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 To summarize the evolution of the web, by around 2004 user-generated content started to overwhelm existing ranking algorithms. This forced changes to ranking algorithms, and as volumes of data continue to grow exponentially, such ranking algorithms couldn’t keep up. Social data is again overwhelming social filters, and therefore we are entering the next wave of the web evolution. During this next wave, new solutions will target information to you based on personal relevance. It is at this point where the web becomes personal, a web that understands you and continually adapts to your every interest.

 

http://www.slideshare.net/matthew.kapp/the-future-of-social-media-ozmota-inc-personalized-web-final-public-210611

 

 

For the social web to deliver greater relevancy, it must evolve. It must become personal. To better understand this, we must look at how the web has evolved and where it needs to get to. The web started as an information portal, and the age of email, directories and search. Therefore it is fair to say Web 1.0 = Content + Commerce directory taxonomy Lacks:

 

1) Context

2) Social interaction

 

Web 2.0 gave us read write sharing on the web which ushered in user generated content and social networking. We now double what we willingly share on the Internet each year. Our search engines couldn’t cope with the overload. Social networks gave us some filtering with the billions of “What the” phenomena narrowing down our attention from trusted broadcasters giving a sentiment or approval of information signaled onto the social graph.

 

• Facebook:What’s on your mind?

• Twitter:What are you doing now?

• Foursquare:Where are you now?

• Instagram:What are you seeing now?

• last.fm:What are you listening to now?

 

Funnily enough, the more these actions happen, the lower the likelihood that your streams of information and content being consumed are of personal relevance. This is because the social graph does not account for the fact we are constantly shifting and evolving individuals whose focus and interest change with real-time.

 

Web 2.0 is the transformation from directory taxonomy to a social folksonomy

 

Web 2.0 = Content + Commerce + Community

 

Web 2.0 has seen the rise of Social Media

• Leverages the social graph to allow user’s to share content and communicate

• The social graph provides viral opportunities

• This gives each user their own brand & reputation

• Unbelievable experiences and value has been unlocked

 

WEB 2.0 platforms are brilliant in facilitating content generation but it is highly inefficient in personalising my social media experience, lack portability and interoperability.

 

As the Web grows with more information, social media, platforms, real-time, connections, mobility we get FLOODED WITH INFORMATION.

 

MORE DISTRACTIONS = LESS ATTENTION

 

To truly harness the power of the social graph, we need more than a platform that connects us with everyone we know……

 

We need

Reduction in noise

Prioritisation of content

Individualisation of content

Implicit learning models (behaviour)

Context Serendipity discovery

 

As Eric Schmidt quoted “The power of individual targeting — the technology will be so good it will be very hard for people to watch or consume something that has not in some sense been tailored for them.”

 

“The next Web is not a separate Web, but an extension of the current one, in which information is given well-defined meaning and context”

• Personalised Web my view of the web shaped for me focused on the individual

• Contextual Discovery information organisation

•“me-onomy” the context is me!

• Autonomous Search machine surfing

• Pull business models

 

No longer one-way push by brands but by connected customers voting in the invitation for brands to connect with them.

 

What are the properties of a personalized Web;

• Mobile

• Influence

• Connecting business to clients dynamically

• Personalization

• Bridging online and offline interactions

• Social Discovery

• Connecting people through the Interest Graph

 

Context advances Web 2.0 towards the next web, a personalised Web. When machines can understand the context of content, and of a user, the web can better satisfy a user’s needs Context helps enable personalisation, but there is more needed……..

 

The interest graph provides a new way to discover content & people with similar tastes to yours. It is the new way to get from both within, and beyond, your social graph, the content that will interest you personally It forms a network of people who share interests with you, but who you don’t necessarily know a connection within the social graph.

 

The interest graph is an online representation of individuals’ interests. Combined with context, it allows us to float relevant content in front of a user’s attention. Some people consider this the middle ground between search, advertising and the social graph .

