The Jony Ive Freakout

For those of you who haven't heard, yesterday Jony Ive was promoted to Chief Design Officer at Apple.  While that may seem like a good thing, the Applesphere and Techsphere are freaking out.  There is a pending doom in the air, Jony Ive is leaving the company.  Hmmmm.  It looks as though he is being promoted, not leaving.

One of the biggest cries come in the title.  The one that is bantering around the most is his lack of ego and no need for a title.  While this may be true of himself, there are people under him that deserve a jump in title.  I believe this allows his lieutenants to get the title recognition they have deserved for quite awhile.

Jony has the same aura as Steve did.  There is this belief that Steve had his hands in every minute decision and he was the mastermind behind all the tech that Apple had created since his return.  That could not be further from the truth.  Steve was brilliant at getting teams to focus, make things simpler, which is a form of design.  Jony falls under the same category.  He does not design everything that comes out of Apple, he leads the team that does it.  While I am not trying to minimizing his role with that statement, I am trying to emphasize that his team designs and comes up with the concepts as well.  Jony has the final say, which nothing changes under the new arrangement.

Apple is a very large company with many brilliant people who dedicate an inordinate amount of effort to produce the products we love.  It is more than just 1 or 2 people that make Apple what it is.  There is an entire ecosystem of brilliance which is lead by very smart people.  Apple has always been about focus, which is how they also operate with public figures.  This is the coming out for 2 strong individuals at Apple.  

Even though I don't know them personally, Richard Howarth and Alan Dye deserve these positions, which I'm sure they have already been doing for quite some time.  The one thing you don't want as an Apple follower is for Jony to burn out, which it seems he was on his way to doing.  This allows Jony the freedom to take a break, and dare I say, travel and decompress a little more than he has been allowed to since Steve's passing. The day-to-day will be just fine without Jony there.  He will be there plenty to guide the teams, which is what a leader should be doing.  Everyone needs to chilax.

Sears Could Disrupt Throwaway Tech Culture

It's funny the timing of this article.  I was just talking with my wife about Sears and how it seems they have no future, it's only a matter of time before the Sears retail store as we know it will no longer exist.  Then to read a headline about Sears disrupting?  Heck ya I'm interested.

The company has launched a Seattle office, and recruited retail tech execs to help it get a handle on the data it has amassed from the 40,000+ daily service queries its Home Services group collects on washing machines, refrigerators, and other appliances. It turns out that the industry average is that about 1 out of every 4 customers don’t get their appliance woes fixed on the first visit. 

“Each truck carries about 400 parts, yet those annual service calls require something like 168,000 different parts,” explained Arun Arora, the group’s president. “We’d have to have our 7,000 certified technicians driving semis around to anticipate them.”

"Big data" has so many applications and to see Sears trying to disrupt in a way that doesn't make headlines is impressive.  This kind of disruption, even though on the surface looks like a cost-savings initiative, can revolutionize the service of appliances.  Why does that matter?  Because loyalty is the name of the game.  If they make the experience of owning a machine better, even when it is getting old and needs some new life breathed into it, they can increase their base of loyal active customers.  

The more customers that are active with a company the more they will make.  If Sears can increase the number of loyal customers by offering a superior customer experience of ownership, they can drive more sales in other areas.  It is the process of rebuilding trust with a brand.  If I knew buying an oven will have a longer shelf-life and the company where I was buying it can make that happen, then it makes where I buy more interesting.  

So many times in the retail space it comes down to price.  Everyone sells ovens and mostly from the same manufacturers, so there is very little to differentiate.  The easiest rode to differentiation is price.  The problem is when competing on price, the business can never win.  They are not cultivating loyal customers, in fact they are probably selling to the exact wrong customer.  If a customer is only going to choose on price, they are by definition not loyal customers.  If Sears can differentiate beyond price and experience in the stores, they can grow their loyal database.  That's a big win.   

The Missing Connection Between Big Data and Great Insights for Data-Driven Marketers

Data-driven marketers today are wondering how they can gain insight from big data. The answer? The ability to change is the connection between big data and insight. Data-driven marketers today know that their roles are changing: 68% of marketers think that marketing has seen more changes in the last two years than it has in the past 50 years, according to a recent survey.  The changes are due to a renewed focus on customer experience within their jobs, and the need to use big data to improve that experience.

Customer Experience is the buzzword over the last 2 years, combine this with the other buzzword of "big data" and you can understand why 68% of marketers think marketing has changed so drastically the last couple of years.  I think what is causing all this change is how technology has shifted the paradigm of marketing.  

For many years marketers were able to call on plays from the same playbook and be very successful.  The technology was never really able to advance the playbook and very few companies were pushing the boundaries.  Today, marketing technology companies are driving the sea change, creating platforms which make creating authentic customer experiences possible on a large scale.  

Companies are having to tear up their playbook and turn their strategy on its head.  This goes well beyond just the marketing playbook.  Companies are having to start culture change throughout the organization as the customer experience goes well beyond just the marketing department.  As customers interact with all parts of organizations, there is little care of operational silos within companies.  

The biggest sea change is what Adobe refers to "marketing beyond marketing".  No longer can marketing leaders be focused on the message and bring in customers, only to wipe their hands after the customer starts engaging with the brand.  Marketers are learning they are the leaders of the customer experience renaissance.  Marketing is having to drive the experience of the customer throughout entire organizations, which is not a skill-set a traditional marketer has.  This change will be driving "big data" initiatives as marketers are learning to understand their customers in new and interesting ways.  

Yelp is Looking For Buyers

In reading the daily update on Stratechery by Ben Thompson, which I highly recommend, he discusses Yelp being on the market.  Yelp is definitely underperforming compared to other social network advertising platforms.  Their revenue is very small, $377 million in 2014 and the growth is not as large as it needs to be for a corporation the size of Yelp.  

What strikes me as interesting in the case of Yelp is their strategy.  Yesterday I commented on an article about strategy and how to assess if your strategy is valid.  I believe Yelp has a strategy that is destined to fail.  Yelp is running the same strategy as the market leaders, which is as an advertising platform.  

The issue I see with their strategy is it is not differentiated.  In fact, their offering is worse than the market leaders when it comes to their ad product.  One may argue their product is differentiated because if a customer is searching for example Mexican Restaurants, then as a Mexican Restaurant it can't get more targeted than an ad for someone looking for that kind of food in a small geographical area.  The problem with this is customers aren't looking for ads on Yelp, they are looking for advice.  An ad is the opposite of what they desire.

 I frequently hear in the tech community that Twitter doesn't understand its product.  They want the product to be something other than what it is.  I fear Yelp may be in the same boat.  Yelp is an aggregator of reviews, they are the trusted source of "where should I eat".  That trust comes from customers reviews.  

elp has the opportunity to differentiate their business.  Their strategy should be the opposite of the strengths of Google and Facebook.  

