Pine Creek Fire

What happened on my summer vacation?

Usually this blog is about my day job - marketing, technology, data, etc.   Today it is a bit more personal.  

Just south of town a forest fire started on Wednesday and has grown from 20 acres to 12,000 in less than 48 hours.   Not only did the fire run up the drainage toward the tops of the mountains, but it also ran south as the winds shifted around.

Livingston Enterprise Photo

And when you know the people who live in the house in the picture and they're planning on evacuating their horses, possessions and memories this kind of news takes on a whole new perspective.  

We had a barbecue last night and it offered a respite to a few of those who couldn't return home and didn't yet know when they could.  Glad we could offer a small community of support to our friends.

Speaking of community, the news of the fire spread quickly on social media - particularly on Facebook - with support, best wishes, and offers of assistance coming from all locations.   The 'chatter' as it was called by officials unfortunately had many inaccurate statements about the burning of particular buildings and the loss of life.   While some structures were lost no one perished in the blaze.   The lesson is to take such news with a dose of skepticism. 

Hopefully the cooler weather with slow this beast down.

Seven Things Marketing Should Know About Big Data

What are the key points to remember about Big Data?

1. The migration to a digital and interactive world creates breadcrumbs of all types everywhere; this in turn dramatically increases the velocity, variety and volume of data.   We need to rethink just what it means to be data.  
2. Big Data is so big that our historic view of processing it - requirements, capture, analysis - just doesn't work anymore.   For those of us who grew up in the marketing database era, we have to completely rethink our relationship with IT.  And IT will have to rethink its role.
3. The idea of Big Data will go thru the typical hype-cycle where it becomes the topic of conferences, technology pitches, and bloggers (including me).  Thus, it will mean different things to different people and that requires patience and a steady hand to navigate.
4. Like all large, complex, and fast moving worlds the best approach is to have a clear objective in mind before you start.  Set the goal first to help deal with the really messy aspect of Big Data - access and transformation.
5. Since the majority of the Big Data is now created 'out there' rather than from just buying stuff from us we have the ability to understand the path to purchase much better than ever before.  New understanding of what happens at each step in the journey will be required thru 'moment' or 'value' mapping exercises.
6. Given that we want to derive insights from Big Data, the deployment methods will have to change.  We can't assemble in a conference room to discuss changes in offers and messaging - we must learn to trust the data and let it decide within a framework.  Predictive analytics will be operational, not project-based. 
7. Your brand promise will have a strong guiding hand on how you leverage Big Data. Understanding what benefit consumers takeaway from your product or service will help you decide how best to facilitate their journey and choice.

The New Face of Database Marketing

Where is database marketing headed?

In the beginning database marketing was defined as

"Database Marketing is an interactive approach to marketing, which uses the individually addressable marketing media and channels ... to extend help to a company's target audience; to stimulate their demand; and to stay close to them..."

That was written just about 25 years ago and still resonates today.   What has changed dramatically is what it means to be 'individually addressable'.   The newest Facebook feature, Page Post Targeting Enhanced, allows messages to be posted to the news feeds of specific segments of people based on a wider variety of demographic information, but not 'likes' at the moment.   Before this the best we could do to narrow the audience was by language and location.  Thus, the FB news feed, once a broadcast tool, now qualifies as a database marketing tactic.

But that's not all.

On the flip side is the opportunity to serve different content at different frequencies to different segments.  So, rather than thinking linearly about who should receive our offers, we need to think in terms of a matrix - which segments get which offers?  This is beginning to sound like how we think about other digital marketing tools where offers or ads are dynamically generated based on context, consumer, and intent.  The implication is that database marketing skills should be combined with digital marketers in a direct-to-consumer function.   Their responsibility is to place offers along the shopping journey that help, stimulate, or connect with the target.

Now, if we combine the legacy of database marketing - using a customer's transaction history to do it 'right' - with the new digital capabilities some new ideas emerge.  Imagine a news feed of

• Recipes augmented by offers based on your previous purchases and content consumption
• Books or music recommendations based on interests, current collection, and friends' lists
• Exclusive content and promotional tie-ins from sponsors of events

For any brand considering these ideas, they should have a large fan base.  Thus, an integral part of the social media plan should be on acquisition - just like database marketing. 

Relevance vs. Incentive

What are we trying to achieve with relevance?

The typical phrase used to describe content is 'be relevant' but what is discussed around content tends to be offer-related.  A lot charts that appear in retail research and presentations suggest that consumers want offers, deals and promotions.  But is that all we mean by the phrase 'relevant content'? 

Some definitions first:

• Relevant refers to being 'pertinent to the matter at hand'.  
  
• Incentive refers to 'stimulating action or effort'.

It is likely true that as consumers we prefer retailers that apply business rules to the potential offer pool to ensure we find things of interest, i.e. personalized coupons based on transaction history.  And it is a small logical leap to go from using the term personalized to relevant.  

While custom coupons are relevant; is all relevant content necessarily promotional?  

It seems that our point of view need not to be the same when it comes to relevant vs. promotional content.   In the first case we need to understand what the consumer is trying to achieve; in the second case we need to serve our best option to generate an event or transaction.  Similar, but not quite the same.   In fact, there may be other types of content that are appropriate depending on the context of the situation.  And it is context, both the consumers and ours, that should shape our content strategy.  

If we want to help her, be relevant by first understanding what she is trying to achieve.
If we want a sale, offer incentives that make sense to her and mitigate the risks of decisions.

