Multi-Channel Attribution: Know Your Audience and Why They Convert

It’s not what you know, but who you know. That quote is supposed to be about networking. But it’s even more important to know who’s converting at your ecommerce shop.

The problem? It’s challenging to know who’s doing what when we live in a multi-channel world. Roughly 75% of marketers are using a multi-channel approach as of 2022. And today’s shoppers often experience a variety of different touch points with a shop before purchasing.

When one of these multiple-touchpoint customers finally makes a purchase, do you know why they did?

Enter multi-channel attribution. Multi-channel attribution refers to the data and analytics you use to measure your marketing success. More specifically, it addresses who your customers are and where they came from using metrics that are relevant to your programs.

Did they buy your product because they saw it on Facebook ads? What if they dropped out of a cart, received an abandoned cart email, and then finally made the purchase? To what do you attribute that purchase?

Answering these questions is complicated. But it’s also rewarding. With multi-channel attribution strategies in place, you’ll know where your future ad dollars need to go to generate the highest possible ROI for your shop.

Table of Contents

1. Multi-channel attribution definition 
2. Why does an ecommerce store need multi-channel attribution? 
3. Types of multi-channel attribution models
4. Common challenges with multi-channel attribution
5. Getting started with multi-channel attribution
6. Two examples of ecommerce stores using multi-channel attribution

Multi-channel attribution definition 

Multi-channel attribution means tracking your conversion analytics and determining which marketing channels in a customer journey leads to a sale. Ecommerce shops do this because they need to know which marketing channels are generating the best ROI.

There are generally two types of attribution in analytics:

• Single-touch attribution. Imagine a customer seeing a Facebook ad you’ve placed. They visited your store and clicked Buy, but never finished the checkout process. They later get a cart-reminder email that encourages them to finish. This type of attribution would view that sale as coming from a single channel, rather than as a multi-touchpoint event.
• Multi-touch attribution. Multi-touch attribution adds more context. In the example above, the credit of the conversion would go to both Facebook ads and abandoned cart emails. 

The goal behind multi-channel marketing attribution? To arrive at realistic conversion numbers for each marketing channel.

Why does an ecommerce store need multi-channel attribution? 

Multi-channel attribution might seem like standard analytics to most. But dig deeper, and you’ll find that sourcing your conversions can be some of the most important work you do as an ecommerce store. Here are some of the reasons you need multi-channel funnel attribution in your analytics.

Multi-channel attribution tracks top-performing marketing digital channels

According to Aman Ghataura, Head of Growth at NUOPTIMA, multi-attribution goes beyond learning where customers are coming from. It means understanding where a shop should spend its marketing budget.

“Typically, ecommerce stores use a combination of paid social and paid search through Google Ads (formerly AdWords) to acquire new customers,” says Ghataura. “They use paid social to generate demand and then Google Ads to Hoover up brand/product-specific traffic where a customer wants to take a second step. Google Ads usually perform at a much higher return on advertising spend (ROAS), as it is high-intent traffic of a limited volume. It is essentially retargeting warm traffic.”

Ghataura notes that paid social ads are typically prospecting cold traffic at a lower ROAS. The problem? Anyone without multi-channel attribution in their analytics wouldn’t be able to recognize the context of each conversion.

This results in misallocating future advertising dollars.

“If one were to ignore multi-channel attribution, they would double down on Google Ads,” says Ghataura. “And reduce spending on paid social to increase overall ROAS. However, this would ultimately result in no sales long-term.”

Growth marketer Zach Grove agrees. “If you don’t have a strategy to give credit to these different channels, you’re flying blind,” says Grove. “A typical buyer journey can involve more than three touch points that ultimately lead to a purchase.”

With that many touch points, only multiple conversion attributions will track which of your digital channels are driving true engagement.

You’ll achieve a better understanding of the customer journey

The more accurate your analytics, the better you’ll understand the customer journey. Multi-channel attribution helps you answer the most basic question of that journey: Which channel did most of the work of converting a visitor into a customer?

