How to Pick an Analytics Attribution Model for Your Business
A baker needs flour to bake a cake. An auto mechanic needs specific tools to fix a car. And marketers need data to maximize conversions.
Marketers thrive on taking campaign, audience, and channel data and boiling it down into actionable next steps or optimizations. However, many marketing teams make the fatal flaw of collecting a wealth of campaign data without a means of organization or attribution.
Multiply that data by the number of products, channels, store locations, and more, and you’ve got yourself an overwhelmed and decision-paralyzed marketer.
Choosing an analytics attribution model will help you make sense of marketing data and use it to make strategic decisions with ease. We’ll show you how to select the right attribution model for your business.
Let’s get started.
What is an Analytics Attribution Model?
Have you ever received a lead from a marketing campaign only to realize you’re not quite sure which touchpoint or tactic to attribute the conversion to?
An attribution model is a process used to identify the source or marketing channel responsible for a successful conversion.
For example, if you have a campaign utilizing a Facebook post, a landing page, and retargeting ads, which tactic or channel should receive the credit for convincing a user to convert?
Analytics attribution models help marketers organize their data and gain insight into which marketing channels and efforts contribute significantly to the overall success of a campaign. Without one or more attribution models, marketers will find themselves once again swimming in data with no sense of direction.
Why Do Attribution Models Matter?
Aside from providing a means of organizing vital data, analytics attribution models provide marketers with multiple benefits.
Better Decision Making
How many times have you had to solely rely on your gut feeling to make a campaign or strategy-based decision? While your gut instinct is a strong compass, nothing beats concrete data showing you the way.
Analytics attribution models allow marketers to back up their gut instincts with hard facts about the success or failure of a tactic, channel, or campaign. With this data in hand, marketers can make smarter and more targeted strategic decisions toward an improved conversion rate.
Accurate Return on Investment
Failing to utilize an attribution model can be costly—literally. By not understanding exactly which marketing channels are generating qualified leads and conversions, marketers run the risk of spending funds on under-performing areas of an overall strategy.
In addition to ensuring that ROI tracking is accurate, attribution models help marketers understand where their hard-earned dollars remain best spent for the desired results.
Unlocking Consumer Behavior
On top of providing quantitative data about conversions, attribution models also highlight the pathways consumers take to conversion. Having this contextual data on hand gives marketers an inside look at consumer behavior patterns within their audience.
With this newfound knowledge, marketers now have a basis for how their customer base interacts with content online. For example, you may discover that your audience prefers to find content via an email newsletter instead of social media. Or, you may find that customers access your website from a less popular search engine before converting.
Imagine if you didn’t have a way to organize and dissect this information! Your marketing team would miss out on substantial consumer insights.
7 Types of Analytics Attribution Models
By nature, attribution models help us assign credit to a marketing channel or campaign responsible for the conversion (a click, purchase, or form entry.)
But, which touchpoint receives the credit will vary based on each brand’s goals. With this in mind, there are seven common analytics attribution models to choose from.
1. First Interaction Attribution
Also known as the “First-Click” attribution model, this option attributes credit to the original touchpoint that ignited the conversion path.
Let’s imagine you click on a Google PPC ad for an e-commerce product. After spending time on the product page, you decide to hold off on your purchase until you’re sure you want to buy.
A few days later, you receive a Facebook retargeting ad for the same product. This time, you click on the ad, interact with the landing page, and ultimately make a purchase.
According to the first interaction attribution models, the Google PPC ad gets credit for the conversion.
Some marketers prefer this attribution method due to its simplicity. There’s no arguing which touchpoint came first. Most marketers use first click attribution to organize top-of-funnel campaigns for this reason.
However, others argue that first interaction models are too basic and ignore other influential conversion factors, such as the retargeting ads mentioned in our example.
2. Last Interaction Attribution
As the name implies, this attribution model gives credit to the last lead interaction before a conversion. In our previous example, the Facebook retargeting ad would be responsible for the purchase under this attribution method.
