Measuring Digital Marketing Performance with Attribution Modeling
Attribution modeling can help you measure your digital marketing performance. It allows you to know when, how, and why users converted on your Google ads. Understanding the steps that clients take before converting is equally as valuable to digital marketers as the sale itself.
As a marketer, return on investment (ROI) from your various advertising platforms is the most critical measurement metric you pay attention to on a daily, weekly, or monthly basis. Often, you probably get pre-made numbers calculated by your advertising platforms such as Google Ads or Facebook and call it a day.
However, these numbers alone cannot capture your real marketing ROI precisely. In many cases, you may even get significantly inflated numbers.
This article explains the essence of using attribution models to measure your digital marketing performance and map the conversion paths of your business clients accurately.
What is Attribution Modeling?
According to Google, attribution modeling refers to the rule, or a set of rules, that determine how credit for conversions and sales is assigned to various touchpoints in conversion paths. In simpler terms, it is telling your analytics which keyword or channel to give credit to for a conversion or sale.
For instance, if a business purchased after clicking on a display ad, you can credit the entire sale to that ad. However, what if the client took a convoluted route before buying? Let’s say that they clicked on your company’s display, then on a social media ad a few days later, revisited your website from an organic search listing before converting in-store.
These days, the above example is a relatively simple conversion path.
Attribution seeks to help digital marketers get a better picture of the specific role that marketing channels play to lead to conversion events. You can then use the information to inform your future marketing decisions and budget allocations.
Why Use Attribution Modeling?
So why does it matter which conversion path takes credit and not just say that your entire strategy drove the sale?
The answer is because thanks to today’s era of inbound digital marketing, things are not that simple anymore. It presently takes between seven and thirteen “touches” (known as engagements) with your business site for a lead to convert.
What this means is that a business that makes a purchase could have visited your website, Instagram, email, remarketing ad, landing page, RLSA, and more, within one month.
Now, do you see the problem?
Simply assuming that it was your remarketing ad that made the conversion is flat out inaccurate. It is impossible to conclude whether it was the ad or a combination or multiple channels without using attribution modeling.
Attribution modeling helps you get precise data on what specific channels played the most significant role in the conversion of prospects.
The following are the commonly used attribution models.
- Last-Click: This model gives all conversion credit to a client’s last touchpoint. It’s a one-touch model that does not consider any other engagements that a user had with your company’s marketing efforts before their last engagement.
- First-Click: It’s another one-touch attribution model that gives 100 percent credit to the first action that a client took during their conversion journey. Therefore, it ignores any subsequent engagements that clients have had with your other marketing efforts before converting.
- Linear: Refers to a multi-touch model that gives equal credit to all touchpoints along a user’s path.
- Time Decay: It gives those touchpoints occurring closer to the time a client converts more credit than those further back in time. Thus, the closer in time to a conversion event, the more credit a touchpoint receives.
- Position-Based: This model gives the first and last engagements the most credit for a conversion event and assigns the rest to the touchpoints occurring in between the two. In Google analytics, the last and first engagements are each assigned 40 percent, while the remaining 20 percent is distributed equally among the middle interactions.
- Data-Driven: It distributes the conversion credit based on past data collected for this particular conversion action. It’s only applicable to accounts that have enough collected data.
Google Analytics Assisted Conversions
Every conversion has a story. Marketing channels often play different roles in assisted conversions, and you should track their performance accordingly. In Google Analytics, assisted conversions allow you to track the number of conversion assists per channels. You can also compare the number with your overall conversions.
Assisted conversions help you evaluate traffic channels that you may otherwise see as underperforming, but they contribute further up the channel. By default, Google Analytics’ Assisted Conversion reports will display Multi-Channel Funnel grouping, which you can customize to your liking.
You can drill down the report with a granular grouping approach to get a better sense of your top performers, including social channels, referrals, paid campaigns, and offline sources.
You can view your conversion reports with the percentage display. It shows you a pie graph of all the assisted conversion percentage that each channel is responsible for, which is useful if you are tracking e-commerce transactions.
Conversion paths give you an insight into how your marketing channels work together to assist your prospects through their journey. Once you can track the paths that businesses take before purchase, you will see your most effective channel combinations. You can also see which channels have a low impact.
The Bottom Line
Google Ads’ attribution models are not unique to the platform alone. You can also find them in Google Analytics. The truth is, just about any other analytics platform has some form of attribution modeling.
Most advertising platforms offer you various ways of analyzing the data within their platforms. They never offer you a way to figure out your specific attribution channel across other platforms. This creates a data barrier between the platforms that you use and makes cross-platform attribution nearly impossible.
To avoid inaccurate data, you must include attribution modeling to your digital marketing strategy. It should always form part of your lead generation analysis since it gives credit to clicks by campaign or channel before the actual sale.