So, let's first be clear about what we're trying to achieve.

Context Generates Big Data

Where does "Big Data" come from?

Lots of discussion these days about "Big Data."  A technical term that made its way fairly rapidly into the daily discourse.   Simply put, big data is the result of the increasing velocity, variety and volume of information being generated as we act like cyborgs.   A recent NYT article describes how we got here and what the opportunities might hold for businesses.  

On the one side of the real are the half-empties who worry that the term 'big' is another nefarious character who wants to control our lives - brother, government, and oil come to mind.  This is the central argument around behavioral targeting - too much data is a bad thing.  For the half-full's amongst us, big data allows for some interesting concepts for marketers, not only in terms of relevance but also in terms of incentive. 

One current idea being tested is the creation of personalized pricing where everything that is known, inferred or surmised about an individual is used to set the prices a specific customer sees. These price differences may be in flyers, coupons, or at the shelf. And since smart phones are the new decision support platform prices could be different in and out of the store. 

The mantra of delivering relevant content to the right person at the right time in the right place means context matters.

And thus it is context, and the need to understand it in real time, that drives big data.

Customer Replacement Therapy

Where do we need to focus our attention?

In many circles the discussion focuses on customer loyalty; it sounds so good.   But the reality is that we lose far more customers on the way to loyalty than we care to admit.  In fact, the odds run 19 to 1 against.

First, just what do we mean by loyal?

Like many concepts in marketing it can be elusive to define what we mean.  For this post, I'm going to define it simply:  A customer is loyal if the probability of another visit exceeds 60% so a bit better than flipping a coin.

Since we tend to be creatures of habit, the probability of shopping somewhere is fairly predictable at least in aggregate.   In fact, we can fit a curve to estimate the number of future transactions a business is likely to have from a cohort of new customers.

The picture shows the results of estimating how many future transactions a group of new customers will make over the next year or so.  The steep drop off from 0 to 1 is quite typical and is a function of the category purchase cycle.  But the crux of the matter is very clear, a lot of people simply don't come back for a second visit.

Given the definition of loyalty above, that doesn't happen until the 4th transaction or higher where the step change from one transaction to the next starts to get small.

The implication:  We go thru a lot of customers to get to one loyal customer.   To see the effect of this curve on a business, imagine starting with 50,000 customers and we want to know how the business looks after 10 years.  In particular,

• How many loyal customers do we have?
• How much focus do we need to spend on acquisition?

The following table simulates the above curve over time and shows the number of expected customers each year by the their visit number.

After 10 years, fewer than 5% of our customers are loyal.   More importantly, 60% of our business comes from new customers. 

So, rather than burn thru bodies to get to loyalty maybe we should think more about our replacement strategy. 

• Why do over half of our customers fail to come back?  How did we disappoint them?
• Why does it take so long to go from trial to loyalty? What are people thinking at each stage?
• What is the essence of our offering that makes the decision to repeat a no-brainer?

Impossible Marketing

What does a walk-in computer have to do with marketing?

Recently a colleague circulated Joel Runyon's chance encounter with Russell Kirsch the inventor of the first internally programmable computer who pretty much summed up his view as: "nothing is withheld from us which we have conceived to do." 

Or, just do the impossible.

And to put a finer point on the idea of conceiving something never done before he also created the first digital image.  And 50 years later we're still living with the square pixel - it was 'logical' to use.

While the storyline centers on computers, particularly those we can use to create stuff versus merely being consumers, the idea clearly extends beyond code and technology.

In fact, this mantra describes the entrepreneurial spirit pretty and should be applied to marketing as well.  The digital era creates the perception and need to both re-imagine how things work and then solve the consumer's need for solutions.

So, what should marketers conceive in the new ROPO world of researching online, purchasing offline that many might deem impossible?  A couple of recurring themes.

• Altering the product assortment that a consumer recently browsed.
• Surrounding the consumer with real content that actually helps her choose.
• Leveraging purchase and event histories to create a media plan for one.

While there are technical challenges; these are not technology problems.   They simply require a will and persistence to overcome.

What would you think would be impossible?

Choice Marketing

What is the next evolution of marketing?

It has been said a million times: Marketers are no longer in control.  Self-expression, technology and media fragmentation have fundamentally altered the flow of information.  As a result we live in a "fluxed-up world" (found that on an agency bio) which is a bit more earthy and descriptive than the fluid fog.

So, if we're not doing business as usual then we shouldn't be doing marketing as usual.  So, what augments Brand Marketing, Direct Response Marketing, Content Marketing, etc.?

How about 'choice marketing'?

People are going to make choices, they will decide regardless of what we do.  Since we can't limit the information they use to reach their conclusion or where they access it, let's flip the table and ask the question:  What can a brand do to facilitate a person's choice?  How do we make it easy to choose us?

• Do we understand the needs and aspirations?
• Do we know the intent of each interaction along a journey?
• Do we know the emotional and rational drivers of the decision?
• Do we know how various types of content influence that decision?
• Do we understand why and how a consideration set is formed?
• Do we know the shortcuts people take in making a decision?

Since a brand is a proxy for information (Chris Anderson from wired's view) or an emotional short cut to a decision (my view) maybe a brand is simply in the information business; it is an aggregator and sometimes filter. 

Actually, 'choice marketing' would be what an agency would sell to its clients.   An altogether different view would be to focus on 'facilitating choice'.   While the wording change may seem simple, the implications of taking the consumer's point of view could be rather striking.