Of course you know what you want users to do when they visit your site and that they come from many different sources, but do you know which sources contribute most to your conversions?
From earned, to owned, to paid, and back again – figuring out which touchpoints contribute the most, least, and all the data in-between throughout a visitor’s history is critical to understanding how to optimize your campaigns.
If you are tracking where visitors come from just before they convert, you’re probably missing a great deal of useful data relating to how your visitor finally decided to perform that desired action; whether they bought something, saw important content, or signed in for access to a key process.
Many organizations have no attribution modeling and instead rely on simple referral information about where customers come from when they finally convert. But there are several different – and more useful – models that can be applied to perform this exercise.
Broadly speaking, touchpoints are any view or interaction with your brand or product. In the digital world, a touchpoint is usually a campaign, a social mention, or a visit to your site. It’s been said that customers almost never convert until they hit several brand touchpoints. Some say it takes as many as eight, others say it can take up to 12 touchpoints on average, before a prospect becomes a customer.
Let’s look at just a few of the most common attribution models in use today. It’s important to note that using just one of these is never as good as applying several models at once. Hopefully this insight will provide you with an informed perspective on just how well your touchpoints are actually working for you.
1. Last click
The most common touchpoint, this unfortunately is what constitutes an entire attribution effort for too many organizations. It gives all the credit to the last reference source before granting a conversion. However, research has shown that customers typically will interact many times before they convert, which means the last click is far less important than it might appear.
2. First click
In this model, you give all the credit to whatever campaign or reference source that first introduced your customer to your content. But wasn’t the last click also important? And what about the clicks in between?
3. Time decay
Time decay allows you to give more credit to touchpoints, as the customer gets closer to conversion. This method tends to minimize your first touchpoint, but it does begin to address the importance of in between steps.
If reflected in a bar chart, position it would look like a valley – tall on the ends and low in the middle. This gives most of the credit to both the initial and final clicks. In my opinion, this is the most simple of the attribution models, as it’s the best way for users to remember your brand.
Just like the name suggests, this attribution model ensures that equal credit is given to each touchpoint. Though it is a safe way to go, it doesn’t really help you make significant adjustments to your campaigns.
The above are all useful ways to understand how campaigns and referrals help your bottom line. However, they are static and as such, may not respond to anomalies in your data. To avoid leaving out key insights, you should also consider:
6. Customized attribution
There are more customized – and arguably better – ways to perceive attributions. You’ll have to develop some logic around the attribution model, which means using an analytics tool to enable this ability and fulfill your professional objectives.
For instance, after setting up this logic yourself, you can develop a model in which you credit one type of channel over another – like crediting more to paid advertising than to social or emphasize a particular email campaign over paid advertising.
7. Data-driven attribution
Finally, if you have the right technology for it, you can set up data-driven attribution. More sophisticated than the models shown above, data-driven attribution allows your analytics tool to analyze your campaign data and look for patterns that suggest the most accurate attribution models. In conjunction with e-commerce and cost data, you can also determine the exact cost of your sales based on how much was spent in getting the sale.
To sum up
By now you should see that the common last-click model is badly flawed and realize that you may want a more conscientious model – even if it isn’t data-driven. If you have the time and bandwidth to invest in a deep dive into your data, then the insight reward will be only more valuable.
*Article images via Flickr.
What’s behind a successful data-driven marketing strategy?
One of the major challenges in the martech industry is getting the attention of prospects in a world where they are bombarded by content and emails on all sides.
Facebook is addressing one of the biggest missing pieces of its chatbot offering: analytics.
Insurers went online a long time ago, but one of the major challenges has been creating an online experience that can handle the relatively complex insurance “form-filling” process.