Use Analytics to Understand Who Won’t Pay

Once you know who is likely to go delinquent, discontinue all marketing efforts to these prospects or customers. Again, this is a fairly straightforward analysis—simply analyze a group of customers who left owing you money. Understand what this group looks like, in terms of their demographics and lifestages. Most importantly, obtain a thorough understanding of how they transact with you. Finally, if you can, use credit attributes to understand how customer/prospects are meeting other credit obligations. If they have stopped paying their mortgages, for example, there’s a good chance that they may stop paying you next.

While this type of analysis may be ongoing within a company’s credit management department, it’s not always widely used by marketers. Unfortunately, we’ve found it pretty common for a firms’ credit department to rarely communicate with the marketing department (and vice versa). By simply opening up the lines of communication, you’ll be astounded at what you can save in terms of marketing dollars.  And, you’d be a hero with your risk management personnel, too. Wouldn’t it be great to make your CFO happy by showing her/him that you are effectively managing the risk of your customer portfolio as you continue to bring on new clients??

As direct marketers, we want to reach as many people as possible; we want high response rates. However, it’s key to keep approval rates high, too. The secret is finding that appropriate middle ground – where you are taking on some risk but still building your overall profitability.

The ROI is pretty easy to build, in terms of justifying the dollars to perform a non-pay analysis. Look for two things: (1) Dollars saved by not marketing to high risk customers/prospects, and (2) Long-term risk mitigated by not bringing on new customers who are unlikely to pay.

Be a hero in your company!  Let your leadership know that you, too, are focused on the bottom-line profitability of your company.

TGIF!

Making the Case for Utilizing an Analytical Approach

We thought it may be helpful to share some of our ideas on how to integrate analytics into your direct marketing strategy.  We’ve created a step-by-step guide that outlines our approach, and thought we’d give you an idea each day this week on this blog.  We hope you find these posts helpful!

Here’s the first nugget:

Use Past Results to Predict the Future

This is the easiest type of analytical work to justify.  Essentially, use statistical modeling techniques to understand what worked in the past and then project those learnings onto future campaigns.  The classic example is your traditional direct mail response model.  Essentially, your analytical resource will study prior mail campaigns to predict future mail results.  Using statistical techniques, they will develop an understanding of who is responsive to your offers and who isn’t.  A model will be built that ranks prospects by their likelihood to respond.  Your prospect universe will be divided into 10 deciles (or demideciles, if you prefer) and a projected response rate will be assigned to each decile.  The projection will not be a ‘guess’ as it is based on actual response rates to prior mailings.  If your analytical provider is doing the job right, the projected response rate will be highly accurate.

Next, think of how you can translate this knowledge into ROI development.  You’ll know with a high degree of accuracy what type of response rate to expect from your next mailing, depending on how deep you’ll be mailing into the model.  Using historic conversion rates, you can now predict how many sales you’ll be able to generate from the mailing campaign.  A quick comparison to campaign costs will allow you to determine how profitable the campaign will be.  If your firm has a handle on lifetime value, you can even demonstrate the long-term value of this new customer you just brought in the door.

Another way to maximize the power of analysis of prior campaigns is to determine who you shouldn’t be reaching.  Taking the above example of a response model–if you know from prior behavior that a prospect is highly unlikely to respond to your offer, you should simply STOP marketing to this group.  One of our financial services clients used our response model simply to eliminate those prospects who looked nothing like their responders and customers.  They stopped mailing to the bottom scoring 30% of the prospect universe and still acquired the same number of new customers.  Since this client mailed more than 1 million pieces each and every month, you can imagine the money saved by eliminating 30% of non-responders.  In this case, the modeling work paid for itself in less than one month.  This was an easy project to cost-justify!

To summarize—wherever possible, use the past to predict the future.  Then translate predictions into dollars gained by acquiring more new customers, or dollars saved by marketing only to the right prospects. 

We hope you enjoyed this first step from our analytical workbook.  Stay tuned this week and we’ll provide you with the other steps to  integrate an analytical approach into your direct marketing strategy.

Smarter Marketing: Using Analytics to Improve Direct Marketing Success

 By now, you probably know that we are huge proponents of utilizing an analytical approach to direct marketing. As a matter of fact, our clients have told us that this is the core competency that sets us apart from our competitors. As such, we love it when someone has come up with a new analytical idea that assists direct marketers in more effectively reaching a specific audience.

