If you're a database marketer like me, you also find it difficult to listen to social media marketers proclaim that social media return on investment is something “bean counters focus on.” Nobody is going to agree on the right set of metrics for determining if social media delivers an increase in sales and profit. But might we be asking the wrong question?
The contention that multichannel customers are the best customers frustrates me more than anything. Technically, they are, as database marketers query databases every day and observe that they are the best customers. But the problem I have with this lies in how this fact is communicated to business leaders.
Many retailers understand that there are significant trade-offs involved when trying to optimize email marketing return on investment. Within the direct channel, the goal of an email marketing message is to get customers to act now. Within retail, the goal is to encourage customers to get into their cars, drive to stores and purchase merchandise. For multichannel retailers, the message must somehow be calibrated to do both.
The marketer focused on return on investment always compares long-term value with short-term profitability. It's when comparing long-term value with short-term profitability that you learn how important it is to be willing to lose money acquiring customers.
Special occasion customers act differently than customers who purchase because of advertising or those who purchase organically. Special occasion customers are often new to the business, buying merchandise for reasons that are different than the average customer. As a result, these customers can be less loyal.
Email marketing made the transition from interesting new advertising technique to established marketing channel during the past few years. Established marketing channels are fully integrated with modern databases, allowing practitioners to better understand how customers interact with advertising. This week, I thought I'd explore some of the ways email marketers use database marketing to improve performance.
It's really hard these days to find a marketing discussion that doesn’t include the phrase “social media.” But it's also really hard to find a case study of someone who created a social media database and then measured return on investment based on the data in that database.
ROI is a very different discipline in e-mail marketing. While there's nothing wrong with measuring ROI using traditional metrics (open, clickthrough and conversion rates), you can use mail and holdout tests to obtain a realistic view of the long-term impact of e-mail marketing.
Database marketers capture information, with the intention of mining that information at a later point in time. Increasingly, they have an opportunity to transform the information into something more meaningful. In the case of half-life, you can create a series of 1/0 indicators in a database, indicators that tell you if the customer is within the half-life window for a various activity.
The inclusion of retail, Web analytics, mobile, social media and whatever other data you want to include has been both a blessing and a curse. Now marketers can track more customer behavior than ever. But they can’t be certain what they're tracking is “right.”