Loyalty

Yelp has a loyal customer base, however they do not take advantage of this.  Their product has not really changed much since its inception, especially in mobile.  With the advent of technologies, such as beacons, it surprises me that Yelp hasn't taken advantage of its loyal base and struck up deals with local businesses to do a loyalty program with Yelp.  Businesses rely on having great Yelp reviews and this can be parlayed into some kind of loyalty program with a beacon backbone that would identify if a customer was at the business and how much was spent using new location aware technologies.

Recommendation Engine

Because of the amount of data Yelp has it is surprising they haven't developed a more intuitive recommendation engine.  I am always looking for places that I would enjoy and it would be nice if an app told me where I should go and what I should order or what services I should buy.  Yelp is in such a unique position to deliver this.  

I believe they have the ability to enhance their product by allowing customers to rate something without writing a review.  This is something that doesn't have to count to the external rating of the restaurant, but as a means to gather likes of an individual.  This is easy and more customers would rate the businesses in turn.  They can then use this information to have the ultimate "lookalike" recommendation engine.  This is far more powerful than anything Google or Facebook can do.

Targeted Ads and Data

With this lookalike system in place, Yelp can then sell back to the businesses in the form of ads and data.  Since they will have information on all the buyers who are interacting with Yelp, not just the people who take the time to write a review, Yelp can then sell all the information about the customers back to the businesses for a fee.  The ads can then become more targeted because advertisers can get on the home screen of the app with a customer that is highly likely to enjoy the businesses offerings.  As customers see the recommendations are more accurate and they enjoy the businesses experiences, they will end up buying more items through Yelp advertising because of the accuracy.  This will drive higher ad prices for Yelp and bigger returns for the business as they can attract customers that will become more loyal.

I would love the opportunity to innovate at Yelp.  They are in such a unique position to do something different, but they are building the exact same monetary offerings as their competition.  The problem is they don't have the scale.  Just like Twitter, they have to be better and more accurate with their advertising.  This will drive advertising dollars their way because it is more efficient spend and that is what advertisers are looking to achieve.

The First Question to Ask of Any Strategy

A great article by Roger L. Martin regarding Strategy.  

Sadly, like the majority of strategies that I read, this firm’s strategy failed my sniff test and for that reason I would bet overwhelmingly that it will fail in the market as well. The test I apply is quite simple. I look at the core strategy choices and ask myself if I could make the opposite choice without looking stupid. For my wealth managers, the opposite of their “where” choice was to target poor individuals who don’t want and aren’t willing to pay for comprehensive wealth management services. The opposite of their “how” is to provide crappy customer service.

The point is this: If the opposite of your core strategy choices looks stupid, then every competitor is going to have more or less the exact same strategy as you. That means that you are likely to be indistinguishable from your competitors and the only way you will make a decent return is if the industry currently happens to be highly attractive structurally. The wealth management company was targeting the exact same clients as every single global competitor and, like every other global competitor, they planned on giving them “great service.”

I recently wrote about the differences between strategies and tactics, this gets to the heart of defining a good strategy.  It is a really interesting take on the definition of the strategy itself.  I am a big fan of differentiation of the a strategy.  Unless your business is the market leader, following the same strategy as your competition is a recipe for disaster.  You will never overtake the leader.  This is an entirely different take on competing with a strategy that is opposite of a winning strategy.  

Most market leaders and successful companies have good strategies.  They make a lot of money and have a lot of customers.  Sometimes as a business you have to take a strategy that is opposite of what those competitors are doing.  For instance, Apple looked at the smartphone landscape and determined their competitors were tailoring their products to business minded individuals, but Apple decided their strategy was not to go after that market, they decided to make a phone for consumers.  Yes this was in their wheelhouse, but it is an example of not following the competition.  Only later in the iPhone's life did it add features to compete in business, but that was secondary. 

The App Store is in Trouble Without Paid Upgrades

I want to preface this by saying I am not an app developer, however I have watched the app store and Apple for a long time now.  I have also lead very successful digital marketing teams for billion dollar revenue companies, so I know a thing or two about marketing ad driving revenue for products and services.  

Ever since the app store was introduced in 2008 it has been a boon for many developers, but more and more I hear their revenues are down even though the app store as a whole is up.  I hear a lot of complaints about the app store is geared to only help the top grossing apps or the apps Apple wants to help.  All of this is true, it is hard to find the app you want in the app store and their curation definitely has some favoritism happening, but that's business.  These are problems that still need to be solved, but the biggest problem in my eyes is the lack of paid upgrades.

Being a consumer of apps I have enjoyed the lack of paid upgrades, it allows me to reap the benefits from the app for a long time.  However, I paid for Instapaper 6 years ago and I have not paid a dime since, this is not a good model for the app developers.  I am a loyal customer, but I don't need the upgrades that come with the monthly fee, which I think is spending too much for the extras.

Loyal customers are the best source of additional revenue

For any business to thrive, they have to be able to establish a base of business that provides the bulk of the revenue.  This is the loyal customer base that equates to 70-80% of the revenue, but accounts for only 30-50% of the investment in advertising and marketing.  These are the customers that love the products, tell all their friends about the products and buy new products when available.  This is why Apple is crushing their competition because they have a loyal base of customers that buy new products from Apple when available.

For app developers, without a model for paid upgrades, they are forced into a model of perpetually finding new customers or create a subscription type model.  For game developers this is fine, because they can create an experience that is easier and more enjoyable for the gamer when purchasing extra coins to make getting through levels faster.  People are willing to pay for these and that is great.  For the indie app developer making polished apps, this model does not work.  For that reason, they are constantly trying to find another customer who will buy their app for $2.99 and then forget about them.  This is not a sustainable business model.  Eventually there are not enough customers to buy the new app to make a living.  As more people buy the app, the less people there are to buy the app in the pool, so it is inevitable that revenues will not be maintained.

Beautiful apps will become fewer and far between

The Apple app store is filled with a lot of garbage, but it is also filled with amazing apps.  Apps that developers have put their heart and soul into.  Even back in the days of only the Mac, an application on that platform was much nicer than applications on the PC.  This is a trend that continued on iOS and continues to this day.  But that may all change soon.

A developer has to feel confident they will get a return on their investment for the time they put into an app.  There are never certainties in this business, but someone who takes pride in what they build will always take the time needed to make it beautiful, functional and have the best customer experience possible.  If there is not a business model that seems viable, the developer is then forced to create many apps or develop for multiple platforms to succeed.  This limits their time.  Limited time results in less polished, less amazing apps.  This hurts the app store.  This hurts Apples platform.

Paid Upgrades is a superior app business model

Paid upgrades give the app developer the opportunity to continue to work on their app while making money from current loyal customers and new customers alike.  This is a sustainable business model.  It is also a business model that will create and maintain amazing apps.  So many developers have created great apps and made very good money, only to see the app become less and less updated over time leaving the customer with the same experience they had 5 years ago. 

