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.

What does it mean to be a data-driven marketing success in 2015?

Ian Michiels writes for mycustomer.com:

Micro segmentation over 1:1 personalisation

Even when data is readily available to inform highly targeted engagement, someone actually has to produce the creative and copy to trigger the engagement.

I was on a panel at an Adobe event late last year when the topic of 1-to-1 marketing came up.  I have always been a huge advocate of trying to get as close as you can to 1-to-1 marketing, but that comes with a caveat.  The cost to get to the elusive everyone is individualized is massive.  When I say as close as you can, what I mean is start from the top of your customer list (not by alphabetical order, but by some worth and frequency or potential worth metric) and work as far down that list as you can to create 1-to-1 marketing for your best customers.  The other customers you want to have as many segments as makes sense, but always allow the data to drive those segmentation decisions,  

Automating up-sell and cross-sell campaigns

Marketing is the only function in the business that actively communicates across the entire spectrum of the customer lifecycle, from the inquiry to a loyal customer. That raises two very interesting questions that data-driven marketing has answers for:

• Should marketing own the customer lifecycle?

• How should marketing allocate time, budget, and effort across the customer lifecycle?

As I commented on recently in my article Retention is King, retention's the first place I start when implementing a marketing automation program.  The customer lifecycle should be owned by marketing.  Marketing has all the tools to automate the communications in the relationship and target based on behavioral and demographic data.  When it comes to the question of time allocation, make sure the retention programs are dialed in.  They will never be finished and you will always be tweaking, but then you can move on to acquisition and reactivation.  It is much easier to cross-sell or up-sell a loyal customer than it is to acquire a new one.

A/B testing on landing pages and email campaigns

According to the 2014 Gleanster Marketing Resource Management report, only 60% of small and mid-size firms conduct A/B tests on email, landing pages, and website properties. It’s actually shocking to learn how much you really don’t know about your customers when you run A/B tests on creative and copy.

In sales they say "ABC", Always Be Closing.  In marketing automation and data driven businesses we should say "ABT", Always Be Testing.  The caveat to this saying is there needs to be an understanding of a baseline first.  So if you are implementing a new program, let it run for a bit (unless it is a total disaster), use analytics to look for opportunities and test those opportunities.  Don't just test for the sake of testing, always let the data drive the opportunities and then test the hypothesis.

Machine learning is your best friend

One consistent theme that keeps coming up in our advisory sessions is that marketers want help in data analysis. Thanks to advances in computing power, data analysis that previously took days can now be done in seconds and often in the cloud. Machine learning applies rules to data sets and looks for correlations between data. Does this do the job of a marketer? Heck no! What machine learning does for marketing is help isolate trends that should be investigated further. Marketers still need the context about customers and products to translate those correlations in the data into action.

As I said just above, let the data drive your testing.  Machine learning and data mining techniques can uncover insights within your data that the human eye could never perceive just by looking.  Many marketers want a predictive modeling tool to spit out an answer as to what they should do and just go do it.  If that were the case, why do we need the marketer?  It is important to make sure to understand what the outputs of these tools provide and test their findings.  Without the business acumen, the output could be very flawed.  Don't jump to a conclusion, use the insight to form hypothesis about your customers and test away.  Remember as I wrote before, Data + Insight = Action.

5 Mistakes You're Making That Are Killing Your Marketing Campaigns

In a past article from Juntae DeLane, he brings up very good succinct points about pitfalls of marketing campaigns.

1. Lack of Audience Understanding

Having a greater understanding of your audience should be the first step when developing a campaign strategy. Some entrepreneurs will produce evergreen campaigns with no specific targets hoping that new targets will emerge. Some may see a practical benefit in doing so; however, why run two campaigns to accomplish one task? Your marketing campaign will be optimized by doing research beforehand so you can make an impactful and relevant introduction to your brand.

The key to digital marketing is knowing your audience.  The more information you have about your customer the better and when using marketing automation tools, it is important to utilize this knowledge.  It is easy to lump as many individuals together and call them segments, however the more individualized your campaigns can become, the better experience the customer will have interacting with your brand or product.  

