Remarketing: wouldn’t they just come back anyway?

A new starter in Team SaleCycle recently asked me the following question… “Wouldn't they just come back anyway?”

A new starter in Team SaleCycle recently asked me the following question… “Wouldn’t they just come back anyway?”

By ‘they’ my colleague meant ‘website visitors’ and to answer this question I need to clarify a few things:

With any remarketing solution (AKA behavioral retargeting), target identified and anonymous visitors behave differently and therefore to answer the question we need to look at the behavior of each type of visitor separately.

Let’s start with identified visitors first. What does it mean for a visitor to be identified or recognized?

identified vs anonymous

Identified visitors

For a website visitor to be identified the visitor needs to have entered unique personally identifiable data (email address or mobile phone number) on the website either during that visit or in a previous one.

Normally this means the visitor has previously purchased from that website, signed up for an account/newsletter or entered their details during the checkout process.

identified visitors

If a visitor is identified it is likely that they already have a relationship with the brand/website.

Or in the last example, where they left their details during a final visit, they are so invested in the purchase and so close to completing that they took the time to type their personal details into a field.

When you look at it in that context you start to draw parallels between the oft quoted stats in many Analytics packages: ‘New vs Returning Visitor’.

Now, many people confuse this measurement with ‘New vs Returning’ customers and often given the nature of multi-device/cross-device tracking, it’s difficult to conduct that analysis in a web analytics platform.

CRM teams obviously know the difference and the challenge becomes even more complex when brands operate both online and offline channels (phone plus bricks & mortar).

Anonymous visitors

Anonymous visitors are slightly different.

When a visitor can’t be recognized and they abandon, it’s very difficult to recognize them when they come back and buy.

If there is no personally identifiable data when they leave a purchase behind, how do you know it’s definitely them when they return?

Sure, there is non-personal data that can help identify them such as IP address and machine information but using that data to recognize visitors is not 100% accurate.

Anonymous visitors can only be redirected back to a site via targeted advertising, and we know that has its place.

anonymous visitors

As many remarketing tools for anonymous visitors focus on keeping the visitor on the site in the same visit it’s hard to test how many would come back.

We at SaleCycle believe that’s how to measure the success of tools like onsite remarketing, unlike other vendors who may claim a returning anonymous visitor up to 30 days after they left.

So our testing only focuses on displaying a message to them and making them buy in the same visit. So for now let’s park that group of visitors.

Overall it’s somewhat likely and easy to prove that identified visitors do come back, but with anonymous its more difficult, although it can be estimated and it’s obvious that some do come back. However, you want to know how many come back.

Well, context is everything, and to answer the question fully I need to give even more context.

How visitors behave

Any test to prove or disprove a theory is a good way to do that and a test is only good as its methodology; results on their own are not always conclusive.

To test how visitors behave we analyzed the data for a number of clients where the visitor was identified to see what happened after they abandoned their purchase. In our testing we refer to this as the “Natural Recovery Rate’.

We run this test regularly for our clients and recently did so for a major retailer.

In this retailers’ test a total of more than 50k unique visitors abandoned purchases online during the period of testing.

Our test split the data in a natural way with both identified and anonymous visitors on both sides.

We then sent remarketing emails to 90% of recognized website visitors and tracked the behavior of the 10% of visitors we did not communicate with.

Over the duration of the test, 33% of unique abandoning visitors ‘naturally’ returned to complete a purchase. On the side of the test where we sent remarketing emails 41% of unique abandoning visitors returned to complete a purchase.

Let’s break that down even further.

Over an extended period of time (30 days) 33% of visitors on both sides of the test came back naturally (no abandonment communications were sent to them) and bought.

salecycle test

On the Remarketing test side an additional 8% of unique abandoning visitors received, opened, clicked and returned to purchase, making the overall conversion rate on this side 41% – 33% +8%.

It’s worth noting around half of the 33% of visitors on this side of the test actually did receive an email and returned to complete a purchase without opening and clicking the email in the same sequence.

It could be argued that they opened on one device and returned to buy on another. In this case their behavior is recorded as natural where it could be argued it is not.

So yeah, some visitors do come back.

If you are a major retailer, you might be lucky that such a high proportion of visitors come back over a long period. These numbers differ for all retailers and in the travel sector for example due to the lack of frequency of visits the numbers are significantly lower. But can you take the chance that they will just return and buy?

Michael Barber is Head of Product at SaleCycle and a contributor to ClickZ.

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