Varos Glossary

Attribution Modeling

What is Attribution Modeling?

Attribution modeling allows marketers to ascertain the most productive advertising channels by apportioning credit for ad performance across many publishers. Advertising agencies utilize marketing attribution modeling to assess the efficacy of various promotional channels.

You may improve your chances of converting more leads by providing credit to your marketing channels and touchpoints by:

  • Figuring out where in the buyer's journey you can make changes
  • Calculating the return on investment
  • Finding out the most productive uses for your marketing dollars
  • Creating personas and focusing your marketing efforts on them

Types of Attribution Models

Several popular varieties of attribution models exist. Each attribution model considers the customer's journey to conversion, but different models assign varying values to the various steps along that path.

  • First-Touch

In the context of conversion modeling, "first touch" refers to the very first point of contact between a consumer and your business.

Pros and Cons

The ease and clarity of first Interaction attribution are what draws most people to it. However, this approach needs to account for the influence of subsequent marketing channels, such as retargeted advertising, which may significantly impact the essence of the business.

If your industry has a quick purchase cycle, this approach might be useful as well. The initial point of contact with a consumer is crucial if there is a high propensity for instantaneous conversion. The first interaction is also a useful approach for assessing the efficacy of various channels if expanding your business's base of early-stage clients is a primary priority.

  • Last-Touch

In contrast to the previous model, last-touch attribution modeling attributes success only to the most recent touchpoint a lead visited before converting.

  • Multi-Touch

The strength of multi-touch attribution modeling is in its ability to include all of a customer's interactions across all channels and touchpoints that led up to a conversion. You may learn which channels and touchpoints had the most impact on a consumer and how they interacted with one another to shape their decision.

  • Cross-Channel

The terms “cross-channel attribution modeling” and “multi-touch attribution” are used interchangeably. But there is some wiggle room in their definitions. Instead of focusing on the individual touch points inside a marketing channel as multi-touch attribution does, cross-channel attribution assigns value to the channel itself, whether that's paid, organic, or social.

  • Linear

Multi-touch attribution may take the form of linear attribution modeling, which attributes the same weight to each channel and touchpoint that a client used before making a purchase.

The best attribution model for ecommerce doesn’t exist. Not everyone has the same needs and many organizations utilize multiple models. 

The Significance of Attribution Modeling

One of the most important aspects of mobile measurement is attribution modeling. It plays a crucial role in helping marketers identify which channels are producing profitable clicks

  • Without an ecommerce attribution model, an advertiser cannot know how much traffic is generated from which channels, how much it is costing them, or whether or not it is generating a return. 

With the right modeling in place, however, marketers can fairly attribute success (and blame) to customers who came to their site through various means. The advertiser may then quickly and simply evaluate the quality of the traffic coming from each channel and make informed choices about how to allocate the future budget best.

With the help of the media attribution model, you can zero in on the customer lifecycle and determine which stages are successful and which may need some tweaking to better serve your clients. Furthermore, it reveals how your various marketing touchpoints and channels are collaborating to bring about the desired outcome of increased conversions.

Identify the proper instrument for you, decide which models will provide you with the data you care about, then get into attribution modeling.