What is marketing attribution?
Marketing attribution is like our magnifying glass for results. It helps us figure out which tactics are really driving sales or conversions. The main goal is to find out which marketing strategies had the biggest impact on the decision to convert. When we know exactly when and why someone decided to convert, it helps us see which marketing tools are doing well and which ones aren’t. In simple terms, it’s our way of proving to the client and helping them understand their target audience better.
How is marketing attribution measured?
There are two methods used for marketing attribution, namely the single-touch attribution model and the multi-touch attribution model.
First-touch attribution operates under the assumption that a consumer converts immediately after encountering the first advertisement they see, attributing the entire conversion to this initial touchpoint. Conversely, last-touch attribution allocates credit solely to the last touchpoint the consumer engaged with before making a purchase.
While these methods can provide some valuable insights, they have their limitations. They overlook the complete customer journey, and relying solely on them doesn’t paint the entire picture of why a conversion occurred.
Multi-touch attribution is the favoured approach for achieving accurate marketing insights as it comprehensively evaluates the events leading up to a purchase decision. Several attribution models offer distinct perspectives:
Linear attribution: This method assigns equal weight to every interaction a consumer has before making a purchase. In this model, no single interaction is considered more important than another, as they all contributed to the eventual sale.
U-shaped attribution: Unlike linear attribution, this model differentiates interactions, scoring them independently. It assigns a 40% value to both the first touch and the last touch, with the remaining 20% distributed among the engagements that occurred in between.
Time-decay attribution: This approach emphasises the chronological path to purchase, granting more credit to touchpoints that happened closer to the point of conversion. For instance, if you ran advertisements for months but a final, impactful sale led to numerous conversions, the sale advertisement receives the most attribution because it was closer to the point of sale.
W-shaped attribution: Like the U-shaped model, this attribution method also includes the “opportunity stage,” which is the last touchpoint before a lead transforms into a customer. Here, credit is distributed as follows: 30% each for the first touch, lead conversion, and opportunity creation, with the remaining 10% distributed among the other engagement points.
These attribution models offer diverse perspectives on customer journeys, helping marketers understand the various touchpoints’ contributions to sales and conversions.
How to choose the right attribution model for you
Remember, there’s no one-size-fits-all approach in marketing, and what works for one may not work for another. This also applies to marketing attribution. You should consider factors like your marketing methods, campaign durations, and the balance between online and offline efforts. Often, companies need to explore multiple attribution models to find the one that suits them best.
Start by deciding how often you want to perform marketing attribution analysis, whether it’s during sales events, monthly, or annually. And don’t limit your analysis to just advertising – take a close look at your content data, too. Find out which types of content generate the most leads and pinpoint the most effective lead generation channels. This will give you valuable insights into your content performance.
Also, assess your website pages and identify those with the highest views before conversions happen. This will help you figure out which pages are contributing positively to your goals, and which may need improvement.
There are plenty of marketing attribution tools available, like HubSpot and Google Analytics. Choose one that suits your business model. Ultimately, the goal is to pick a tool that provides accurate data. The more you understand about your brand, product, or service, the better you can fine-tune it for improved conversion rates.