How do you create a data-driven culture in your marketing team?

Becoming a data-driven organisation doesn’t just rely on the right technology, structure and processes. The human element is essential, and without the right skills, qualities and roles, any effort to be successful at data-driven marketing is destined to struggle.

And the kinds of skills that support a data-driven philosophy are rich and varied.

This is very true.  The "art" and "science" that requires actionable data lean more to the art side in most marketing departments.  The biggest change is to respect what data can bring to the equation.  Many marketers don't respect data, they respect their gut and soft metrics like awareness.  While data doesn't solve all problems, it helps inform direction.  It helps decide what is happening with the customers you are trying to target, plus the ones that you aren't targeting and whether you should.  

“The data-driven marketing team is knowledgeable enough to converse freely with technical and statistical resources while staying laser-focused on getting the right message to the right person at the right time. But the most important quality needed in a modern marketing team is curiosity. Without that, I may as well outsource all of my data related work to a third party. Curiosity stimulates creativity and conversation, and aids decision-making.” 

I like the statement of staying laser-focused on getting the right message to the right customer at the right time.  Too many times teams lose their focus and start drifting on to answers that are either easy or different from the most relevant topics.  Understanding what data is saying is more valuable than having the person who can put the report together.  Money is made by providing the insight to the data, that is what I look for in my team.  But don't forget to have the guy that can put all the data together.

Quintero adds: “Building a data-driven culture is not an overnight process. It takes time. To me, a data-driven culture means building a safe environment where experimentation is encouraged and mistakes are tolerated. It’s less about having all the right tools in place – although that’s a critical part of the process – and definitely more about cultivating excitement around discovery and objectivity. Being data-driven is exciting and people should be encouraged to enjoy the process as much as making things happen.”

Changing a culture is a journey.  Teaching the team about why decisions are made from looking at the data and what the thought process for coming to the conclusions is critical in building the data culture.  No matter how smart a person is, if they don't understand the thought processes of decisions they will never be able to take leaps with the data.  If they understand what to look for in data, they beginning asking the right questions and delivering recommendations along with their questions.

The Dangers of Data-Driven Marketing

Marketing has gone digital, and we can now measure our efforts like never before. As a result, marketers have fallen in love with data. Head over heels in love—to the point where we want data to drive our marketing, instead of people, like you and me. I think this has gone too far.

I'm a big proponent of data-driven marketing, in this article Ezra Fishman uses semantics to say this is bad, but what he is trying to get is there is a need to go beyond just the data.  As I wrote in Data + Insight = Action, data all by itself cannot create actionable outcomes.  

Data-informed marketing

Instead of focusing on data alone, data-informed marketing considers data as just one factor in making decisions. We then combine relevant data, past experiences, intuition, and qualitative input to make the best decisions we can.

Instead of poring over data hoping to find answers, we develop a theory and a hypothesis first, then test it out. We force ourselves to make more gut calls, but we validate those choices with data wherever possible so that our gut gets smarter with time.

This is what I was trying to articulate in my article.  To be an excellent data-driven marketing organizations takes a little bit of "science" and a little bit of "art" to determine the best course of action.  When a data scientist is driving your organization, there are years of experience being unused to help him understand even further what the data is saying.  

Most times when a data scientist is off on their own, it takes an inordinate amount of time to come up with a conclusion, mostly because they lack the context of how the business is generating the data.  How the strategy manipulates the data.  How a customer being underserved may be an intentional outcome.

The ease of measurement trap

When we let data drive our marketing, we all too often optimize for things that are easy to measure, not necessarily what matters most.

Some results are very easy to measure. Others are significantly harder. Click-through rate on an email? Easy. Brand feelings evoked by a well-designed landing page? Hard. Conversion rate of visitors who touch your pricing page? Easy. Word-of-mouth generated from a delightful video campaign? Hard.

Right on!  Of course the organizations that take the easy way out are ones that I would not consider to be data-driven.  KPI's are a great item, but they can be deadly.  There are usually so many moving parts that make up the business and the data being generated.  This can cause business KPI's to look fine, yet drilling down into the performance from a customer perspective may show some very scary trends that would cause alarm.  However, a non data-driven company will continue with their strategy because of the KPI's (hello RIM/Blackberry).  

The local optimization trap

The local optimization trap typically rears its head when we try to optimize a specific part of the marketing funnel. We face this challenge routinely at Wistia when we try increase the conversion rate of new visitors. In isolation, improving the signup rate is a relatively straightforward optimization problem that can be "solved" with basic testing.

