Category Archives: Advertising

People Turn Toward “Data Banks” to Commoditize on their Purchase and User Behavior Profiles

Anyone who is anti “Big Brother”, this may not be the article for you, in fact, skip it. ūüôā

 

The Pendulum Swings Away from GDPR

In the not so distant future, “Data Bank” companies consisting of¬†Subject Matter Experts¬†(SME) across all verticals, ¬†may process¬†your data¬†feeds collected from your purchase and user behavior profiles.¬† Consumers will be encouraged to submit their data profiles into a Data Bank who will offer incentives such as a reduction of¬†insurance premiums to cash back rewards.

 

Everything from activity trackers, home¬†automation, to¬†vehicular automation¬†data may be captured and aggregated. ¬† ¬†The data collected can then be sliced and diced to provide macro and¬†micro views of the information. ¬† ¬†On the abstract, macro level the¬†information¬†may allow for demographic, statistical correlations, which may¬†contribute to corporate strategy. On a¬†granular¬†view, the data¬†will provide “data banks” the opportunity to sift through data to perform analysis and correlations that lead to actionable information.

 

Is it secure?  Do you care if a hacker steals your weight loss information? May not be an issue if collected Purchase and Use Behavior Profiles aggregate into a Blockchain general ledger.  Data Curators and Aggregators work with SMEs to correlate the data into:

  • Canned, ‘intelligent’ reports targeted for a specific subject matter, or across silos of¬†data types
  • ‘Universes’ (i.e. ¬†Business Objects) of data that may be ‘mined’ by consumer approved, ‘trusted’ third party companies, e.g. your insurance companies.
  • Actionable information based on AI subject matter rules engines and consumer rule transparency may be provided.

 

¬†“Data Banks” may be required to report to their customers who agreed to sell their data examples of specific rows of the data, which was sold on a “Data Market”.

Consumers may have¬†the option of sharing their personal¬†data with specific companies by proxy, through a ‘data bank’¬†granular to the data point¬†collected.¬† Sharing of Purchase and User Behavior Profiles:

  1. may lower [or raise] your insurance premiums
  2. provide discounts on preventive health care products and services, e.g. vitamins to yoga classes
  3. Targeted, affordable,  medicine that may redirect the choice of the doctor to an alternate.  The MD would be contacted to validate the alternate.

 

The curriated data collected may be harnessed by thousands of affinity groups to offer very discrete products and services.  Purchase and User Behavior Profiles,  correlated information stretches beyond any consumer relationship experienced today.

 

At some point, health insurance companies may require you to wear a tracker to increase or slash premiums.  Auto Insurance companies may offer discounts for access to car smart data to make sure suggested maintenance guidelines for service are met.

 

You may approve your “data bank”¬†to give access¬†to specific soliciting government agencies or private firms looking to analyze data for their studies. You may qualify based on the demographic, abstracted data points collected for incentives provided may be tax credits, or paying studies.

Purchase and User Behavior Profiles:  Adoption and Affordability

If ‘Data Banks’ are allowed to collect Internet of Things (IoT)¬†device profile and the devices themselves are cost prohibitive. ¬†here are a few¬†ways to increase their adoption:

  1.  [US] tax coupons to enable the buyer, at the time of purchase, to save money.  For example, a 100 USD discount applied at the time of purchase of an Activity Tracker, with the stipulation that you may agree,  at some point, to participate in a study.
  2. Government subsidies: the cost of aggregating and archiving Purchase and Behavioral profiles through annual tax deductions.  Today, tax incentives may allow you to purchase an IoT device if the cost is an itemized medical tax deduction, such as an Activity Tracker that monitors your heart rate, if your medical condition requires it.
  3. Auto, Life, Homeowners, and Health policyholders may qualify for additional insurance deductions
  4. Affinity branded IoT devices, such as American Lung Association may sell a logo branded Activity Tracker.  People may sponsor the owner of the tracking pedometer to raise funds for the cause.

