In my family, one of our favorite games to play is to quote a line from a movie and guess what movie it is from.  In that spirit, I actually thought of a movie quote that meshed well with my blog topic today:  “We’re way past birthdays now”.  If you know the movie and the character, feel free to comment below.

Now on to today’s blog.  Many of the smarter companies today are taking a look at their customer data and transactions and developing customer segments and making marketing decisions on how to better engage their customers.  Of course, this is a good start, but it’s kind of like using your birthday or anniversary as a password—it’s better than nothing, but let’s look at going “Way Past Birthdays Now”.

There are three key factors, in addition to your customer data, that you must have to get the most out of your customer insight:

1.  Robust External Data— You need access to external data that can give you insight into the behaviors, purchasing patterns, and financial situations of your customers.  Access to online activity, recent purchases, and credit worthiness are important in painting a complete 360 view of your customer.  You know what customers are buying at your store, but you don’t know what they are NOT buying.

2.  Advanced Analytics— With all of the data, both internal and external, available today, it is critical that you find an experienced analytical resource.  More than just a statistician, an experienced analyst will have client-side experience and will be able to offer valuable strategic advice in addition to technical expertise such as segmenting your customers and building predictive models that will increase your results immensely.

3.  A FAN Reporting— A FAN (As Fast As Needed) Reporting means that you get access to your information in meaningful reports and dashboards as fast as you can act on it.  For some companies, this is monthly, some weekly, some daily and for more and more it is real-time.

Once you have these three critical components in place, then you can really get to know your customers.  You will be able to develop more accurate metrics on total wallet, share of wallet and market share.  In addition, you can better plan your engagement strategy based on the known behaviors from online and offline data including social media and web advertising scenarios.  And, you can determine offers based on risk and ability to pay.

The goal is to get a true 360 degree view of your customers.  Without external data, you will only have part of the story and you will be stuck at “Birthdays”.

In response to the poor housing market, job losses and an aging baby boomer population there has been a steady rise in multigenerational households. There are 16.1 million households that have two adult generations* and 4.3 million households that have three generations** totaling 20 million households representing 14.22% of all U.S. households. This dynamic presents a marketing challenge. In order to reach more consumers within multigenerational households there is an opportunity for our clients to focus deeper into each household. The head of the household is typically chosen as the contact for direct marketing unless the segment is defined specifically by gender or age. Multigenerational households create three additional opportunities: 1) reach younger generations returning home, 2) older generations moving in with children, and 3) indirect marketing to the head of the house. These three opportunities fall within both the prospect and consumer populations. In fact the added dimension of generations within cross sell/up sell campaigns creates great cohesion for your brand within the household.

The head of household that inevitably takes on additional decision making, creates opportunity to market to them on behalf of other generations. For example, marketers normally wouldn’t solicit 40 year-old consumers for Medicare, but in the instance of a multigenerational household that was recently formed by the addition of their 65 year old parent, it is worth considering. This represents opportunity for managers of banking, investments, and senior focused products.  Also, with the potential for pooling resources, financial services marketing to the multigenerational household will change.

Marketing to generations above and below the head of household opens up additional possibilities. The younger generation will be establishing financial relationships, preparing to become independent, and searching for permanent residence. The older generation may be helping pay down debt, adding on to the house or finishing the basement, and revisiting healthcare and financial needs.

A representative sample is seen below.  Contact me for the full chart.

*2 adult generations – within a household unit there are adults greater than 20 years apart in age. This household could be college graduates returning home or parents moving in with empty nest adults. A household is defined as the same address and same last name.

**3 generations – within a household unit there are adults greater than 20 years apart in age as well as school age children.

According to a Q4 2010 survey by Unica measurement, analysis, and learning is the most frequently cited bottleneck for marketers.  In the same survey, turning data into actions was a top priority of marketers.  This makes it clear that as the pressure to turn data into action mounts, the bottleneck of measurement, analysis, and learning will become even greater.  The marketers in this survey overwhelmingly agreed that additional technology would ease their pain.  Additional technology is like buying the cool Snap-On tool set and expecting the ability to fix your car to come with it.  This panacea proves to be dangerous because an Econsultancy survey reports that only 2 in 10 US and UK companies have a company-wide strategy for collecting and integrating data analysis with business objectives.

The real problem isn’t the technology.  I’ll leave software and hardware out of the equation because we all agree it is there.