The problem is, we don't just want visitors to sign up for our Free Plan. We want them to sign up for our Free Plan, then use their account, then tell others how great Wistia is, then eventually purchase one of our paid plans (and along the way generate more and more positive feelings toward our brand).

This can be combined with the previous bullet.  When analytics is only seen from a high level, simple statements like "we need to increase the number of signups, which will flow down at the same rate as we currently have, will increase conversion."  Nothing could be further from the truth.  To increase anything there needs to be an additional action.  This action may include advertising to a different group of individuals or giving an incentive that will increase signups.  The issue with this thinking is these aren't the same individuals that are converting in your current funnel.  The proper strategy is to figure out the converters and try and target customers like them, which may actually decrease the size of the funnel if done right.

The data quality trap

We are rarely as critical of our data as we ought to be. Consider, for example, A/B tests, which have become the gold standard for marketing experimentation. In theory, these tests should produce repeatable and accurate results, since website visitors are assigned randomly to each page variant.

In practice, however, there are lots of ways even the simplest A/B tests can produce misleading results. If your website traffic is anything like ours, visitors come from a variety of sources: organic, direct, referral, paid search, and beyond. If one of those sources converts at a much higher rate than others, it's easy to get skewed results by treating your traffic as a single, uniform audience.

One should rarely just take the conversion or redemption results from the A/B test without digging into the data.  Making sure all segments are driving the results is key.  Don't take for granted the customers that were randomly selected for each group ended up being totally random.  Ensure there was proper representation from each segment of the business and identify any other changes that could be tested based on different behaviors within the segments.

Data vigilance

As marketers, we should continue to explore new and better ways to harness the power of data, but we also must remain vigilant about becoming overly reliant on data.

Data can be a tremendous source of insight. Harness that. But don't pretend it's something more. And definitely don't put it in charge of your marketing team.

This reminds me when I was a product manager and we would receive these RFP's to determine if we were the right company to supply them with our product.  Sometimes the requirements were such that we wondered if the company wanted humans to continue to work for them.  I would comically refer to some of these as automated manager.  It seemed companies wanted to press a button and have a system do everything for them.  This is the trap Fishman is referring.  Humans have great insight.  Humans are the "art" in the equation to actionable outcomes.  This is equally important as the "science".

How Not To Use Marketing Automation

Normally I would never suggest not using a marketing automation for anything, but it is a funny title so I'll let this slide.  I would even argue that bad marketing automation is better than no marketing automation, but not by much.

Generic Broadcasting – The time that you save with marketing automation should be used to not only improve your content in the first place, but also to personalise through segmentation. Consumers in all market places are becoming more and more sophisticated, and can spot poorly executed marketing automation. And their perception is likely to be that you don’t care about the communication.

This is the first step of marketing automation.  So many times the implementation strategy of the marketers installing the new system is to do what they are currently doing, but in a new fancy tool.  I think this is an okay step if the desired outcome is to QA the output to make sure all the data is correctly hooked up.  Other than that, marketers should have an understanding of what the new capabilities of the tool they have purchased and at least start with a few general segments to make sure there are some differentiation in the messaging.

My advice is to bring in a group that has experience in the tool who focuses on the strategy behind utilizing the tool to help build a roadmap.  It's okay to start broad, in fact I recommend it.  But don't tart from scratch.  Start implementing the "low hanging fruit" opportunities in your business right away.  This will be your baseline and then you start to grow from there.

Being A Spammer – Automated emails are a great way of engaging with recipients who have shown an interest in your email, but you should still spend time focusing on the quality of your communication. Avoid the usual spam trigger words and don’t go sending an email to thousands of people all at the same time. Marketing automation can increase the risk of spam, but a good email provider will help you with this.

All the good Email Service Providers (ESP) will provide services to assist you in "warming up" your domain to the Internet Service Providers (ISP).  This is a necessary first step to make sure everyone can see your emails when you send them (deliverability %).  

However, this does not mean your job is over.  If you decide automation will allow you to send emails to your customers everyday with messages which do not resonate with most of them, you will quickly be flagged as spam.  If this happens too many times, the ISP's will block your emails.  When I started at one property, Yahoo was blocking all the emails and the deliverability rating was in the high 60% range.  It took a long time to get unblocked, so make sure your content is relevant and you stop sending to customers that are not opening your email.

Bad Time Automating – Automated communications are tricky: you’re writing them at a time where the context of how the communication will be received isn’t known. Most of the time, this is absolutely fine as you are only scheduling a few hours ahead, but beware of shifting events. 

