What happened after my TED Talk? I quit my job, wrote a book, grew my organization, and promoted a US postage stamp in Times Square

Originally posted on TED Blog:

Hannah Brencher carried a USPS mail crate with her when she spoke at TED@NYC. Photo: Ryan Lash

Hannah Brencher carried a USPS mail crate with her when she spoke at TED@NYC. Photo: Ryan Lash

Hannah Brencher strolled onstage to give her TED Talk, “Love letters to strangers,” with a US Postal Service mail crate propped on her hip. And that mail crate full of letters turned out to be a metaphor for what happened next — a box of surprises and possibilities.

Onstage at Joe’s Pub in June 2012, Brencher told her story of writing love letters to strangers — yes, in her own handwriting — and leaving them on café tables, tucking them in books at the library, and sending them to anyone on the internet who asked. The project, which she began as a way to fight her post-college depression, took on its own life, so Brencher set up the website More Love Letters to help the letter-writing project expand to anyone who…

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If I Were 22 – Three Things I would Tell My Younger Self (Who Might not Listen)

As a LinkedIn influencer I was asked to write on the topic of If I Were 22, some words I might share with my younger self and things I was doing at that time.  This was a great exercise to bridge multi-generations of readers.  Follow all blogs on LinkedIn and Twitter at #IfIWere22.  Thanks for reading.

A lot has happened since I was 22 but I remember those and the immediate years afterwards with fondness. Graduating college. The first job. Living on my own out of school and moving to my own apartment. Water skiing the summers on Lake Havasu. Those crazy super bowl parties (it’s on during the afternoon usually on the Pacific coast). Volleyball each weekend in Hermosa Beach. Think the B-52s song “Deadbeat Club” – I lived that song each weekend replete with the 25c beers at the Poopdeck. Looking back on it now I lived a great dream.

If I did know what I knew now back then I would probably offer some kind advice to the young man I once was (knowing full well my younger self may opt not to listen to my advice). Here are the top three. Since my advice would have been good enough for my younger self I do try to offer it to my own grown children (and do my best to lead by example, albeit not always successfully).

To read my top three list, visit my LinkedIn post.  Photo courtesy of Zeta Psi North America.

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June 2, 2014 · 2:06 pm

Why Customer Engagement Matters – Customer Dynamics and Business Judo

My briefing on The Customer Edge with host Butch Stearns and colleague Matt Healey from Technology Business Research provided the post-game interview with SAP Insider CRM 2014 conference.  Some highlights may also be found in my LinkedIn post this week, including some thoughts around generational shifts around social marketing expectations and the business judo that needs to happen to give the power of the brand back to the customer.

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Click on the photo to go to the briefing or select this link

 

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Changing Intended Human Behavior, and Liking It

More on my coverage of convergence forces, recently I interviewed a number of customers and executives at the SAP CRM 2014 conference in Las Vegas.  One of the big topics was the focus of location-based services, social, and predictive analytics to offer real-time perks to consumers who have opted-in for such deals.

I’m walking through the park with my wife and I receive a notification on my smart phone.  Because my wife and I enjoy a particular film festival, an offer comes to us for a free ticket with one purchase to an event happening in a nearby venue.  When we finish a lovely movie experience, we receive additional offers for a bite of dinner from three local establishments which we have frequented in the past.  We have taken a leisurely stroll in the park and extended this into a full day of entertainment and relaxation.

Science fiction? Hardly, as we saw this week at the SAP Insider CRM 2014 conference in Las Vegas the citizens of Montreal can live this experience every day with the use of the Societe du Transport Montreal (STM) application.  This location-based customer engagement mobile app identifies where the citizen is, how they can route from point to point inside the city’s transit system, and offer perks and offers along the way by participating establishments which the citizen may or may not already have a customer history with.

This was just one of several customer engagement (CE) scenarios that were discussed with applications across a wide range of product and service industries from public sector, to telecommunications, to discrete manufacturers. Unlike other location based services apps driven by big data where data privacy issues surrounding dynamic pricing my create societal concerns, this fully opt-in community-based approach works.

I am posting the STM promotional video here as well.  For my full report on findings from CRM 2014 check out my blog on the SAP Community Network (login required for comment).

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Coffee Break with Game Changers 2014 Predictions Pt 3 – More on Convergence Forces

The popular internet radio talk show program hosted by Bonnie D. Graham returns for its third full season of predictions and trends which will impact business and technology. What will be the disruptive factors in the market in 20-14? I joined Bonnie and the panel during the fourth segment around 56:00 with my take on “convergence forces” to beg the question “can you fish in a tsunami?”

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My opening statement – besides my annual holiday Irish Cream recipe which you can find elsewhere on my blog – is summarized below. You can also find more on this blog and on my SCN page.

