Stoo Gill, dotdigital product manager, is back with some more practical working examples to power your marketing strategies. This time we’re looking to help retailers using the dotdigital platform get the most out of all that awesome data they can pull through the Magento platform.
Setting up automation programs is a top priority for most marketers selling online through Magento. However, knowing where to start building a program is another matter altogether. As more of our clients explore using the automation program builder, we find we are getting more requests for practical automation advice by both retailers and ‘dotdigital for Magento’ users. (For anyone who hasn’t seen or heard of our automation offering, check this page out)
Specifically, we are asked for examples of some of the more popular and effective marketing automation programs, that dotdigital clients are setting up using the ‘drag & drop’ builder combined with the Magento integration.
We’ve pulled together some great examples of programs that use the key customer data points that our platform is able to synchronise with your Magento account, giving users a full range of RFM-based segmentations.
As we often say in our webinars and seminars, it’s best to start small and scale quickly.
Date Created and Last Order Date
The simplest program any eCommerce marketer can set up, is a ‘Welcome Series’. We look to send a welcome email to a new site registrant, and then send them a follow-up 7 days later – but only if they haven’t made a purchase. That might look a little like this:
The purchase field LAST_ORDER_DATE can really open up a lot of different decisions for your automation program to take.
Personal Details (Birthday) and ‘Wishlist’
The next program that we can look at is a ‘Birthday’ program. This one sends out an email 7 days before the user’s birthday, and another one on their actual birthday. There are three different campaigns that could be sent, and a total of four different user experiences that could result from this.
We would recommend having at least three different pieces of content to plug into this program, based on the value of the customer. A customer with a wishlist is obviously someone that has an ever-green affinity for your brand, and a high value that you might wish to nurture with an equally high-value discount. Those without, you might think to send then a voucher that would encourage wishlist creation.
Chances are that you won’t want to stop just on their birthday, you might go on to create follow-up emails along the lines of “Did you get everything you wanted for your birthday? If not…”; but that shouldn’t stop you from building a simple 1- or 2- step program today and adding to it at a later date.
Last Order Date and Order Value
There are many occasions within retail when you want to nurture along the post-purchase path, and obviously high-value purchases will have a different feedback loop to low-value purchases. Here’s an example of how you could tier your post-purchase feedback
In a program like this, a retailer might look to send different content depending on how much a customer has spent across all their purchases. Towards the end of the post-purchase process the retailer would look to see if the customer has made any further purchases since. If not, they can send a final post-purchase email before enrolling the customer into the other email marketing activity and potentially a win-back program.
As you grow your email program you could consider different post-purchase paths depending on the kind of categories of products your customers are buying. Once you’ve got a basic post-purchase program running, fine-tuning it for things like replenishment programs may be your next step.
While a retailer might branch on TOTAL_SPEND, you could theoretically branch programs on many different comparisons. One common way to increase customer spend is to incentivise by offering free shipping. So perhaps branch your program based on AVERAGE_ORDER_VALUE and send offers directly to your lower spending customers.
Survey and Behaviour Response Triggers with Customer Insight
Our last example is straight out of the books of retail CRM. This image of a Lead Nurturing program shows a beast of a program. It shows how you can link in surveys and data capture with the program builder; it sends two welcome messages and then starts branching as your contacts provide you (or don’t provide you) with valuable data.
The third message has different content depending on if a user has completed a survey. After that there are follow-up messages depending on which data capture opportunities contacts did or did not complete. Towards the end of the program we’ve worked in custom content depending on what segment contacts are identified as belonging to, by using data from our Customer Insight Module to see if contacts are identified as Luxury Purchasers, Bargain Hunters or Impulse Buyers.
This program has a huge number of possible customer journeys. But how did we plan and build these out?
In simple terms, we devised generic ‘buying personas’ in order to try and predict possible user experience paths and discern what the most likely outcome would be from a certain pathway of email marketing. This sounds resource intensive – and it is. However, automated programs such as these are invaluable, and can be built up over time. The amount of work on active segmentation and database management are substantially reduced.