Airbridge
PricingCustomers
Log InGet Started Free
A

Airbridge AI

Ask anything about Airbridge

Responses are AI-generated and may not always be accurate.
Conversations may be recorded to improve answer quality.

Airbridge

Stop paying for ads that don't perform. Track ad performance to know exactly what's driving your ROI.

Plans

  • Compare All Plans
  • DeepLink
  • Core
  • Growth
  • Pricing

Features

  • Airbridge AI
  • Marketing Analytics
  • Fraud Protection
  • Web & App Attribution
  • ROAS Measurement
  • iOS & SKAN
  • Deep Linking
  • Data Export
  • Audience Manager

Resources

  • Blog
  • Case Studies
  • Glossary
  • Library
  • Academy
  • User Guide
  • Developer Guide

Company

  • About Us
  • Terms of Service
  • Electronic Payment Terms
  • Privacy Policy
  • Information Security
  • GDPR
  • Data Processing Addendum
  • System Status

© 2026 AB180 Inc. All rights reserved.

AB180 Inc. | Business Registration: 550-88-00196

Last Touch Attribution (LTA)

Definition

Last Touch Attribution credits the final customer interaction for conversion, offering a simplified view of marketing effectiveness.

A
Airbridge
May 20, 2024·3 min read

Table of Contents

  • What is Last Touch Attribution (LTA)?
  • What are other attribution models?
    • What’s the challenge with Last Touch Attribution?

What is Last Touch Attribution (LTA)?

Last Touch Attribution (LTA) or Last Click Attribution is an attribution model in performance marketing where the final touchpoint or interaction before a conversion is given full credit for that conversion. It assumes that the last ad, click, or interaction in the user journey is the deciding factor leading to the sale or desired action, hence emphasizing the importance of the closing touchpoint in the conversion process.

What are other attribution models?

Last Touch Attribution: As described, this model attributes the success of a conversion to the final interaction. It is straightforward and easy to implement but may overlook other contributing factors. However, LTA is still an industrial standard and proves to be the most commonly used attribution model up till now, for both advertisers and MMPs like Airbridge.

First Touch Attribution: In contrast, First Touch Attribution gives all credit to the initial interaction that introduced a customer to the brand or product. It's useful for understanding what drives awareness but can ignore the influence of subsequent touchpoints.

Multi Touch Attribution: This more complex model distributes credit across multiple touchpoints along the customer journey. It provides a holistic view of how each interaction contributes to the end conversion, offering a more nuanced understanding of customer behavior based on granular data.

Each of these models has its strengths and weaknesses and should be chosen based on the specific context and goals of the marketing campaign. Mobile marketers should consider their business model, sales cycle length, customer behavior, and available data to select the most appropriate attribution model. To get a better understanding of all the attribution models, please refer to this blog by Airbridge.

What’s the challenge with Last Touch Attribution?

Before diving deeper into this part, you should keep in mind that despite having some shortcomings, LTA is still an indispensable model for both advertisers and MMPs like Airbridge. Such a model has a certain level of clarity, cost and effort efficiency that surpasses other models like Multi Touch Attribution. You should take into account these challenges for a better usage of LTA, rather than totally abandoning the model.

The primary challenge with Last Touch Attribution is its oversimplification of the conversion journey. It ignores all the marketing efforts leading up to the final interaction, which can lead to a skewed understanding of what's driving conversions. This model doesn't account for the full customer journey, potentially undervaluing touchpoints that play a crucial role in nurturing leads and building customer relationships. Other than that, these are some specific challenges this model presents:

  • Bias Towards Certain Channels: LTA can bias in favor of channels that are more likely to be at the end of the customer journey, such as retargeting ads, while minimizing the role of channels that contribute to awareness.
  • ‍Ineffectiveness for Long Sales Cycles: For products or services with longer sales cycles, there are often many significant interactions. LTA does not capture the incremental value these interactions provide over time.
  • ‍Inability to Adapt to Multi-Device Journeys: With the prevalence of multi-device usage, LTA does not account for cross-device influence and conversions that may start on one device and finish on another.

‍

Put these concepts into practice

See how Airbridge helps teams implement mobile attribution strategies at scale.

Get Started FreeView Case Studies

Related Glossary Terms

Expand your understanding with related concepts.

A/B Testing

A/B Testing, a cornerstone of performance marketing, is a methodical approach that compares two versions of a webpage or app to determine which one performs better.

Active User

An Active user refers to an individual who interacts with a digital product, such as a website, app, or online platform, within a specific timeframe.

Ad exchange

An ad exchange is a facilitator of buying and selling advertising inventory.

Ad inventory

Ad inventory is the available spaces for ads on a particular platform or medium.

Ad mediation

Ad mediation is a technology that allows multiple ad networks to be managed through a single SDK. Ad mediation platforms streamline the ad delivery process and maximize revenue, CPM, and fill rates for publishers.

Ad monetization

Ad monetization generates revenue from advertising on a website or mobile app.

Back to Glossary
L