Most of the time your emails will not be "set it and forget it".  You may run with an automated email blast for customers that signed up today with an offer to engage further, and that is fine in most cases.  In a lot of the cases the automation is used to increase the segmentation capabilities, not to create a generic email blast to all your customers over and over again.  

If you run into this problem of timing, then forget about scheduling too far in advance.  Take your time and make sure the message is relevant to the customer at the time the email is sent.  This will save you from looking like someone that doesn't understand the customer at all.  That is the worst thing that could happen.

Communicating Constantly – With marketing automation, communications with your audience should become a lot easier. But don’t get carried away. If it is easier, then the temptation will be to communicate more often, but this is as off-putting for a recipient as communicating poorly. It can also have a detrimental effect on the size of your audience.

The quickest way to being marked as spam or unsubscribed is to over communicate through email.  Just because its easier to do, doesn't mean you should.  Make sure you are communicating a little more than your customer is engaging with your brand.  Its okay to communicate everyday if your customer is buying something everyday, but this is usually not the case.  If your customer purchases a product once a month, maybe every other week is a good cadence to start.  Remember, the beauty of a marketing automation tool is your customers don't have to all be on the same communication cadence, they can be on their own, as long a you have enough content to make that strategy make sense.

Send And Forget – One of the objectives of most communications is to elicit a response. Whether that is an open from an email, a click on an advert or a reply / share from a social media post. So when you are automating, you should always have a process in place for monitoring their impact – you should be able to set this up as an email or smart phone notification. Ignoring this can result in recipients not talking (positively or negatively) to anyone, something to avoid at all costs.

As I said above, this strategy can be detrimental to having a marketing automation tool.  Never send without analyzing the results.  All marketing automation campaigns are living and breathing entities, they need to be changed and enhanced constantly, because as you change behaviors the communication cadence and the offers need to change with it.  There are also segments of customers in the campaign who are not getting what you are throwing out, so constantly look for opportunities to enhance the campaigns taking these customers into account.  Analyzing is the most important step of the process.

Why CEOs Say Yes to Marketing Automation

Ten short years ago, it was rare for a company to have a marketing automation platform in place. Since then, it’s become ever more clear that acquiring marketing automation (and applying the expertise to make it hum) is a huge competitive differentiator. SiriusDecisions research indicates that 80% of the organizations with the highest-performing demand waterfalls (based on the number of won deals per 1,000 inquiries) have implemented marketing automation platforms. This tallies with other research; the 2015 report “Rethinking the Role of Marketing” from Gleanster and Act-On found that Top Performers were 20% more likely than the average organization to use marketing automation technology..

I think it is still rare for most organizations to have a marketing automation platform, but what is even more rare are companies who are taking advantage of their platform.  The promise of marketing automation is very enticing as this article articulates.  The benefits of a well-run marketing automation program is an extreme competitive advantage.

1. Marketing Automation Lets You Put the Customer in the Center of Your World.

List management. Marketing automation lets makes it easier to segment your lists by field values (explicit data such as title, department, industry, company size) and by implicit, inferred factors (often actions) such as web pages visited, eBooks downloaded, emails clicked on. It also lets you sync chosen data back and forth with a CRM system.

Well beyond the realm of salespeople, marketing automation lets you manage your customer base on a level of personalization that is not possible otherwise.  Some say these platforms make the relationships with customers less personal, but that is a fallacy.  With the amount of personalization and targeting capable with these platforms, the customer gets a more personalized experience with marketing automation.  

The amount of time manual processes take to manage the customer, it is impossible for these processes to really give the best experience to the customer.  There is just not enough time in the day.  However, a marketing automation platform can create customized communications based on all of the data described above, including behavioral information, geo aware messaging and preferences of communication channels.

Campaign management. Automated programs can save time (which is money, yes) and take a little human error out of your programs. You can set them up to replicate successful lead nurturing or onboarding programs, for example, and they will run exactly as programmed, no matter who misses work on Tuesday. You can add prospects as they enter your world (perhaps through a form) and exit them (perhaps to another program, or to sales) as you learn more about them, or as they become increasingly qualified. You can set up trigger emails (thank-yous, congratulations, expiring trials) and landing pages that make offers or fulfill requests, showing how responsive you are.

Campaign management is a difficult process if you have different programs pulling lists, then fulfilling communications and measuring results.  The amount of time saved by having a platform where everything is integrated and can trigger off the behavior of the customer is very powerful.

