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Attribution Modeling in Marketing

What is attribution modeling in marketing? Attribution modeling is a process that identifies and assigns credit to marketing touchpoints during the customer journey. Touchpoints are simply single events where customers or prospects engage with a business. They can range from first interactions (where customer data is collected) to down-funnel interactions or in B2C for example, physical PoS (point-of-sale) transaction events. 

A common form of attribution modeling is multi-touch attribution, where interactions -- ranging from first-touch to repeat engagements or business -- is collected, weighed, and analyzed to better understand customers conversion events and spend optimization across the various customer touchpoints.

Attribution modeling variations

Below are some of the most common attribution variations in marketing:

  • First-touch attribution: in this model, full credit is given to the marketing activity or channel that generates the first customer interaction
  • Last-touch attribution: In this variant full credit is given to the marketing activity that directly precedes a customer transaction or deal. It is not uncommon in B2C marketing for first- and last-touch attribution to overlap.
  • Multi-touch attribution: This model shares credit among all defined touchpoints, often weighed uniquely for impact. When credit is assigned equally, this variant is called linear attribution.
  • Time-decay attribution: This variant assigns higher value to touchpoints that happen closer to the transaction. The further back in time a touchpoint is recorded, the less credit it is given in influencing the transaction.
  • U-shaped attribution: In this model, first-touch and last-touch are assigned more value over the touchpoints that occur in-between.

While the above models are most common, there are also many marketing organizations that employ highly customized models that may combine elements from the more traditional models.

The common connector in all these models, as always, is data, often lots of it. With campaigns running across various inbound and outbound channels -- and in some cases, mixed with physical interactions such as on-premises purchases and service interactions -- collecting, processing, unifying, and analyzing data in near real-time is essential.

Snowflake and Marketing Attribution Modeling

Snowflake’s AI Data Cloud virtually eliminates data silos to create a single repository for a single copy of your data. As a result, marketing teams extract deep insights and deliver timely, relevant and consistent customer messaging and offers. With Snowflake for Marketing Analytics, businesses can gain a single, 360 view of the customer to enhance personalization and boost ROI. In addition to internal attribution data, Snowflake allows secure data sharing across departments, geographies, and partner ecosystems as well as access to third-party data augmentation through the Snowflake Marketplace.