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.

How To Win Customers Without Data-Driven Marketing

The human element – even for online businesses – always shapes the final judgment on customer retention and acquisition.

This is the exact reason why becoming a customer-driven organization is so important, even in the age of data-driven marketing.  In most cases a human interaction will determine whether customers remain loyal or churn.  This is part of the customer experience, just as much as delivering the right content to individuals to drive the desired behavior.  While data-driven marketing can handle most customer experience, for offline businesses and even online businesses, the human interaction is critical to handling the cases where things don't quite go as well as you hoped.  

The morale of this story is: make sure that your employees are your strongest, most amazing asset because the most sophisticated technology or data-driven marketing can’t replace what your employees can deliver – caring, thoughtful, on-the-spot customer happiness.

Period. Full stop.

here is so much talk about who owns the customer experience and why CMO's are reluctant to own the entire experience.  In this article the letter describes the interaction with Terry from the call-center.  Now this interaction is as much part of the brand as an advertisement driving a customer to a website or in-store.  This experience defines the brand, yet the overall person in charge of this is not the CMO, it is more than likely an callcenter manager that reports up through an operations division.  

This is where the customer-driven organization has to be a culture, not an individual.  It doesn't matter what the position title is, there is no one person that can be the customer advocate throughout large organizations.  The customer advocate has to be all employees, period.  There could be a person leading the charge, but until an organization has changed its culture to be truly customer-centric, data-driven marketing and great advertisement will never drive the most ROI possible because the organization is not focusing on the customer experience as a whole.  

For data-driven marketing to succeed doesn't need a customer-centric organization, there is a lot of value and areas to increase revenue.  My belief is all organizations should be customer-centric, this enhances all aspects of the business, not just the data-driven marketing side.

The State and Drivers of Data Marketing

What matters most is the optimization of the customer experience, relevance and (perceived) customer value as a driver of business value. Data-driven marketing certainly is not (just) about advertising and programmatic ad buying as some believe. Nor is it just about campaigns. On the contrary: if done well, data-driven marketing is part of digital marketing transformations whereby connecting around the customer across the customer life cycle is key.

Very succinct vision of what data-driven marketing is, it's all about the customer experience.  The advent of "big data" was nothing more than gathering extra data about the customers.  Gathering data is only the first step of the process, albeit a time-consuming one.  The good news is after the hard work of gathering the data has been completed, the harder part starts.  Once you have data, making sense of the data and creating actionable outcomes to enhance the customer experience becomes the goal.  This is very hard work.  It takes plenty of analysis and insight to reach this goal.  But the companies who will do this the best will be the ones that succeed in the digital age.

Among the key takeaways of the data-driven marketing report by the GlobalDMA:

• 77% of marketers are confident in the data-driven approach and 74% expect to increase data marketing budgets this year.

• Data efforts by far focus on offers, messages and content (marketing) first (69% of respondents). Second ranks a data-driven strategy or data-driven product development. Customer experience optimization unfortunately only ranks third with 49% of respondents.

• Among the key drivers of increased data marketing: first of all a need to be more customer-centric (reported by 53% of respondents). Maximizing efficiency and return ranks second followed by gaining more knowledge of customers and prospects.

I believe the first step in the process is understanding where the puck is going to be and skate in that direction.  Marketers are understanding this data revolution is coming and they are saying the right things in surveys.  The real question will be how to get there.  It's easy to identify problems, it's hard to implement solutions.  The marketers who will show they are adept at change will thrive in this new paradigm.  

Customer analytics is something I have focused my entire career.  In the casino industry we have had the optimal opt-in mechanism for many years and have collected amazing amounts of data about our customers behavior.  We have used this to create targeted marketing campaigns to our customers, so I believe in the direction the entire industry is taking.  Always start with the customer.  It will lead to creating better experiences and more profitable results.

 

Shoot for the Stars! 4 Ways to Bring It with Your Marketing Automation Platform

...marketing automation is an all-in-one marketing powerhouse, allowing you to generate leads, follow up with consumers, and even demonstrate return on investment. Think of your marketing automation platform like it’s a video game. Lead scoring and personalized email campaigns are just the first level. As you move up through the levels, you access more gold coins, superpowers, and additional lives until you are a powerhouse marketing machine! Below are four ways to move on to the next plane of marketing automation…and you don’t even have to battle the boss to win the game!

Many companies who purchase a marketing automation platform are doing it with a few use cases in mind, but embracing your marketing automation platform can change the way you do business.  Because these platforms can take in data, segment, manipulate and target communications, while also writing out to databases, these tools can enhance many business practices in the organization.  

Your marketing automation platform allows a change in thought process of what a communication is.  For instance, you might have an email marketing team, a mobile team, a social media team.  Well all of these are channels of communication and your marketing automation platform can manage a lot of the content being driven through these channels, while maintaining a consistent message to the customer.

3. Real-time Personalization

Imagine this for a moment: what if everyone who visited your website received a personalized experience? Let’s say you serve a number of different industries. Using a marketing automation platform, you can set up your website so that when someone in the manufacturing industry visits, she sees a different set of content, calls-to-action, and web copy than a visitor in, say, the finance industry. Each visitor has different needs—period. So, giving each individual a targeted experience, whether that’s providing him an industry-specific case study or inviting him to an industry-specific event, makes the information more relevant and encourages conversion.

Most organizations would never consider using their "email marketing system" they just purchase to delver personalized content to their website in real-time, isn't marketing automation an outbound tool?  Not necessarily.  Because marketing automation tools can listen for events and trigger a realtime campaign for 1, and then deliver results through web services, it allows for ultimate customization, even for inbound.