Sometimes, the answers are obvious. Take JuiceBlendDry, which discovered about 50% of its conversions came from mobile and tablet devices. It knew if it didn’t optimize these channels, it would risk alienating half of its converting customers.

You may not even know your customers are having specific issues until you optimize the customer journey. That was the case for Spotify. It wasn’t until it surveyed a detailed customer journey map that it discovered customers were having trouble finding Share buttons.

It wasn’t that customers didn’t want to share, it was that they couldn’t figure out how.

How does multi-channel attribution help? With more accurate gauges of what isn’t driving conversions, you can spot similar holes in your customer journey.

Types of multi-channel attribution models

Multi-channel attribution goes beyond single-touch and multi-touch analysis. Let’s break up these categories into different attribution models and try to figure out which one is right for your shop.

Single-touch attribution models

This is the simplest form of all marketing attribution models because it credits one channel for each purchase. But you can still break it up into different strategies depending on how you want to weigh your attribution.

First-click attribution. This is the simplest form of attribution. Whatever generated the customer’s first click gets credited with the conversion. This is true no matter how many channels the customer visits between the first click and their order.

Last-click attribution. The same as above, but reversed. What was the final channel that pushed the customer to the order page?

Last non-direct click attribution. Let’s say a customer clicked around your website a little bit before making a purchase. What was the last touchpoint before their purchase? Under this last touch attribution model, that’s the click that will get the credit.

Multi-touch attribution models

You might have guessed by now that multi-touch attribution models tend to be more accurate. After all, if a customer finds you on Facebook, reads your blog, and decides they love your company, shouldn’t both the blog and the Facebook ad get credit? 

Here are some of the multi-touch attribution models that you might incorporate:

Linear attribution. Someone clicks on an Instagram ad, which takes them to a newsletter signup page, which sends them an email, which results in a purchase. What channel made the sale? Under linear attribution, you would divide the conversion across all channels involved equally, or 33% of a conversion for each.

Last-channel attribution. Similar to last-click attribution, this attribution model disproportionately awards credit to the last channel a customer visited before a purchase. The difference? You would still share attribution with the initial reasons a customer clicked.

Time-delay or time-decay attribution. We’ve previously written about delayed attribution during seasonal promotional events. The time decay model of attribution can alter how much a channel is credited for a conversion depending on its time distance from when the sale goes through.

Position-based attribution model

Finally, position-based attribution models are a hybrid of single-touch and multi-touch styles. 

Also called first-and-last channel attribution, this model puts added weight to the customer’s first and last clicks.

But rather than giving these clicks the complete weighting of the conversion—splitting them 50-50 with no attribution to any channels in between—there’s still some left for any other channels that user may have visited.

If a customer visited four channels, this attribution model might award 40% each to the first and last channels that brought in the conversion. You’d then distribute something like 20% to the channels in the middle.

Common challenges with multi-channel attribution

Of course, multi-channel attribution is not without its challenges. These are some of the most common challenges associated with trying to attribute across multiple channels. 

Misattributing conversions

When you’re first figuring out how to attribute your conversions, you can make mistakes. That was exactly the case for William Harris, founder and CEO of Elumynt. 

Harris cites a study Elumynt conducted. It would scale Facebook ads for a period of 13 weeks. There would be no other changes to its marketing campaigns.

Elumynt noticed that revenue in Google Analytics it could attribute to organic search went up in the exact proportion it did for Facebook ads.

“When we looked deeper into this correlation via Google Search Console we discovered that the growth in organic search was almost entirely from an increase in brand terms,” says Harris. “What first appeared to be staggering weekly growth from SEO was actually only misattributed revenue from brand terms skyrocketing following an increase in Facebook ads.”

Problems like these are why it’s so important to choose an accurate attribution method. Picking one that makes sense for your company may require a few months of experimenting and testing until you feel you have an accurate view of where your conversions are coming from.

New data regulations

In the far-off age of third-party data collection, it was once possible to follow customers around online. 

