Why You Look Forward
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A look at how business will change due to new technologies and expectations of the Millenials. Understand what drives Gen Y's decision making, what technologies will impact how we do business and where things like SEO fit into this future mix.
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Why You Look Forward
- 1. Why You Look Forward Duane Forrester Sr. Product Marketing Manager Bing
- 2. @duaneforrester Bing EcoSystem Speaks at shows, runs the WMT blog, provides guidance, works with businesses & Devs www.bing.com/solutions Does he have a clue? 15+ years as an inhouse SEO; ran seo at MSN; has helped Disney, GAP, Walmart, GM … http://www.linkedin.com/in/dforrester And this helps me how? He runs his own sites, has worked from SMB to enterprise, owns ~150 domains http://twitter.com/DuaneForrester what does duane do
- 3. What’s at stake over the next 10 – 15 years? $1 Billion $100 million $1 Million $1 Trillion Images from: http://www.pagetutor.com/trillion/index.html
- 4. • • Know The Buyer – align or fail Resources: http://www.forbes.com/sites/karstenstrauss/2013/09/17/do-millennials-think- differently-about-money-and-career/ http://time.com/money/2820241/10-things-millennials-wont-shell-out-for/ http://www.forbes.com/sites/samanthasharf/2014/07/30/the-recession-generation- how-millennials-are-changing-money-management-forever/ Did you think more keyword research would solve the problem?
- 5. Mobile First Samsung Android / Windows device Project Arcadia: Easily port Android &iOS apps across 1B Windows devices Continuum
- 6. Global Penetration of Mobile Phones 2013
- 8. • • • • • • • • • Coffee, café, latte, cha-ching-ay!
- 9. • • Apple Pay & Mobile Payments
- 10. Bye Bye Wallet, Hello…Freedom!
- 11. Mobile creates a funnel effect Everything on the Web Only what I need now (context)
- 13. My Car, My Friend
- 15. Tapping into the Mobilized World
- 16. Tapping into the Mobilized World Images Videos Popular Celebrities Nav Galleries Name Local Autos Commerce
- 17. Data Signals Are Everywhere
- 18. nn
- 19. Information and Data Growth From the start of time to 2003 2010: we did this in ~2 days 2013: we did this in ~10 minutes 18 2015: while you ordered a coffee
- 20. Information and Data Growth 100 Billion 32 GB iPads If the entire US market tweeted 3 tweets/minute, we’d be tweeting for 38,000 YEARS.
- 21. “In the next 20 years, machine learning will have more impact than mobile has.” - Vinod Khosla
- 22. Search systems now have the raw data to start making sense of the world in which they live
- 23. “What is it?”
- 24. Search has evolved to encompass social & entities 6 billion facts, ~28 billion entities 1.2 billion 1.1 million • 8.5 million km2 8 cm resolution
- 26. The future of search
- 27. Instant Answers, so you spend more time doing the things that matter
- 28. Want in on all that richness? Schema.org Mark. Up. Your. Content.
- 32. “I need a cable for my phone.” Cortana
- 33. So will SEO matter anymore? “I fear cute animals now…” - Anonymous SEO Director “Accosted by a hummingbird…” - Disgruntled SMB Owner “I feel like I’ve been in a sandbox all my life…” - Ecommerce Manager
- 34. Rel=Canonical Bounce Rates Robots.txt Link Policing Site Design Differentiation CMS Updates Malware Watch Authority Crawlability Site Structure Mobile Shift Instant Answers Consumer Behavior Where/When/What Intent Alignment Markup
- 35. The Bottom Line
Editor's Notes
- Mobile queries outpace desktop today – and that won’t flip back. So what’s the BEST investment for your mobile dollars? Responsive design. But this approach doesn’t work for EVERY instance, so tomorrow’s SEO is about helping the company understand what to promote, as much as actually promoting it. A long hard look is needed to determine what content should be supported and what content is ancillary and best left as “linked to” as “related”.
- But its really something called Machine learning? In essence, ML is what enable sites like Amazon to tell you what you will likely buy, can make your phone understand what you are saying, and generally take this mass of data we’re all creating and use it to divine intelligence about the world. It sees patterns where we cannot and it says “if you see this pattern frequently, this is probably what it means and what will happen next.” Its much the same as how a we learn. As a child we may see a round object, people may utter “ball” around that object, we may see it bounce, and eventually, we begin to realize that these round objects all around us are likely these ‘balls’. Same thing happens with ML, except that rather than a few inputs to help a machine learn about a ‘ball’, there are now several trillion. That’s the brain, but we’re also giving them eyes, ears, and a mouth.