A paid upgrade model will allow developers to build apps that they want in their heart to build, continue to improve that app, while having a revenue stream that supports the added development work.  This will result in apps that have longer shelf lives.  Imagine if this model existed and Marco Arment was still toying with Instapaper because their was a revenue stream that could sustain the business?  Developers like him and many others would continually improve and push the envelope of what their apps can do.  All this would cost the customer $3.99 a year, or every other year, or whenever the developer decided the upgrades to the app warranted an upgrade?  And if the customer didn't want to upgrade, that's fine, they can stay with an older version.   

I would like to see Apple adopt this model.  I know app developers have been begging for years, but I am an app consumer that is now begging.  I don't want amazing, innovative apps to go away.  I want apps where developers spend many hours toying with the customer experience until it is just right.  Where they obsess over every little detail because they know their most loyal customers will remain loyal because of that obsession.  Where they create the next "pull to refresh" because they know there is a better way.  

I don't want to live within a platform where the developers don't improve upon their original design because it is not worth the effort from a revenue perspective.  Please Apple, just for us app consumers.

Gartner Predicts Three Big Data Trends for Business Intelligence

Always good to see what the researchers are predicting for the future.  This is an interesting take on big data.  It focuses on an outcome of big data and then from a business perspective, what will happen to big data.

No. 1: By 2020, information will be used to reinvent, digitalize or eliminate 80% of business processes and products from a decade earlier.

Very interesting.  Most successful products take a human process and automates the process to increase efficiency.  I'm sure this prediction is a slam dunk as businesses will use massive data to help enhance current products and processes.

No. 2: By 2017, more than 30% of enterprise access to broadly based big data will be via intermediary data broker services, serving context to business decisions.

This is another no brainer.  As companies like Experian and Acxiom make it easier to access their data, more and more companies will begin utilizing this data to make better decisions about their customers.  This is something that I believe in greatly.  The more data to enhance marketing campaigns, the better equipped marketers are to change the behaviors of their most valuable, or better yet, their most potentially valuable customers.  

No. 3 By 2017, more than 20% of customer-facing analytic deployments will provide product tracking information leveraging the IoT.

The Internet of Things will be very interesting when it comes to data.  How companies use data about customers behaviors in their own house with the items they use will be a touchy topic in the coming years.  If companies can prove they are using the data to make the customers lives better, it will be a smash hit.  If they are becoming creepy with the data, then the IofT will never reach its full potential.  

Additional Thoughts on Twitter

A comment from John Dexter had me thinking even more about the Twitter problem.  I think it is clear to me, more than ever, that owning the platform is more important than owning the interaction when it comes to Twitter.  

In 2012 Twitter decided it was going to be an app company instead of a platform company.  They blew off their third-party developers in hopes to bring all of the eyeballs from the Twitter stream/firehose into their own app and webpage to monetize with advertising.  This essentially laid the groundwork for Twitter not owning just the platform, but owning the entire experience.  In the case of Apple and Facebook, this is good because it is their core competency to own all the widgets.  When looking at Twitter, a big reason they are where they are today is because of innovations by third-parties.  They would not be in mobile if it wasn't for other developers getting there first.  All of the app innovations have been made by third-party developers, so much so that Twitter had to purchase one of them to catch up.

Twitter should take a step back and develop the platform to generate revenue.  If agreements were laid out to developers allowing them to get a piece of the ad revenue generated through their apps, they would be great partners in pushing the ads in new and intuitive ways.  Twitter can then focus on knowing the Twitter customer, the logged in user, better than Facebook knows their customers.  I believe Twitter has an advantage because they know peoples interests better. The people I follow on Twitter align more to my interests than the people am "friends" with on Facebook.  Facebook tends to focus more on real-world relationships and the close knit social graph.  

Once Twitter can repair the relationships with third party developers and focus on developing the platform to maximize ad placement, they don't have to worry about innovating apps that sit on top of that platform, which they are not particularly good at doing anyway.  This model would bring the most app innovation, while at the same time, allow Twitter to focus on revenue generation for the platform.  The third-party developers would have to share all the data back  and then Twitter can be the master of the customer, which is where the ad revenue will come from.  Focus on being able to deliver the best ad to people consuming the stream.  

Does Twitter Need A New CEO?

Twitter is all over the news after its big misses in Monthly Active Users (MAU) and Revenue.  While this is not a good sign for Twitter, does it really need a new CEO and a revamp of their leadership?  In todays article on Stratechery, Ben Thompson outlines his case for new leadership in the ranks, and I don't disagree with his sentiments.

TWITTER’S FUNDAMENTAL PROBLEM

Twitter’s fundamental problem is that their active user growth is simply too small given their current size. Twitter yesterday reported the service had 302 million Monthly Active Users (MAUs), an increase of only 18% year-over-year and 5% quarter-over-quarter (and the company said the current quarter would be worse!). This is a fraction of Facebook, half of Facebook Messenger, fewer than Instagram and not that much bigger than SnapChat; presuming the latter service passes Twitter later this year, Twitter will be only the 5th most popular U.S.-based social networking service looking to monetize through advertising. This distinction — which excludes WhatsApp, at least for now — is a critical one, because the issue with advertisers is most don’t have the time or ability to work with multiple services; it’s likely most digital advertising spending (which I believe is set to expand greatly) will be consolidated onto the biggest networks (along with Google’s properties), with Facebook taking the lion’s share. Were that to happen, it’s easy to see Twitter as the odd network out.2

302 million MAU's is a lot of people, yet it's too small for advertising?  I agree with Thompson here.  Even though I have said before Twitter has enough users to monetize efficiently, they are being dominated by other networks when it comes to size and reach for advertisers.  Without the reach, advertisers will not use Twitter in their bag of tricks, they will opt for the platforms that give them the most return for their time and money.  

This is where I believe the argument for new leadership is warranted.  They need the reach because they are trying to play the same game as all of the other social networks.  The game is garner the most active users and create the reach that advertisers will jump all over.  What if that is not the game Twitter should be playing?  When in a position of weakness, which Twitter clearly seems to be in at this point, the strategy has to change.  By following the lead of Facebook and the like, Twitter can't win.  Facebook will always win in this scenario.  Facebook as the leader can follow competitors, because they are the biggest.   Facebook's competition has to find a different strategy to make the most profit in the social arena.

