VICTOR CHU UI DESIGNER III, 4
Special Projects, Google
2011, 2010
NEW YORK & SAN FRANCISCO
Special Projects at Google
At Google Special Projects, Victor researched and created mobile intelligence strategies and concept applications.
Special Projects is a research and development division led by Google cofounder Sergey Brin. The R&D concepts apply machine learning to social habits and interests to create and maintain relationships during phone use. The user experience goal was to provide timely social automations for daily life. Victor calls this Social Intelligence.
Mobile is Personal
The Google Social Intelligence graph learns by creating an ongoing machine relationship with the user through surveys and messaging. Social intelligence builds over time to create a "personal socio-intelligence graph" that can be matched against individually relevant places, events, information, deals and ads.
Mobile is personal and subjective. Information is only relevant to the person, their location and proximity.
All other info is extraneous and overwhelming, i.e. inefficient for users eager to make quick decisions and plans.
Social intelligence is knowing where you stand in relation to your peers.
Generic information, reviews, and averages of ratings from strangers has little use in a device that is so personal and time sensitive. Closed systems for tracking and collecting indirect user data on the web does not apply to native apps.
Ratings are so commonplace that the average of ratings from the average population, in combination with inflated and fake ratings will always equal 4.2 stars out of 5. How can an averaged range of ratings from so many unknown standards be subjectively relevant to an individual user with a particular set of standards and desires?
Where the party at? Social intelligence is knowing who’s doing what, when and how much.
Henceforth, for mobile applications, it is key to discern (as a user) what a user will prefer (to buy) based upon personal standards, preferences and dislikes, i.e. taste. And not from random user reviews, ratings and other indirect tracking methods. Social activity and passive peer pressure are heavy influencers of taste.
Mobile: "match my personal preferences" vs. Web: "the average of random social influences".
The phone is primarily a communications device for relationships with friends, family and interests. Communication is by choice. For individuals, choice defines taste. Amongst individuals and friends, taste defines the individual (and the group). This is especially true and critically relevant to choice in restaurants, coffee shops, clubs, events, [culture].
Mobile information is very personal in nature. Phones are carried in pockets and handbags filled with personal belongings. Phones are the ultimate expression and keepers of personal electronic individuality [information].
Mobile search is personable and individual. Mobile searching is more match making, making personal connections with local businesses [matches]. Searching the Web returns the averages of site to site, statistical connections relevant to the words entered [results]. Individual and personal information is not a large part of the Web search calculation.
Social intelligence is keeping communicating.
Mobile search = Matching
Choices [selection]
Preferences (surveys, settings)
Personal patterns [calling/texting certain friends, walking to girlfriend's address, lunch break, alarm set to 7:15am, etc.]
Locality; immediate locale, patterns in locality and travel, direction of travel, travel time
Time; current date and time, current moment of day (breakfast, brunch, lunch, dinner, drinks, dessert, snack, holiday, birthdays, events, etc.) [data source: phone calendar]
Mobile search results = Matches ["map" against]: similarities [traits] in local businesses
The essence of the Facebook threat is the vast potential of personalizing the world's information to individuals, friends and groups of likeminded individuals bound by taste (Instagram) and personal preference. Furthermore, the threat extends to the ongoing relationships and communication between individuals, friends, groups and other entities [such as local businesses].
Hence, returning mobile search results [matches] is only half the equation and captures only half the opportunity. Making the match between local businesses to individual’s tastes and taste groups creates the connections [platform] for ongoing communications which builds relationships, trust and continuous commerce.
Social intelligence is knowing exactly what people like and will buy based upon taste.
Local Business Interface
Socially intelligent businesses are the ones who know who their customers are. They have relationships with their customers and know what they like and enjoy. In contrast, businesses who do not know who their customers are use socially unintelligent marketing methods such as demographics.
This translates to a mobile experience based upon a personal touch in communicating (not broadcasting) to patrons (not customers).
Social intelligence is just asking your user instead of being a creep and using surveillance.
Concepts
Be the Local(e)
Relationship platform b/t local businesses and customers
Specials and deals for local/loyal customers
Communicate directly with your customers
Compelling, unique
Heat Map
Hot spots, activity, people at clubs, pubs, traffic in stores, where are the hot spots
Cartogram
Statistics, locations, spots by the numbers, information
Choice
Organizing places to go next
Favorite spots [emotion]
Lists on left (like FB friends)
Collection of favorite places
Defining self through where have been, travels, factoids/ditties/cool trivial conversational bits of info and where like (consumer self defining through material items)
Dates
New places to go, new ideas for dates
Planner layer
String places together for a date night
Share dating, dates data so know favorites, hates, likes, etc.
Cartomancy (fortune-telling by interpreting a random selection of playing cards)
Divining
Chance (spin the wheel, shake the phone)
Fortune
Magical places
Destinies [Destinations]
Treasure Map
Magical Places
Romance (Romantic Views, Locations)
Views
Historic
Nature
Audio
If listening to music, robot voice can announce deal
Audio deal navigation
Audio tour guide
Deal Scanner
Map orientates ahead of you, vs. from satellite; user views outlay of map in front and as user rotates around sees what's ahead, more natural way of navigating immediate locale
True deal map, lays out what's ahead of you
Playbook [dates]
Rules
Night stuff only shows up at night, etc
Brunch, etc.
No more than 5 items on map, on view, list at a time
All generic locations are never shown as results unless something special about that particular location- ie: Starbucks on 15th and 9th ave is where Google NY started up
New products that are in stores, new restaurants can be clicked and mapped to user's most frequent destinations/routes, scheduled destinations
Highlight only cross streets, cross street names and destination address, all other information is too much information
Information s/b about the destination and not details of map [visual mess]; directions and transportation built into, between points of interests/destinations
Every journey is a journeyed experience no matter if next door, around the block or across the world
Exploration, richness of exploration, life experiences
Photos tag to location can be sorted and viewed [recorded] with locations destinations
Sign Up
Programming the app with initial preferences through choices (high tech tone) "user programmable"
Categories [Destinations]
Foodie
Drinky
Shopping
Sites & Seeing
Sporty [fitness, classes, sports, equipment]
Services beauty salon, services, cleaning, laundry, hair, upkeep, massage, pets, delivery, etc.
Pets
Naughty
Nice