- To the point where I can now ask, how do I put a cat in a shredder…and the system will say you should not. Machines have outgrown their maker. Leads to what looks like intelligence. Not true intelligence, but actually what happens when you process vast amounts of data quickly and in context.
- What has happened as a result of this mass digitization? Allowed computer scientists to begin t recreate the real world inside a digital construct
- Bing is stitching together the pieces of the digital web to reassemble them into coherent objects. (ie., an airplane has thousands of characteristics, but those characteristics are spread out on sites across the web. Some sites might have the plane’s length, another has the seating capability, another has safety record.) The challenge is to scour each of these sites, understand they are talking about the same plane, and ‘rebuild’ the physical object in digital so Bing can understand what it is, and what it can be used for. (Scenario: imagine you want to know the largest aircraft with the fewest engine failures, with the above scenario, Bing could do it.) · Bing has 6 Billion facts, 28 Billion entities, and growing very rapidly · For people, we have the largest collection 1.2Billion. · For places such as US restaurant alone, we already have 1.1mm entities · For things like Movie, we have over 800K entities with very rich information. This information fabric is the connective tissues for our devices to seamlessly connect to the people, places, and things that our users care about. For search, this is a major accomplishment. But it isn’t enough. People are trying to do more things with more things.
- Search is the bridge between a user’s intent and the information and experiences the world has to offer. Today search blends personal, real world and real time information in a seamless manner to help users accomplish their tasks. It relies on allowing users to express themselves, not by guessing key words, but by interacting in ways that are more natural and intuitive, combined with an understanding of their preferences, interests and context, sometimes using text, sometimes gesture, speech, conversation or images to interact with their PCs and devices. With search, we want to enable people to achieve more while doing less searching – rather than simply finding more. Bing’s approach to search involves helping people take action based on understanding their intent. Bing has integrated more data sources and the ability to deliver actionable results with entities, such as booking a restaurant or app linking into a service with a single click or comment. A new search paradigm means revolutionizing search to become an ecosystem of connected devices that serves relevant information – and action – to us in a way that is natural to how we learn and interact. Understanding what’s on the web, how people use information to make decisions, and knowing when to filter the important from the trivial are today’s baselines. People expect tech to make their lives better.
- We live in a time of limitless expectations and technology. Technology promised to make work and life easier, instead it created a pace and expectation of efficiency that people can’t keep up with. What people want today is: the ability to do less of the things they have to do and more of things they want to do the ability to focus on what matters to them, without distraction to feel in control and empowered Technology has created an always-on world, where it’s really hard to disconnect and turn off. How do people know when it’s okay to disconnect, what’s important or unimportant, how to connect the dots and when connecting the dots isn’t even necessary?
- By giving direct answers to obvious questions, Bing provides clear results. You’re still free to choose what you like, but for most people, with common questions, the answers are provided enabling you to get on with your task, instead of needing to click more to accomplish things.
- What will these enhancements bring? Efficiency – we cannot multitask. Need a clear thinking opp. Greater efficiency No one wants to manage a complex daily calendar that includes commuting, remembering appointments and tasks, mailing a package at the post office, and other responsibilities large and small. No one wants to measure the UV index before deciding what to wear. No one aches to spend thirty minutes browsing through a hundred bad direct‑to‑Netflix movies to find the one gem that might bring joy or insight to a Friday night.
- Let’s say you’re doing some shopping and your phone buzzes in your pocket. Not only do you get a coupon, you’re offered price comparisons. This is how an intelligence fabric works.
- Search will connect digital and physical (predictive and insightful?) Examine the phone model from which I am issuing the request (something done all the time today) • Derive my intent (that I need to buy a cable) • Figure out the constraints (I need it before my calendar says I am on a plane, minus the time the system predicts it will take me to get to the airport and check in) • Determine which services on the web can fulfill my request • Issue a request to the app using a defined set of information (requester, delivery address, amount the requester is willing to pay [derived either from my personal profile or the average price for a delivery task reported by the service], what the task is, and when it needs to be completed)
- Search will connect digital and physical (predictive and insightful?) Examine the phone model from which I am issuing the request (something done all the time today) • Derive my intent (that I need to buy a cable) • Figure out the constraints (I need it before my calendar says I am on a plane, minus the time the system predicts it will take me to get to the airport and check in) • Determine which services on the web can fulfill my request • Issue a request to the app using a defined set of information (requester, delivery address, amount the requester is willing to pay [derived either from my personal profile or the average price for a delivery task reported by the service], what the task is, and when it needs to be completed)