the premium brand. Finally, they get their mail and low and behold, it’s a direct mail piece for the premium brand they are looking for.

Meanwhile, Household #2 (the value conscious family) is watching TV, but their focus is on an entirely different set of commercials than Household #1, even though they are in the same “cluster.” They also check the weather online, but they see different ads than the first household. And when they open their mail, there is notice of a sale at their local department store.

So much for John Wanamaker’s comment that half of his advertising is wasted – he just didn’t know which half. Today he could figure it out. The fur department would be marketed to one group, lower-priced sportswear to another. This second group would be notified of sales. The first group would be the first to know about

Imagine a retailer in the process of determining its advertising and promotional strategy for the next year. The retailer knows that there are millions of potential customers, but knows too that not all of them are the right targets for their brand. So, how can a retailer – or any marketer for that matter – identify the right targets for their brand?

Traditionally, marketers have relied on demographics – age, income, geography. But these characteristics can lead them astray.

To get a clearer picture, let’s look at two, seemingly similar, households:

Household #1 has an income of $90K. A married couple between 35 and 54 years old, with two children, they own a home in the suburbs. Ditto for Household #2.

They sound alike but behind closed doors, these families are really quite different. So how can the retailer tell the difference between these two households?

What if the retailer also knew that Household 1 exhibits high spending behaviors: they own a Cadillac Escalade, they took a luxury cruise in the past 18 months, and that they remodeled their kitchen to the tune of $100,000+. Meanwhile, Household 2 shows low spending patterns: they recently purchased their home, they have payments on a Toyota Camry, and they shop at WalMart. Demographically similar but their purchasing patterns are dramatically different.

Household 1 will likely be attracted to more premium brands and have more sophisticated financial services needs. They might even be seeking new sources of credit to support their purchasing habits. Household 2 on the other hand, is likely to prefer more moderate brands. Their debt is likely to be lower and brand takes a back seat to price.

Now that’s actionable information.

But marketers would never know it based on traditional segmentation.

Clearly, even the best marketing models fall short when they rely only on income and other demographics. To make the most of their budgets – and to build their brands – marketers must look at information that provides a deeper understanding of consumer needs, wants, propensities, and ability to purchase. Financial assets, such as stocks and bonds, as well as home equity and transaction history mean a great deal in terms of a consumer’s ability and propensity to buy in specific product categories. And, more importantly, this information has great meaning in terms of the types of brands and brand messages to which they respond.

In the old world, “birds of a feather flock together” segmentation systems were the only systems available to target consumers. Now, armed with more intelligent data on the spending power of households, we can single out those “birds” with the most potential to respond to a specific branding message and to buy a particular brand. So while everyone else is following the flock, marketers utilizing more granular information will be increasing both their efficiency and effectiveness in customer acquisition, development, and loyalty.

How can our retailer integrate this powerful data on spending power into its advertising and marketing strategy for the next year?

Let’s go back to our Two Households.

Household #1 (the big spenders) is watching TV. They see a commercial and take immediate note of a new model for a premium brand. Then they check the weather online, and they see an ad for the premium brand. Finally, they get their mail and low and behold, it’s a direct mail piece for the premium brand they are looking for.

Meanwhile, Household #2 (the value conscious family) is watching TV, but their focus is on an entirely different set of commercials than Household #1, even though they are in the same “cluster.” They also check the weather online, but they see different ads than the first household. And when they open their mail, there is notice of a sale at their local department store.

So much for John Wanamaker’s comment that half of his advertising is wasted – he just didn’t know which half. Today he could figure it out. The fur department would be marketed to one group, lower-priced sportswear to another. This second group would be notified of sales. The first group would be the first to know about n

tell the difference between these two households?

What if the retailer also knew that Household 1 exhibits high spending behaviors: they own a Cadillac Escalade, they took a luxury cruise in the past 18 months, and that they remodeled their kitchen to the tune of $100,000+. Meanwhile, Household 2 shows low spending patterns: they recently purchased their home, they have payments on a Toyota Camry, and they shop at WalMart. Demographically similar but their purchasing patterns are dramatically different.

Household 1 will likely be attracted to more premium brands and have more sophisticated financial services needs. They might even be seeking new sources of credit to support their purchasing habits. Household 2 on the other hand, is likely to prefer more moderate brands. Their debt is likely to be lower and brand takes a back seat to price.

Now that’s actionable information.

But marketers would never know it based on traditional segmentation.

Clearly, even the best marketing models fall short when they rely only on income and other demographics. To make the most of their budgets – and to build their brands – marketers must look at information that provides a deeper understanding of consumer needs, wants, propensities, and ability to purchase. Financial assets, such as stocks and bonds, as well as home equity and transaction history mean a great deal in terms of a consumer’s ability and propensity to buy in specific product categories. And, more importantly, this information has great meaning in terms of the types of brands and brand messages to which they respond.

In the old world, “birds of a feather flock together” segmentation systems were the only systems available to target consumers. Now, armed with more intelligent data on the spending power of households, we can single out those “birds” with the most potential to respond to a specific branding message and to buy a particular brand. So while everyone else is following the flock, marketers utilizing more granular information will be increasing both their efficiency and effectiveness in customer acquisition, development, and loyalty.