Not so anymore. The new rules of data privacy require using first-party data to figure out what your visitors are doing before they convert into customers. 

Data can be difficult to track and manage in this environment, says David Lee, CEO of Inyouths LED Mirrors. To combat this, “Businesses need data from all of their marketing efforts to attribute sales to specific channels,” he says.

Once upon a time, it would have been possible to use one analytics solution to cover it all. These days, businesses seem to need entire suites of programs to track all conversions. One possible solution is to use apps within Shopify, such as Google Analytics 4 and Google Tag Manager, or Peel Analytics.

Figuring out offline attributions

If the goal of multi-channel attribution is to generate a more complete picture of which channels are converting, you can’t afford to leave any out. So what happens to offline attributions, like if an ecommerce shopper mentioned your store to someone else in person?

One step is to use customer surveys to fill in these gaps. Some ecommerce owners use Shopify + SurveyMonkey integrations on Zapier to automate this process. Or you might use a Shopify app like Zigpoll.

Set Zigpoll or SurveyMonkey to collect data after purchases. You can use the questions to target the specific channels you haven’t been able to set up with multi-channel attribution, especially conversions with first-touches that mostly happened offline.

Getting started with multi-channel attribution

Setting up your custom attribution model typically involves three key steps: choosing your attribution style, configuring your analytics, and testing and analyzing your data.

Step 1: Choose your attribution style

The first step sounds easier than it is. You’ll choose the style of attribution that most accurately paints a picture of where your conversions are coming from.

For most, a multi-channel attribution strategy is a slam dunk. But which multi-channel strategy is right for you? 

Should you emphasize last clicks? First clicks? Split attribution between both? 

There are a few ways you can diagnose which will work for you:

• Look back at existing analytics. Collect the data you already have and analyze it. What is the picture your analytics are painting? Try running different calculations between first and last-click attributions to see which set of data better resembles your experience.
• Compare multiple data sources. If customers are telling you they converted because of an abandoned cart email, but you’re using first-click attribution, you need to switch strategies to resolve the discrepancy. If you aren’t sure what to do yet, expand the types of data you collect to get a clearer picture. Then revisit the data in 90 days to see if there are insights that can help you choose your attribution strategy.

Step 2: Configure your analytics

“Google’s shift to GA4 from UA will pose another challenge for multi-channel attribution,” said Joe Karasin, Head of Growth at CircleIt Inc. “Most marketers will need to get a firm understanding of how to use GA4 in conjunction with Tag Manager, Meta, and Google Ads to keep attribution models relevant.”

Google Analytics 4, for example, might be set to single-touch attribution by default. And before you choose the attribution model you want to use in Google Analytics, you’ll want to be clear about how it attributes each conversion.

• Cross-channel first click. A single-touch attribution channel that gives 100% of conversion credit to the first channel your customer clicked.
• Cross-channel linear. Multi-touch attribution that divides the attribution equally along all channels the customer engaged with before converting.
• Cross-channel position-based. 40% to the first interactions and last interactions, and then 20% divided among “middle” interactions during the customer journey. 
• Cross-channel time decay. Prioritizes touch points that happened closer to the actual conversion. “A click 8 days before a conversion gets half as much credit as a click 1 day before a conversion,” writes Google Analytics.

Step 3: Test your data and analyze

Once you’ve chosen an attribution model and configured it in your analytics, your next step is to wait.

Why wait? You need to gather enough of a sample size to determine whether your multi-channel attribution is accurately reflecting the conversion data.

“Test,” says Nate Nead of SEO.co. “Test, test, test. … Nothing speaks better than your own data. Your own page will likely convert very differently than a competitor’s—even if someone landed on both pages from the same search.”

