We believe a data-driven marketing plan is the most effective marketing plan, and it’s at the heart of everything we do here to make your marketing campaign a success. Whether we’re working on a direct mail campaign or an integrated campaign with digital advertising, here are some of the ways we integrate data to drive greater advertising ROI.
- Our Strategic Analytics team brings together many types of data to create a much more insightful view of your customers than a geography-based mailing list. They create a mailing profile that tells you who your best customers are, where they live, what they like, and where you can find prospects that most resemble your customers.
- Do you know what offers work best for your products and services? We provide you the ability to test what offers are more likely to drive response from your customers and can track responses at the household level.
- We use data to create quality maps to assist our customers in visualizing where their best customers are located and identify how they can reach them with different types of direct mail.
- Our Strategic Analytics team can analyze post-promotion data and deliver actionable data solutions to help clients refine their message, improve mailing profiles, and increase their advertising return on investment.
- We analyze data to help our customers shape their marketing messages to their target audience. The data we produce provides insights on how to differentiate your marketing message to your customers.
- Data analysis is a broad term, but we use it by design because we use data in so many different ways.
- As mentioned above, we analyze data to create impactful mailing profiles to deliver your message, help you determine the best offers for your products and services, as well as report on your campaigns and create a plan of action to use moving forward.
Micromarketing is another way of saying that we develop a marketing strategy in which your direct mail advertising efforts are focused on a small group of highly targeted customers.
For example, if we’re working on locating areas for a pool company, we want to find areas with owner occupied, single family homes. Those homeowners need to have the financial means to purchase a pool. For this type of client, we would want to pull areas with the highest percentage of homeowners with above average income (for the trade area) combined with any survey data we have for pool ownership. By focusing on a smaller group of more likely and qualified pool buyers, you drastically reduce the amount of wasted advertising spend, which increases your return on investment.
For a casual dining client, we might use a drive time to create a trade area (10-15 minutes for example). Then, based on input from the client or info from their investor reporting, we can tailor our customer targeting data. We might consider competition, disposable income, propensity for dining away from home, percentage of children, or specific survey data related to that client. This type of data analysis allows us to focus on a smaller subset of customers, which is a much more insightful and profitable way to approach your direct mail advertising campaign.
These examples are just a small sample of the many things we take into consideration when developing your mailing profile. When we put all of that data together, we give your message the best chance possible to be seen by the right customers at the right time.
This form of data analysis calculates the market penetration based on the number of customers within an area compared to the total household population. In other words, this data will tell you how many of your current and potential customers reside within the areas you wish to mail. This is another way that data analysis can save you money because it eliminates the need to send your message to every single person in the geography. Eliminating waste helps increase ROI.
The lifestyle analysis reveals lifestyles, behavioral characteristics, and purchasing preferences for a client’s customers, creating a portrait of a company’s customers. This reaches one step further than a customer penetration analysis. Customer segmentation allows us to discover the customer’s affinities and preferences by coupling lifestyle characteristics with customer expenditure, behavioral data, and brand preferences from syndicated research sources. You may be asking, “How does this help my business?” A lifestyle analysis provides a complete understanding of your business’s customers, shopping patterns, media preferences and consumption habits, cross selling options, and loyalty patterns and opportunities.
Many direct mail companies are only able to provide lists in a radius around your business location. While this is a standard practice, we believe that the “spray and pray” method of sending out your message to everyone around your location is an outdated way of thinking. It is also a waste of your hard-earned money, especially when you have the option of creating a much more accurate profile of who your customers are, where they live, and what they like. That is why we call the end-product of our data analysis a mailing profile. It gives you a complete picture of who you are trying to reach and the best way to reach them.
Why settle for a random list when we can offer you a mailing profile that considers so much more than geography alone?
This pyramid represents all the different types of data we pull together and analyze to create your mailing profile. If you look at the pyramid structure, you can see how the data is stacked by order of importance, creating a holistic mailing profile. The higher up the pyramid you go, the more focused and accurate your mailing profile becomes. By layering in these different types of data, we give you a highly customized and accurate picture of who your customers are and where they are located.