Last interaction attribution is also incredibly simple to implement and understand. However, once again, this model ignores every touchpoint and lead interaction that happened before the conversion.
With this in mind, last interaction attribution models are ideal for products and services with short turnaround or buying cycles.
3. Last Non-Direct Click Attribution
Imagine a customer found your website from an email newsletter link. After clicking on the link, they browse your website content and leave.
A few days later, they decide to return to your website. But this time, they type your URL into the search bar and go. During this visit, they convert. Which source of traffic gets the credit for the conversion?
According to the last non-direct click attribution model, the email newsletter campaign is the conversion source.
Last non-direct click attribution models assign credit to the last place a user clicked and do not include any direct interactions or traffic.
This model assumes any direct traffic after the click results from the visitor learning about your website and brand through the last interaction. Like the previous models, this attribution method is simplistic and does ignore other touchpoints.
But, depending on your goals—such as identifying high-performing marketing channels—last non-direct click attribution may be the right avenue for you.
4. Linear Attribution
A linear attribution model grants credit equally among the interactions or touchpoints leading up to the conversion.
For instance, if a lead clicked on your organic search listing, entered their contact information into a form, received an email newsletter, and saw a retargeting ad all before converting, each channel would receive 25% of the credit.
If that purchase totaled $200, each channel generated $50 worth of revenue toward your bottom line.
While easy to understand, linear attribution models can be tricky.
With each piece of the puzzle receiving equal credit, it becomes difficult to understand which channels and strategies are carrying the weight and which are merely a blip in the process.
5. Time-Decay Attribution
Much like linear attribution, time-decay attribution distributes conversion value across touchpoints. However, this model considers when each touchpoint happened and delivers the most credit to the last touchpoint or interaction.
Engagements that occur closer to the conversion receive more value, while those at the beginning receive less.
Time-decay attribution models work best for those operating on a longer sales cycle, such as for larger products or B2B relationships. With this model, however, you can use the data to determine which tactics work best as top-of-funnel campaigns and which drive the conversion home.
6. Position-Based Attribution
Also known as a U-shaped attribution model, the position-based attribution method assigns the majority of credit to the first and last touchpoint.
The first touchpoint is responsible for initiating the process, while the last generates the conversion. Each interaction should receive most of the credit.
Let’s imagine a user had four touchpoints: an organic Instagram post, a retargeting ad, an email campaign, and a Google search.
Since the customer found you through Instagram and ultimately converted after searching for your brand on Google, these two interactions receive the majority of the conversion credit. The remainder gets divided between the other touchpoints.
That is among the most desirable attribution models due to acknowledging the starting and ending point of a conversion path.
7. Custom Attribution Models
If none of these attribution models sound right for your marketing needs, you can create your own!
Consider the following when developing a personal attribution model:
- How long your typical sales cycle or process is
- What type of tactics you’re using to entice a conversion (Top-of-funnel? Relationship building? Etc.)
- Do you have the data you need to fully create an attribution model?
Custom attribution models can be set in Google Analytics, as well.
How Do I Choose the Right Attribution Model?
With so many attribution models available, knowing which one to pick can be a challenge. Some models will work great for one marketer and not for another.
It all boils down to considering:
- What are your marketing goals?
- Which attribution models make sense for my end goals?
- Which method is most effective at providing the data I need to be successful?
- What am I trying to accomplish by selecting a specific attribution model?
In the end, you may find that you need to test out a few models before choosing one to move forward with.
Attribution Models Without Call Tracking Will Ultimately Fail
At the end of the day, reporting platforms like Google Analytics only tell half the story.
Your designated attribution models are only factoring in a fraction of the touchpoint data. In reality, many customers are interacting with your brand offline before committing to a purchase or conversion.
Call tracking can fill in the offline interaction gaps.
Using specific vanity and/or toll-free numbers, call tracking can tell marketers how customers found their brand information before placing a call. This extra touchpoint provides qualitative and quantitative data marketers can use as part of their analytics attribution models.
Add call tracking capabilities to your marketing strategy and experience a fully transparent and data-filled attribution model.