2. No Strategy

Many marketers get confused when talking about strategies and tactics.  A tactic is how you are going to do something, the strategy is what you are going to do.  They must work in tandem.  Many times marketers start with the tactics, "we are going to send an email to all of our customers who abandon a cart".  Why are you doing this?  You have to start with the strategy of "increase our sales from all parts of the funnel" to reach the tactic.  Otherwise, how do you know the goal?  The goal may be simplified in this case, but so many times a marketing plan is not strategic, it is a list of tactics the company is going to employ.  

Having an overarching strategy will help guide decision making.  Just because you can do something doesn't mean you should.  Focus is the key and understanding the strategy assists in that focus.  

3. Too Much Sales Pitch

I think another way to think about this is understand your customers are not stupid.  They know when they are seeing content from your company they are being sold something.  They want to understand why they need something, how will this make my life better, will I feel satisfaction with this purchase.  By trying to convince them to buy leads to buyers remorse.  The ultimate goal is to create loyal customers that will return again and again to purchase. 

4. No Tracking or Data

With all the tracking services out there, you should be able to easily track your campaign efficacy. From Google Analytics to KISS Metrics you can establish a tracking dashboard at virtually no cost.

However, what will kill your marketing campaign is if you identify the incorrect metrics.

I don't see this too much, most everyone is tracking some kind of performance.  I believe in the comment from above, what are the key metrics that drive the business.  If number of sales is your key metric, this can come at a loss because the amount of money invested to drive those increased sales is more than the revenue being generated.  Be careful to choose your metrics wisely.

5. Too Much Branding

I think everyone believes in increasing brand loyalty is key to a successful business, but this goes so much deeper than pushing the brand.  Brand loyalty comes from consistency, delivering the promise of the brand and always putting the customer first.  These don't come from a catchy slogan or advertising, this comes from hard work to deliver the best customer experiences.  The brand is all aspects of the transaction, from the customer service agent answering the phone to the ways in which a mobile app enhances the buying experience.  

6 Ways Mobile Marketing Automation Boosts App Engagement And Monetization

"These are a few of my favorite things", mobile apps and marketing automation.  A perfect marriage.  Mobile is the channel of the future and marketing automation can enhance it to improve monetization no matter what the business model.  This article is focused on the freemium business, but I believe it applies to everyone who has a mobile app.  Marketers should start thinking of mobile as a channel instead of a business unit, then the understanding of marketing automation and true omni-channel marketing can come to fruition.

1) Understand users’ behaviors

For any type of campaign to succeed, developers must first understand their users’ behaviors and the motivations behind them.

What price point is likely to get a certain user to make a purchase? Which items or services are they most likely to pay for? What is most likely to trigger their first purchase? Their second? Their tenth? What kinds of rewards (free coins, extra lives, unlocked content) do they want most? How likely are they to refer a friend? Why or why not? Which features do they use most often, and what new features would they most like to see?

This is marketing automation at its finest.  Taking the users behavior and trying to drive additional behavior or change the current behavior if possible.  Using mobile as a channel allows for the ultimate in timeliness.  Most people have their mobile device on them all the time, so being able to communicate and knowing it will reach your intended target immediately makes mobile the best channel for marketers.  Targeting the offer and the message is just icing on the cake.

2) Build advanced user segments

Not all users are created equal. They must be treated as individuals, and in order to do that at scale, developers have to divide their user base into distinct segments.

Is there any other way to build segments?  Start small and grow your segments.  There are numerous ways to skin this cat, but segments should be grown out of analytics.  Don't segment customers by gender if males and females behave exactly the same.  Segments are built from knowledge of behavior that is different from the rest of the group.  That's how new segments are born and they are different for every business.

3) Set up custom messages and campaigns

Once cohorts are created, developers can start targeting those groups with custom messages and campaigns.

Segments are built for customizing offers and messages.  If this is not going to happen, then there is really not a need to identify the segment other then for analytical purposes.  The reason these customers stood out from the rest is they were different, so make sure they receive different messaging and offers.

