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.

 

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".

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

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

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

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

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

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

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.  

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.