Probably all marketers are now aware that there are very effective web analytics tools to optimise web site sales.
However, Jupiter Research suggests that few marketers are integrating their web analytics into their email marketing programs. As email newsletters are mostly geared towards driving customers to web sites, there is obviously an opportunity that marketers may be missing.
By integrating your site analytics data into your email platform you can make your email marketing program more profitable. Analytics data is especially useful to create segments based on how your customers are behaving on your web site.
And remember, it is not just a matter of monitoring what has been purchased. You can gather valuable insights by knowing what was not purchased. For example, analytics can help marketers understand which products and categories are frequently abandoned. These non-completed purchases can be followed up with email.
Of course, it is imperative to keep privacy issues in mind. Customers are uncomfortable if they feel they are being followed.
One simple but effective technique is to note what product a customer has abandoned, then include that product as one of several "featured products" in a future email. With this sort of tactic, customers are likely to find such an email relevant without feeling like they have been followed.
Apart from making better use of analytics, there is still the troubling issue of how often to send emails.
Taking a one-size-fits-all approach, might seem like the easy way out of this one, but it is unlikely to be the best answer.
One proven approach to getting frequency right is to ask customers when they sign up how frequently they would like to receive your newsletters. Be sure to include a sample version so they understand the full value of the publication and have an idea of what to expect.
But there is a more sophisticated way. You can analyse your email response data and segment it using customer behaviour methods such as RFM, or other profitability metrics, to determine the optimal number of contacts for each segment.
Of course, there is nothing better than testing. Ideally, you should segment your list and run tests around frequency. There have been many cases where marketers have found that they can increase their frequency provided the communications are relevant and offer appropriate value with each interaction.