6. Marketing Automation Takes Care of the Established Customer

The platform gives you a structure you can scale in your retention strategy. Start with using a nurturing educational strategy to support onboarding. Move on to keeping your customers in the loop, educating them about new features, showing them new plays with old features, and keeping them abreast of changes in the industry that affect them. Take the same techniques you use to notice when a lead is warming up and apply them to noticing when a customer is looking at an upsell … or needs attention to prevent churn.

Retention is the most important part of the database.  The greater the number of sales coming from your established customer base allows for the greatest growth in your business.  Marketing automation at its heart is best for the established customers.  The platform is designed to drive more business from this segment.  Since the majority of most companies revenue comes from loyal customers, having the ability to grow this groups sales is essential to a longterm stable business model.  The marketing automation platform should be at the center of this model.

7. Marketing Automation Spurs Revenue and Growth

These benefits are all pieces of a puzzle that every company using marketing automation puts together in its own unique way. The common denominator is that most companies that apply marketing automation – whether they use every feature or just the basics – will see faster growth and post more top-line revenue.

Well who doesn't want that?

Five Ways to Win with Data-Driven Marketing

Data-driven marketing has come to the forefront for companies that want to better engage their customers and prospects. With data-driven marketing, firms are able to gather, integrate, and assess data from a variety of internal and external sources to help enhance value.

Marketing automation starts with data.  In fact, in the digital age, almost all marketing initiatives start with data.  Companies who are data-driven have a distinct advantage over their competitors.  When a company is data-driven, they focus on their strengths, enhance their weaknesses and they don't obsess over their competition.  They have the data to understand how they can improve.

1. Determine what really makes customers tick. According to the DMA, data-driven marketing is about discerning what customers want and need and engineering the company to provide it: “The more firms can use data to develop a 360-degree, multi-channel view of what customers think and want, the more the customer will truly be king.” Through the use of both internal and external data, companies are learning how to “crown” their customers — truly understand what makes them tick, and then develop campaigns that engage them in the most effective manner possible.

This all comes with data analytics.  Understanding what drives your customers behaviors is step one to developing campaigns and offers.  Without an understanding of what your customers want, there is not an efficient way to determine what they would like from you.

2. Set baselines for campaign effectiveness. Data-driven marketing has effectively replaced the traditional “hit-or-miss” test component of the typical direct marketing campaign.

Baselines are a very important piece to understand when analyzing campaigns.  This is the beginning of the journey to understand the effectiveness of any changes that are made.  If an organization cannot answer what a particular program is bringing them, they should test the campaigns without the program and determine what, if any, the effectiveness of the program is bringing.  

3. Block out the “noise” and focus on what’s relevant. When assessing data over multi-year periods — and across different marketing channels — it’s not unusual for things to be extremely “busy” at the outset. There’s a lot of static and responses are all over the place. However, by using proven data-driven marketing techniques, you can start to pull out the relevant information, analyze it over time, pick up on traffic patterns, and drill down to specific marketing touch points (i.e., number of website hits that come in when a specific direct-response show airs).

This is a lot harder than it sounds.  Marketers are the kings of taking a piece of data and selling their story with it, even though it is just noise or a small sample of customers.  This is where the "art and science" approach is necessary.  Being able to combine data mining techniques with the business acumen is key to focusing on the relevance of the data.

4. Determine exactly how customers are responding.

Again, this is important to understand multi-channel marketing.  The ability to reach your customers on the right channel at the right time is only possible through data.  

5. Reach extremely targeted customer bases.

The promise of 1-to-1 marketing is arriving.  Be careful to shoot for this level of personalization, because it is very expensive and the pearl is not worth the dive for the majority of your database. However, being able to target your best customers in a very personal nature could help grow the business exponentially.  This takes extreme focus.  

Closing the Loop on Marketing Automation

Marketing Automation is starting to come into the mainstream, but many companies are not using the toolset to create amazing interactions with their customers.  I know many brands that have sophisticated toolsets and it is used to show me points and my name.  I get the same exact email that all of their customers get with my name attached, this is not an amazing interaction.

Data and Analytics as the Foundation

Seems logical, right? You would be amazed at how many brands are still working through “We don't know how to get our transactional point-of-sale integrated with our demographic and third-party purchase data.” Solid data management and extract, transform, load processes form the foundation from which a solid enterprise marketing platform is built.

