Direct Marketing Strategy: Direct Mail Testing

Author: Maggie Stack, Account Director

At least once a week, while doing homework, one of my kids will say “when will I ever use this in real life?” I like to point out to them how often I use my Algebra skills, but I never thought I would use science in my marketing career. As my colleague, Alan Sherman, mentioned in a previous blog, we use direct mail testing to determine the best direct marketing strategy. This is where science comes in. By following the steps of the scientific method with a continuous improvement mindset, we aim to exceed our clients’ marketing goals.

Purpose

When thinking about our clients’ direct marketing strategy, our question is always how can we improve results. The exact Key Performance Indicator (KPI) we are trying to improve varies by client, but it always means a better Return on Marketing Investment (ROMI).

Research

We start by reviewing current marketing efforts. Who is the target audience? What motivates them to respond? What tactics are currently being used? How do those tactics work together?

Hypothesis

Once our research is complete, we make recommendations for the elements or options we believe will improve results. Sometimes this is the choice to reduce the cost of a campaign while maintaining response and sometimes it is a higher cost option that will improve response. This could be a new data source, a new offer positioning, a new direct mail format, or addition of a complimentary digital tactic. In direct marketing, the options are truly endless. Once we decide on what will be tested, we can begin the experiment!

Experiment

The two most commonly used experiments in direct mail testing are a split test and a multivariate test. Split tests, or A/B tests, involve testing the same package except for the specific element to be tested. Multivariate testing involves testing multiple elements at the same time. The right one to use is based on several factors: budget, available quantity, quantity needed for the result to be statistically significant, and the number of items we want to test. Once the experiment is in the hands of the prospects, we wait for results.

Analyze Data

Depending on what we are measuring, results could take months to gather. There must be enough responders to be confident in the results. Analysis comes in the form of charts and graphs. Our goal is to always improve results, but sometimes we learn what does not work. As my high school science teacher would say after a failed experiment, “if you learned something, the experiment wasn’t wasted.” In direct marketing, the win in a losing test is that it leads to better, more refined hypotheses.

Conclusion

While there is a conclusion to every individual experiment, direct mail testing should never end.  We believe marketers should always be striving to improve their data, improve their messaging, and improve the tactics they use. And we love partnering with those that feel that same. Looking to apply a little bit of the scientific method to your direct marketing strategy? We are here to help.

Bio: Maggie Stack is an Account Director with over 20 years of experience in marketing services and direct mail production. When she isn’t discussing data and creative with her clients, you can find her and her husband cheering on their children in hockey, baseball, and dance.

The Importance of Data in Direct Mail Marketing

Author: Alan Sherman, VP of Marketing Strategy

Quite often, when we work with clients in direct mail marketing, creative development is the first focus. But, just as in any marketing channel, who we target is just as important, if not more so for driving increased direct mail response and a successful direct mail campaign. For a full-service direct marketing company like Nahan, using data in direct mail marketing is a crucial component of an integrated success chain that includes strategy, data, creative and production execution.

Direct mail provides more data points to target against than any other marketing channel. The typical national data compiler manages over three thousand data points per person.*  Combine a multi-sourced wealth of data with sophisticated predictive analytics, and we can precisely rank prospects based on their propensity to respond (or other desired outcomes).

Let us take a look at typical data used by various direct mail industry clients. In the interest of time and space, what follows is not an exhaustive list.

Financial Services and Insurance – Credit Data

For financial and insurance clients, we see widespread use of credit bureau prescreened data – both in terms of trigger (credit or insurance inquiries by consumers) and broad market (often dictated by credit score and other data points) campaigns.

As a direct marketing service provider, Nahan partners with credit data agents, which can provide unique sources of value. Credit data agents typically receive and maintain real-time data from all 3 main credit bureaus, providing a comprehensive picture of all credit behavior across bureaus. More data across all 3 bureaus means more net qualified names, typically 15-20% more, and improved credit decisioning.

It also means more flexibility in terms of FCRA regulations, allowing for counts to be more easily run before actually pulling a file. Typically, when one pulls a complete prescreened credit file, one is obligated to make everyone on that list a firm offer of credit. Credit data agents have more flexibility in this regard. Custom models can make use of both credit and non-credit data for increased predictive power.

While credit data is usually the go-to data source for most financial and insurance acquisition mailers, it can often be supplemented by Invitation to Apply (ITA) data, which is primarily driven by a lifecycle event – such as college graduation, marriage, having children and buying a home. While ITA prospects are typically not as responsive, it is less expensive, and can be tested and paired with credit data as an effective supplemental data source.

Multiple Industries – Modeled Compiled Data

Compiled data is just that – data compiled from multiple sources and then linked to individuals and households. It’s typically used in travel, healthcare, retail, telecom, and auto direct mail.  There are a number of medium and large-sized data compilers that we partner with to provide the best data for our clients. Compiled data typically includes demographic, psychographic, and attitudinal data. 

Demographic data includes data elements like age, gender, income, occupation, and more.

Psychographic data is focused upon people’s interests and hobbies, often obtained via surveys, donations, and specialty lists.

Attitudinal data reflects attitudes and belief systems, typically from surveys and donations made to non-profits.

