Ecommerce attribution is one of the most complex areas of online retail. Yet, it's also one of the most important. Why? Because if you can measure precisely which channel made your customers come on your website and buy your products, you'll be able to spend your money more wisely and increase your sales.
But even if it's really hard to master, you can't really do without it if you want to precisely control your business. And in a world where ads spending is growing while the true power of platforms like Facebook or Instagram is questioned, being able to have a clear understanding of what's working or not is mandatory.
But first of all, what are we talking about? What is attribution?
An attribution model is a system showing the channels that influenced your sales. It includes advertising channels like Google, Instagram, Facebook or TikTok, Social Media interactions, SEO, influence, etc.
When you track attribution, your goal is to understand which channels are performing, which ones are drives sales, to focus your budget and your efforts on what will get you the best results.
Types of attribution models
Classic attribution models are mainly based on analytics and the source of traffic on your website.
1️ Last Click
This is the most common and easiest method to set up. It means that you'll take into account the last channel that generated the visit and the sale, even if this customer already came on your website from another channel in the past. For example, you discover a brand on Instagram, visit the website but don't buy right away. 3 days later, you type the name of the brand in Google, clicks on the first Google ad to go to the website and order a product. With the Last Click method, the sale will only be attributed to Google Ads, even if Instagram played a huge role in it.
So Last Click is flawed, but still really popular because it's really easy to set up and track. That's the model most early stage eCommerce websites adopt, before evolving to more precise ones when they grow.
2️ First Click
First click is kind of the anti last click. It means that we will only link the order to the first channel who made the customer come to the website. In our previous example: Instagram. It may make sense in some cases, but it's also flawed because it doesn't take into account all the efforts you may have made to make the visitor come back and to convince them to buy. But it's great to measure which channel has the strongest impact on the awareness of your brand.
With the linear method, you'll split equally the attribution to every channels used by the customer before ordering. In our example, it means that Instagram will get 50% of the credit, and Google Ads the other 50%. This won't be accurate, but it's more fair than the two first methods. And it will help you to map the journey of a customers before an order.
This is the hardest model to set up, but it's quite an interesting one. This model gives more credit to channels closer to the sale. The idea is to say that the closer the channel is to the sale, the biggest impact it had. It may be true in some cases, the last efforts you made to convince your customers being decisive, but it doesn't show what really made your customer consider the order at first.
The limits of attribution models
As we can see above, every attribution model has a limit. So with analytics it's really hard to truly understand what convinced people to buy and which lever had the biggest impact. Therefore, it's complex to know on which channel you should invest more or less to increase your performances.
And more and more popular channels are not trackable with analytics solutions. Podcasts or influencers, for instance, are channels where you can't put a tracking pixel. Even if you can get data on how many people listened to an episode or saw a story, it's not enough to measure the impact of these campaigns. And even if coupons or special URLs can give you an idea of the performances, they can't tell if the customer already made their buying decision thanks to another channel and was just waiting for a small cut on the price.
Yet, every eCommerce website needs to have a clear understanding of all of this to optimize their ROI and ROAS. So finding a solution is key.
'How did you hear about us?' Discover the Attribution Survey
To solve this critical issue, an attribution survey could be the key.
An attribution survey is a simple survey, asked right after a purchase, that will help you to understand how your customers knew about your brand and what pushed them to order.
Most of the time, the survey will start with a straightforward 'How did you hear about us' question and a list of options. This may seem basic but, actually, it's one of the most efficient way to have a clear picture of what really drove action.
The responses you'll collect will be a great way to complete the analytics data you already have and will help you to balance your spendings and invest more and what is really working for you.
What question should you ask?
Keep it simple. 'How did you hear about us?' works really great. You can also try variations, like 'One more thing, how did you hear about us?' or 'Where did your first discover us?' or be a bit more precise about what you want to learn, like 'Where did you most recently see and ad about us?'.
In addition to the question, list the options of responses. This will be easier for your customers to respond and so you will get more answers. Social Media, TV Ad, Podcast, Influencer, Google, etc. List everything that is relevant to you. And don't forget to add an option for your customers to respond something else. You could discover that you've been mention in a community you don't know that is actually driving a lot of trafic on your website, for example!
Where should you display this survey?
The most efficient way to collect accurate responses is to ask this question right after a purchase. At this moment, your customer is highly engaged with your brand, happy about the purchase they just made and still remember the context that brought them to order.
Another benefit to asking questions here is that you'll also be able to link order informations to the responses and so you'll be able to analyze data even more precisely. For example, if you link the amount spent to the responses (something you can do with Screeb), you could discover which channels are the most efficient for the people who spend the most on your website, etc.
How to analyze data?
By deploying an attribution survey, you'll start to collect responses that, obviously, you'll need to analyze. The first thing you can do is simply read the results. The breakdown of channels will give you an idea of the volume, for all your customers. You could already spot huge differences with your analytics!
This breakdown could also help you to see if platforms are over or under reporting their performances. And if you link traffic sources to your responses (something you can do with Screeb), you could spot differences between the traffic drivers and the perception of your customers.
In addition to this simple breakdown, use the linked informations to segment your data and have a better understanding of your customers' behaviour.
For example, filter the results on every order above a specific amount and see if the channels are different. Or if you link the type of products bought by people to your answers, filter on product categories you want to invest more on in the future to know what is driving sales.
The more data you'll link to responses, the more precise your analysis will be.
When do I start?
Right now! Start in a few clicks with Screeb. Deploy our tag on your eCommerce website and trigger an attribution survey on your confirmation page. With our 60% response rate in average, you'll get responses and a better understanding of the performances of each channel in a few hours!