Data is the backbone of any marketing automation solution.  This may be why the technology isn't as pervasive as it should be.  Getting all of the data into one location in a consumable format for marketers is not an easy task.  This is the first step in the marketing automation journey.  Starting with the data will increase the chance to have amazing interactions with your guest.  The more knowledge about the customer, the more customized a communication can be and this is what delights the customer.

Integrate, Orchestrate and Optimize

This is a large category, but an important one as far as customer engagement is concerned.

First up is integration. Integrate marketing programs across channels — leverage insights from outbound marketing programs to better serve customers on inbound channels and vice versa. With consumers switching channels as frequently as they do today, this is imperative.

Marketing automation tools today can currently run many inbound tasks.  This is especially true when sub second response is not necessary.  When giving the customer an option to to click on a button to serve up an offer or promotion, use the marketing automation tool to serve up the offer.  This way it ensures the customer is seeing the same offer they saw in an email you sent yesterday.

Orchestrate campaigns and their offers so that the timing and sequence, as well as the channel delivered, make sense based on individual consumer preferences. 

So many brands are tied to their own timing of communication, not the customers.  For instance, we alway send our bi-weekly communication on every other Tuesday.  This makes it easy for the marketer, however this does not take into account the customer.  

All customers should be on their own timeline.  Marketing automation tools are very sophisticated and can handle this type of philosophy.  Planning the interactions with customers based on their behavior will result in much higher response.  This is the type of delightful interaction customers expect.

Optimization is the final step in the execution phase. Make sure you use analytically based optimization across all channels to avoid over-contact and saturation of consumers. Consumers are only annoyed by receiving an email offer for a product or service that they just signed up for last week during an inbound contact center conversation.

Be sure to optimize constantly.  Marketing automation campaigns are living and breathing entities.  They are never finished and there is always money to be found in optimizing the programs.  Optimization goes much further than over contacting the customer, just as bad is not contacting the customer at the time they want to purchase.  Even worse is offering the customer something they would never be interested in, especially if they have been your customer for an extended period of time.  Tiffany, I already bought my wife the diamond, stop telling me about how amazing it is, you had me at hello.

The last step is to close the loop in order to perform truly integrated marketing. Take the information you learn from the delivery of both inbound and outbound offers: Did a customer open an email, respond to a social message or accept a verbal offer delivered via the contact center? If so, what effect does that have on downstream marketing efforts?

It all comes back to constantly learning.  The more your customer interacts with the brand, the more they tell you about themselves.  I am not the biggest fan of over surveying the customer and when asked why that is, I say its because I survey my customer all the time.  I send them outbound communications with call to actions and if they reply, they are telling me what is more important, voting with their wallet.  If they don't reply, they are telling me they don't appreciate this offer, or maybe it is this time, etc.  Learn from these interactions and enhance your campaigns.

Remember, Data + Insight = Action.  Always be looking for actionable data on your customers and using that in your marketing automation programs.

6 Rules for Creating Killer Email Campaigns

Email marketing still reigns supreme for most businesses when it comes to ROI.  The funny part is how many businesses are not taking full advantage of the medium.  Email is a channel and should not be seen as a strategy unto itself, it is just another way to communicate to the customer.  But because of its low cost and effective targeting capabilities, it is a channel that should be at the top of most companies priority list.

1) Map out the customer flow

Once upon a time I worked on the growth engineering team at Twitter. We were tasked with building something that could turn new signup users into die-hard Tweeters. The secret sauce to user activation was…email! But before we knew when to use email, we had to map out the Twitter user journey.

This is key to a marketing automation.  The first step of a campaign is to identify the goals for the campaign.  After that, the visual mapping of the workflow will save hours of time and allow for better if/then scenario processes to take place within the campaign.  When done visually, it also is easier to see pitfalls and mistakes.  This may seem like double work, but it is an essential step.

2) Master the balance of building your list, while not asking for too much

You’re ready to begin building your email list and customer base. You’ve also heard that the more info you have on a customer, the better. Besides, how are you supposed to create highly personalized email campaigns without any data on a user? Before you start pushing sign up forms with 20 form fields to all of your website visitors, you must first understand that customer intelligence should be built over time.

I am a big fan of finding out 1 thing about your customer in every interaction.  Transactional data about what your customers are buying is the best information to have, but also asking your customers a question with each interaction is not time consuming for them and through time will build a plethora of information for you which then can be used to further segment your customers.  Be careful what you ask.  If you ask something specific about behaviors, your customer may expect you to use this information right away and if you don't, they may become disenfranchised.  

