AXI, or Audi Experience Index, is a robust metric designed to quantify and analyze user engagement on a website. Unlike traditional key performance indicators (KPIs), AXI provides a more comprehensive view of user interactions, helping dealers identify high-value shoppers and optimize their marketing strategies.

AXI assigns a value to online behaviors throughout a shopper’s journey. Higher scores indicate deeper engagement and a stronger inclination to purchase. AXI can be aggregated into a Visitor AXI Score which is a single score out of 10 that can be used to gauge how close to a conversion a particular user may be. The scores of all of your visitors can be aggregated to show how effectively your website is driving engaged customers.

Historically, lead submissions have been considered the highest value digital action a shopper can take on a website. However, lead submissions as a standalone metric have two significant limitations:

2. Limited Conversion Tracking: A substantial number of car shoppers browse a website without submitting a lead. Many shoppers prefer to visit the dealership directly after doing online research. Traditional digital KPIs, like lead submission, often fail to capture these engaged users, resulting in a significant gap in understanding user behavior and potential sales.

Traditional machine learning models can be opaque, providing limited insights into why certain scores are given. AXI addresses this by offering clear, actionable insights based on user behaviors. It evaluates various site interactions, such as clicking calls-to-action (CTAs), viewing vehicle detail pages (VDPs), and configuring vehicle options, to generate a comprehensive engagement score.

In many traditional measurement frameworks, the only way of determining whether a visitor is high quality or not is whether they submitted a lead. AXI opens up additional actions in addition to lead submissions that can be used to judge the quality and propensity to purchase.

AXI operates similarly to a lookalike mode. In this case, T3 lead submitters are used as the seed list, whose data is used to create a lookalike audience. High AXI visitors are those whose behaviors closely resemble these T3 lead submitters. This includes various actions performed on the site, such as:

AXI scores provide a quantifiable measure of the digital sales funnel. A low AXI score does not necessarily indicate low-quality; it may simply reflect users performing upper-funnel activities, which are valuable but do not typically suggest an imminent T3 lead submission. For low AXI score segments, additional analysis is recommended.

AXI is most useful as a relative measure. Comparing AXI performance over time or across different cohorts and segments (e.g., email traffic vs. social traffic) offers valuable insights into user engagement and traffic quality. This comparison helps businesses understand how different user groups interact with your website.

Devices used to view your website can often impact lead submission rates. Mobile users, for example, often engage heavily in research but are less likely to submit leads due to the challenges of form submission on small screens. AXI helps capture the value of these users, who may prefer to call or visit your dealership in person rather than submit a digital lead. This ensures that browsing behavior and potential conversions are not overlooked.

AXI monitors over 100 different actions, known as High Value Actions (HVAs), which contribute to the overall Visitor AXI Score. These actions include:

The AXI algorithm calculates a score indicating the relative importance of each action. Essentially, an AXI score is the sum of the scores of various HVAs:

AXI Score = HVA1 + HVA2 + …

Each visitor receives a score based on their actions, which can be aggregated or filtered to any desired level of granularity.

AXI offers a powerful and nuanced approach to understanding website engagement. By moving beyond traditional lead submissions and providing detailed insights into shopper behaviors, AXI enables dealerships to identify high-value shoppers, optimize their marketing efforts, and ultimately drive more sales. Whether comparing traffic segments or analyzing device-specific behaviors, AXI is an invaluable tool for enhancing digital strategies and maximizing shopper engagement.

AXI is a machine learning model that uses visitor website interactions as the training data set. As a result, this training period can only begin once real shoppers begin visiting the website in production.

During the first few weeks of launch, the AXI and HVA data will be more sparse and as a result fluctuate as the model is trained on real visitors on your new website. While AXI and HVA data will still be available during this training period, it may fluctuate from day to day more than would be expected from a fully trained model.

Additionally, once the training period is complete, in order to archive accurate data, we may retroactively update the initial few weeks of historical data. This way, any comp period in the future will be accurate, however, it may result in different results being archived than you see in the dashboard at launch.