How can our retailer integrate this powerful data on spending power into its advertising and marketing strategy for the next year?

Let’s go back to our Two Households.

Household #1 (the big spenders) is watching TV. They see a commercial and take immediate note of a new model for a premium brand. Then they check the weather online, and they see an ad for the premium brand. Finally, they get their mail and low and behold, it’s a direct mail piece for the premium brand they are looking for.

Meanwhile, Household #2 (the value conscious family) is watching TV, but their focus is on an entirely different set of commercials than Household #1, even though they are in the same “cluster.” They also check the weather online, but they see different ads than the first household. And when they open their mail, there is notice of a sale at their local department store.

So much for John Wanamaker’s comment that half of his advertising is wasted – he just didn’t know which half. Today he could figure it out. The fur department would be marketed to one group, lower-priced sportswear to another. This second group would be notified of sales. The first group would be the first to know about

ack seat to price.

Now that’s actionable information.

But marketers would never know it based on traditional segmentation.

Clearly, even the best marketing models fall short when they rely only on income and other demographics. To make the most of their budgets – and to build their brands – marketers must look at information that provides a deeper understanding of consumer needs, wants, propensities, and ability to purchase. Financial assets, such as stocks and bonds, as well as home equity and transaction history mean a great deal in terms of a consumer’s ability and propensity to buy in specific product categories. And, more importantly, this information has great meaning in terms of the types of brands and brand messages to which they respond.

In the old world, “birds of a feather flock together” segmentation systems were the only systems available to target consumers. Now, armed with more intelligent data on the spending power of households, we can single out those “birds” with the most potential to respond to a specific branding message and to buy a particular brand. So while everyone else is following the flock, marketers utilizing more granular information will be increasing both their efficiency and effectiveness in customer acquisition, development, and loyalty.

How can our retailer integrate this powerful data on spending power into its advertising and marketing strategy for the next year?

Let’s go back to our Two Households.

Household #1 (the big spenders) is watching TV. They see a commercial and take immediate note of a new model for a premium brand. Then they check the weather online, and they see an ad for the premium brand. Finally, they get their mail and low and behold, it’s a direct mail piece for the premium brand they are looking for.

Meanwhile, Household #2 (the value conscious family) is watching TV, but their focus is on an entirely different set of commercials than Household #1, even though they are in the same “cluster.” They also check the weather online, but they see different ads than the first household. And when they open their mail, there is notice of a sale at their local department store.

So much for John Wanamaker’s comment that half of his advertising is wasted – he just didn’t know which half. Today he could figure it out. The fur department would be marketed to one group, lower-priced sportswear to another. This second group would be notified of sales. The first group would be the first to know about

on systems were the only systems available to target consumers. Now, armed with more intelligent data on the spending power of households, we can single out those “birds” with the most potential to respond to a specific branding message and to buy a particular brand. So while everyone else is following the flock, marketers utilizing more granular information will be increasing both their efficiency and effectiveness in customer acquisition, development, and loyalty.

How can our retailer integrate this powerful data on spending power into its advertising and marketing strategy for the next year?

Let’s go back to our Two Households.

Household #1 (the big spenders) is watching TV. They see a commercial and take immediate note of a new model for a premium brand. Then they check the weather online, and they see an ad for the premium brand. Finally, they get their mail and low and behold, it’s a direct mail piece for the premium brand they are looking for.

Meanwhile, Household #2 (the value conscious family) is watching TV, but their focus is on an entirely different set of commercials than Household #1, even though they are in the same “cluster.” They also check the weather online, but they see different ads than the first household. And when they open their mail, there is notice of a sale at their local department store.

So much for John Wanamaker’s comment that half of his advertising is wasted – he just didn’t know which half. Today he could figure it out. The fur department would be marketed to one group, lower-priced sportswear to another. This second group would be notified of sales. The first group would be the first to know about

the premium brand. Finally, they get their mail and low and behold, it’s a direct mail piece for the premium brand they are looking for.

Meanwhile, Household #2 (the value conscious family) is watching TV, but their focus is on an entirely different set of commercials than Household #1, even though they are in the same “cluster.” They also check the weather online, but they see different ads than the first household. And when they open their mail, there is notice of a sale at their local department store.

So much for John Wanamaker’s comment that half of his advertising is wasted – he just didn’t know which half. Today he could figure it out. The fur department would be marketed to one group, lower-priced sportswear to another. This second group would be notified of sales. The first group would be the first to know about new jewelry shipments.

The implications of this information for brand marketers – from retail to financial – are huge. The bottom line is that there are differentiating factors that are not identified by standard demographic selects. Just think what brand marketers could do with more intelligent data on the spending capacity and propensity of consumers!

This information is available today and can be used to create more successful marketing campaigns, more targeted advertising strategies, and a stronger brand. It is the information that successful marketers will use to distinguish between price-conscious customers and those that value name brands. With this information marketers will discover those prospects with the discretionary funds and the interest to buy their products. This is the information that will help a company succeed.

Thomas E. Dailey, is President & Chief Executive Officer of IXI Corporation. Echelon Targeting, a division of IXI, offers proprietary products including Echelon Discretionary Spending Index™ and Echelon Discretionary Spending Propensity™. Tom Dailey can be reached at echeloninfo@echelontargeting.com or 703-770-9677.