E-mail marketing is gaining significant attention from all quarters of the marketing value chain as firms seek to reinvigorate their approach and tap this abused channel to drive customer value while simultaneously lowering overall marketing costs. Driven in part by the recent economic downturn, firms are in a bind to leverage this very low cost channel, while rising above the tide of clutter and customer’s poor perceptions that they helped form with years of blast tactics.
Today’s e-mail lexicon is now shaped by terms like A/B testing, multivariate testing, and rules engines, to name just a few. Gone are the days of campaign management, list operations and more mundane aspects of the customer communication process. While these advancements are certainly needed and welcome, e-mail service providers are leaving out the most critical element of relevancy: customer-based analytics.
As service providers and their customers seek to increase relevance and click-through rates, they are bundling capabilities to test different calls to action, creative elements, key message points and other components of e-mail that will drive response. However, while these capabilities may be used to understand the click-through rate of one creative against another, or even across several variables through multivariate testing, they often treat the customer base as a whole. At best, the leading platforms offer regional differentiation or segmentation that is limited to a few small groups.
The estimated $200 billion of total direct marketing spending outside of advertising services is clear evidence that understanding a customer’s unique perspective, relationship status, and share of wallet are all critical factors in their decision to respond or open an e-mail. Adoption of these long standing, one-to-one marketing principles are missing in many of the current leading email solutions or at best are difficult to manage or integrate.
Organizations looking to drive e-mail relevance need to ask several critical questions when considering service providers. How are even basic statistical modeling techniques leveraged to drive relevance? At what level can e-mail be differentiated? When I provide unique offers/emails with varied content, how do I as a marketer get a handle on the distribution of these offers across my customer base? How do I see the offer mix before sending out company initiated e-mails? What level of control do I have to integrate my assumptions and tests with the recommendations driving by customer level statistical recommendations?
Answers to these questions will not only help organizations better understand the capabilities of the e-mail service providers, they will also bring to light the level of effort and investment a firm must make to overcome the approach of these service providers. In other words, if relevance and results are the primary objective, ensure that the lessons of traditional one-to-one marketers are at least embedded in the solutions of the future. If not, you may find that another significant investment and transition is just around the corner.