Any data-driven marketer knows that having data at your fingertips is just the start of the battle. The real value comes when you are able to use that data to influence your decisions. Here are just a few ways that our customers are acting on the data in their RJMetrics accounts.

While the following examples can be applied to many business models, we will be focusing on e-commerce analytics.

Ping your customers at the right time

One of the standard RJMetrics reports is called “average time between customers’ orders.” This reveals the average time between historical customers’ 1st, 2nd, 3rd orders, and so on.

This report can easily be broken out by the product purchased by that customer, their geographic region, their referral source and other defining characteristics.

With this information in hand, you can easily create intelligent drip campaigns to remind customers to come back for a visit when their peers have historically been most likely to come back and buy again. Using an email service such as Hubspot or Mailchimp, you can create drip email campaigns scheduled at different intervals from a customer’s 1st purchase date. You can even customize these lists based on more specific characteristics to conduct more focused targeting.

When implementing these drip campaigns, it will be very important to monitor performance and iterate to improve the message. One of the best ways to do this is to A/B test different email content and timing.

Activate your registered users

For some businesses, not all registered users have become paying customers.  “activating” these prospects is an extremely important and valuable process.

Our “time to 1st order cohorts” report groups users that joined or registered in a particular time period and shows you the percentage of those users that have made a 1st purchase by each month after their registration.

Typically, these curves become horizontal lines after some period of time, indicating that few additional cohort members are converting organically after that point. In other words, most users that are going to make a purchase organically have already done so. At this point, these members are highly unlikely to convert and constitute dead weight in your user base. Reaching out to them with custom promotions or specifically targeted emails is an extremely low-risk way to jump-start conversion of this population.

With RJMetrics, it is easy to identify this population of users for any time period and export that list to your email service provider.  Simply follow the steps below:

  1. Initiate the chart creation process through Charts -> Create Chart.
  2. Choose the “new users” metric.
  3. Choose a table chart by clicking the table icon on top of the preview:
        1. Untitled
  4. Now set the Time Period of analysis to your user registration period of choice, and set the Time Interval to “None”
  5. Go to the “Group by” tab to segment by “email” and choose to show the top 100 percent of the dataset.
  6. Add a filter under “Filter by” for “User’s lifetime number of orders = 0” to filter for users who have not yet made a 1st purchase.

Once we have the list of unconverted users, you can directly export it from RJMetrics and upload it to a mail service like Mailchimp or Hubspot and reach out with an offer.

Re-activate lapsed customers

Once your users have made a purchase, we want to make sure that they come back for more.

Using a similar technique to the one shown above, you can generate lists of your users that have not come back to make a repeat purchase after some amount of time. Pairing this with an “average time until second purchase” chart can give you an indication of when a customer may have “lapsed.”

Reaching out to this population of users can similarly be a low-risk way of increasing conversion and repeat purchase rates. A/B testing a few different campaigns across customer groups who have lapsed can often reveal effective marketing techniques that are specifically tuned to this population.

Good luck reaching out!

If you need any help creating some of these reports or would like to perform even deeper analysis, simply contact us via “Help” -> “Contact Support” from your dashboard.