Instead, Twitter should redouble its efforts to acquire new users even as it redefines what Twitter the company is all about. I wrote about this in What Twitter Might Have Been: 

Alternatively, Twitter could empower third-party developers to build these sorts of applications that feed back information into the Twitter interest graph. An application like Nuzzel, for example, which uses your Twitter graph to create a news app, has much more of a one-way relationship with the social network: Nuzzel is getting all the benefit, and not sending much information back to Twitter. Twitter would be better off retooling their API and developer agreements to ensure they are learning from every application they interact with, and in return sharing their graph along with advertising in the form of their MoPub or Namo Media-derived offerings. The advantage of this approach is that the imagination and ingenuity of a massive developer ecosystem will always be far faster and more innovative than anything any one company can do on its own — just ask Apple.

I really like this strategy.  Third party developers are what made Twitter in the first place.  The firehose which is Twitter is better served as a platform for news and advertising that any third party can reach into and intake.  They just have to intake the advertising to be a part of the program.  I use Tweetbot and I don't see a single ad.  This should never happen for a company like Twitter.  Tweetbot, for the right to make a living off of the Twitter platform, should be required to show me advertising.  

My issue with Twitter is the firehose.  When you start to follow enough people, it is too hard to keep up with everything you want.  Facebook uses their algorithm to eliminate this phenomena, yet it does so in a way that doesn't create a bad experience for the user.  In fact, the user experience is greater because over time the user will see what they want as Facebook learns.  Third Party apps could do wonders with the firehose.  There would be so much innovation with the Twitter platform if Twitter embraced their third party partners.  This I believe would triple the MAU's for Twitter as the third party innovations would bring different ways to interact with the Twitter firehose.

Twitter also needs to eliminate partners that don't provide it with as much value as they provide.  When Steve Jobs took over he killed many projects and I believe Twitter cannot let other parties use their social graph for nothing in return.  There needs to be an ad platform that is established for this right.  When a partner uses the social graph, they have to use the Twitter ad platform.  

TWITTER’S ABANDONED USERS

The trouble for Twitter is that awareness of the service has long outstripped its usability. And yet, despite the fact that Twitter has struggled with new user growth for years, almost nothing was done to improve the product or on-boarding experience until just the last few months, when the company finally rolled out a new logged-out page meant to entice people with Twitter’s content, as well as an instant timeline that helped people get started. Unfortunately, both efforts seem to be too little too late: Twitter admitted on the earnings call that neither improvement had increased retention.

This isn’t a surprise: Business Insider reported last year that Twitter likely had 697 million abandoned accounts (and that number, presuming it was correct, has certainly grown). The problem is that those 697 million users, having already decided that Twitter isn’t a useful service for them, are much less likely to even experience things like the new logged-out page or instant timeline, even though Twitter @-handles and hashtags continue to be plastered all over TV and the web.

The focus should not be on finding new users to the service.  If these numbers above are correct, it is much easier to communicate and bring back these users ten it is to constantly find new users.  Any new users at this point would be low margin for Twitter at this point anyway.  They are more than likely new to the web, in emerging markets that don't have the income compared to the 697 million users that have already used the platform.

While inactive campaigns are very hard, it is essential to get these inactive users back on the site.  Step one is to find out why they abandoned.  Is there a common theme from inactive users that can be fixed by Twitter or a third party?  Next step is to get the word out on changes.  Twitter needs to jump at making changes to accommodate the inactive users and then let the inactive base know.  They have the emails from all of these users already, unless they spammed them endlessly and they have unsubscribed.  Email is a great tool and Twitter uses it poorly in keeping users active and getting return business.  

While I agree with Thompson that these changes aren't impossible to implement, the current team seems to be focusing on making Twitter, Facebook.  For that reason alone I would let them go.  Twitter should focus on service the customers that it has and providing an ad network that targets users so specifically the returns for advertisers is more compelling than the other networks.  Then the MAU problem goes away.  Easier said than done I know, but they have all the data and information to do it.  Plus they have the platform already built.    

Big Data: How Netflix Uses It to Drive Business Success

Bernard Marr writes how Netflix uses data to fuel their business:

Netflix is said to account for one third of peak-time internet traffic in the US. Last year it announced that it had signed up 50 million subscribers around the world. Data from all of them is collected and monitored in an attempt to understand our viewing habits. But its data isn’t just “big” in the literal sense. It is the combination of this data with cutting edge analytical techniques that makes Netflix a true Big Data company.

Netflix is a fascinating company.  They were able to build a business model that put a giant industry, retail movie rentals, out of business and then pivot to streaming before being out innovated by other companies.  They are constantly ahead of the curve when it comes to recognizing the next new technology and digital strategy.  They recognized early that original content was also a key to success, so they are pivoting into becoming greater than HBO at their own game.

More recently, Netflix has moved towards positioning itself as a content creator, not just a distribution method for movie studios and other networks. Its strategy here has also been firmly driven by its data – which showed that its subscribers had a voracious appetite for content directed by David Fincher and starring Kevin Spacey. After outbidding networks including HBO and ABC for the rights to House of Cards, it was so confident that it fitted its predictive model for the “perfect TV show” that is bucked convention of producing a pilot, and immediately commissioned two seasons comprising of 26 episodes.

This is how data-driven organizations behave.  They look at their customers and use data to determine the optimal next move.  All their strategy and tactics are based on using what they know about their customers and what they will do.  So many times organizations are obsessed with what other companies are doing, regardless of what their data is telling them.  They will copy their competitors for fear they are missing out on opportunities.  

The question I always ask is, "how do you know what the other guys are doing is working?"  What you see as a threat, may be a disaster because they haven't set up the correct means to measure the performance or are looking at the wrong KPI's.  Worse yet, they may be attracting an entirely different customer than what you are trying to target.  

A data-driven organization looks at their data and reacts.  Netflix, I am assuming, saw that many of their users were binge watching TV series as soon as they came out.  I'm sure this started with Breaking Bad, Mad Men, great content.  They saw an opportunity to create this content on there own as the majority of the time spent on Netflix is binge watching TV.  They looked at their own data and saw the opportunity to increase time on Netflix and add subscriptions by creating content.  But not just any ole content.  They had the data which showed what their customers loved watching and what resonated with them.  They were able to see what shows were being dropped off of the binge halfway through.  They saw what types of shows were most addictive.  

The content creators gave their biggest competitor the keys to the kingdom, data.  Now Netflix is poised to put a lot of the content creators out of business because they know way more about their customers behaviors than the content creators know.  Because Netflix controls the entire experience, from creation, to delivery, to analyzing the behavior, they can create superior content.  It is a model that is brilliant.  Netflix will continue to dominate, especially in the age where people are looking to become "cord-cutters".  I believe we will see even better content coming out of Netflix in the near future as they learn even more about what we like to watch.

Turn Your Data Into Smart Data

Great insights from Scott Houchin regarding data.

To harness and convert data into stronger business strategies and overall profitability, approach data practices with a holistic integration of people, process and technology, following three key steps: collection, strategy and alignment.