The phenomenon of data collection and measurement not being part of the business objective is rampant in every vertical I’ve run across.  What’s worse, it is likely the most valuable asset you’ll have.  It doesn’t matter if it is banking, insurance, retail, entertainment, or healthcare.  They have reams and reams of data collected and stored in the hopes of one day turning it into the golden egg.  The famous, or more likely infamous, “Now what?” question:  We have billions of data points – Now what?

To make sense of the data first you must bring it all together.  In some instances that is easy enough, and in other instances you may need the help of someone with experience bringing together data from different sources and compiling the file for analysis.  At the same time, you’ll want to transform many of the elements into categories or groups that allow for better insight.  For instance a report that has dollar amount frequencies from $0.01 to $150,432.45 doesn’t help you, but buckets in denominations that make sense for your business will.

Once the data is together, you can see all the elements/variables you have available and you can also bring in additional variables that will always play a key role.  It’s important to remember you will have tons of information about what the consumer does with you, but not the outside world.  Third parties will have that data and can append it to your file.

Now you have a file that can generate as many reports as you have time and technology to handle.

Altair will be posting a series of blogs which will focus on the benefits of using a Primary Market Area (PMA) geographic selection to more effectively utilize limited marketing dollars.  Over the next few weeks we will address the building, implementation, measurement, and refinement of PMAs to help direct marketers improve marketing selection and increase Return on Investment (ROI).

Here is a brief overview to get you started:

• Defining your Primary Market Area (PMA) using Altair’s proprietary process brings the benefit of better geographic selection at the individual branch level.  The ROI at the location level will increase due to the ability to narrow or broaden the prospect pool based on the location’s ability to serve a particular customer.
• PMAs naturally account for surface road access, natural barriers and proximity to your other locations.   PMAs also outperform other methods of geographic selection.  By using your recently acquired customers as a base, we are able to select prospects individually using the most refined geo coding versus more blunt options such as radius or zip code.
• PMAs provide a relative measure of proximity across the branch network instead of utilizing a constant radius.
• Utilizing PMAs in conjunction with other targeting tools, such as a response model and selection criteria, allow you to further refine the selection of your best prospects.

Next, we dive into what you will need to build and how to build your PMA.

You’ve enhanced your customer file.  Now you are ready to begin the process of Understanding your customer.  Building one or multiple profiles will lead you into the next phase of Understanding, segmentation.  Profiles can be built on the entire customer base or a more granular level such as:

• Product – Dividing an insurance company’s clients into Term, Whole Life and Final Expenses.
• Channel – Dividing a retailer’s client’s by Internet, Catalog and In-store.
• Geography – Dividing a bank’s client’s by branch, state or region.

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Sure, of course you know exactly who your customers are.  You have their names and addresses.  You even know their transaction history with you.  You may even know some things like age and income if they have submitted that kind of information on forms.   But does this mean you really know who they are and who they are not?

At Altair we have been helping companies learn more about their customers by creating customer profiles that show distributions of 20+ attributes for your customers.  And more importantly, in order to add context, these distributions are compared against national consumer distributions along with index values so that you can see exactly what sets your customers apart from the herd.

In my most recent blog, Customer Intelligence Begins with Clean Data, I covered the preparation of your file.  Now, you are ready to begin enhancement of the file.

Enhancement of your customer file is more than appending data variables; it is appending the correct variables.  You want the data you add to your file to tell you something.  You want to be able to profile, segment and predict with the data you append.  At the same time you want to control the cost of the data in relation to the value it brings.

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Do you measure the success of your direct marketing with just the response rate? If so, you may not be getting a good measure of success. Especially for financial products, responders often fail to convert into buyers. This can be problematic if you are selecting prospects to mail by using only a response model. A strong likelihood to respond often means financial issues that mean a low likelihood of being approved as low credit-quality consumers seek additional credit.

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Sitting in a meeting with a client the topic of marketing measurement came up. I have worked with this client for almost a year now and it was the first time I was able to get them to look past response rate. A break through!

In the business of direct marketing we tend to focus on creative, print cost, production cost, and response rate. But many stop there. What about the other metrics on measuring a successful campaign.

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Most customer analytics projects should start with geography as geographic segmentation tends to be the most predictive elements in many direct marketing initiatives.

There are several key questions to consider when determining how to analyze your customers geographically:

1.  What mapping tool should you use?

2.  What type of segmentation should you employ?

3.  Will geographic segmentation work better than household segmentation for your offer?

Let’s take a brief look at each of these questions.

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