3) Embrace marketing automation 

People say marketing automation isn’t personal and ruins your brand reputation with robot-like communication. I’m going to argue that it actually makes your communication more personal because it can be used to send messages based on individual behavior. Marketing automation makes it so that no two people receive the same messages.

This is a must in my book.  There is no better way to have targeted, individualized communication with large sets of customers without it.  Marketing automation tools should be a fundamental piece of the marketing technology.  It allows for the management of the customer, regardless of the channel.  It makes multi-channel communication possible.  I believe this is the center for all outbound communication, regardless of the channel.

4) Offer value with every touch  (Eat24)

You don’t need a reason to call grandma, but you should have a reason for sending an email to your subscribers. Promotional blasts are the bread and butter of ecommerce companies, and I’m not saying they’re a bad practice, since they do generate revenue. But, before you send another marketing campaign, you should always ask yourself, “Will my customers care?” The answer of course should always be, “Yes!”.

I worked with a company that did an email blast every 2 weeks regardless of if there was anything new to communicate.  The offer that was sent was usually the same offer with a different twist.  

Not only does this approach start to feel the same, which will lead to customers ignoring the email, it also doesn't create a sense of urgency for the customer.  If there is always a timed offering and it is always the same offer, customers will not feel the need to reply to the call of action.  They will start to learn there will be this new offer next week so maybe I'll just wait until then.  This limits the effectiveness of your communications.

5) Recognize lapsed users and bring them back  (Memebox)

Customers sometimes leave. While some loss is inevitable, others are absolutely preventable. A bad marketer doesn’t know who has left or who is about to leave. A good marketer recognizes the signs of churning and targets those users with the perfect message to bring them back.

The best time to market to a customer is before they become inactive.  Once a customer is inactive or has left, it is usually too late and those customers are very hard to regain.  It is very important to identify customer that are about to churn or are changing their buying habits in a negative fashion.  

For instance, a customer may purchase from you with a frequency of once a month, however over the past 3 months they have not purchased anything.  Lets say in this instance your active customer database is purchases within 12 months.  If someone who consistently purchases every month, but has not in the last 3 months, you as a marketer have to change your communications with this customer.  This customer is in danger of churning and you can't wait for 9 more months before they become inactive to recognize this.  At that point it will be too late.

6) Perpetually tinker with A/B testing

Email campaigns, like fine art or software, is never finished. There will always be something else you can do to improve the performance of a campaign. When looking for an email platform, find one that allows you to A/B test any part of your email.

Marketing automation campaigns are never finished.  They are constantly evolving no matter what the situation is.  Testing should be a standard part of all your campaigns.  It is important to remember that a baseline needs to be established before the testing takes place.  Also, be careful not to overlap tests that may have influence on results at the same time.  You always want to make sure you understand what changes drove what results.  If there are too many tests and changes at once, there is no way to possibly understand the impact of the tests.

I would add a number 7, analysis

Find yourself a good, easy to use business intelligence tool and analyze the performance of these email campaigns.  Create many different attributes of your customer.  Slice and dice the data to look for opportunities.  Identify groups of customers that aren't performing up to the standards of others, these are the customers that become new segments to target with different communication and content strategies.  This also is a must in my book.

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.

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.

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.

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.  

Enrollment vs Engagement: Loyalty In Action

Getting to the checkout without hearing that phrase is a modern feat of humankind. Retailers, financial services, and expanding sectors like drugstores and restaurants know that loyalty membership programs are one of the easiest ways to get individual data on shoppers while enhancing the brand-to-consumer relationship. But when shoppers are asked (and asked, and asked again), they often can’t see the forest for the trees—that a loyalty program is an opportunity for consumers themselves to customize a relationship with brands.

The average number of loyalty programs per US household has grown to 29, based on data gathered by Colloquy. That same loyalty data shows that only 42 percent of those memberships are currently active. Just imagine what advantages consumers are missing out on when over half of their memberships are disused. Enrollment doesn’t necessarily mean engagement.

In an offline world the enrollment of a customer into the loyalty program is the main metric associates are measured to determine if they are pushing the loyalty program.  I have never liked this metric, because it doesn't measure the true purpose of a loyalty program.  

The true purpose of a loyalty program is to get your customers to engage with it.  Enrollments are a byproduct of engagement.  The metric that should be used is an engagement %.  Instead of measuring the Enrollments by associate, a better metric would be to measure the amount of sales tracked with a loyalty rewards number versus the total amount of sales for each associate.  The higher the %, the better the associate.  When this engagement % increases, I will guarantee the enrollments will increase with it.  Plus it enforces associates to be on the lookout for the best customers, not just the customers that will help them reach their goal of enrollments.