A data strategy is the first step in becoming a data-driven organization.  Setting up the structure and expertise of the organization has to start before jumping into data strategies.  This can happen outside of the confines of IT.  The business leaders should own the data, as long as they have the expertise and knowledge to do so.  Try to set up procedures to be agile with your processes.  The longer it takes to implement changes in data, the less of a competitive advantage your organization has.  It will also be near impossible to become data-driven if there is a constant wait for data to be delivered to the end users.

Collection

Start with a clear understanding of project goals and requirements to guide the collection process. Establishing this helps ensure data collected is “smart” or meaningful. Collection shouldn’t narrowly focus on new data. Many organizations already have a goldmine of owned data that should be tapped. To make the most of historical data, scan legacy systems, such as social pages or purchase history, map findings back to strict uniform terminology, and fill in the gaps where data is missing across the organization.

Having a process for collecting new data and examining historical data up front ensures quick and accurate collection, minimizing time spent on governance practices and carving down unnecessary data sets.

There is a treasure trove of data already being collected in most organizations.  Ensure that this data is being properly collected and stored.  The goal is to ensure as many people can get to the data as possible, data democratization.  If data is stored and is hard to get to, takes complicated joins and there are no tools available to the organization to easily access the data, then more has to be done to reach these goals.

Strategy

Once data is collected, work with data-marketing specialists to analyze and align functional uses and marketing’s business goals. This requires a team of analysts and strategists who have both high levels of industry and domain expertise to identify sources, manage collection and road-map operations processes.

Teams of analysts can help organizations identify, collect and integrate data from sources and channels, like web traffic, Facebook, Salesforce, etc., into a proprietary database. Once established on a datamart, it can be integrated into current campaign tools through human labor. Having this data integrated into marketing tools gives brand-side marketers the insights to improve customer experiences, measure performance of digital assets, predict customer decision stages, etc.

Data should not be financial focused, it should be customer focused for the greatest impact on ROI.  Marketers have to own their data.  Hiring analysts and data domain expertise is imperative for success.  If ownership lies outside of the marketing resources, there is a much higher likelihood of failure.  Remember, CMO's and CIO's don't speak the same language.  

Alignment

Another example can be demonstrated with IT and marketing. Marketers spend more on technology than some IT departments now, but need alignment to ensure data is stored, platforms are integrated and in-house technical support is available. Alignment between these two departments appeases both marketer’s need for autonomy and IT’s domain over platforms, allowing for the integration of datamarts into other units’ datasets from the onset.

IT is still very critical for success with this strategy.  Just because IT does not own the data, doesn't mean they aren't extremely important.  IT needs to ensure the network is working, data is flowing and collection tools are working.  They also need to be support for when things break and they should control the access to the systems.  Make sure IT understands the goals and agree on the toolsets being chosen, so they can support them.  

To Benefit From Big Data, Resist The Three False Promises

From Forbes.com:

Gartner recently predicted that “through 2017, 60% of big data projects will fail to go beyond piloting and experimentation and will be abandoned.” This reflects the difficulty of generating value from existing customer, operational and service data, let alone the reams of unstructured internal and external data generated from social media, mobile devices and online activity.

Yet some leading users of big data have managed to create data-driven business models that win in the marketplace. Auto insurer Progressive PGR -1.22%, for instance, uses plug-in devices to track driver behavior. Progressive mines the data to micro-target its customer base and determine pricing in real time. Capital One, the financial services company, relies heavily on advanced analytics to shape its customer risk scoring and loyalty and offer optimization initiatives. It exploits multiple types of customer data, including advanced text and voice analytics.

I believe what most people miss when they hear these success stories is the amount of human capital that gets thrown at these problems.  Hundreds of data scientists create thousands of models, of which very few are actually incorporated into final production.  The reason the Gartner stats ring true is most companies don't have the kind of resources to throw at the problem and most companies won't realize an ROI even if they could throw these types of resources at a problem.

Promise 1: The technology will identify business opportunities all by itself.

This is the direction the technology is moving towards, but it is not there yet.  The technology enables a group of data scientists to identify the opportunities, it's not magic.

Promise 2: Harvesting more data will automatically generate more value. 

The temptation to acquire and mine new data sets has intensified, yet many large organizations are already drowning in data, much of it held in silos where it cannot easily be accessed, organized, linked or interrogated.

More data does not mean better ROI on your initiatives.  In fact, most companies don't take advantage of the data they already have to generate the maximum ROI.  I always use a rule of thumb when purchasing new technology.  If as an organization you don't believe you are already using the technology you currently posses to its fullest, then its not time to move on to something better.  Your current technology should be preventing you from innovating, if its not then you either have the wrong technology or the wrong people.

Promise 3: Good data scientists will find value for you. 

To profit consistently from big data, you need an operating model that deploys advanced analytics in a repeatable manner. And that involves many more people than data scientists.

Remember, data + insight = action.  Actionable data is a combination or art and science.  data scientists provide the science, however you need the team with the business acumen to provide the insight, this is the art.  Data scientists will create a lot of questions that you never thought to ask of your data, but they cannot provide a solution in and of themselves.  

Remember to walk before you run when it comes to data initiatives.  It's always good to have a goal of using "big data" to improve your business and create ROI from where it didn't previously exist, however the journey to "big data" is more important.  These examples of success with "big data" did not happen over night.  They happened because advanced companies were butting up against the limits of their current technology and they were ready to take the next step.  

Is Loyalty Boring Customers?

Found an interesting article from September 2014 from Caroline Papadatos which discusses the gamification of loyalty programs.  It really gets the mind going, because I think the gasification side is not data driven enough and the opposite is true from the data side.

A few weeks ago, I had the privilege of judging the 2014 LoyaltyGames, an incredible week-long global challenge involving 1,500 practitioners and students from 102 countries, with 15 judges who were remarkably, never in the same room nor on the same continent.

The 2014 contest had three components: awareness building, game design and loyalty building.  The game experiences were clever and fun, and I was won over by the sheer creative genius of the contest submissions. The loyalty component was straightforward: reward and recognize customer / donor tiers without breaking the bank. With a gamification spin, it meant solving a conventional customer engagement problem with an unconventional tool set. Sounds simple enough, but as I scanned case submissions looking for earn ratios and attainability models, all I could find were badges, likes, certificates and pins.

It is fascinating how much badges and pins can get people excited.  The basis of these games has a lot of merit, but what I have a problem with is the same with social media as a channel, it is not targeted at all.  There's no meat behind the game.

My answer came from Gabe Zichermann who in a recent eight-part gamification series in COLLOQUY Magazine makes the bold statement that “loyalty isn’t fun enough anymore” and our customers are bored. Gabe clearly has a point – loyalty now competes for attention in a world where Angry Birds has been downloaded two billion times. It gets worse. At the LoyaltyGames award ceremony, a renowned gamification expert accused loyalty programs of “bribing” their customers. Now my back is up, but are we outraged or outdated? 