4) Deliver messages during contextually relevant moments

The next step in perfecting a mobile marketing automation strategy is to pick the right moments to serve campaigns.

The right offer to the right person at the right time.  This has always been the direct marketers mantra.  Timing is very important in marketing.  In this context, the discussion is when to serve up an app in a game, but this applies to all marketers.  I bought an engagement ring at Tiffany's for my soon to be wife.  I received weekly emails after that purchase advertising the engagement ring.  This would have been the optimal opportunity to sell me a wedding band, both male and female.  

5) Select the right channel

In-app messages aren’t the only way to promote campaigns.

In the context of marketing for freemium games this is always a tough one, but for regular brick and mortar businesses, this brings home the point I started the article with, mobile is a channel.  Sometimes it will not be the right channel. For instance, as a hotel mobile is a great channel for marketing offers while the customer is at the property.  For when they are at home, they don't need to see there is a free cocktail waiting for them at the bar, bad channel and timing.  A lot of times, email is the preferred channel and mobile is used for more contextually aware needs.  But test that theory.

6) Track, measure, and optimize

The final step, as with any campaign, is to continually improve upon your results.

This is the best final step there is, because without it there is no way to really enhance the campaigns.  Be sure to capture all the relevant data and be able to access it through a BI tool that can represent data visually.  This will allow for greater insight to the data.  Once hitting a wall with the BI tool, then advanced analytics can come into play in the form of data mining and predictive analytics, but there will be plenty of segments created without those tools.  Remember, marketing automation campaigns are living and breathing.  They are never finished, so constantly be looking for that next great segment.

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.  

Retention is King

There are too many companies asking, “How do we acquire more users?” that should instead be asking “How do we get better at keeping the users we already have?”.

Its easy when approaching the problem of growth to think that you just need to get more users, after all that seems to be the very definition of growth. However, if you take a step back though and think about growth as the maximization of user-weeks over time, it quickly becomes apparent that focusing on retention has a much larger effect than topline growth. This is also much more of a sustainable growth mindset. Rapid user growth followed by rapid user attrition is an indicator of unsustainable growth. Strong retention of users over time is a good indicator of product-market fit, something you’re hopefully looking to achieve anyway.

Retention is the place I start everywhere I go.  Building a strong retention program is the key to success for any business.  There's the old "It's much cheaper to keep a customer happy than find new ones" saying, but it goes beyond that.  If one thinks about it logically, the bigger base of loyalty business that is retained, the more money one will make.  Retained/loyal customers have many advantages over new or dormant ones.  

Customers in retention campaigns have a well-defined pattern of behavior

These customers are perfect for targeted promotions, cross-sells and upsells.  Because of the purchasing and communication interaction behavior stored from these customers, tailoring offers specific to the needs of customers is the easiest way to convert into sales.  The less that is known about a customer, the more shotgun approach is taken and less likely to obtain real revenue.

Customers in retention campaigns have less expensive communication channels

Because the customer is known, the communication with the customer is much cheaper on a converted basis.  Even through the direct mail channel, which can be as high as $3-4 per piece depending on how elaborate it may be, the conversion rate is much higher on this type of communication.  Most communication in this channel can be near free, with email and push notifications through apps.

On the other side, acquiring new customers is very expensive.  Even if going completely online, the conversion rates are so small compared to the cost per click or action, that it makes the customer acquisition cost upside down for 2 - 3 purchases for many companies.  If the business needs to go traditional advertising routes, now the cost becomes staggering.  

Retention customers bring in the most revenue

While this varies from business to business, I doubt you will find many longterm successful organizations that don't have this phenomena.  The loyal customer is the bread and butter for the business and can be relied upon to grow revenue.  Within retention campaigns there are customers of all different types and understanding the loyal customer that can spend more money is the best opportunity for profit growth.  

It may seem counterintuitive to look for growth in your loyal customer base, but I have always thought of it like this.  The more customers that I can have in the active customer base, the more opportunity I have for growth.  Acquisition rarely can go away and there should always be a plan to acquire more customers, but that cost should decrease as the business matures.  For a very mature business, this cost should be as low as possible.  

