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.  

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.

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.  

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.  

When it Comes to Data, Small is the New Big

A great example of taking the data you already have by Anthony Smith:

Customer data is a commonly unrecognized superpower. Companies that provide software as a service (SaaS) are especially likely to have massive amounts of uncategorized, unmanaged customer data, creating a well of potential that largely goes unused. This data, when analyzed properly, can provide companies with unlimited opportunities to improve product functionality, increase customer satisfaction and stimulate business growth.

As I wrote in Data + Action = Insight and Back Again, big data is not necessarily the next key driver for a business.  The next key driver may be harnessing the data you currently have and using that to glean more insight.  Once you have this insight, you can develop new strategies and tactics to deliver targeted content and create great customer experiences, which in turn lead to increased revenue.

Anthony talks about how he did this with his company and I believe so may companies can do this too.  Make sure you have exhausted all current data possibilities before leaping into "big data".  The data you have may be the next key driver for your business.

Busy is not a Strategy

One of my favorite people once taught me the mantra of "Busy is not a Strategy".  So many businesses use the wrong metrics or KPI’s when measuring success of the business.  For brick and mortar companies, their eyeballs tend to deceive them and they use that as their main metric (we were so busy).  For other industries it is market share.  How many widgets can we sell.  The problem can be using the wrong KPI’s along with having the wrong culture can lead to an unprofitable business.

I have implemented the “Busy is not a Strategy” with resounding success before.  We had a casino/hotel in a declining market that had 1,800 rooms.  They were moderately successful considering their location, but they were using the wrong metrics.  Their KPI’s were hotel occupancy and casino revenues.  Now anyone who knows the casino/hotel business is going to ask, what is wrong with those metrics?  They had good casino revenues for the market and an occupancy of 87%.  Most anyone would love these numbers.  Plus, they were really busy.

When we took over the business strategy of the property we saw to get these impressive numbers, there were a lot of giveaways and very low hotel room rates.  To drive the wrong metrics, they were servicing a large number of unprofitable guests.  The belief was if the hotel is full, more profits would eventually flow to the bottomline.  There was just one problem, the other centers of business were not large profit centers and the customers coming in at very low hotel rates did not gamble, because they didn’t have a lot of money.  

To increase profits, we decided we were not going to busy, we would focus our attention on the best customers and try to drive more frequency from these guests while sacrificing the low-end of the business.  This resulted in decreased occupancy and decreased casino revenues.  Uh oh.  Hotel occupancy went down to 44% and casino revenues were down 10%.  The operators were crying “the business is being ruined”.  Even competitors were coming over and asking the operators “are you going to be able to remain open until the end of the year”.  There was pure panic.  That was until the financials came out.  EBITDA was up 100% for the quarter.

By focusing on the best and most profitable customers, this property saw increases where it mattered most, the bottomline.  How did this happen?  The expenses to drive the KPI’s that were important to this property were astronomical.  They were essentially competing for market share instead of profit.  What happened through time, is the best customers started to come more often as that was the new focus of the property.  Casino revenues started to increase through time to levels much higher than before the strategy change, however occupancy remained at 44%.  They did this by focusing on:

• Increase frequency of their top tier from the players club
• Increase hotel room rate
• Target giveaways to the more profitable sector of the database
• Increase customer satisfaction of the best customers

This is very similar to what I see is happening in the phone industry.  There are many manufacturers and most of them are focusing on “Busy” as a strategy.  Now the metrics for busy in this industry are phones sold and market share.  Android accounts for approximately 80% of the worldwide market share for phones sold.  Yet when it comes to profit, that metric is almost reversed.  In fact it is a lot less than 20% in the last quarter.  So how can this be?

The phone manufacturers are selling basically the same thing.  They run Android software that they manipulate in small ways, but all the apps are compatible with their competitors.  This creates an experience that cannot be differentiated in any way but price.  This is the same thing that happened in the PC industry.  All manufacturers ran the same operating system, Windows, and they had to compete on price which forced them to make deals of adding bloatware onto their machines that destroyed the customer experience.  This is where the phone industry is heading.  When price is the main differentiator, businesses eventually will go out of business unless they can outlast the competition.  

So these OEM’s sell many millions of phones to increase market share which leads to…  To what?  I don’t know.  From what I have read these manufacturers have a decent amount of customers that are buying new phones, but they are buying them for the price.  So the manufacturer sold an unprofitable phone so they can gain a customer who will buy another unprofitable phone.  That doesn't sound like a sustainable strategy.  There is nothing that differentiates the experience of the customer enough to make that return customer more profitable.  It is a vicious cycle.  

The only company that is running a different strategy is Apple.  Apple is making almost all of the profit in the phone industry by having a differentiated product that is customer focused.  Apple is doing the same thing in the PC industry, their Macs account for about 10% of the market, but more than 50% of the profits.  Apple has been able to run the “Busy is not a Strategy” strategy to ultimate success.  Sure Apple sells a lot of phones and they would like to sell more, but these sales are the outcome of their strategy, not the focus.  Apple has a culture that is design focused which leads to a product that has a better customer experience.  

Apple is dominating the phone industry because they do not bow down to the marketshare gods.  They focus on the customer first through their design culture.  They make profitable, differentiated products which bring in the majority of the profits in the industry, which then allows them to spend more money on R&D to create more products and services to keep their customers in the ecosystem.  These customers buy new phones at a nice profit which creates a beautiful cycle.  All because Apple is NOT implementing “Busy as a Strategy”