The truth is that loyalty programs need a shot in the arm, and while experience design always has a place in the loyalty tool set, few data practitioners are charming or entertaining. And gaming is not just for Millennials. The average social gamer is a 43-year-old-woman, which just happens to be the primary target market for grocers, drugstores and a host of other retailers. So why aren’t loyalty practitioners flocking to gaming? 

I totally agree, loyalty programs need a shot in the arm.  As I have written before, most people engaging with loyalty programs are just taking the free stuff, theres very little loyalty or behavior being driven from them.  It is fascinating to combine the rich data from the loyalty programs to the fun concepts in gamification to create a targeted loyalty gamification model.  I think this would work extremely well.

I could imagine a program where certain behaviors are awarded more points and a bounce back offer could include multiple point thresholds for buying everything in a market basket analysis.  So if the customer who usually buys a TV also buys cables, programmable remotes and a blue-ray player, the customer will get multipliers if these are purchased in the next 2 months.  This gives some fun to the loyalty program, while driving the behavior to purchase items that are typically purchased with TV's.  The best of both worlds.

There’s no doubt that loyalty programs lose their luster when they became overly programmatic, but where gaming meets transactional data analysis and customer behavior change, there are notable exceptions. BrandLoyalty’s Instant Loyalty Programs in Europe, Asia and South America have a huge fun-factor for retail shoppers – on the surface they’re a widely popular collectible game for children but there is a financial underpinning that drives incremental spend, participation and superior financial performance based on maximum turnover & transactions from family households.

Whether you’re pro-loyalty or gamification, you can certainly agree with Gabe on this: “taking something that’s crummy and putting some game frosting on it won’t magically change your customer”. But let’s face it, the mix of gaming techniques and data-driven loyalty can only be good for business. And be honest, if you were given the choice of getting on a plane for yet another industry slideshow or signing up for a multi-player gaming challenge, which would you choose?

Perfect combination, a shot in the arm.  The technology exists, lets gamify our programs.  This is what I have been harping on about for a month.  These are the types of things that create great customer experiences.    

The Messy Business of Reinventing Happiness - Fast Company

Austin Carr wrote a fascinating piece in Fast Company about the behind the scenes struggles to implement Disney's MagicBand at Disney World.  It details the infighting and politics at one of the most revered brands in the world.  The MagicBand is a new innovation to Disney Theme Parks (only at the Orlando Disney World Theme Park at this time) which brings NFC technology to life in a 40 year old product.  The ideas behind the MagicBand were well thought out and they were trying to solve real problems at Disney World, but they couldn't deliver on the entire dream and it proves that Customer Experience is a cultural change more than an initiative which I have been writing about for a few weeks now.  

The article is very in depth and I think points out a few mistakes in launching an initiative this grandiose.  The main point it proves is how hard it is to change a culture when it comes to customer experience, because so many people in the organization want to eep their points of power rather than thinking of the customer.  It is human nature to be scared of technology that may serve the customer better, it puts people in a defensive mode.  Even when a company as big as Disney commits $1 Billion to the initiative, without the cultural change it makes it near impossible to create magic.

Dream Big, Implement in Stages

The dream was large for the Next Generation Experience (NGE) team at Disney.  They wanted to solve the real world problems that were influencing customer satisfaction at the park.  Long lines, juggling multiple pieces of paper and keys were bringing down an experience that is supposed to be one of enjoyment.  One of the main issues is they were trying to bite off more than they could chew with their implementation.  At one point they were trying to change the airport arrival and had meetings with TSA on airport security procedures.  I understand controlling the entire experience, something Steve Jobs has taught all of us, but at some point these types of distractions take away from the big picture, which is implementing and iterating.  

The biggest problems Disney was trying to solve was long lines and handling of multiple items (tickets, Fast Pass tickets, money, hotel room keys, etc.).  The team was 2 years late delivering on their initiative because they forgot what the main goal of the project was.  The team was distracted with all the technology could do, instead of solving the immediate problems and then iterating on the technology to enhance other experiences.  Always handle the low hanging fruit first, then iterate to enhance the next set of opportunities.  

Keep the Team Small for as Long as Possible

Once the team grows to include more people to implement, projects start spinning out of control.  Change is very hard for people and they will fight it especially when it comes to areas they control within an organization.  Because the plan was growing larger than solving the immediate problems, more people from the organization had to be brought in which slowed the project down to a crawl.  The leaders of the areas being affected wanted control and they wanted a say in the development of the technology.  Embrace the leaders of the areas that will be affected and make sure they are represented on the early small team.  If they embrace the change and feel they had a part in the development, they will get the troops aligned once implantation begins.

Clearly Articulate Goals

The goals of the initiative in my eyes were to enhance the customer experience at the theme park.  What happens in these large initiatives is the organization gets hung up on the technology instead of what the technology is trying to help solve.  Technology in and of itself is worthless, unless used for a purpose to solve a real world problem that cannot be solved another way more efficiently.  NFC technology in a bracelet does not solve any problems by itself, it is the implantation of this technology that is the magic.  Always keep the goals, which is enhancing the customer experience in this case, front and center.  Never start from the technology and work backwards, start from the problem and work forward to how the technology can help solve the problem.

I am fascinated how organizations behave.  Each culture is very different, but they all tend to have the same issues.  The bigger the organization becomes, the harder it is to accomplish innovative change.  Politics and human ego can be the death of innovation.  The Disney project succeeded through sheer will to get it done, but proves that even throwing money at something doesn't guarantee success.  The culture of the company has to be customer-centric before it can solve the problems of the customer.   

Two Major Marketing Automation Myths

By Mat Sweezey:

Marketing Automation is Only for Marketing -- FALSE

Really I care about the second myth.  In my last position, we used our marketing automation tool for so much more than marketing.  Marketing automation tools can create business workflows and email tasks to operations folks.  We also used it in terms of creating better customer service, to alert of a customer service issue and email the best solution to the problem.  Marketing automation tools from a high level take data and triggers and provide an output.  There are numerous opportunities to enhance workflows with your automation tool.

Great Brand Apps Create Loyal Happy Customers

Mobile apps are the way we will interact with all of our loyalty programs in the digital age.  Smartphone apps can do so much more than a piece of plastic or punchcard could have ever imagined, yet so many companies have built half-baked, poorly thought out attempts at creating a customer experience.  But the good news is there are some leaders that are nailing it.

The 4 qualities a mobile app should possess are:

A mechanism to capture transactions 

At the heart of the mobile experience should be the mechanism to capture data about the customer.  This data should feed into the loyalty program of the brand.  This should come in the form of transactional, interests, surveys and geo location data.  Data is the building block for a loyalty program to succeed.  