A simple way to illustrate this is 

New Customers + Retained Customers + Reactivated Customers = Active Customer Base.

So if the business can acquire at a consistent base, lets call this 1 million customers per year and retain the majority of their customers, lets call this 10 million customers, then they can grow their active customer base by close to 1 million per year.  Now if those customers are retained and a new million come in, the growth lies in increasing the retention customers.  Otherwise, it costs too much to try to double your acquired customers, especially the more mature the company is.  Try to focus on retention first, it is truly the King.

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.    

Study: 80% of Companies Will Increase Digital Marketing Budgets

Woohoo!!!  I think this is a wise move as we move into the golden age of digital marketing.  Until now I believe the many companies viewed this area as media buying and website analytics.  Digital marketing is the force that will bring the customer experience to fruition by combining online and offline behavior.  Creating consistent content and messaging from one channel to the next will be key in the coming years.

"One challenge that has been very prominent for digital marketers is the hiring of great talent, and companies are finally getting the budget to do that," said Laura McGarrity, VP-digital marketing strategy at Mondo, a technology and digital-marketing resource provider.

According to the study, the top hiring barriers are finding skilled talent (cited by 65% of respondents); the cost of quality staff (30%); attracting top talent (21%); retaining top talent (16%); and culture fit (26%).

Talent is in high demand and I think what companies have to realize is the talent they are looking for do not necessarily have many years experience in the field.  In fact, there is very little experience in the new age of digital.  Finding talent will be harder than looking at a resume and seeing if the applicant has X number of years and X degree.  These are not the metrics companies should be aspiring to hire.  The metrics should include applicants that have expressed their thoughts about digital marketing and whether their thought leadership is the direction the company is trying to go.  

"Turnover has been a really big issue," Ms. Garrity said, noting that the average tenure for digital marketing professionals is 12 months to 18 months. By comparison, average CMO tenure is 45 months, according to executive recruiting firm Spencer Stuart in a March 2014 report.

"There is such high demand and it's such a new space -- people are hopping around to find the best jobs," she added. "It is a candidate's market, particularly in digital marketing."

The top skill sets companies are hiring for this year are digital/social (54%), content creation (44%), big data/analytics (33%) and mobile strategy (30%), Mondo found.

There should also be a questioning of why there is so much turnover.  Even though it is a talent market, there should be less turnover if the work is rewarding and CMO's are really bought into the innovation.  Too many times CMO's tend to be brand focused and the digital marketer will get frustrated in that environment.  

The study also asked marketers which digital platforms will drive customer engagement in the future. It found that today, mobile is seen as a key driver of customer engagement by only 24% of respondents, but in the next three to five years, that will increase to 70%.

The 24% number is too low for mobile as a key driver.  Today is the age of mobile and if companies aren't focusing on mobile, they will be behind in three to five years.  Mobile strategy takes time to implement and companies need to start now.  

The next 12 - 18 months will be very interesting in the digital space as technology vendors are building platforms that can support the wants and needs of marketers.  Upcoming technology will push the boundaries of what is possible.  Many companies will want to leapfrog steps to get to the end goal quicker, but it is important to realize to take advantage of the next low hanging fruit before jumping too fast.  That is why it is imperative to start now on the digital strategy.

Data is the First Step to Marketing Automation

I have implemented many marketing automation solutions over the past decade and one of the perplexing findings is how organizations put the cart before the horse when they are installing their solutions.  I like to say marketing automation solutions are "dumb".  Not the kind of dumb as in "this is stupid, why are we implementing these solutions, why not do something else".  They are "dumb" in the essence of they need help from something else to be successful.  They cannot work on their own.

Marketing automation tools are a slave to the underlying data.  All marketing automation tools do is query data and create metadata that is used to create content and messaging for your customers.  Now I am minimizing the importance of the marketing automation tools in that sentence, but from a high level, it works.  

