Beyond Opt-In: Making E-mail Smarter
Behavioral Insider: What sorts of targeting data has "traditional" e-mail advertising relied on?
Vezina: Five years ago marketers got on the e-mail bandwagon, and that at first meant accumulating as many names within a wide geographic or demographic parameter as possible. When that proved too general a basis for targeting, and there was a predictable backlash by consumers to intrusive and irrelevant messaging, marketers finally bought into the concept of permission-based marketing. But too many understood only the technique and not the spirit of opt-in, looking to generate as many opt-in names as possible by enticing people to sign up with promos and gimmicks if necessary. Clearly that was an improvement. Opt-in works better than random mailings. But now it's become evident that for true sustainable boosts in ROI, it's no longer quantity but the quality of databases that matters.
BI: The spirit of opt-in as you describe it seems to be about building loyalty through trust. But what are the limitations of opt-in?
Vezina: Trust begins when the consumer opts-in--but it needs to be strengthened over time by reinforcing the credibility of the marketer. That means consumers have to grow in confidence that every message they're going to open up is going to be both relevant and timely.
Marketers need to keep up to date with consumer attitudes, perceptions and behavior towards e-mail. Five years ago, anything not opt-in was considered spam, which was assumed to mean that anything opt-in was relevant. But companies have evolved their own behavior that opt-ins don't insure interest. Unless it's relevant, it's spam. So opt-in is not where you finish--it's where you start.
BI: So what's the next step? How does targeting, particularly behavioral targeting, fit into an opt-in mailing program?
Vezina: Relevance is about creating respect, honoring the consumer's opt-in preferences and always keeping the context of the moment in mind, understanding that what a subscriber deems relevant today could and will change tomorrow. Context can depend on demographics, purchase history or time of year. For example, one consumer may welcome holiday gift ideas in early October, while another doesn't think about doing holiday shopping before Thanksgiving is over. It's obvious that you'll do better targeting customer A in mid-October and customer B in early December than vice-versa, or sending both a holiday mailing at one or the other date.
In addition to the four W's--who you're mailing to, what you're mailing, where it's going and when--there's the question of how consumers prefer to respond... and the time frame they take to respond, and how long they take to open, click, or forward messages. These are all subject to wide personal variation and make a huge difference in how a customer should be marketed to.
BI: How does your technology help enable this for clients?
Vezina: One-to-one marketing has been the holy grail of direct response advertisers for well over a decade, but the technology was never quite ready to make it feasible. Accumulating, storing and integrating customer, qualified lead or prospect data from many different sources used to be a very expensive proposition. One of the things we've been most involved in is streamlining and simplifying the process.
BI: What types of ad campaigns and goals is BT most suited for? Can you cite examples or case studies of how BT is being successfully deployed in the industry currently?
Vezina: We have one specialty retailer client which has 150 stores devoted to skateboarding clothes. They've more than doubled their response and direct sales metrics by integrating loyalty program data, geographics, demographics and e-mail response behavior to segment their lists according to loyalty levels. A pharma research firm we consult with does surveys with doctors to predict sales of new drugs. Their goal in prospecting is to generate an optimal level of doctors to register to participate in specific surveys. They're not only looking for high percentage of registrations, but need to try to distribute scheduling of interviews out so that there are never too many or too few in any given time slot. To do this, they incorporate information about the doctor's background and practice along with over 100 behavioral data points based on each doctor's historical participation in surveys over several years, including not only the types of drugs they are most interested in, and what types of incentives they've best responded, but also when and in what format they prefer to conduct surveys.
BI: What are the main challenges and opportunities for BT in this space going forward?
Vezina: The key challenge going forward is, once you've succeeded in getting all the data in one spot, knowing what to do with it. Another challenge is knowing how to segment the list, now that there are so many variables you can slice and dice. Paucity of information used to be the biggest problem for e-mail marketers; now it's not knowing how to effectively organize all the information we have.