By collecting information about your lists, you can send relevant offers based on a user’s prior purchases. Instead of just relying on demographic data, you can deliver each unique addressee offers and information that they want, according to their behavioral patterns.

Stop assuming

Targeting by demographics alone is pure guesswork. You are assuming that someone who is female will respond favorably to a skin cream product. What you are missing out on are the men who have previously purchased similar cosmetic products for reasons unknown to you. A user who has purchased flowers as a mother’s day gift and on secretary’s day is a prime target for chocolate or wine gift baskets during other holidays.

By segmenting and targeting your lists via past behavior, you are reducing wasted resources such as bandwidth and manpower on mass campaigns. You will no longer send 3 mass emails to your entire list of 3 million, generating 9 million emails sent. Instead, you can send 100,000 emails to users most likely to respond to such messages, resulting in the same number of conversions and exceptionally higher CPMs.

By splitting that list of 3 million and sending each user a relevant message based on past behavior, mailings can be cut into a fraction of what was previously sent. This brings costs down while still achieving the same sales or better, since the messages become more relevant and less prone to deletion by users bombarded with too many irrelevant emails every day. Imagine what that can do to your ROI.

The upsell opportunity

Using the same approach, behavioral targeting can be applied to upsell efforts. Instead of upselling because a user purchased “something,” use past purchase behavior coupled with most recent activity to paint a picture of the user, and send an upsell message that takes all of this behavior into consideration. This means that even though Joe bought a plant on Mother’s Day, he also bought a shovel, a gardening book and some seeds a few weeks ago. His past purchase behavior can be used to build a profile and send him relevant messages and offers that may not have been evident from just a plant purchase on a holiday.

Email affords the opportunity to collect immediate results so that you can apply your metrics to your user’s behavior. Past purchase behavior is not your only indicator or target. Applying knowledge gained from what a user clicks on can tell you a lot about their behavior and possibly turn a chronic browser into a buyer.

The only way to know for sure just how well BT will do for your email campaigns is to test thoroughly. Begin by building your database and get to know your users. Then create connections between past behavior and new opportunities. You can make assumptions, as all marketers are prone to do, but unless you test them, you will not know what works and what to scratch. Once you start understanding your users better, you will better serve them by stopping assumptions and offering relevant messages based on past behavior.

Paying for leads is the ultimate gamble for any business that needs an ongoing stream of new prospects to convert into sales. Let’s say you are selling toothpaste. You pay an agency, affiliate or any online marketer $5 for every lead they deliver that was interested in your toothpaste product. You collected 10,000 leads in one month, costing you $50,000. Of those leads, 50% converted into a sale with an eight-dollar profit that generated total profits of $40,000 before figuring in the cost per lead. You are now out $10,000.

This happens to marketers more often than they would like to admit.

Enter list management. By adhering to best practices in your data collection methods, you can turn those 5,000 non-converting leads and the converters into extra revenue by sending them third party offers, bringing your marketing costs to zero or adding an additional revenue stream. Why doesn’t everyone do this? It takes a massive effort to manage and successfully deliver high volume email campaigns in an ethical manner. Anyone who has tried to send more than 50 messages at one time to an in-house list can attest to that.

There are two main issues that all high volume mailers must consider: controlling delivery and controlling conversions.

In order to deliver successfully you need to be assured that the emails will be whitelisted across all ISPs being delivered to. If you are not whitelisted, chances are your message will not be delivered or will be whisked into the junk mail folder, never to be seen by its intended recipient. Avoiding these deathtraps for mailers entails successful branding of the emails and their sender, which means no hiding behind fake names or flipping IPs. You must also adhere to the highest standards in data collection and list hygiene methods, constantly monitoring results such as bounces and react immediately to complaints.

Conversions vary greatly, the key being that the list needs to be tested with several types of creative and offer types to find the right fit. While your toothpaste leads may not be interested in a payday advance, they probably would love a tooth whitening cream but aside from the obvious assumptions, you will not really know until you test the campaign. You may be surprised to find that your list also reacts favorably to education offers or something else that wasn’t immediately apparent.

Does list management mean that you have no control over what happens with your lists? Not at all. You can choose the types of offers promoted on your lists, which types you want to leave out and how often your database will be mailed to; after all, it is YOUR list. You can also choose the format whether it be a “joke of the day” or a weekly brief after asking the recipients on your lists if they would be interested in receiving such communications.

List management has been around long before the Internet made it more affordable. As new standards are created and the industry evolves, it will continue to become a very lucrative and profitable business model. It is an excellent means for marketers to monetize their data creating more room for calculating the cost of the initial acquisition of that data.