Frictionless transactions

A mobile app has the ability to eliminate the frictions of the transaction.  For example, at an Apple Store the customer can enter the store, open the app, scan the item they would like to purchase and then leave the store, all without having to interact with a human or wait in line.  That is eliminating friction.

A mechanism to communicate with your customers

Mobile is a channel.  It is perhaps the most important channel in the new digital marketing era.  The phone is always on your customers body and that will soon include wearables.  The ability to push messages to your customers through this channel is extremely important.  The ability for your customer to open the app and see their loyalty program details makes communicating with your customer more personal than ever before.  This includes beacon support to guide the customer through the offline experience as well.  This should be the channel that receives the most focus in the coming years.

An engaging experience without a transaction

Mobile apps hold a space on the customers phone.  If you make your app engaging, even when the customer is not making a transaction with you, you may keep a good position on the phone.  Think of it as search rankings, the more prominent position, the more engagement with your brand.  Get stuck in a folder on the third page, you will only be utilized as a mechanism for transactions which is not the worst thing in the world, but doesn't drive behavior. 

Starbucks has been on the forefront in the mobile app space since it introduced its mobile app in 2011.  Starbucks took the approach of creating an app that engages customers when not in a Starbucks, along with making the transaction process frictionless.  Starbucks has long partnered with Apple by giving away free music and apps, but they also moved this functionality to the app.  By doing this, Starbucks has been able to engage their customers with their application outside of the brick and mortar stores.  I consistently look at my badges from Starbucks to see what free apps or music they are giving away this week.  Most of the time I don't get the freebies because they are not to my liking, but every once in awhile I do.  But it also has trained me to constantly go to the app.  I check my points and how far away I am for a free award and I am not even a big free award kind of a guy.

Starbucks has also made a frictionless payment process that also tracks my behavior.  I always received gift cards from Starbucks and had them strewn all over the place.  Some made it to the wallet, some were in drawers, but they were never consolidated.  Starbucks also had a loyalty program that was tied into a gift card, but it was confusing on how to interact with the program when I wasn't using that particular gift card.  Plus having to manually add money to the specific gift card was far from frictionless.  So I never really used the loyalty program and I was going to Starbucks less.  The app has removed all of this friction.  It is easy to transfer gift card money to the main loyalty account, which was a main pain point for me.  It also allowed for easy addition of funds into the card through the app.  These two items made using the program much easier.  

The other app that I have been very impressed with is the Chipotle app.  This app is a little different from the Starbucks app because it is just solving one problem, waiting in line.  The app allows you to place a Chipotle order and skip the line to pick it up at a designated time.  Now I don't know if any of you have been in a Chipotle and have to wait in the line to order, but it could be a fifteen minute exercise in browsing Twitter.  The app saves your favorites and recents so it takes approximately 20 seconds to place an order.  Pay online, just walk to the cashier and they hand you your bag of goodness and you are off.  Simple, frictionless and awesome.   

Improvements can be made in both of these apps to include more of the 4 qualities.  The Starbucks app nails 3 out of the 4, but can do a better job at using the app as a personal, targeted channel.  Right now the offers they have are not very tailored to my experience.  This is a big opportunity to make the app even more engaging.  For Chipotle, they only possess 1 out of the 4.  They might be monitoring my transactions, but they don't have a loyalty program tied to the app, so I am not sure.  The app is a great start, but they could hit a home run with the addition of some functionality.  Either way, I will still use it weekly to avoid the lines.

If Algorithms Know All, How Much Should Humans Help? - NYTimes.com

Steve Lohr writes for NYTimes.com:

Armies of the finest minds in computer science have dedicated themselves to improving the odds of making a sale. The Internet-era abundance of data and clever software has opened the door to tailored marketing, targeted advertising and personalized product recommendations.

Shake your head if you like, but that’s no small thing. Just look at the technology-driven shake-up in the advertising, media and retail industries.

This automated decision-making is designed to take the human out of the equation, but it is an all-too-human impulse to want someone looking over the result spewed out of the computer. Many data quants see marketing as a low-risk — and, yes, lucrative — petri dish in which to hone the tools of an emerging science. “What happens if my algorithm is wrong? Someone sees the wrong ad,” said Claudia Perlich, a data scientist who works for an ad-targeting start-up. “What’s the harm? It’s not a false positive for breast cancer.”

I have written here many times of analytics being a combination of "art" and "science".  Having data and insight leads to the most action, yet some data scientists want to remove the "art" part of the equation.  The belief is that computers and algorithms can see more about the data and the behavior than a human ever could.  Also, once there is so much data about an individuals behavior, there is no "art" left, all the data points are accounted for so the "science" is indisputable.  

However, I have a hard time believing that "art", or the human insight, will ever be replaceable.  There are so many variables still left unknown and a computer can't know all of them.  The "science" portion will always get better at explaining the "what" happened, but they don't understand the business operations and strategy that goes behind the decisions that were made. I am a true believer in the "big data" coming of age.  I believe it is fundamentally changing the way companies have to do business, but never forget about the human side, the "art" of understanding "why" the data is telling you "what" is happening.  

These questions are spurring a branch of academic study known as algorithmic accountability. Public interest and civil rights organizations are scrutinizing the implications of data science, both the pitfalls and the potential. In the foreword to a report last September, “Civil Rights, Big Data and Our Algorithmic Future,” Wade Henderson, president of The Leadership Conference on Civil and Human Rights, wrote, “Big data can and should bring greater safety, economic opportunity and convenience to all people.”

Take consumer lending, a market with several big data start-ups. Its methods amount to a digital-age twist on the most basic tenet of banking: Know your customer. By harvesting data sources like social network connections, or even by looking at how an applicant fills out online forms, the new data lenders say they can know borrowers as never before, and more accurately predict whether they will repay than they could have by simply looking at a person’s credit history.

The promise is more efficient loan underwriting and pricing, saving millions of people billions of dollars. But big data lending depends on software algorithms poring through mountains of data, learning as they go. It is a highly complex, automated system — and even enthusiasts have qualms.

“A decision is made about you, and you have no idea why it was done,” said Rajeev Date, an investor in data-science lenders and a former deputy director of Consumer Financial Protection Bureau. “That is disquieting.”

Blackbox algorithms have always been troubling for the majority of individuals, even for the smartest of executives when trying to understand their business.  Humans need to see why.  There is a reason why Decision Trees are the most popular of the data models, even though they inherently have less predictive prowess than their counterparts like Neural Networks.

Decision Trees output a result that a human can interpret.  It is a road map to the reason why the prediction was made.  This makes us humans feel comfortable.  We can tell story around the data that explains what is happening.  With a blackbox algorithm, we have to trust that what is going on inside is correct.  We do have the results to measure against, but as these algorithms become more commonplace, it will be imperative that humans can trust the algorithms.  In the above bank loan example, when making decisions regarding bank loans, a human needs to understand why they are being denied and what actions they can take to secure the loan in the future.  

