Remarketing with Email – Web Analytics Brainstorming
I have seen some articles that mentions some great findings and research from eMarketing or pitches from Email marketing solutions tying up with some web analytics solutions. I was thinking, what can we do or even think from web analytics perspective before jumping on to implementing remarketing program.
In this writing, I would like to focus on remarketing with email. Keep in mind that in order to remarket via email, people have to have registered on your site or who have opted into your email program.
The best starting point is to review the type of site you are running the remarketing program. Your site could be an e-commerce, content, lead generation, etc.
Second point, what interactions by these identifiable visitors would you consider as abandonment? Abandonment in this case could be anything that you consider people who didn’t execute the desired action, after subscribing or registering for communication.
Examples based on an assumption that the site visitors are logged into the site and registered for email communication:
- People who added items into shopping cart, but did not completed checkout.
- Visited a specific page (like promotional page), but didn’t complete a desired action like subscribing/registering/applying for promo.
- Didn’t sign up for magazine subscription.
- Didn’t bounce, saw old product, but missed viewing the new product pages.
- Registered users with twitter account (based on profile info), but didn’t click or attempted to show interest in following the site owner or company’s twitter account.
You get the idea. Remarketing could yield positive results. According to a research found on a study for ExactTarget and TicketsNow, researchers found that transactional emails sent after a shopper had abandoned items in a shopping cart actually worked to improve overall company revenue by 30%. Therefore, remarketing could be an effective marketing tactic based on people’s interaction with the site. So far, re-marketing sounds great and very promising.
A lot of the findings based on research talks about X% improvements in revenue or increase in conversion by Z% after doing XYZ. That makes me wonder about the kinds of web analytics data, which should be reviewed prior to investing your time in executing remarketing program.
Here are some ideas that I think web analytics metrics can help you decide rather to tackle remarketing with email or not. Idea is to understand where your site stands in terms of data, and gain a better sense of expectations from remarketing.
Number of registered users who can be emailed:
You site may be selling your products pretty well, but if a lot of them shoppers didn’t opt-in to your newsletter (for whatever reason) then the overall volume of re-marketable people may not be significant.
Imagine an e-commerce site where the owner decided to give customer an option to opt-in for email communication at the thank you page, which caused only 1% of the overall customers to register. Let’s assume there were 10,000 absolute customers to date. That means there are only 100 remarketable customers. Is that a good number for you to invest in re-marketing? You decide.
Email click-through rate (unique):
If your average click-through rate (unique clicks per email delivery) was around 1%, then only 1 response would be generated from 100 emails that you sent out (based on the above example).
If your site is awesome, and have 1,000,000 absolute customers, with 1% of them registered for email, there will be 10,000 remarketable customers. With 1% click-through rate, you have about 100 responders to your remarketed email.
Self explanatory, but let’s assume your re-marketing tactics are so great (the best in the world), and 10% of the email responders actual complete the desired action. With the case with 1,000,000 absolute customers, you’ll get 10 conversions.
Average order value (AOV) or Average Conversion Value (ACV):
Regardless of your site being e-commerce or not, it would be important to understand how much your conversion are valued. Say your site sells an item that worth $100 on average, then that will be your ACV or AOV. With the 1,000,000 customers example, that will mean your remarketing efforts may generate about $1,000 in value. Not sure if that is good yet.
Return on Advertising Spending (ROAS):
So you may be happy that $1,000 is a great outcome, and now you can go buy your team some drinks… but wait. Ask you self, about how much money are you planning or expected to go out of your pocket for this remarketing program?
Let’s say you paid this one freelancer that use to work at a top marketing agency for about $1,500 (I’m sure it is more in reality…). Using above scenario, your ROAS is 67% (1,000/1,500). You basically lost some money just running the re-marketing program. Nice… maybe that’s why you hear a lot of fancy agencies having trouble making their clients happy because clients might be seeing this ROAS below 100%.
Additional/potential value generating from re-marketing outcome:
This is where your segmentation in web analytics tool come into play. If your remarketing efforts are to drive certain outcome or interactions, what does your web analytics segmentation tells you about those visitors after they converted or show potential additional value?
Say you segmented those 10 converted customers (visitors coming from re-marketing email), and found out that they advocate the site’s product through tell-a-friend feature. You happen to know that tell-a-friend or advocacy by customers generate about $50 in value (this is just an assumption for example).
Therefore, 10 customers telling 10 of their friends generated additional $500, making your ROAS 100%. The idea is to look at the segment of different interaction and outcomes so your remarketing efforts are based on interactions that drive the biggest return.
These interactions could be existing even before you run the re-marketing program, so understand the values from different “micro conversions” using segmentations. Here is a nice article that talks about “Macro and Micro conversions“.
I guess the challenging part is to assign some kind of $ value on to those micro conversions, or those segmented interactions that leads to additional returns for your site/business.
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