5 habits of effective data-driven organizations

Size doesn’t matter, but variety does. You would think that a data-driven organization has a lot of data, petabytes of data, exabytes of data. In some cases, this is true. But in general, size matters only to a point. For example, I encountered a large technology firm with petabytes of data but only three business analysts. What really matters is the variety of the data. Are people asking questions in different business functions? Are they measuring cost and quality of service, instrumenting marketing campaigns, or observing employee retention by team? Just getting a report at month end on profits? You’re probably not data driven.

As I have articulated previously, data-driven organizations are a culture, it is not about toolsets or data scientists.  It doesn't matter how much data you have, it matters that you have enough data to make an informed business decision.

Everyone has access to some data. Almost no one has access to all of it. There are very few cultures where everyone can see nearly everything. Data breach threats and privacy requirements are top of mind for most data teams. And while these regulations certainly stunt the ability of the company to make data available, most data-driven companies reach a stage where they have developed clear business processes to address these issues.

It comes down to what data is important for each business unit.  Most business units don't need credit card information or PII information about individual customers.  Understanding what data will drive better business decisions in each unit and focusing on getting those units the needed data in a consumable format is the key.

Data is all over the place. One would think that the data is well organized and well maintained — as in a library, where every book is stored in one place. In fact, most data-driven cultures are exactly the opposite. Data is everywhere — on laptops, desktops, servers.

This can be dangerous.  Remember there is nothing worse than fighting about the validity of data.  If operating units all have their own sets of data, then it becomes a competition of who's data is right instead of what decision we should make based on the information at hand.

Companies prize insights over technology standards. Generally, the principal concern of people in data-driven businesses is the ability to get the insight quickly. This is a corollary of point #3. Generally, the need to answer a question trumps the discussion of how to best answer it. Expediency wins, and the person answering the question gets to use the tool of their choice. One top 10 bank reported using more than 100 business intelligence technologies.

I really like this, as long as you don't fall into the trap I discussed above.  To get people to adjust to a technology instead of providing insight is lost time.  Getting a huge organization on 1 platform is problematic at best, a disaster at worst.  If analysts can work in tools they have mastered, it will allow them to get insights faster.  Faster insight is a major competitive advantage.

Data flows up, down, and even side to side. In data-driven companies, data isn’t just a tool to inform decision makers. Data empowers more junior employees to make decisions, and leaders often use data to communicate the rationale behind their decisions and to motivate action. In one data-driven company, I observed a CEO present a 50-slide deck to his full team, and almost all of those slides were filled with charts and numbers. Most fundamentally, data empowers people to make decisions without having to consult managers three levels up — whether it’s showing churn rates to explain additional spend on customer services vs. marketing or showing revenues relative to competitors to explain increased spend on sales.

The old thinking was to create a business intelligence team that would provide the data for the organization.  Each operating unit should be in charge of their own data analytics.  There should be a centralized business intelligence team to provide a checks and balances, but operating units are best to answer their own questions, they know their business best.  Democratizing data throughout the organization is key to having a data-driven organization.  

Southwest Airlines Making an Impact in Marketing Automation

I love Southwest Airlines.  They have been the ,most profitable airlines by creating a business model which serves both their customers and their shareholders.  Southwest has managed to delight their customers and they are one of the few airlines that actually turn a profit, plus they haven't gone to the nickel and dime your customer model that has been popular in the industry.

The one area they have been weak in is database marketing/marketing automation.  The emails my wife and I get from them are very generic.  These emails have never been tailored.  This is the same in direct.  I have a Southwest Visa card and I still get an application direct mail to this day.  They also send some of these applications multiple times per week.  I tend to forgive because I am not a fan of the nickel and dime approach most other airlines employ.

Out of the blue I got an email that was actually targeted, well I hope it was targeted and not everyone received.  They sent me a tier upgrade promotion if I flew 3 roundtrips in a 2 month period.  To give a little background, I was flying much more a year and a half ago and I was an A-list, but recently I haven't needed to fly as much and I lost that status.  What I hope they are doing is looking to see that I have the propensity to become an A-List and they are betting that I will take them up on this offer. 

