Effective Machine Learning has Human Agreement

Effective Machine Learning needs buy in from the chosen humans. Photo by Anders Jilden
Effective Machine Learning needs buy in from  chosen humans. Photo by Anders Jilden

Machine Learning is quickly becoming one of the fastest growing technologies and when it works, it is amazingly effective.  Google, Oracle, IBM, Salesforce, Palantir, and Iris AI are some of the leaders in machine learning who pride themselves in assisting clients in ways that were unthinkable only 10 years ago.   Now computing power, thanks to cloud computing, is at an all-time high.  Processing power due to distributed computing and parallel processing allow more algorithms run simultaneously, speeding up the time it takes to get results.

Machine learning allows software programs to learn on their own without custom programming.  One of the most impressive examples to me is the Google translation machine.   Apparently the program decided to write an intermediary step, translating text into machine language that first identified the meaning of the paragraph. It then translated it into the various languages.  The result is amazing!  The machine figured out a solution that had stumped the programmers. Now the machines are ready to learn and ready to take on amazingly challenging tasks that before were humanly impossible.

For this new era to work  humans need buy-in. Processing power is no longer the problem.  Human willingness to take these evolutionary steps will be the next challenge.   Companies who are user friendly always have been more successful.

When I led the media department of DDB,   I challenged Dottie Hall and Vern Rayburn of Microsoft.  I suggested that if they could create a calculating program like that wouldn’t make Corporate Managers, namely men, feel like they are taking on clerical duties, Microsoft would become an amazing successful company.  Dottie Hall and Vern Rayburn pushed this initiative through. It really worked. American productivity sky rocketed and started a new era of tech induced productivity around the world.   MIcrosoft changed the world, because we wanted people to feel good about using the personal computer.  We wanted them to feel smarter.  Machine Learning will have to overcome this same hurdle.

Database managers, Big Data experts, SEO managers, everyone who is used to Oracle, IBM, PeopleSoft, and Unix based programs will have to start opening themselves up to these changes.  For Machine Learning to work human behavior and willingness to adapt to change will be once again become the biggest challenge.  AI is the only way we will benefit from Big Data.  It will be so exciting to participate in this next evolutionary step.

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What My Grandfather Taught Me About Branding

Mickey Mantle
Mickey Mantle

My grandfather Harry Peck founded an advertising agency in New York City in 1922.

This was unusual for several reasons. Advertising agencies were not very common at the time. And agencies founded by Jews was almost unheard of.

My grandfather’s advertising and branding claim to fame was the work he did for Timex watches. Who can forget the Timex torture test campaign where the brand’s durability, shock resistance and waterproof benefits were demonstrated using dramatic executions (as we call them in the ad biz). The campaign went on for years.

A Timex watch was strapped to the propeller of the Queen Mary, placed on a plate on the Old Faithful geyser at Yellowstone National Park and even was taped to the bat of my baseball idol Mickey Mantle. Remarkably, Timex withstood the test every time. And at the end of every ad the consumer heard or saw this tag line:

It takes a lickin’ and keeps on tickin’.

My grandfather sold his agency when I was young, but he lived to see my wife and me start our own advertising agency in New York City. What he did for Timex proved to be a model for the best work I’ve done in my marketing career. Here are 6 things I learned from him.

  1. Have a great selling idea.
  2. Demonstrate your idea in a compelling and memorable way
  3. Make sure you build a campaign not just a one-off ad
  4. Use breakthrough visuals to get consumer attention
  5. Have a well-crafted tagline that summarizes your brand positioning quickly, precisely and lyrically
  6. Keep your campaign going strong for as long as possible.

My grandfather passed away many years ago. His take on branding lives on.

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Only 24% of people use cash in the US to pay most of their bills.

photo by Grace Strok

The IoT so practical.  Credit and Debit Cards are still popular. Since the 2008 recession and a number of hacking incidents that affected  personal data of 100 million credit and debit cards at big retailers have changed the way people feel about using their cards. This is improving the chance of the latest trend of using mobile wallets.  Either way only 24% of people use cash any more.

“A mobile wallet can turn a smartphone into an access device to connect with a payments network,”  says George Peabody, senior director at Glenbrook Partners, a payments research and consulting firm in Menlo Park, California. “The phone is the most convenient tool (for this purpose),” Peabody  continues, “It’s always within reach, and it’s providing the user interface to existing payment vehicles like prepaid or credit cards.”

Apple Pay, Android Pay, and Samsung Pay  are quickly gaining acceptance, and it’s very likely that within the next few years, they will be the dominant forms of payment across the board.  One reason for their rapid growth is that they work faster than Chip Cards.  Square accepts EMV based chip cards which are safer than cards with merely a magnetic strip and since chip cards often take a long time to work at the cash counter more retailers opt for the contactless version of payment via smart phone.

The security and the convenience supports this trend to contactless payments.  To learn more about how we have assisted financial institutions and tech companies gain customers at below typical acquisition rates contact us now, we look forward to working with you.

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