Since the underlying data is what drives the marketing automation tool, that data is the first step in implementing the tool.  Without the proper data, your implantation will fail.  Getting the data into the proper format for consumption from the automation tool is the most important step of marketing automation.  

Understand the problems to be solved

Write out all the different types of campaigns or communications to be run with the automation tool.  This step is vital to understand if there is a gap in your data collection strategy.  Also, this identifies if the data is structured properly to even run these types of campaigns.  This step comes before buying a marketing automation tool.

For example, I want to send a reminder email to all customers who bought a television that specific cables will enhance the performance of their new purchase by 50%.  For this, the data will have to be structured to understand which customer bought a television set, along with cables because you don't want to sound like you don't know your customers, within X amount of time, their email, mailing or app device ID, and the channel they prefer to be communicated with.  Now the data team can make sure they have the proper structure for just this one use case. If the data can't be structured accordingly, then the marketing automation tool will not be able to deliver this campaign.

Define success for the campaigns

This can be a simple sentence in each case.  What this determines is how the analysis of the campaigns performance will be achieved.  Analysis is also part of the marketing automation tool implantation, because I guarantee you that the executives will want to know the impact of this large investment, so the data needs to be prepared to answer these questions.

For example, I want to see the redemption rate and revenue generated, along with the expenses for delivering and cost of goods for the customers who returned to the store and purchased upgraded cables for their televisions.  For this the data will have to meld together the ID for the offer, in this case the cable, along with the purchase item along with the expense data from the marketing automation tool and the sales system.  These tasks aren't easy, but they will pay dividends if this legwork is done upfront.  There is nothing worse than flying blind with your marketing automation..  

 The expectations for campaign execution times

This is one that almost always gets missed.  I have heard of campaigns that run almost all day because the data is not organized in a fashion that is not optimized for the marketers.  That kind of performance may be acceptable if the campaigns are run once a month, but for most businesses that is not the speed of digital marketing.  

For example, I want to be able to run the campaign for the television purchasers every day.  This includes time to run the automation, send out proofs for the collateral and have the deliveries out to the customer by 10AM.  This allows the data team to be able to optimize the data structures to make sure the data can be pulled fast and efficiently for all your automation campaigns.  

This by no means is an exhaustive list, but it is a start to having a successful marketing automation implementation.  No matter how many bells and whistles the marketing automation tools have, if the data does not support the wants and needs of the marketer, it doesn't matter because the tool is "dumb".  It needs the data to perform magic.     

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.

Building credibility for your analytics team—and why it matters

If you work with data regularly, chances are you trust it. You know how it's collected and stored. You know the caveats and the roadblocks you face when analyzing it. But, when you bring your findings to those further removed, you're asking them to take a leap of faith and trust in data they may know very little about.

Multiple times in my career I had to come into organizations and take teams that were not trusted in the organization and help build them into the trusted source of data accuracy and insights.  This journey is never easy.  It takes patience and requires a lot of persistence to change an organizations perception of the department.  But these points are good advice on a roadmap to do this.

Start Small

When trying to get people to believe in your team, it can be tempting to chase the biggest problems first. These problems often take a long time to answer, and can take several tries to get right. It's often better to first establish trust by picking early projects that you know you can win, and win quickly.Try starting with basic arithmetic to answer crucial business and product questions. For startups, some example questions might be:

• What are the most engaging features of your product?

• What is the company's core demographic? What do they like about the product?

Often, people don’t judge the answers to these questions on technical rigor, they judge them on business impact. Starting small can open doors to the big questions that you may have wanted to start with; if you've earned credibility along the way, you'll have more time, flexibility—and maybe resources—to tackle them.

I always find it helpful to start answering questions that are not currently being answered.  As Derek Steer points out in the article, don't start by trying to solve the worlds problem.  If your team tries to tackle tough problems, there will be a much more critical eye on the work and the data produce.  Allow your team to get some wins under its belt.  Remember, this is a journey, not a sprint.  Trust comes with wins, not home runs.

