What is multi-channel attribution?
Multi-channel attribution refers to the process of determining which marketing channels ultimately lead to a sale and giving each channel the appropriate amount of credit per its role in the sales cycle.
How multi-channel attribution modeling helps marketers
Multi-channel attribution helps sales and marketing teams determine which marketing channels and campaigns are contributing the most towards driving leads and ultimately sales. The current state of marketing is multifaceted, and the sales cycle includes many more touch-points than in the past. The Online Marketing Institute indicates that it takes “7 to 13+ touches to deliver a qualified sales lead.” The advent of digital marketing techniques and the various ways to track leads means that it can be difficult for marketers to know which of their efforts — or which combination of efforts — ultimately drove the sale.
For example, a user may search a keyword related to a Business XYZ’s product or service. XYZ has pay-per-click ads for that keyword, so the user clicks on the top ad result. The user peruses the website for a few minutes and then decides to check other companies and compare offerings and prices. The user gets busy and forgets about the search, but is reminded a few days later when XYZ’s remarketing campaign pops an ad on the user’s sidebar while they’re reading a news article.
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From there, the user searches XYZ’s brand name and clicks on the top organic result. The user decides to check out reviews of XYZ and goes to a few third-party review platforms and XYZ’s social media pages. An interesting article published by XYZ caught the user’s eye on the Facebook page, and the user clicks back to the site. The user might sign up for an email newsletter and then come back to XYZ’s site directly to show his or her boss before finally getting approval to reach out to XYZ’s sales department.
This kind of interaction with a business is becoming more and more frequent. Gone are the days where a single word-of-mouth referral was the deciding factor in someone making a purchase. As such, marketers need a way to track and assign value to these steps –– not only to prove individual ROI per channel, but to improve the way they’re allocating their marketing dollars and properly fund all the channels driving purchases even when the results from certain channels are not readily apparent. Multi-channel attribution gives sales and marketing teams that data.
What is a conversion?
A conversion is the name we give for an action taken on or off our website that we’ve deemed valuable. Whether that’s a phone call, an e-commerce purchase or an inbound email, these kinds of interactions are what we’re looking to track with any attribution model. What a business defines as a conversion varies based on their own metrics and goals.
For a local bakery, you’d likely be tracking calls, maybe clicks to your “Directions” page, but for another business there could be a host of other website actions that you’d want to track. A car dealership website has options to “Save this Car,” call the sales department, call the service department, get financing info, submit financing info and more; all these should be tracked as conversions in order to better optimize your marketing efforts online.
There are often multiple points of conversion along the way to a final sale, but with default attribution models, these touch-points can often be overlooked. Attribution modeling and more specifically, multi-channel attribution can give you the insight necessary to assign value to these various touch points during the online and offline user journey.
What does attribution mean for my business?
Having a clearer idea of which marketing channels are driving conversions and sales means you can better allocate your marketing dollars to the most effective channels and better track the interactions on a prospective customer’s journey. This helps your business by increasing the efficiency of your spend as you decide to focus on only the channels you know are driving growth.
Additionally, by knowing that certain segments of your market engage more or less on different platforms, you can start to optimize your content to fit each platform for that specific demographic. This again increases the efficiency of your spend as you see higher engagement on these platforms and higher conversion rates, but it also enhances the customer experience.
Proving value per channel
The biggest benefit attribution modeling can give to your business is being able to properly attribute conversion actions taken on and off your site to the correct marketing channel that drove said action. A default look in analytics may show that you’re getting 30% of purchases from direct traffic, 30% from organic, 20% from PPC (pay-per-click) and the rest from social media, but the reality may be far different.
Google Analytics gives credit for conversions to the most recent, non-direct action and Google Ads (formerly AdWords) gives it to the last direct action, ignoring all the steps that could have taken place before. As we dive deeper into the different attribution models available to us by default in a program like Google Analytics, we’ll start to better understand how we can attribute value to touchpoints earlier in the sales cycle.