The World Bank has a repository of data, World DataBank, which seems to store a large depth of information:

World Bank Open Data: free and open access to data about development in countries around the globe.”

Here is the article that inspired me to write this article:

http://www.marketwatch.com/story/you-might-be-wearing-a-health-tracker-at-work-one-day-2015-03-11

 

Privacy and Data Protection Creates Data Markets

Initiatives such as¬†General Data Protection Regulation (GDPR) and other privacy initiatives which seek to constrict access to your data to you as the “owner”, as a byproduct, create opportunities for you to¬†sell your data.¬†¬†

 

Blockchain: Purchase, and User Behavior Profiles

As your “vault”, “Data Banks” will collect and maintain your two primary datasets:

  1. As a consumer of goods and services, a Purchase Profile is established and evolves over time.¬† Online purchases are automatically collected, curated, appended with metadata, and stored in a data vault [Blockchain].¬† “Offline” purchases at some point, may become a hybrid [on/off] line purchase, with advances in traditional monetary exchanges, and would follow the online transaction model.
  2. User Behavior (UB)¬† profiles, both on and offline will be collected and stored for analytical purposes.¬† A user behavior “session” is a use case of activity where YOU are the prime actor.¬† Each session would create a single UB transaction and are also stored in a “Data Vault”.¬† ¬†UB use cases may not lead to any purchases.

Not all Purchase and User Behavior profiles are created equal.¬† Eg. One person’s profile may show a monthly spend higher than another.¬† The consumer who purchases more may be entitled to more benefits.

These datasets wholly owned by the consumer, are safely stored, propagated, and immutable with a solution such as with a Blockchain general ledger.

AI Assistant Summarizing Email Threads and Complex Documents

“Give me the 50k foot level on that topic.”
“Just give us the cliff notes.”
“Please give me the bird’s eye view.”

AI Email Thread Abstraction and Summarization

A daunting, and¬†highly public email has landed in your lap..top to respond. ¬†The email thread goes between¬†over¬†a dozen people all across the globe. ¬†All of the people on the TO list, and some on the CC list, have¬†expressed their points about … something. ¬†There are junior technical and very senior business staff on the email. ¬†I’ll need to¬†understand¬†the email thread content from the perspective of¬†each¬†person that¬†replied to¬†the thread. ¬†That may involve sifting through each of the emails on¬†the thread. ¬†Even though the people on the emails are English fluent, their response styles may be different based on culture, or seniority of staff (e.g.¬†abstractly written). ¬†Also, the technical folks might want to keep the conversation of the email granular and succinct.
Let’s throw a bit of [AI] automation at¬†this problem.
Another step in our AI personal assistant evolution, email thread aggregation and summarization utilizing cognitive APIs | tools such as what IBM Watson has implemented with¬†their Language APIs.¬† Based on the documentation provided by¬†their APIs, the above challenges can be resolved¬†for the reader. ¬† A suggestion to an IBM partner for the Watson Cognitive cloud, build an ’email plugin’ if the email product¬†exposes their solution to customization.
A plugin built on top of an email application, flexible enough to allow customization, may be a candidate for Email Thread aggregation and summarization.  Email clients may include IBM Notes, Gmail, (Apple) Mail, Microsoft Outlook, Yahoo! Mail, and OpenText FirstClass.
Add this capability to the job description of AI assistants, such as Cortana, Echo, Siri, and Google Now.   In fact, this plug-in may not need the connectivity and usage of an AI assistant, just the email plug-in interacting with a suite of cognitive cloud API calls.

AI Document Abstraction and Summarization

A plug in may also be created for word processors such as Microsoft Word.   Once activated within a document, a summary page may be created and prefixed to the existing document. There are several use cases, such as a synopsis of the document.
With minimal effort from human input, marking up the content, we would still be able to derive the  contextual metadata, and leverage it to create new sentences, paragraphs of sentences.
Update:
I’ve not seen an AI Outlook integration¬†in the list of MS Outlook Add-ins¬†that would bring this functionality to users.