I happen to be taking a couple of flights in that time period, but I was going to be one roundtrip short.  Now this is where the psychology of tier benefits are interesting.  In my experience, a company doesn't necessarily get a customer to do something drastically different in their behavior to get to the next tier level.  This is true in my case.  If I hadn't been taking those 2 other trips, I would not have flown 3 roundtrips to make it to A the rest of the year.  But since I was taking those trips and I was going to be close, I decided to take 1 more trip up north and see my stepdaughters.  I would not of otherwise taken this trip.  So the promotion made them some incremental revenue and has kept my loyalty with Southwest.

This could be a less targeted approach and I just happen to think it is because of my propensity.  They send me an email last week reminding me of the promotion ending, however they did not reference I was 1 roundtrip away, so they aren't exactly where they need to be yet.  But, if Southwest can put together a strong direct program with their superior business model, then other airlines will have even more to worry about.  Here is to hoping they are moving in that direction.

Using Smartphones and Apps to Enhance Loyalty Programs - NYTimes.com

I am such a big fan of using rewards on a smartphone.  There is no better way to communicate with a customer than with the device they are carrying around in their pocket.  The next evolution for rewards programs is moving from a card in the hand or a punch card mentality to devices that allow even smaller businesses to compete against bigger competitors.  

Smartphones and loyalty apps have begun offering small businesses enhanced program features and automated administration capabilities once affordable only to large companies like airlines and hotel chains. These capabilities also offer the equivalent of a real-world psychology lab for easily evaluating the effects of offerings and incentives on customer loyalty.

The key to any reward program is to capture data about a customers behavior.  If your program isn't allowing you to capture transactional level data in conjunction with the program, there may be a need to consider this approach.  If only to capture the amount spend and the date, this will allow a lot more opportunity for the business.  As I wrote in The True Purpose of a Loyalty Rewards Program, it is imperative to have a program that incentivizes a customer to share their data with you, but not over-incentivize.  The key is to drive behavior by targeting the customer, rather than giving everyone the same rewards.

“Clearly, this is the best of times for loyalty programs,” said Mr. Bolden of the Boston Consulting Group, who recommended that small businesses “focus on the non-earn-and-burn aspects of the program.” He suggested that spas consider a separate waiting room for their app-identified best customers.

“Or when the treatment is over, you hand the customer a glass of Champagne and strawberries,” he added. “If you’re an apparel retailer and you get in a new line from a new designer, invite the top 5 percent of your customers in first so they can see it before anyone else.” The point is that many effective rewards need not cost much to bestow.

Driving behavior is not all about a discount.  Understanding what your customers want and delivering them an experience is more important than a discount.  Because a customer that is coming just for a discount is more than likely not your most loyal customer.

“With apps you now can target specific customers and influence specific behaviors and keep track of all the results and understand the results,” Mr. Smylie said. “Because the check-level detail is now tied to a customer’s profile, we can understand what their purchasing behavior is, what their interests are and cross-reference that against their social media profiles and market to them more effectively and involve them at a deeper level with our brand.”

 

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.  

Social Media: Stop It With Pointless Metrics

From Martin McDonald:

We’ve all been there, sat in a meeting with your boss, or client, and they’ve said something like:  “Our competitors have got 40,000 Facebook likes and 20,000 followers on twitter more than we do, we need to double down on our Social Media!”.

Let’s be perfectly clear, tracking social media based on likes, or follower numbers, is a pointless metric. For a start, both can be easily gamed, but increasingly platform are moving towards more sophisticated content targeting which for many companies means their chances of getting an ROI out of social media is significantly reduced.

I couldn't agree more.  I remember when we were first launching our social media sites for our brands at a casino/hotel company I was working.  We were so obsessed with gaining followers, yet no one was really engaging with the content we were providing.  Gaining followers was important, but if we weren't producing relevant content, then the followers would not lead to any brand equity.  

The analytics that Facebook and Twitter are putting out are a good start:

Social media should never be considered a “broadcast medium” ,  its no longer suitable as a one to many distribution – it should be considered a discussion medium, where you can engage your audiences with your message, your brand and your personality.

Moving away from messaging and towards discussion and interaction reveals the true metrics you should be concerned with: Engagement rates!

Measuring Social Media Effectively

Thankfully, both Twitter and Facebook provide lots of metrics, and have robust, free, analytics platforms.

Twitter recently revamped their entire analytics platform and its accessible to everyone with an account just by going to http://analytics.twitter.com and it provides in depth statistics on a per tweet basis. 

Being able to manage engagement has always been something I have been very interested in.  Content is king and just broadcasting what you're selling or information that doesn't appeal to the many of your followers will result in ignoring your messages.  This is very similar to email marketing.