Connect to Customers Where They Are

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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 how your target customers will respond to your product, you need to know how to recognize those customers. That’s where demographics come in. Factors such as age, gender, income, education, and number of children living at home 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?[/vc_column_text][/vc_column][vc_column width=”1/3″ css=”.vc_custom_1615323275683{background-color: rgba(93,155,137,0.52) !important;*background-color: rgb(93,155,137) !important;border-radius: 2px !important;}”][vc_column_text css=”.vc_custom_1615323368793{border-radius: 2px !important;}”]Some brands are very clear about the right product feature to offer, promotional tactics, and 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?

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Data from YOUR Customers

At Breakthrough, we predict market demand for new products based on data collected from your target customers. Our analytics generate a marketing mix based on perceptions of how your product is valued.

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. However, our clients need more. To be successful, the targeted customers have to be found. We connect this future to data on the lives target customers are currently living.

We gather data from other sources at the zip+4 level² about the retailers where people shop, the products they buy, their credit rating, cable networks they watch, and more. Then, we add this data to the new product predictive data we generate. This enables us to know where target customers reside and how they live. This information is an arrow for effective marketing communication.

We offer a connection at the zip+4 level to the specific location of prospective customers whose demographics and behaviors make them most likely to value your new product. 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.

With extensive analytics generated from our zip+4 level data, we can 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

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