AI Personal Assistants are “Life Partners”

Artificial Intelligent (AI) ¬†“Assistants”, or “Bots” are taken to the ‘next level’ when the¬†assistant becomes a proactive entity based on the input from human intelligent experts that grows with machine learning.

Even the implication of an¬†‘Assistant’ v. ¬†‘Life Partner’ implies a greater degree of dynamic, and proactive interaction. ¬† The cross over to becoming ‘Life Partner’ is when we go ‘above and beyond’ to help our partners succeed, or even survive the day to day.

Once we experience our current [digital, mobile] ‘assistants’ positively influencing our lives in a more intelligent, proactive manner, an emotional bond ‘grows’, and the investment in this technology will also expand.

Practical Applications Range:

  • Alcoholics Anonymous Coach , Mentor – enabling the human partner to overcome temporary weakness. Knowledge, ¬†and “triggers” need to be incorporated into the AI ‘Partner’; ¬†“Location / Proximity” reminder if person enters a shopping area that has a liquor store. ¬†[AI] “Partner” help “talk down”
  • Understanding ‘data points’ from multiple sources, such as alarms, ¬†and calendar events, ¬†to derive ‘knowledge’, and create an actionable trigger.
    • e.g. “Did you remember to take your medicine?” unprompted; “There is a new article in N periodical, that pertains to your medicine. ¬†Would you like to read it?”
    • e.g. 2 unprompted, “Weather calls for N inches of Snow. ¬†Did you remember to service your Snow Blower this season?”
  • FinTech – while in department store XYZ looking to purchase Y over a certain amount, unprompted “Your credit score indicates you are ‘most likely’ eligible to ‘sign up’ for a store credit card, and get N percentage off your first purchase” ¬†Multiple input sources used to achieve a potential sales opportunity.

IBM has a cognitive cloud of AI solutions leveraging IBM’s Watson.¬† Most/All of the 18 web applications they have hosted (with source) are driven by human interactive triggers, as with the “Natural Language Classifier”, which helps build a question-and-answer repository.

There are four¬†bits that need to occur to accelerate adoption of the ‘AI Life Partner’:

  1. Knowledge Experts, or Subject Matter Experts (SME) need to be able to “pass on” their knowledge to build repositories. ¬† IBM Watson Natural Language Classifier may be¬†used.
  2. The integration of this knowledge into an AI medium, such as a ‘Digital Assistant’ needs to occur with corresponding¬†‘triggers’¬†
  3. Our current AI ‘Assistants’ need to become [more] proactive as they integrate into our ‘digital’ lives, such as going beyond the setting of an alarm clock, hands free calling, or checking the¬†sports score. ¬† Our [AI] “Life Partner” needs to ‘act’¬†like buddy and¬†fan of ‘our’ sports team. ¬†Without prompting,¬†proactively serve up knowledge [based on correlated, multiple sources], and/or¬†take [acceptable] actions.
    1. E.g. FinTech – “Our schedule is open tonight, and there are great seats available, Section N, Seat A for ABC dollars on Stubhub. ¬†Shall I make the purchase?”
      1. Partner with vendors to drive FinTech business rules.
  4. Take ‘advantage’ of more knowledge sources, such as the applications we use that collect our data. ¬†Use multiple knowledge sources¬†in concert, enabling the AI to correlate data and propose ‘complex’ rules of interaction.

Our¬†AI¬†‘Life Partners’ may¬†grow in knowledge, and¬†mature the relationship between man and machine. ¬† Incorporating derived rules leveraging machine learning, without input of a human expert, will¬†come with risk and reward.

The Race Is On to Control Artificial Intelligence, and Tech’s Future

Amazon, Google, IBM and Microsoft are using high salaries and games pitting humans against computers to try to claim the standard on which all companies will build their A.I. technology.

In this fight ‚ÄĒ no doubt in its early stages ‚ÄĒ the big tech companies are engaged in tit-for-tat publicity stunts, circling the same start-ups that could provide the technology pieces they are missing and, perhaps most important, trying to hire the same brains.