4. Go Mobile

Mobilization is becoming increasingly necessary. According to Nielsen, the average consumer spends more time online via mobile devices than she does via a desktop or laptop computer. And the majority of that time is spent on apps—not the mobile web. All-in-all, companies need to go mobile, but without the right tools, it can be difficult. Not only do you need a strategy, but you also need to work with much more data. But with the data from marketing automation platforms combined with mobilization strategies, companies can effectively implement mobile campaigns, whether that means a native app or an optimized page.

I'll continue to harp about the mobile strategy.  This is a channel that needs to be targeted to customer behavior, however it will be the ultimate channel when used properly.  The marketing automation tool can listen for cues, such as geo location and deliver a customized mobile experience for the customer, whether that be in-app content or push notifications, the marketing automation tool should be at the center of your mobile strategy.  

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.

How CMOs Can Make Sure Their Companies Are Customer-Obsessed

CMOs are charged with making their companies customer-obsessed — so they can win in an age where customers are highly empowered. But the irony is that many marketing shops themselves are not customer-obsessed.

I am continually thinking about the customer-centric approach and who should own it in the organization.  The CMO is the obvious choice, however are they the best choice?  I have seen where organizations have a C-level position, something to the tune of Chief Customer Officer.  This is also thought because it ends up being another level in the organization, another potential touchpoint in the organization that has to bring different groups in the organization together around one common goal.  I think it comes down to having the right person.

Marketers are predisposed to think about the market first. So why are marketers not naturally predisposed to be customer-obsessed? The answer lies in gravity — the gravity of the P&L and the associated product, solution or service performance.

It's always about the customer.  Everything should come back to customer analytics.  I think Finance departments have too much power in some organizations where high-level KPI's are all about a product or a service.  The problem with these KPI's is they don't go far enough down to the "people" who are driving those metrics.  It is similar to fixing a symptom instead of the actual source of the problem.

For example, the company sells 1,000,000 widgets and they want to grow this by 3% in the next quarter.  This is the entire wrong approach to the problem.  Widgets don't grow by 3%.  3% more customers buy widgets in the quarter.  It is imperative to start with the customer because they are the ones that are purchasing these widgets.  So to grow those numbers, marketers need to embrace the customers to grow their numbers.

I have spoken with many CMOs — across industries and geographies — and this common theme has emerged: Marketing’s relevance and performance is now predicated on putting the customer at the center of the universe. This is neither elective nor minor surgery. Most believe an overhaul — not a simple refinement — is needed to make marketing customer-obsessed and truly able to drive growth.

Changing to a customer-centric organization is a complete change in culture.  This does not happen overnight.  It takes a dedicated team with a singular focus many months to accomplish.  I once read to change a culture, a great organization with amazing focus will take 18 months.  There are not that many of these organizations out there.  The average is 4 years.  So organizations need to start their culture change today.  There is no time to waste.  The customer-obsessed organization will be the most successful in the new customer empowered buying dynamic.  

Business Intelligence vs Analytics vs Big Data vs Data Mining

To help you navigate the terrain of business data concepts, we’re going to give you a basic summary of what some of the most common terms refer to and how they relate to each other.  

This is a very good article on definitions in the data space.  So many times I hear executives talk about topics such as "big data", but they are really referring to analytics or data collection.  

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.

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.

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.  

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.  

Business Intelligence for the Other 80 Percent

Ted Cuzzillo writes for Information-Technology:

We give business people everything. They’ve got data, and often it’s clean. They’ve got tools, and many are easy to use. They’ve got visualizations, and many of them speed things up. They’ve got domain knowledge, at least most do. Tell me: Why hasn’t business intelligence penetrated more than about 20 percent of business users?

This is a great question.  So many organizations have executive leadership that says they want information, dashboards and realtime information, yet when provided to them, it goes unread.  How does this happen?  The answer is what most executives want is a story.  They want someone to interpret the analytics and let them know what they should be looking at.  The dashboards act as content for speaking points.  Executives want the most important numbers at their fingertips so they can spit them out at a moments notice.  

What executives want is the rest of the data to be fed to them in a story with a narrative.  Here is the data, here is what we believe it says and here is what we are going to do about it.  It coincides with my article Data + Insight = Action.  

What executives need is all of these parts (data, insight and action) in one analysis.  They need to see the data, using visualizations to make the data easier to read.  They need the insight of the business experts in the form of a commentary, succinct and to the point.  Then they need what action is the business going to take with this newfound knowledge.  With all of this information to arm the executive, they can understand and make a decision on what to do.  

To reach "The Other 80 Percent," let’s turn away from the “data scientist” and to the acting coach. “A lot has to do with intangible skills,” said Farmer. A lot also has to do with traditional story structure, which appeals to “a deep grammar that’s very persuasive and memorable.”

Storytelling isn’t a feature, it’s a practice. One practicing storyteller, with the title “transmedia storyteller,” is Bree Baich, on the team of Summit regular Jill Dyché, SAS vice president, best practices.  While others talk about stories, she said, most people seem to start and end with data and leave out the storytelling art. They fail to connect data with any underlying passion. “What we need are translators, people who understand data but can tell the human story from which it arose.”

There is always an assumption that is made from an analyst that a visualization or a table of data is plain and understandable.  A good rule of thumb is to assume the audience of an analysis doesn't see what the analyst is seeing.  If analysts start with this assumption, they can then tell a story of why this data is fascinating.  An analysis without text that explains why the data is interesting is going to fall on deaf ears.  Once the analysis gets to a higher level, the executives will not have time to create the "insight" portion of the data and they will either send the analysis back, or ignore it completely.  Always remember to include the data, with the insight as a story and what action is going to be taken.  With this formula analysts will become more than report generators.