Attribution

What is Multi-Touch Attribution?

Multi-touch attribution is a marketing measurement approach that assigns credit to each channel involved in the consumer journey, helping marketers understand each channel’s impact on conversions.

This data enables marketers to make informed decisions about which channels to use for brand awareness and which to focus on conversions, while also identifying channels that work well together.

For example, a consumer might ignore a display ad but engage with an Instagram ad and later respond to an email offer. Multi-touch attribution allows marketers to credit both the Instagram ad and the email for the purchase.

Types of attribution models in Lifesight

• First Touch: All the credit for a conversion goes to the first interaction a customer has with a brand. It's useful for understanding how marketing efforts initiate customer journeys (i.e., at the top of the funnel).
• Last Touch: This model assigns all the credit for a conversion to the final touchpoint or interaction before the conversion (i.e., bottom of the funnel).
• Multi-touch (Linear): Linear attribution spreads the credit evenly across all touchpoints in the customer journey. It assumes that each interaction contributes equally to the conversion.
• Time delay - This model assigns higher conversion credit to later touch points. The first interaction gets less credit, while the last interaction will get the most
• U-shaped - U-shaped models give 40% of the credit to the first interaction and another 40% to the last. The remaining 20% is split evenly across all intermediate touchpoints.

Types of attribution windows in Lifesight

• 1-Day: Shows all revenue recognized the same day. For example, a users views an ad and purchases immediately.
• 2 Day: Shows all revenue recognized within 2 days of.
• 7-Day: Shows all revenue recognized within seven days of. For example, a user views an ad and purchases 4-5 days later.
• 14 Day: Shows all revenue recognized within fourteen days of.
• 28 Day: Shows all revenue recognized within seven days of.
• Lifetime: An indefinite attribution window; this shows all revenue recognized from an ad regardless of how long it took for the customer to convert. For example, Customer 1 clicks on an ad but doesn't purchase until two years later. Customer 2 views an ad and purchases on the same day. Both of these conversions would be using the attribution window.

Choosing the Right Attribution Model

Selecting the appropriate attribution model is crucial for accurately assessing the effectiveness of your marketing efforts. The right model depends on your business goals, customer journey, and the role each touchpoint plays in driving conversions. Below are common attribution models to consider:

Common Attribution Models:

• First-Touch Attribution:
  • Use case: Best for businesses focused on brand awareness.
  • Description: Credits the first interaction a customer has with your brand for the entire conversion.
• Last-Touch Attribution:
  • Use case: Ideal for conversion-driven businesses.
  • Description: Attributes the entire conversion to the last interaction before purchase.
• Linear Attribution:
  • Use case: Suited for businesses looking to value all touchpoints equally.
    • Description: Distributes equal credit to every touchpoint in the customer journey.
• Time-Decay Attribution:
  • Use case: Best for long sales cycles.
  • Description: Assigns more credit to touchpoints that occur closer to the final conversion.
• Position-Based Attribution (U-shaped):
  • Use case: Effective for lead generation.
  • Description: Splits credit between the first and last touchpoints, with some credit to interactions in between.
• Data-Driven Attribution:
  • Use case: Best for businesses with sufficient data and advanced analytics.
  • Description: Uses algorithms to assign credit based on the actual contribution of each touchpoint.

Key Considerations:

Business Goals: Are you focusing on awareness, engagement, or conversion?
Customer Journey: How many touchpoints do customers typically engage with before converting?
Available Data: Do you have sufficient data to use more complex models, like data-driven attribution?
By aligning the attribution model with your objectives and customer behavior, you can more accurately measure the performance of your marketing channels and optimize your strategy.