Know your audience

Keep your audience in mind as you begin to craft the story from your data. Add in the appropriate amount of detail your audience needs to focus on decisions rather than methods. What context might they need? Spending a little time thinking about what your audience cares about most also helps you anticipate possible questions and prepare answers in advance. Few things can help establish credibility faster than fielding a question during a presentation and immediately flipping to a slide that answers it.

This point is critical to garner trust.  When presenting data, make sure there is a story that is being told along with the data.  Guide the audience to the answers that you have found, don't let them have to figure it our themselves.  Be sure to explain to the audience what they are seeing and why it matters.  Make it simple, quick and insightful.

Don’t be a House

House, a brilliant albeit fictional doctor, routinely diagnosed rare diseases but had abysmal bedside manner. The thing was, House didn’t have to win his patients over—they were so desperate to survive that they would listen to his every word.

It's subtle, but consider your findings a conversation starter. Understand that the non-analysts have valid points too: they have experiences you don't have and they likely know something you don't. These discussions aren't about winning an argument, but making the right decision for the business.

Never use data for evil.  This is fairly common in Finance departments, but it is important not to attack decisions, but rather try to initiate conversations to come to the best business decision.  Once there is a tone of implication in the analysis, your team will lose the trust of the department that you are creating the analysis for.  Those departments made decisions that didn't have data to drive their decisions, so treat them as a partner, not someone that needs help.

Be Transparent

Analytics can feel like a black box to many people—making that leap of faith appear even larger. By showing even just the basics of your process, you can help others believe in it. To increase transparency try:

• Making your work simple and understandable. Monica Rogatti would urge you to try division before doing anything harder. As your audience becomes more comfortable, up the game to simple regression models—it's not usually difficult for folks to understand the direction and magnitude of coefficients.

• Finding simple ways to convey advanced concepts. For example,confidence intervals and p-values can be confusing for many people, but charts with error bars make these concepts easy to understand.

• Using stories. If you're presenting information about feature usage, or events with technical backend names, paint a picture of how a user would see these features, or put events in plain-English names.

Numbers are difficult to interpret at times, taking the complex and being able to tell a story with it is an art.  Most analysts are great at finding data and creating insights if they have domain knowledge, however they can be terrible at communicating their findings.  Always have available the methodology for coming up with the answers, even if you believe it is a waste of time.  The haters in the organization will demand this, but it also humanizes the process for the non-analytical audience members that you want on your side.  

The most important part of the journey is to persevere.  The beginning of the journey is the hardest part.  I remember in my last position, the department I took over was the laughing stock of the organization.  It took them weeks to come up with an answer and no one believed in what they were saying because they were just being report monkeys, instead of providing any insights.  By the time we got going, we were the defacto data source for the organizations.  We created analysis for parts of the organization we didn't have anything to do with, but when the organization needed something done right, it came through our team.  That was because we had many wins along a journey.  

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 James Hotel Combines Beauty and Elite Customer Experience for its Loyalty Guests

Mark Johnson from Loyalty360.com writes:

The James is redefining luxury boutique hotels in New York, Chicago and soon in West Hollywood for its loyal guests. The hotel focuses on providing beautiful designs and outstanding customer service.

Lisa Zandee, Senior Vice President of Brand Management, told Loyalty360 that The James is a leader in creating design and guest centric services. “Both are extremely important,” she explained. “It’s about form and function. It has to work and look good.”

An interesting interview with the Senior Vice President of Brand for the boutique chain.  Many of the points Zandee brings up are very true to run a successful hospitality operation, especially in the high-end boutique industry.  Customer service and differentiated experiences are the key for these types of properties to thrive.  Being a small hotel allows for personalized service which is the definition of a boutique experience.  

Where I think problems will start to occur is the lack of respect for data in driving decisions.  Zandee dismisses data as something that clouds the teams judgement when developing initiatives.  I think this will come back to haunt this team.  Again, there is an art and science to marketing in the digital age and The James is disregarding the science portion.  Creating a loyal database is key to surviving in the hospitality industry and solely relying on social media and your loyalty rewards program is leaving profit on the table.  