For years, tech companies have used man-versus-machine competitions to show they are making progress on A.I. In 1997, an IBM computer beat the chess champion Garry Kasparov. Five years ago, IBM went even further when its Watson system won a three-day match on the television trivia show ‚ÄúJeopardy!‚ÄĚ Today, Watson is the centerpiece of IBM‚Äôs A.I. efforts.

Today, only about 1 percent of all software apps have A.I. features, IDC estimates. By 2018, IDC predicts, at least 50 percent of developers will include A.I. features in what they create.

Source: The Race Is On to Control Artificial Intelligence, and Tech’s Future РThe New York Times

The next “tit-for-tat” publicity stunt should most definitely be a battle with robots, exactly like BattleBots, except…

  1. Use A.I. to consume vast amounts of video footage from¬†previous bot battles, while identifying key elements of bot design that gave a¬†bot the ‘upper hand’. ¬†From a human cognition perspective, this exercise may be¬†subjective. The¬†BattleBot scoring process can play a factor in 1)¬†conceiving¬†designs, and 2) defining ‘rules’ of engagement.
  2. Use A.I. to produce BattleBot designs for humans to assemble.
  3. Autonomous battles, bot on bot, based on Artificial Intelligence battle ‘rules’ acquired from the input and analysis of video footage.

Make Finding a Movie Just as much Fun as Watching it.

Content is king.  It seems to be resonating throughout the Entertainment universes.  Fantastic!  Content creators managing their content through licensing, and through their own distribution channel(s). The creation of short clips to entice viewers.   Of course, navigation to view content on a revolving carousel.

The entertainment industry has had successful initiatives in marketing their own content. and licensing their content for distribution and viewing to consumers.

What’s next?

  • Augmented and Virtual Reality

Sitting in your living room with VR headsets, enabling¬†you to socialize before virtually entering the Theater. ¬†Virtual meet ups for discussion / interaction around Genre, e.g. Action, Sci-Fi; or Adhoc meet ups, ‘e.g. by Actor, or Movie interests

Enable a viewer to select, and rotate perspectives of the actors/actress currently in the scene.

  • Movie / Television Trivia (by Genre, by Actor, by Movie)

Another creative way to match up viewer with media beyond the ‘Carousel’: Design games around the content provider’s owned or licensed content. ¬†It will make for a more enriched experience, and help the viewer find their entertainment for the evening. ¬†Even put together a licensing relationship with¬†Hasbro¬†for a spin off¬†Trivial Pursuit. ¬†‘Sponsored puzzles’ like on ‘Wheel of Fortune‘ may help to¬†bring in Advertising dollars. ¬†Or a licensing deal with Screenlife, ¬†makers of¬†Scene It?, ¬†Looks like Screenlife is a Paramount property, small world.

Game examples:

  1. reconstituting a ‘famous and recognizable’ image. ¬† The image is taken directly from one of the movies being streamed.
  2. Guess where the movie or TV show short clip originated.  Select to stream, or play another round.
  3. In what movie or TV show did ‘this’ main theme song originate?

Google Offers Partner Program Incentives for Google Glass

It is rumored that Google will offer a partner program with incentives that allow a user to look at an object, recognize the object, and overlay or mock up the object. ¬†This opens up amazing possibilities for partners, pushes sales for Google Glass, and it’s partners.

As an example, if a user walks up to a Redbox and looks at the device, one of two possibilities are true, if the third party vendor is not a partner, Google will provide an advertisement for competitive partner offerings like it’s own service. ¬†If breakfast cereals partner with Google Glass, as you walk down the isle in your local market, you might see an overlay on some of the boxes, a piece to an invisible puzzle, if you buy all the boxes,and send the proof of purchase and the puzzle pieces, then you are entered in a contest to win ….