Compiled data is best paired with predictive analytics to identify the data elements that will give the greatest response.

Catalogers, Non-Profits, E-tailors and Others – Cooperative (Co-op) Data

Co-op data is customer purchase data collected from thousands of co-op members and maintained in a database. Typically, a member marketer must provide their customer data on a regular basis to join and participate. Co-op members include companies from the catalog, retail, etail, continuity, non-profit, publishers, finance, insurance, and business-to-business industries. Some co-ops focus on non-profit donation behavior specifically.

Co-ops collect over 1500 data elements for a given household and cover 190MM U.S. consumers. The depth and granularity of the data can vary by co-op. Given that customer behavior is often the most predictive of future behavior, this data is very powerful in its ability to predict the future response and purchasing.

Using marketer-provided customer purchase data, the co-ops use predictive models to find prospects elsewhere in the database with similar product and purchase behavior. Co-op data has long been a go-to data source for catalogers, replacing many of the more expensive specialty, “vertical” lists that exist, such as magazine subscriber files.

Business-to-Business (B2B) Data

B2B direct mail data used to come from two main data sources – Data Axle (formerly InfoGroup) and Dun & Bradstreet. They are still major players providing excellent data. Both, along with a continual flow of new players, now offer much more than the traditional data points like annual sales, number of employees, SIC code, and NAIC Code. Data points such as B2B buying behavior, public filings and linked consumer information all provide additional targeting insights. Because people change jobs much more frequently than they change addresses, B2B data is more challenging and labor intensive to maintain and keep up to date, resulting in a higher cost.

The Role of Analytics

The performance of all data mentioned here can and should be enhanced by predictive analytics. We simply can’t leverage any of these types of data to their full potential without the use of modeling to prioritize prospects. While a predictive model adds to the cost, it usually pays for itself in the first direct mail campaign with the increased direct response it produces. Depending on the circumstances, the model can be re-used until market conditions change. Machine learning and artificial intelligence have sped up the modeling process, and in certain cases, such as co-op data or credit models, new models may be built with every direct marketing campaign.

Our Data Role

Nahan has deep and long-time relationships with many types of direct mail data providers and list brokers. We can determine which source is the right fit for our clients’ objectives. Typically at a lower cost than our clients can obtain on their own. Our expertise ensures the best possible data at the best possible price. For any questions about data, please feel free to reach out to me at alan.sherman@nahan.com.

*Source: WebFX

Bio: Alan Sherman is our Vice President of Marketing Strategy. Alan enhances Nahan’s current value proposition with strategy solutions that support new/existing client relationships. For clients, he leverages market, customer, and competitive intelligence to build achievable strategies for omnichannel marketing success. His marketing plan strategies include targeted data, predictive analytics, testing and creative that drive ongoing client performance improvement. In his spare time, Alan enjoys spending time with his family, traveling, going to concerts, watching sports (he’s a fan of the NY Giants, Boston Red Sox and Celtics) and walking the dog, even though it was just out.

USPS Informed Delivery: A Great Way to Drive Increased Direct Mail ROI

Author: Melissa Fransen

If you are looking for a way to drive incremental responses and increased ROI from your direct mail campaigns, USPS Informed Delivery is a great way to do just that.

What is USPS Informed Delivery?

Informed Delivery from the United States Postal Service (USPS) gives consumers a sneak peak of their letter-sized mail (outer envelope or self-mailer image) before it arrives in their mailbox through a daily email that the consumer signs up for.

It consists of two main elements:

1) A large grayscale image of the piece or a 4-color representative image of the mailer.

2) A smaller, accompanying image that offers interactive marketing potential. Clicking on this image or on the “Learn More” call to action opens the URL associated with the campaign. It can also be used to open a marketer’s phone app for the recipient to call.

How Many People Are Signed Up for Informed Delivery?

As of 4/23/2021, the USPS reports that Informed Delivery has nearly 38 million users and a national saturation of over 22%.

Based on a 2020 Spring Mail Moment Study, the USPS reports that 50% of the audience surveyed had seen an interactive ad in the past 6 months. Of those, 74% have clicked on an interactive ad, and an astounding 63% had purchased from the website they accessed from the Informed Delivery campaign!

This presents a huge opportunity for marketers to drive incremental sales before the mail piece even arrives to the consumer’s home!

What Data Can I See as a Marketer with USPS Informed Delivery?

The following data is provided for Informed Delivery Campaigns.

  1. Density and Email Statistics (Number of users and % who elect to receive Informed Delivery emails)
  2. Email Open Rates (Number and % of emails opened)
  3. Click Through Rates (Number and % of people that clicked through on the digital content)

Nahan Can Help You Get Started

Our team at Nahan is here to help! We can provide input and guidance on setup, creative, measurement, and more with USPS Informed Delivery campaigns. Plus, as an extra bonus, the USPS is offering an Informed Delivery promotion later this year, so this is a great way to save on postage! Contact us to learn more!

Bio: Melissa Fransen is our Marketing Manager. She started with Nahan in May of 2017. Melissa is responsible for Nahan’s marketing initiatives, which includes everything from conference planning to social media initiatives. In her spare time, Melissa enjoys spending time with her husband and enjoying time in the outdoors with family and friends.