Optimizing conversion paths
As we start to get a more holistic picture of the prospective customer’s journey – we’ll start to acquire information that will change the way we run our marketing campaigns. Maybe we find out that X% of prospects convert faster when they’ve seen three social media ads. Maybe we’ll realize that prospects who’ve received one or more email are more likely to convert than customers who have not.
It’s this kind of insight that can help us both allocate more time/budget to these channels, but also optimize the conversion paths in said channels.
If prospects who’ve seen an email are more likely to convert – let’s analyze our email campaigns to make sure there’s a clear call to action for every email and once that link is clicked – there’s a clear path to purchase.
By figuring out where these additional touchpoints are taking place we can ensure that these channels are properly funded and optimized.
Types of attribution models
This is the go-to attribution setup for most web analytics tools (minus Google Analytics) and is profoundly deficient at accurately representing the customer path to conversion. Regardless of what touchpoints a prospective customer had with social media, organic or what have you, whatever the last interaction is before the conversion, gets full credit.
Last Non-Direct Click
This model is similar to last interaction but ignores direct traffic. As a result, this option severely under-credits direct traffic. This is the default model used in Google Analytics.
Last Ads Click
This model gives all the credit to the last click on an ad – again – disregarding any other touchpoints a prospective customer may have had prior. This will overvalue Google Ads as a component of your overall strategy.
A first interaction model will give all of the credit for a conversion to the first interaction the customer had with your advertising. If they originally found you via organic search, interacted with you on social media, then converted in the end via a pay-per-click ad, the credit would be given to organic.
The linear attribution model equally divides credit amongst all the touchpoints that took place leading up to a conversion.
Time decay is the first model that starts to solve the problems that exist in the previous models, but is still flawed. Based on a pre-set “half-life,” the time-decay model increasingly gives more credit to touch-points that happen closer to the final conversion event. If for example you set your half-life at 14 days, clicks/interactions that happened 14 days prior to the final conversion event, would receive half credit.
The position-based model allows you to assign X% of the credit to the first interaction the prospect has with your brand and X% to the last interaction and then evenly distribute the rest of the credit amongst the interactions in-between.
This is often the beginning/foundation of some of the more successful custom models employed by businesses as it makes a lot of sense. We can credit the initial interaction with bringing the prospect into our funnel and the final interaction with closing them.
After delving into different pre-set attribution models, some businesses choose to build or utilize more advanced multi-channel attribution models (custom models, data-driven attribution models, Markov models, and more). These models are often more complicated than those listed previously, but can provide more detailed and specific information.
Though more complex, other attribution models are often built on the information provided by the previous, less complicated models. So, if you’re using one of those, don’t fret. Everyone starts somewhere. A business typically either has someone on their team who can program these attribution models or they use a third party service to help them create and track the more in-depth models.
More comprehensive attribution models often assign particular values to points in the user journey based on previous data and conversion values. These values are not often set in stone, but are instead dynamic based on user interactions. For example, Google’s Premium Analytics offers data-driven attribution that assigns value to certain touch points and adjusts based on the most recent conversion paths.
Which attribution model should I use?
It depends on multiple factors including which marketing channels your business uses, how extensive your marketing mix is, what your goals are, and how sophisticated you want to get. Businesses just starting out with attribution should definitely take advantage of Google Analytic’s attribution comparison tool. Here you can apply different filters to determine how each attribution model would represent your data. Google Analytics has Last Non-direct click as the default model, so many businesses often use the existing model without changing it.
There is no “one-size-fits-all” method to track all your marketing channels, so do some comparing and testing to see which model you think best represents your industry, your business, your data, and your customer journey.
How does call tracking help with multi-channel attribution?
Call tracking can tell you what conversion paths your leads are taking before calling your business for both online and offline marketing campaigns. By using call tracking phone numbers, marketing departments can determine which combinations of marketing efforts are leading to the most calls and the best quality leads.
In this post, we explain, “You can view your attribution information through your Calls By Source report and through your Visitor Timeline for each caller.” Online analytics alone cannot tell you which offline campaigns are also contributing to your marketing and sales success. With call tracking, you can see every touchpoint that’s leading to phone sales and optimize your marketing campaigns based on that data.