The overlay or mock up of a real world object with a virtual object  has limitless potential, all types of retail objects, even people walking on the street using Google Glass may see a tee shirt differently than you because there is a special print image and message that associates with the shirt.  Advertising, contests, promotions, and goofy tee-shirts are just the beginning.

BigQuery, Big Money: Google, get the Megaphone

BigQuery is a¬†RESTful¬†web service¬†that enables interactive analysis of massively large datasets working in conjunction with¬†Google Storage. Google Cloud Storage¬†is a¬†RESTful¬†online file storage¬†web service¬†for storing and accessing your data on¬†Google’s infrastructure. The service combines the performance and scalability of Google’s cloud with advanced security and sharing capabilities. It is an¬†Infrastructure as a Service¬†(IaaS), comparable to¬†Amazon S3¬†online storage service.¬†The Google advertisement should be:

You remember all those books we scanned and indexed?¬† The indexed words and counts are in a database table available in BigQuery. ¬†Query the table to show you the speed of Google’s Cloud Database system, BigQuery. It’s the SCOTT schema of Oracle, but in the cloud…the upgrades to hardware are non-existent, and the database upgrades are seamless. ¬†That’s the power of Google!

Google’s response to Windows’ Azure¬†and Amazon S3. ¬†Powerful statement.

Audio Hashtags Automatically Created When a User Uploads Podcasts or Videos

As mentioned in the post, BI Applied to YouTube Yields Value for Advertising, Marketing, & Sales, YouTube could dynamically scan audio for words and/or phrases when it processes the videos, and the most frequently used, or N threshold number of words appearing, or more to the point said in the video, would:

  1. Be recommended automatically as the words to used as the comma delimited list of words describing the video
  2. A hash tag cloud could appear on YouTube’s front page, with each word growing or shrinking based upon the current trends of words used in the videos uploaded. ¬†People may then click or ‘lasso’ a single or several words and drill down to specific videos within a specific genre.
  3. Business intelligence can be applied in a search screen, to allow the user, advertiser or marketers, to find most frequently used words or phrases, the hip words, or trending phrases so they can use them in advertising or commercials.  For example, a search can be performed on comedy genre videos between X and Y dates, and the most used words and phrases can appear with number counts in a table.

The above intelligence, user interface, and technology may be applied to audio podcasts as well to help users find the type of podcasts they like to hear, or advertisers and marketers to target their audiences more specifically.

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Opportunities for Viral Exposure of Amazon and Netflix Unique Content

It is completely unclear to me why Amazon and Netflix have not developed a widget that allows anyone with a blog, or website to incorporate a particular type of video player widget.  Amazon Associates does have static images for their movies so their associates can enable these plugins on their web sites.  There is also the opportunity to earn some revenue with click through as well as if the click through turns into revenue.  Netflix should also adopt a similar model.  It seems they advertise with select partners. 

What neither company has to drive more revenue is a video widget plugin that allows any blogger to embed it in their site, and plays a trailer of video, a 30 second clip, looped.¬† This video, once clicked, links to a free view of their¬† unique content video hosted on the vendor’s site.¬† The viewers are obligated to rate the video if they want to qualify for a discount.¬† If it’s a streaming video service such as Netflix,¬† the discount can be applied to a month of service, or if it’s the purchase of a movie on demand, the discount may be applied to another video of unique content.¬†¬† They should also track back the revenue earned to the blogger site to pay a nominal referral fee.

Privacy, Eye Movement Technology, Twitter and Advertising

As I was reading my stream of tweets my brain started to wander and think about that new eye movement technology Samsung, and LG are/will utilize to change smartphone screens with your eye movements.¬† As I looked at words in the tweets, the idea occured to me that privacy laws will need to accommodate a new potential frontier in advertising, eye focus advertising.¬†¬† If a person looks at a word in a tweet for 3 seconds,¬† all of that eye focus data, how a person of a certain demographic looks at a particular word, how long, possibly their facial expression,¬† index and abstract that information,¬† it could give the concept of advertising a whole new meaning.¬† Big marketing is watching what you’re watching.¬†¬† Brave New World.