DM News reports today that TransUnion and Edgar, Dunn and Company have come up with such an idea, and have built a model that is currently in the testing phase with one of their largest customers to do just that — help credit card companies more effectively target consumer revolving credit card users. According the the article “The Revolver Model is marketed primarily to credit card issuers, banks and other financial institutions that issue credit cards. It shows consumer preferences on managing credit card balances, credit card use and use of other forms of payment, such as debit cards and cash, and is intended to help card issuers manage and segment product portfolios and focus offers to new and upgrading customers.”

We’ve all seen credit models used before for prescreening potential consumers — particularly in the financial services market. This one is a bit different in that it looks specifically at the consumer — as opposed to past behavior data from a single card issuer. In looking at all of the credit cards that a consumer utilizes, you can really determine their spending behavior, how open they are to revolving debt and how they use cards over time. As Beth Costa, director at Edgar, Dunn and Company states: ““The Revolver model gives a holistic view of the wallet and can bring in what is the consumer’s attitude towards revolving balances and rewards, and how they use debit cards, cash, checks and the whole equation.” Pretty darn nifty!

The article reports that this model was built on a survey of more than 10,000 consumers that the two companies conducted in 2007. It will be interesting to see how effective this analytical tool works for the financial services market.

As you plan your direct marketing campaigns, we urge you to consider utilizing an analytical approach. Put simply, integrating analytical intelligence with your DM campaigns will make each campaign much more successful — both in the present and in the future. We’ve written an Analytical Workbook that may be of interest to you if you’re heading down this path. Let us know if you’d like a copy and we’ll be happy to send it your way.

Direct Marketing Segmentation Ideas

As we work with our clients, it becomes more and more apparent that having an advanced segmentation game plan is important to your success. This is such an important idea that we’ve written a white paper on this very topic. In today’s post, we wanted to give you an overview of our thought-process on this concept. In our humble opinions, if you use analytics, smart business sense and tactical/practical deployment, you’ll be able to better target and sell to your customers and prospects.

Here’s our Checklist for Effective Direct Marketing Segmentation:

1. It’s all in the Analytics! It’s important to have an analyst who not only knows statistics, but who also has an excellent grasp on real business needs and objectives. Oftentimes, we’ve seen our customers engage really intelligent statisticians who don’t understand what the business is attempting to accomplish. This is a recipe for disaster and a lot of wasted time and money. Statistics alone don’t get you a lot. Additionally, if you have to take your valuable time to figure out how to utilize them — or force them to fit your business scenario — it equates to a lot of lost effort and frustration.

2. Make It Actually Work. Sometimes, if you don’t plan correctly, segmentation systems are too complicated to actually use. I know, logic tells us that we are too smart to allow this to happen — but we’ve seen really bright people who didn’t put enough forethought into how they were going to use their segmentation schemes, and were actually stymied as to how to make them work once they were delivered. Start simply — and ensure that you’ve mapped out the important business factors that will drive your segmentation schemes. Ensure that you’re not over-customizing or making your system overly complex because, we’ve seen that when this happens, the segmentation systems sit on the shelves and never get used because they are so difficult to understand and implement.

3. Now, Use Your Segmentation Schemes! Now that you’ve gotten the insight from your business-savvy analyst, and she’s provided you with a system that is simple — yet accurate — it’s time to have some fun! Perhaps you’ll start with tweaking a couple of your creatives to better speak to those segments that are found to be most highly profitable. Look at who your customers are and figure out how to best get your message to them — and to have them react to it in a positive way.

It’s really that simple. If you put some thought into who you use and what direct marketing problem that you want to solve through the creation of a solid segmentation scheme, you are going to be able to more accurately speak to those customers and prospects with the important messages about your products or services. We’ve seen some great successes with our clients when we’ve worked with them on building intelligent segmentation schemes. This can prove to be highly profitable — because you are marketing intelligently and using the right messaging for each customer segment.

If you’d like to read our full white paper on this subject, either comment on this post or send us an email to info@rrwconsulting.com. We’ll send it over to you!

Analytics Overview

We firmly believe in the power of analytics.  We use analytics to turn data into intelligence, ultimately boosting overall marketing performance. Our combination of analytical skills, smart business sense and experience in implementation helps businesses better target and sell to their customers and prospects.  We specialize in three areas:

1.  Customer Profiling

2.  Modeling for Profit

3.  Segmentation Solutions