There are two different types of data we analyze to create your mailing profile: predictive data and your client data. Predictive data refers to everything on the pyramid that is underneath “Client Data.”
Predictive data is a combination of geography, demographics, consumer expenditures, consumer behaviors, and brand preferences. In other words, we want to understand who your customer is, where they live, and what they like. We access this predictive data through various sources, and our Strategic Analytics team brings it all together to find your best customer.
Let’s break down each category of predictive data. This will give you a better idea of just how effective a mailing profile built from predictive data can be for your business.
Types of Predictive Data
Geography
- The first piece of the puzzle is geography. When we talk about geographic data, we are referring to targeting based on geographical location only. Simple radials around a store location are the most basic geographic targeting we do. Other methods for determining geography include drive time, DMAs, MSAs, and selected geography (like zip codes).
Demographics
- Our next set of data comes from demographics. These data come from the U.S Census Bureau. Examples of demographics include (but are by no means limited to) age, ethnicity, income, home value, home ownership, and household size. Demographics are very powerful and easy to use, but they do have a drawback – simplicity. Demographics only tell part of the story. That’s why we use them in combination with other data sets to create a more accurate mailing profile.
Consumer Expenditure
- After demographics, we look at consumer expenditure data. This data comes from the U.S. Department of Labor’s Bureau of Labor Statistics. These data relate to how consumers are spending their money in the marketplace. Examples of this data include pet food, men’s apparel, food away from home, healthcare, gasoline, transportation, entertainment, and much more. This data is great at giving you a category-level view of a consumer’s propensity to buy, but it does not include brand or demographic information.
Consumer Behavior and Brand Preference
- Consumer behavior and brand preference data pick up where consumer expenditure data ends. In other words, this is where we gain a deeper understanding of your best potential customers. It allows us to understand not only what types of products and services people spend money on, but also what types of brands they choose and where they purchase products. This data is derived from a 96-page booklet that is answered directly by US consumers. Some examples of this data include the following:
- customer usage of products and services
- customer media usage and consumption habits
- lifestyle information
- behavioral information
- psychographics (the study and classification of people according to their attitudes, aspirations, and other psychological criteria)
Why Combine Predictive and Client Data?
Your client data is the ultimate source for understanding who your customers are and what types of offers will appeal to them. If you look at the pyramid above, you will see that client data sits at the very top. That is because integrating it with the other data types beneath it takes the guesswork out of a mailing profile. It also provides clear direction as to which households, carrier routes, zip codes, or markets you need to mail. The main benefit of incorporating your client data into our predictive data is that you will be talking to your known best customers who are already aware of and interested in your products and services, as well as potential customers in the marketplace that are “look alikes” to your existing customers. This, in turn, will improve your response rates and increase your return on advertising spend.
More on Why Client Data Matters
Advertising to current customers is just as important (and some would argue even more so) than reaching out to potential customers. Research has proven many times over that it costs far more to gain a new customer than to keep an existing one. Growing your business is as much about keeping your current customers happy and engaged as it is an effort to bring new customers to your business.
What if I Don’t Have Client Data?
We just made a big deal about how important client data is to your mailing profile, but what if you don’t have any? Don’t worry. You have options.
We can help you create a customer list.
“How?” you may ask? We can use our Impact Postcard (which is trackable at the household level when we perform a redemption analysis using unique barcodes) and perform test mailings based on predictive data. After we have completed the test, we will be able to deliver you a list of everyone who responded to your mailing and which offers they redeemed. All of this can be done in a few mailings and will allow you to increase your return on advertising investment and build the basis of your client data list.
Once we have your initial client data list, we can then expand on that list by adding what we call lookalikes. Lookalikes are potential customers of your business who have similar interests, shopping preferences, and lifestyles as your current clients. In-depth data analysis allows us to identity these people and include them into your mailing profile which will increase the number of people you can share your offers with via direct mail.
What’s the other option?
The reality is, we can still create a highly targeted mailing profile based on predictive data alone (referred to above as Micromarketing). Remember that predictive data includes geography, demographics, consumer expenditures, consumer behaviors, and brand preferences. Our Strategic Analytics team are experts at creating a strong profile to give your mailing the best chance possible for success.