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How To Determine Which Attribution Model To Use

Agencies and clients looking to expand their knowledge of the digital marketing space where many potential customers live are inevitably faced with a quandary. How do I know my media is working? They need to know how to determine which attribution model to use.

Of course, the answer depends on the answers to other questions: Who is your audience, and where are they? 

Fortunately, Leavened has simplified the process for you. Here are several common attribution models and how they can be applied to you or your clients’ business.

Attribution Models: Which One To Use?

The most common attribution models differ in the respective weight they assign to customer journey touchpoints. Each has benefits and limitations, a few of which we’ll go over with each type of attribution.

  • First-touch (or first-click) attribution: This model is just like it sounds! First-touch attribution models give credit for sales to a customer’s first interaction with the business.

Easy to set up and understand, there are nevertheless limitations in what it reveals about customer journeys.

Perhaps the biggest criticism of this approach is that it oversimplifies what can be in reality a complicated series of events leading to a sale.

  • Last-touch (or last-click) attribution: The flip side of first-touch attribution. With this model, conversions are credited to the final touchpoint.

This is a standard attribution model for Google Analytics, and it’s generally considered a conservative approach. It’s easy for marketers to set up, and it provides a relatively error-free analysis.

However, like first-touch attribution, it doesn’t reveal much about the customer journey, which can be more complex than this model can depict.

  • Time decay: This attribution model also helps marketers pinpoint which channels are generating conversions. It assigns credit to each channel that drives conversions. It takes into account the relative weights of last touch (gets the most credit) and first touch (gets the least amount of credit). It is a step on the road to multi-touch attribution.
  • Linear attribution: Rather than give all the credit to one channel or touchpoint, linear attribution reveals all the marketing channels that contributed to a conversion.

With this attribution model, all the channels visited or touched by the customer leading to a sale or conversion are given equal credit. It’s a good way to get a broad overview of which channels are leading to the most conversions.

However, assigning equal weight to each touchpoint makes it challenging for marketers to optimize future ad spends. Linear attribution models are also one step closer to our next category.

  • Multi-touch attribution: This model makes an attempt to fill in gaps or blindspots created by the weaknesses of the previous models on this list. Multi-touch point attribution allows for the evaluation of an entire customer journey toward a conversion.

With this approach, one can determine which touchpoints — or combinations of touchpoints — are most likely to lead to conversions.

Choosing An Attribution Model

Over time, attribution models provide us with a picture revealing how marketing tactics contribute to key performance indicators (KPIs). In turn, we can see how KPIs contribute to revenue.

Consider the marketing costs of advertising for linear TV, streaming video/OTT, Google Ads, Facebook ads, Instagram ads, organic search, content marketing, or other channels. Both large and small businesses want to know that whatever amount of money they spend will provide a quality ROI and help them achieve their marketing goals.

Regardless of which model you choose, you’ll want to base your decision on the type of customer journeys most often associated with your customers and your predetermined KPIs.

Without those two fundamental pieces of data, it will be hard to pinpoint the right attribution model for you and, therefore, the right placement and level of marketing spend. 

For those looking for more comprehensive measurement and strategic solutions, we utilize a proprietary marketing and data analysis solution that we call the Leavened Iterative Hypothesis Testing Engine (LIHTE). 

We’ve discovered that cookie-based performance signals provide few actionable insights for business growth. Leavened’s full-picture approach examines ad spend and determines how each did or did not contribute to incremental impacts on revenue. This helps inform the next round of media spend.

It’s a powerful combination of factors and efforts which will help businesses achieve sales right now while building long-term, reliable growth.

Marketing Mix Modeling

We focus on marketing mix modeling and marketing measurements that track and quantify incremental lifts in online and offline revenue streams.

Leavened can reveal incremental impacts of marketing tactics in ways that are not available with first touch, last touch, or multitouch attribution models.

In fact, our tools run millions of models in a fraction of the time it takes more traditional and less insightful models to compile their data.

The Leavened model can scale up or down with ease, too. And our model is not a black box; each step of our analysis is downloadable and completely transparent.

Finally, Leavened can incorporate other potential impacts on business in our analyses. For example, we can account for industry and business trends — from pandemic strains on business supply and demand to changes in consumer buying habits.

Questions about Leavened’s approach compared and/or contrasted with the attribution models listed above? Eager to discover which attribution model to use for your own agency or business? 

We can teach you how to use our powerful suite of tools to arrive at marketing solutions specific to your business and your customers.