One of the big news stories in strategy, innovation and tech circles is the growth and convergence of four key trends from the past two years. These trends – social networking, mobile computing, cloud applications and big data – are not new.  In fact our firm covered these extensively in 2012 and continue to advise clients on how to leverage these trends strategically, both individually and collectively. What is occurring now as we move into 2014 is the cumulative effect of these trends into force directions of their own.  These so-called convergence forces – or what Gartner Group calls nexus of forces (NOF) – have a tendency to amplify and extend innovation in new and more powerful directions, much like strong winds, lunar position, and seismic disturbances can affect the behavior of ocean tides.  To put it another way, you might be able to plan to fish based on high tide but planning to fish during a tsunami is, well, a bit more complicated.

You can plan to fish in a high tide but fishing in a tsunami is a bit more complicated.

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2013 – the WordPress Review from C-Level

The WordPress.com stats helper monkeys prepared a 2013 annual report for this blog. I hope you enjoy it. Peaceful and prosperous New Year 20-14!

Here’s an excerpt:

A New York City subway train holds 1,200 people. This blog was viewed about 4,700 times in 2013. If it were a NYC subway train, it would take about 4 trips to carry that many people.

Click here to see the complete report.

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Convergence Forces – The Coming Ethics Debate on Predictive Analytics and Location Based Services

One of the big news stories in strategy, innovation and tech circles is the growth and convergence of four key trends from the past two years. These trends – social networking, mobile computing, cloud applications and big data – are not new.  In fact our firm covered these extensively in 2012 and continue to advise clients on how to leverage these trends strategically, both  individually and collectively. What is occurring now as we move into 2014 is the cumulative effect of these trends into force directions of their own.  These so-called convergence forces – or what Gartner Group calls nexus of forces (NOF) – have a tendency to amplify and extend innovation in new and more powerful directions, much like strong winds, lunar position, and seismic disturbances can affect the behavior of ocean tides.

Photo credit, Cisco Systems.

One of the areas where we are seeing this play out is in the business to consumer pricing strategies of in-store retail.  Location based services – either by way of opt-in applications or mobile browsing cookies – allow known customers to log-in to store applications and view special VIP promotions, to quickly locate where items may be found in the store, and to recommend products which based on sentiment analysis and buying pattern might be of interest to the customer.  Location based predictive analytics can also help retailers determine the best location in a particular store to position items based on customer traffic (using big data to monitor your path via GPS as you actually browse the store or predict where you will go based on history and profile) as well as to dynamically create promotions based on your position and buying status.

Creating special offers and promotions based on an existing relationship is not new in the business to business world.  Suppliers and customers alike receive special treatment and extended services and bundle pricing based on volume of sales, excellent quality, and other relationship management KPIs.  In fact in the world of wealth management and retail banking, customers may find that with particularly large financial institutions the first question they are asked after pleasantries may be “what is your current relationship with us?” While this is hardly endearing to the uninformed, it does grant status to those who may, have for example, several accounts, a loan, a trust and other financial products all aggregated under the same customer portfolio with a particular financial institution.

Where things may run amok in the future is when customers (a) receive deferential pricing based on relationship without permission and (b) when a relationship is implied based on socio-demographic profiling or  when facial recognition technologies are employed.  Let me give two very possible scenarios.  I have an account at a sports and recreation retailer and I walk into the store. As a member I have given them permission to my specific profile information (where I live, what I purchase via history, my demographics) in exchange for an annual dividend at no fee.  The retailer has the ability while I am in-store to make me aware of specific items I might want and key promotions going on at that store on that day.  What the retailer can do is also annotate the base price while I walk through the store.  Meaning that what price I may see before logging in and what price I see after I log-in may be different.  Imagine digital price tags changing and updating dynamically as I walk through the store.  Now in this scenario I am going to assume that the incentive I have to purchase items is a benefit versus a cost so I assume that the store is truly giving me a deal even if they don’t.

Another scenario gets more futuristic but again the convergence forces suggest all plausibility.  I walk into a store that I don’t actively have a relationship with nor have I given permission to share my profile and demographic information.  However due to advances in facial recognition technology (such as what is available in Facebook and other applications commercially), the store can tap into vast image databases and make a best estimate at who I am based on my movements in the store and camera images obtained while I move throughout the store.  This correlation of implied relationship and implied demographics can, under the proper scenario, suggest promotions and product recommendations not aligned to my actual relationship nor my actual demographic and in extreme cases improperly tweak dynamic pricing levels.

While this extreme case is just that, convergence forces already have the attention of retail strategists, ethics experts, media tech publications and even sparked political debate. Earlier this year, U.S. Senator Charles Schumer (D-NY) suggested that analytics companies engaging in such practices without customer knowledge would be “intrusive and unsettling.” prompting the Senator to issue a statement with eight of the key location analytics companies in this space to a new code of conduct which would discourage such practices. Other industry segments have also begun to weigh in on the legitimate and ethical use of predictive analytics including higher education, which can use the technology as a early warning system for right-tracking student performance through degree programs.

Convergence forces in this area have already begun and the debate is reaching the mainstream.  What are your thoughts? And – outside of leaving your phone in the car or forgoing permission to give your profile information to any customer loyalty system or social media site – how do we as consumers protect ourselves from retail profiling when we don’t want it?

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