 

Gorillas are vying for position.

 

“The notion of autonomous search – to tell me things I didn’t know but am probably interested in – is the next great stage of search”

Eric Schmidt, Google

 

“Google search will continue to become more personalised. “ He noted that thousands of Google engineers are currently working on beefing up search with artificial intelligence in hopes to find us the results we want right away.

Eric Schmidt, Google 28th Feb 2012 Barcelona

 

“With 100 million tweets flowing through the system on a daily basis, there’s something for everyone, but the real challenge is finding the most valuable stuff for you”

Evan Williams, Twitter

 

“With a normal website, your technology is focused on caching. But Facebook is completely personalized. Every time you visit, you get a unique personal experience”

Bret Taylor, Facebook

 

The interest graph introduces a new challenge and opportunity for brands to communicate their messages to those people that will genuinely be interested in what they have to say

 

The interest graph promises to deliver marketers messages to those that are, or should be interested

 

 Web personalisation puts the user in the centre. It converges the broadcast centric social graph with the interest graph and both explicit and implicit behaviour to give the user highly personalised discovery, curation, transaction, communication and socialising functions with both information and people of common and similar interests.

 

A Personalised web will be very relevant, and very dynamic. Marketeers will need to create content that can travel through the interest graph. The intelligence must be embedded, or discoverable within the content and with context and advanced metadata. Sites and applications must deliver on-demand, interest focused content for socialisation on the web. How this content moves through the web will be fundamentally outside of content providers control.

 

By directing people’s attention provides many opportunities, particularly given attention is truly our most valued currency. Once the web knows your interests, the way in which we consume the web can start to change. Information that is not discoverable through keyword search starts to float to the top of your interest streams. New people and information can be discovered, rather than pushed at us. Or more precisely, information is pulled to the surface to the huge corpus of information for each user. This will not only drastically improve information discovery, but it will accelerate collaboration and conversation and focus our attention on what matters most.

 

With a personalised view of the web, each and every user will be connected with the right information at the right time.

 

Further, by accessing our technology through defined interfaces, any website or application can use knowledge of a user’s interests in order to give them a personal experience.

 

The potential of harnessing this data will become invaluable for brands, so marketers will be using the power of the data in the near future to their advantage. When brands create content, they will also need to define the context that links the content to the interest graph.

Marketers will have the ability to take this personalised data to drill down to find their core customer accurately.

 

The evolution to a personalised web is not without its challenges.

1. Web-scale interest ranking engines

2. Artificial intelligence

3. Machine learning

4. Content categorisation

5. Linking it all together

 

Context Discovery platform used within web applications allows each user the flexibility to immerse themselves into their own “slice of the stream” by filtering for relevance. And by conversing in the stream, our platform allows a user to subscribe to signals reflecting what their friends, colleagues, and like-minded people are finding relevant.

 

The signals don’t stop there. Context Discovery platforms will evolve further harvesting other web signals and further specialise from the monolithic Interest Graph into Taste Graphs, Financial Graphs, Psychometric graphs, Local Network Graphs, Transaction Graphs..think Square.com etc. through implicit graph definitions. Think of the psychometric data we could add or harvest. This signal could be used to find affinities or the best collaborative mix to organically setup task force teams in the social enterprise. This technology has already begun.

http://tweetpsych.com/?q=kampers

. Imagine the potential for structured innovation solutions either for social networking around interests or business agility. To quickly deploy available human resources with skill, psychometric recommended highly comaptible membership linked into a task force that organically fuses around a customer opportunity. The team creates solutions, integrates into processes and the social enterprise holistic system and is ready for the next task. Organic teams, valuable, holistic and visible, and rewarded in social enterprise eco system. If I were a CEO transforming to this new attention/digital economy I’m sure I would see that as a  valuable capability. However that’s another topic.

 

Matthew Kapp

@matthew_kapp

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