This ties into creating superior customer experiences.  Companies that will be able to harness "big data" and blackbox algorithms and create simple narratives for customers to understand will have a significant competitive advantage.  Creating algorithms to maximize profits is a very businesslike approach, but what gets left out is the customer experience.  What will happen over time is the customer will dislike the lack of knowledge and communication and they will not become future customers.  A bank may say, this is good, they would have defaulted anyway.  But what happens in the future when too many people have bad customer experiences?  I don't believe that is a good longterm strategy.  

In a sense, a math model is the equivalent of a metaphor, a descriptive simplification. It usefully distills, but it also somewhat distorts. So at times, a human helper can provide that dose of nuanced data that escapes the algorithmic automaton. “Often, the two can be way better than the algorithm alone,” Mr. King said.  

Businesses need to also focus on the human side.  When we forget there is also an "art" to enhance all of these great algorithms, businesses will be too focused on transaction efficiency instead of customer experiences which in turn will lead to lower sales.  

Across The Board, CMOs Struggling To Deliver An Integrated Customer Experience

Daniel Newman writes for Forbes:

Back in January of this year in an article entitled Are CMOs Poised To Take Over Technology Purchasing? I wrote that “Whether they (CMOs) are ready or not, technology is fast becoming an inextricable part of the CMO’s functions, and they need to participate in making tech decisions in order to determine the ROI for purchases.”

Based upon the results of a recently released study from The CMO Club and Oracle Marketing Cloud a great number of CMOs are indeed not ready to utilize the technology that is available to them as a means to deliver upon long sought after integrated customer experience.

The days of a CMO not being technology savvy are over.  CMO's need to understand technology as well as they do brand.  The tools being developed in the marketing cloud space are very compelling, but they are nascent, so the demands to implement are greater than they will be 5 years from now.  Implementing technology toolsets are not for the faint of heart and the better the CMO understands the toolsets, the faster to market.  

CMO's should be data savvy.  They should understand where the data lives, how it flows and what the data is telling them about the customer.  It all starts with the data.  

Be the customer champion every step of the way: CMOs need a clear understanding of how customers and prospects interact with their brands at every stage, from consideration, to engagement, to purchase and advocacy. They are the voice of the customer, translating insights to actions across every organizational function.

This was a big focus of Adobe Marketing Cloud Summit 2015.  Their tagline "Marketing beyond Marketing", which didn't resonate as much as they hoped, is what the customer experience is all about.  Marketing has to be involved with all touchpoint throughout the organizations.  This involves operations units which have not been a priority for marketing in the past.  

Become BFFs with your CIO: Of those surveyed, only one of 110 respondents referenced a positive relationship with their CIO. A critical action item for a CMO is to reach out to their CIO to collaborate, plan, and integrate activities.

This may be easier said than done.  Most CIO's and CMO's do not speak the same language.  If a CMO is technologically savvy, it will be easier to communicate with the CIO to create the technology roadmap for the customer experience.  The scary part of this is only 1 out 110 CMO's surveyed have a positive relationship with their CIO.  Either the CMO has to move toward technology or the CIO has to move towards marketing.  I prefer the former.  

Co-design the optimal customer-driven technology roadmap: CMOs need to develop an understanding of the technology that is required to deliver the optimal customer experience and co-design the technology roadmap with the CIO, allowing flexibility in design to incorporate new technology and third party applications.

Again, this becomes impossible if the CMO and CIO are not in sync.  Both sides have to respect each other for the relationship to become collaborative and if the CMO is not also a technologist, the chances of this item happening are slim.  

Rethink your marketing organization and processes: There are many formal and informal opportunities to create collaboration across marketing departments and technology. As critical as it is to building the right culture and cross-functional environment, it’s also critical to hire the right talent.

As I wrote in Agile is the Key to Digital Marketing Success, the structure of the marketing organization needs to be changed.  Marketing organizations need to include technology resources in order to be agile in the digital marketing age.  Developing a technology culture within the marketing organization is a main component for delivering great customer experiences.

Establish a system for continuous improvement: The customer is outpacing companies in terms of their expectations for personalized service compared to a company’s ability to act on the information – both technologically and analytically. The CMO of today must – in addition to being agile – be open to taking chances and remain risk receptive.

If you're not failing you're not trying.  Marketing is a living breathing entity, especially in the digital age.  There will never be a time when a marketing organization can implement a plan and then check it off the list.  CMO's need to have their fingers on the pulse of society and the technology that customers are moving towards.  Just when a company has implanted their mobile strategy, here comes the watch and the Internet of Things that may change the way marketers have to think.  Having a technologist as the CMO will increase the chances that the organization will stay in touch with the customers, no matter where they move to next.

Meerkat is dying – and it’s taking U.S. tech journalism with it

About three days after it received a lavish new funding round, Meerkat died an ugly and embarrassing death. It is hard to decide whether the Great Meerkat Debacle that has unfolded over the past week is a tragedy or a comedy — probably a bit of both.

The mobile streaming app that had whipped U.S. tech journalists into a frenzy announced $14 million in new funding on Thursday. Money poured in from Jared Leto, Greylock Partners and other illustrious sources. On the same day, Twitter launched its rival streaming app called Periscope. Apparently, investors didn’t stop to ponder why Meerkat people rushed to cash in so aggressively only a month after the app had debuted.

When there is talk about another tech bubble, this will be where they point to.  I won't say it's easy to get the attention of many with an app, but we have seen very little staying power with apps.  The demise of Zynga points to their premature purchasing of very basic games that didn't have long staying power.  Meerkat was popular for like a week.  I have been using Periscope for the last few days and it may take a lot more to keep the staying power.  Theres a lot of terrible content on the service.  Twitter will have to solve finding good content.  Otherwise this will be a fad and that will be too bad because I do think it has the opportunity to be amazing.

Managing Your Mission-Critical Knowledge - HBR

Martin Ihrig and Ian MacMillan for HBR:

Tantalizing as the promise of big data is, an undue focus on it may cause companies to neglect something even more important—the proper management of all their strategic knowledge assets: core competencies, areas of expertise, intellectual property, and deep pools of talent. We contend that in the absence of a clear understanding of the knowledge drivers of an organization’s success, the real value of big data will never materialize.

This continues to be a theme I am seeing with "big data" and I wrote about here.  This applies to "regular ole" data also, the key is to apply the knowledge and insight of the operation with the data to create actionable strategies and tactics.  Data analytics, big and small, is a combination of Art and Science.

This is a fascinating paper and one that I would recommend reading.  It attempts to identify company knowledge to find strengths and opportunities within that base.  It also attempts to spread that knowledge and expertise throughout the company to different divisions, which would assist on where to use that knowledge for the most profitable or strategic initiatives.  Very high level and difficult work, but very valuable.