Most CRM programs make the most money from customers who aren't giving you the loyalty you are looking for, so to minimize this group can lead to reservations coming through less profitable and less loyal channels.  Increasing the base of the business coming from known customers increases profits while enabling control of the customer experience.  Delivering great customer experiences in the digital age relies on data as an important component.    

Best Buy Wants to Build a Differentiated Customer Experience

During Tuesday’s fourth-quarter earnings conference call, Joly said he believes a differentiated customer experience can happen at Best Buy.

“We are pursuing a strategy that is focused on delivering advice, service, and convenience at competitive prices to our customers,” Joly said, according to Seeking Alpha. “Within this strategy, we are focused on driving a number of growth initiatives around key product categories, life events, and services. To drive these initiatives, we are pursuing and investing in the transformation of key functions and processes. We will also, in fiscal 2016, be facing industry and economic pressures on our business related to deflationary pricing and weak industry demand in certain product categories that we discussed last quarter.”

There's that new buzzword, customer experience.  What I find fascinating is why a market leader like Best Buy hasn't been trying to differentiate customer experience for years?  Amazon has clearly hurt their business and low-price alternatives like Walmart have been coming after them for years, why all of the sudden is a differentiated customer experience important now?

I know personally I try to never step foot in a Best Buy.  I used to be a very loyal customer, however there were a few experiences that made me so upset, I never went back.  These experiences were anti-customer experience moments.  They were trying to up sell so hard, it made me uncomfortable, to the fact they were trying to make me feel stupid for not getting the protection plan.  As a customer, I didn't like the feeling and stopped going back.  

They will have quite the challenge to create a differentiated customer experience in the stores.  Their salespeople, in general, have not given me great customer experiences in the past.  Whenever I have had the opportunity to engage and ask questions, they have read the stickers and told me what was on their brochure, like I already didn't do that.  

What I would like to see in Best Buy is the days of the "old" Home Depot model.  Home Depot used to pay its employees top dollar for their expertise.  The idea was that a plumber who was tired of working in less than stellar conditions would work at Home Depot and they would be able to give expert advise to customers looking to do home improvement.  Over the years, to save payroll, Home Depot went away from this model and most of the staff can't help you with great advise.

If Best Buy softens the sales approach and becomes more of an expertise experience, I could see wanting to shop there again in the future.  When I am shopping for a camera, I want the salesperson to be able to tell me about why this camera will be better for me than another camera.  I want them to ask me questions and figure out what I need instead of reading off of a price ticket at the features of a camera.  This would be a great experience and something Amazon could never match from an online perspective.  

The one reason I don't believe this will succeed are the words coming out of the CEO's mouth about this change.  He talks about "growth initiatives" which is not a customer-centric way to speak about the business.  Customer experience is a culture change, not an initiative.  

The Current State of Email Marketing in 9 Fascinating Stats [#SlideShare]

Some very interesting stats on the slideshow, just click the title and you can view them.  The interesting stat to me was 20% of marketers link their primary revenue back to email.  I think this number is too low.  Email is still the best channel for businesses.  

Now I believe mobile will overtake email soon because it is a more direct channel.  Mobile apps have the potential to be the greatest marketing channel in our lifetime.  The phone is always with us.  It knows where we are, where we've been.  It knows if we are moving or standing still.  It knows where in our store our customers have been.  It is also always on, always available.

Email is not dead, but it already knows who will kill it.   

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.   

Eliminating the “Graffiti” in Your Customer Experience Program

Leadership Behaviors Drive Change
Executive behavior is as much of an influence on employee behavior as graffiti is on the behavior of those who use the subway. It’s symbolic of the success of the system, and leadership needs to drive the cultural change required.  

A superb article by Nancy Porte regarding the cultural change needed to truly deliver on the customer experience and the role executives play to ensure its success. I recommend reading this article, very thoughtful writing.  

As I've been harping on for the past couple of weeks, customer experience goes well beyond creating teams and having initiatives.  Customer Experience is a culture, one that revolves around the customer and makes sure every decision the company makes is for the customer.  The rationale behind this theory is that great customer experiences will result in happy, loyal customers who will buy more and become advocates for the brand.