the Facebook experience in addition to the News Feed and Timeline. This post will review the features of Graph Search while also outlining what it all means.

Here is the official announcement from Facebook

The creation of Graph Search is reflective of the current direction of social which is the inevitable convergence of social and search. With so much information being created and limited alignment between traditional search and the social graph, Graph Search could be a key bridge to a new type of search behavior based on relevant and timely socially curated content.

Example of Bing Facebook integration which applied social as an additive to traditional search. Graph Search takes the inverse approach of searching inside of Facebook.

When you begin to dig into the initial information about Graph Search, it is not intended to be a true web search engine like Google or Bing, but an engine that will search out information across all of Facebook and provide personalized answers to queries about people, photos, places & interests.

Here are various examples of the types of searches that can be conducted.

Here is an example of my friends in San Francisco, as well as recommendations of individuals with similar interests in the area.

Here is an example that leverages Friends Check-In’s via social graph data to uncover Restaurants that may be of interest when in London

Here is an an example of the capability to search for specific types of photos either that you as a user have liked, or topical such as the recent Red Bull Stratos jump.

The Search Graph is a natural extension of the curation of social graph data. By creating deeper connections across interests and access to crowdsourced information, Facebook will now be enabling a cleaner connection to relevant content beyond simply searching for users, brands and apps.

This immediately jumps to questions of privacy from a users perspective. The current explanation is that the Graph Search will honor your privacy settings and only show information to your friends if your privacy is not set to public.

WHAT DOES THIS ALL MEAN?

For starters this will eventually play into the Facebook revenue model. Initially this will be an ad free feature, but make no mistake, by further aligning interests with broader behaviors beyond a profile, it will help to further enable personalization as a search and interest overlay and will become an even more accurate tool to re-target relevant ads.

Also, by adding this as a third pillar, Facebook will eventually be able to monetize against Facebook centric search in a similar manner to how Twitter can place ads via search results with their various promoted products.

Here is an example of a Disney Twitter query that immediately ties into the upcoming Hansel & Gretel movie as a paid unit.

From a brand perspective, this will mean more avenues to differentiate via search results. If the users behaviorally adopt the new way to engage with the rich and relevant content within the social graph, then placement upon search category & interest relevance will be at a premium.

Similar to Google Adwords & promotion of Google+ accounts, brand positioning associated with search may become the new premium Facebook units if users adopt the platform.

It will be interesting to see if the existing Facebook recommendation engine will be put into service as the vehicle that enables placement associated with the results of the search. I did recently speak directly with Facebook and confirmed that the current recommendation engine is not a brand controlable asset, meaning it is not currently part of the paid options to insert a brand, it is strictly algorithm based. But with this new development, the recommendation engine may be a critical component to differentiate from the rest and that will most likely come with a cost.

Example of the Facebook Recommendation Engine for Apps

I am certain that this will have a significant impact on Facebook as a platform moving forward. The amount of objects being added to the social graph will continue to scale at an exponential rate as the introduction of action objects (verbs) into the social graph in addition to all of the various pieces of content that create via interactions with Facebook will now be applied to a system that will make connections beyond the individual more feasible and better align individuals and brands.

Building a system that can now quickly mine relevant information that is based on interests and likes vs. traffic is an interesting proposition, especially when applying the overlay of your social graph with real world use cases such as finding a restaurant recommendation in a new city through the platform you already check 20 times a day.

While there was no immediate mobile support announced, previous behavior suggests that this will also further drive the move towards mobile enablement. If you are able to extend your social graph beyond 1:1 interactions to actually leveraging the data while you are on the go, this is an incredibly important addition and one that will have a significant impact on the future of Facebook’s mobile ad platform.

It will also be interesting to see if a new algorithm, such as edgerank for the newsfeed, can be organically impacted by the amount of followers to a brand (similar to Google+ recommendations via search) or if other factors such as engagement or virality rates will impact which content types (brand content) will be served.

Example of the EdgeRank Algorithm

Facebook initially has recommended the following:

1) The name, category, vanity URL, and information you share in the “About” section should be up to date.
2) If you have a location or a local place Page, update your address to make sure you can appear as a result when someone is searching for a specific location.

There was also an ominous tease towards other factors defining search results. Some early thoughts are possibly tied to engagement & virality rates. It will be interesting to monitor the progression of Graph Search with no immediate mobile version, no Instagram integration, API’s and English only at this stage of the beta, we will monitor the evolution of Graph Search and Facebook SEO.

Follow Tom Edwards @BlackFin360