In other words, there is no universal answer here, no rule of thumb that says you should always attribute 33.178392% of your conversions to Facebook ads on a Wednesday. However, there are a few steps you can take during the tweaking phase:

• Roll out post-purchase surveys. How do you know what to test in the first place? If you roll out post-purchase surveys, you’ll have data you can compare to your multi-channel analytics. Here’s where you can find the gaps, such as if customers say your landing page made the sale, but you’re awarding 50% of that conversion to paid social media.
• Watch the timing. Even if you’re not sure if you’ve chosen the best attribution model yet, you can get an idea of how accurate it is by watching the timing of your conversions. For example, if conversions spike after you launch a Twitter ads campaign but every other aspect of your funnel is the same, you may think about weighting conversions towards the first click.

Two examples of ecommerce stores using multi-channel attribution

Now that we’ve walked through how to configure multi-channel attribution, let’s look at some examples of ecommerce stores that are doing it well. 

Lil’ Tulips

Lil’ Tulips, a client of Elumynt’s, used the agency’s multi-channel attribution approach to diagnose where its leads were coming from. A majority of their leads were sourced through Google and Facebook ads.

Though the execution of multi-channel attribution takes time, the results were clear for Lil’ Tulips. By using analytics to identify their strongest-converting channels, Elumynt was able to generate 5,600% return-on-ad-spend on Facebook ads.

The Vitamin Shoppe

The Vitamin Shoppe has always worked with both online and offline retail. Through the past several years, it’s slowly combined the two. In 2017, it made it possible for customers to sign up for online auto-delivery within its brick-and-mortar stores.

Working in a hybrid environment like this can make it difficult to tell which customers came from where. Do in-person orders that auto-ship over the web every month count as retail conversions? What about someone who browses online first, then decides to visit a brick-and-mortar store? 

Over time, The Vitamin Shoppe has found a mix of multi-channel attribution that helps them better understand what customers want.

Use multi-channel attribution to better understand your customers

Multi-channel attribution sounds complicated, but it should be the opposite. Once you properly configure your attribution, it should clarify who your customers are and where they’re converting.

It won’t happen overnight, but download our Omnichannel Commerce Guide and you’ll see how simple it can be to build a multi-channel ecommerce presence you can scale, grow, and optimize.

Multi-Channel Attribution FAQWhat is multi-channel attribution?

Multi-channel attribution is the assignment of conversions to customers based on specific acquisition points. That’s points, plural. Using multi-channel attribution, you can credit purchases to different channels in your sales cycle, such as 40% Facebook ads, 40% abandoned cart email, 20% newsletter content.

Why should I use multi-channel attribution?

If you use omnichannel marketing, multi-channel attribution is the only way you can accurately gauge what’s converting your customers. Given that so many customers use multiple channels before buying a product these days, multi-channel attribution gives you a more thorough understanding of your customer data.

What are the advantages of multi-channel attribution?

Improving accuracy is the key here. But the benefits of increased accuracy when measuring your conversion value can extend far beyond marketing analytics. Many companies find that they increase their ROAS (return on ad spend) once they’ve properly configured their analytics. 

How do I know if I need multi-channel attribution?

Using omnichannel marketing strategies may require multi-channel attribution if you want to make sense of your conversion data. Check your ecommerce data analytics for signs that your conversion data is out of whack with your marketing activities and spending. 

Simply put, if your data isn’t up to snuff and it’s leaving you guessing where you should spend your next ad dollar, you may need to embrace multi-channel attribution.

What are the types of multi-channel attribution?

Within multi-channel attribution, there are a few strategies you can adopt, depending on how you think you should weigh each conversion. Here are a few:

• Linear. Linear multi-channel attribution takes every channel involved in a customer’s unique journey and divides the credit for the conversion equally.
• Position-based. Do you want to weigh the last click before the conversion? Position-based multi-channel attribution might award 40% each to the first and last interactions, then divide the rest between channels in the middle.
• Time decay. Google Analytics can sometimes use cross-channel time decay to prioritize touch points that happened closer to the conversion.

The linear attribution model gives equal weight to all channels involved, while other strategies will give weight to specific points in the customer conversion path.

What key steps should I take for multi-channel attribution?

Configure your existing data analytics to handle multi-channel attribution with your chosen formula. For example, Google Analytics might be set to single attribution if you don’t configure the attribution model you want to use.