Finding the Right Customers
New product launch best practice dictates that you build “the voice of the customer into a market-driven, customer-focused new product process.”1 That entails collecting intelligence about the market you want to serve and data about how customers are likely to respond when you offer a new “…unique, superior product…”1
Once you know about how they will respond to your product, you need to know how to recognize them. That’s where demographics come in. Age, gender, income, education, children at home, etc., all characterize individual customers to improve your odds of winning in the market. Combined with details like what targets buy, the kind of entertainment they enjoy, their credit rating, and behavioral data, you get a fact-based picture of who you want as your customer.
Integrating the right data sources provides you with a bridge between how customers will behave toward your offering in the future and how they are behaving in their lives in the today. You may have names and addresses of those who respond to a survey testing the details of your new offering, but privacy regulations prevent the other side of the bridge from being that specific. So what to do?
How can you get a full picture of the customers you want to target so your message and offer can become part of the things they do every day?
Some brands are very clear about the right
- Product features to offer
- Promotional tactics
- Price to attract the share of demand that delivers profit
Often, the selection of the right distribution channel depends on where targeted customers expect to find the products. The big questions are often
- Which competitor do my target customers like to buy from?
- How do I zero in on where they live so I can efficiently engage them?
Data from YOUR Customers
Segmentation links to the business objectives; price sensitivity models define the relationship between supply and demand; customer outcomes and attitudes are inputs for positioning; and the preferred channels for the new products tell our clients how to launch. But they need more. To be successful, the targeted customers have to be found. We connect this future to data on the current lives target customers are living.
To new product predictive data that we generate, we access and add data from other sources about the retailers people shop, the products they buy, their credit rating, cable networks they use, and more at the zip+4 level2. This enables us to know where target customers reside and how they live. This information is an arrow instead of a shotgun for effective marketing communication.
We offer a connection at the zip+4 level to the specific location of prospects whose demographics and behaviors make them most likely to perceive your new product has value. Our solution falls within the acceptable bounds of privacy regulations and can be as narrow as a city block or a group of apartments in an urban area. With knowledge at this level, you can meet your target customers where they are in the lives and in their homes.
Extensive analytics generated from our zip+4 level data allows us to deliver
- Segmentation models
- Combining current behavior and perceived value for a future offering, which makes for rich predictive segment profiles
- Linking internal sales data with current behavior data
- Predictive models to track the evolution from one segment to another over time
- Response models for specific marketing campaigns
- Lifetime value models
- Retention and attrition analysis
- Marketing mix analysis for optimizing marketing spend across the different channels
- Competitive comparisons by brand or category and, in some cases, products
2Zip+4 codes were developed “to identify a geographic segment within the five-digit delivery area, such as a city block, a group of apartments, an individual high-volume receiver of mail, a post office box, or any other unit that could use an extra identifier to aid in efficient mail sorting and delivery.” Wikipedia https://en.wikipedia.org/wiki/ZIP_Code#ZIP+4
About the Author
Pamela Roach is CEO of Breakthrough Marketing Technology. She is dedicated to our mission of enabling businesses to make decisions based on fact. She has designed, collected, analyzed, and delivered the intelligence necessary to produce insights into the motivations, attitudes, and outcomes that characterize multicultural targets. In addition to her work at Breakthrough, she also teaches graduate students Integrated Marketing and Media Campaigns at NYU School for Professional Studies.