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On this page

  • Current State of Web and App Attribution
  • Observe user journeys across the web and app at a glance
  • Unified Attribution Measurement for Web and App
  • Building a Web-to-App Experience and Measuring Performance
  • Key marketing approach: Unified web and app attribution
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Your key marketing approach: Unified web and app attribution

2024年1月8日6 分钟阅读
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Your key marketing approach: Unified web and app attribution

The advent of mobile devices has significantly transformed the marketing landscape, with these compact and user-friendly devices becoming integral tools in our daily lives. As users seamlessly navigate through diverse devices, platforms, and spaces, accurately measuring marketing performance has become a critical task for digital marketers. However, the difference in attribution logic between the web and apps adds complexity, making it challenging for marketers to assess the effectiveness of their campaigns. This post delves into the ever-increasing importance of unified web and app attribution analysis, shedding light on its role in addressing common challenges in today's dynamic internet landscape.

Table of Contents

  • Current State of Web and App Attribution
  • Observe user journeys across the web and app at a glance
    • Unified Attribution Measurement for Web and App
    • Building a Web-to-App Experience and Measuring Performance
  • Key marketing approach: Unified web and app attribution

Current State of Web and App Attribution

In the early days of the Internet, user journeys were confined to the web, primarily on desktop platforms. Unique users were identified using website cookies, HTTP Referers and UTM parameters helped determine the source website and keyword from where the user originated. While cookies play a role in user identification for web attribution, their limitations, such as expiration dates and browser-dependent differences, prevent them from providing a comprehensive identity. Once a user is identified, the HTTP Referer value for Site A's URL enables verification of whether the user visited Site A before reaching your website. However, it’s important to note that the HTTP Referer can be manipulated and may be lost during user redirection. UTM parameters offer a solution to collect extra campaign information, allowing the addition of five custom campaign details to the URL. Leveraging the data from these parameters is crucial in optimizing campaigns and maximizing marketing performance.

Meanwhile, apps were born with the introduction of smartphones, tablets, and other devices. User journeys have become more complex with the mixed use of web and apps across mobile and desktop. The introduction of the app store and the necessity to analyze app installs and conversions ushered in a new phase of attribution. Unlike web attribution, where clicking a link directs users to a webpage, using apps involves redirection to an app store. This redirection creates a tracking gap in monitoring the user's journey from ad click to app open, particularly given that app stores are outside your ownership, unlike websites where direct access to and analysis of log data is possible.

App attribution tools take center stage in bridging this gap. When running an ad campaign with a link provided by an app attribution tool, you gain the ability to link and trace the user's movement from the app store to the app's opening. Identifying users engaging with various apps and web browsers on mobile is made possible through unique advertising IDs like GAID and IDFA, each assigned to a specific device. In addition to identity matching using these advertising IDs, app attribution tools employ both deterministic methods such as Google Play Referrer and Deeplink matching (providing approximately 100% matching) and probabilistic methods like fingerprinting (matching a combination of the user’s web browser information, such as IP, OS, device name, etc., with information collected from the app SDK) to track users in and out of the app.

However, concerns arose about privacy infringement regarding the advertising ID assigned per device. With the implementation of the GDPR (General Data Protection Regulation) in 2018, the industry faced a unique set of challenges in protecting user privacy while enhancing sophisticated performance tracking. In line with this initiative, Apple launched a new attribution framework called SKAdNetwork(SKAN) to replace unique identifiers and measure the performance of cross-channel platforms. 

👉 Learn more about the SKAdNetwork(SKAN) framework

Observe user journeys across the web and app at a glance

Unified Attribution Measurement for Web and App

Traditionally, marketers measured attribution separately for web and app spaces, leading to siloed attribution practices. For marketers managing both websites and apps, this has led to using multiple analytics tools to measure ad performance in different segments, even for a single campaign. When a user arrives on the web through a web campaign and subsequently installs the app, triggering an in-app purchase event, the task of identifying if this is the same user becomes challenging.

Moreover, if conversions take place from browsers other than the web campaign or from apps, they might be labeled as organic or unattributed, potentially fostering a perception of underperformance. For a comprehensive understanding of your marketing performance, utilizing an analytics tool capable of measuring attribution across both apps and the web is imperative.

Airbridge provides both Web SDK and App SDK (Software Development Kit) to collect data from each platform. The Aribridge Identity Resolution engine allows you to combine this data and easily view app and web attribution performance based on Airbridge ID in one dashboard.

Building a Web-to-App Experience and Measuring Performance

Illustration

Web and app marketing each have their advantages. Website marketing, drawing in more traffic and offering diverse spaces, generally proves to be more cost-effective than app marketing. However, as conversion rates and revenue tend to be higher on mobile apps than on the web, it becomes essential to encourage users to transition to the app. This can be achieved by using call-to-action (CTA) buttons on the web, prompting users to install the app or navigate to a specific page within the app.

Several Airbridge customers are leveraging contextual deep linking, a powerful feature that allows for the inclusion of custom data regarding the specific links users clicked on, the original link sharer, and additional relevant information. This capability enables the redirection of users to in-app pages seamlessly connected to the content they viewed on the web. Moreover, businesses can enhance user engagement by incorporating personalized welcome messages and promotion codes directly on the web page, tailoring the overall user experience.

By building a finely tuned web-to-app experience and integrating attribution analytics, companies can establish a more effective and targeted marketing strategy. This approach not only enhances user engagement but also enables businesses to understand and optimize the user journey across both web and app platforms.

Airbridge offers a Smart App Banner feature on the mobile web for seamless transitions between platforms, encouraging app installs and in-app conversions. Through smart app banners, you can build an effective web-to-app attribution environment by improving app installs and in-app conversion rates for users acquired from the web
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👉Learn more about web-to-app marketing guide

Key marketing approach: Unified web and app attribution

Along with changes in the era and industry, the methods of analyzing performance and marketing campaigns are continuously evolving. We are now in an age where a user seamlessly moves across various devices and platforms, creating a constant demand for solutions capable of comprehensively monitoring these user journeys. Airbridge is taking a proactive approach to tackle these challenges, prioritizing the protection of personal information and addressing the obstacles faced by marketers. Explore a single view of user journeys across web, app, and web-to-app attribution, all without any disruptions in the analysis.

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