If your organization is like many Altair works with, the amount of customer information you have is restricted by the retrieval/input method.  For instance, your point of sale (POS) only captures name address, phone and/or email.  Even then you are counting on the sales associate to correctly spell and enter these elements.  Now you have two problems, a limited amount of data on the customer and potentially incorrect data from the POS.  Many times you would like to have additional variables to help drive decisions, or selections for mail campaigns/promotions but you can’t get there with what you have.

I worked in the banking world for over 15 years, and many of those years in the marketing/analysis side.  We always wanted to know more about our customers, but we didn’t always have the cleanest data or the most complete data.  I learned not only how to clean the data but get more matches by matching at the level of the corresponding data elements.  Given the amount of information you have you can get more data than you think.  There are levels you can match at that will help this.

Overlay match levels:

Individual – First Name, Last Name, Address

Household – Last name, Address

Address – Address only

Some data elements need be done at the Individual level (age, gender, etc).  However, many variables can be overlaid at the household level (Household income, Number of Children, etc), or the address level (house square footage, lot size, summarized credit data, etc.).  So even when the retrieval/input limits the information you have, you can add data to your customer file that enhances the capabilities for analysis and selection for marketing.

There is a full range of things that can be done to make your customer file work for you.

• Hygiene such as NCOA and Delivery Point Verification (DPV) can prepare your file for mailing.  This not only benefits marketing but billing and collection as well.
• Data append as described above can enhance decision making with additional information outside what’s been given.
• Profiling is the next step to learning more about your customer.  A profile is different than an append in that you are now comparing your customers to their peers in the same geographic footprint.  See an example of our profile here : Customer Profile
• Modeling outcomes are much more robust with outside data.  The combination of your data and the third party data allows for the prediction of outcomes such as booking a loan, responding to an offer or leaving you as a customer.

To learn more contact Troy Blackman at tblackman@altairci.com or 615-468-6821

Having multiple locations within a customer’s footprint is not a bad thing.  Although, sending a location based message can be challenging.  Sometimes the customer/future customer does not even know they have multiple locations to use.  In many instances you’ll already have your customer assigned to a “home” location but there could be additional locations you want them aware of.  To tackle the location assignment you can do a simple radius search from the home to the nearest locations OR as discussed in a previous blog you could use drive time or a primary market area.  ”Radius Based Selections“

Now you’ve got multiple locations assigned to each customer/prospect.  By using variables in your creative, you can add verbiage to your communication about your convenience.  “Don’t forget we have 3 locations within 10 miles of your home”.  Or we can pin point the closest store to each customer and add that stores address and/or phone number to your mail piece.  You can customize each mail piece with a few variable lines, and our help creating the data fields for your mail file.

Using a specified radius around your location(s) is a typical method of geographic selection for prospecting.   In many instances this method of selection works without a problem.  In some programs you need more sophistication.  When this happens we move to Drive Time or PMA.

Drive Time

Some stores are in a metropolitan area may only need to go out a couple of blocks, while others are in rural settings your customer may have to travel 5-10 miles.  We have found that using drive time calculations help reduce waste and pinpoint opportunities missed by simple radius pulls. Our technology allows us to pull list by drive time minutes or a straight line radius.  See example below of 5 minutes drive (Yellow) vs 2 Mile radius (Blue).

PMA

Beyond radius and drive time is PMA.  I say beyond because PMA takes into account the location of your customers.  In calculating the PMA for a bank branch we use the customers that recently opened an account at that branch to define the area around the branch for prospecting.  PMA’s will also take odd shapes like drive time as this naturally becomes a component based on the customer behavior.  The example below shoes the river as a natural boundary.  You also see that 60% of the customers are inside 5 miles and 80% are well within 10 miles.

Not only are these methodologies great for prospecting they also inform print, outdoor media, radio and TV.  Contact us to learn more.