METRIC: Measuring Engagement Through Real Interactions of Customers
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METRIC: The presented invention ( is a tool for collecting, measuring, analyzing, and reporting the engagement of online systems through real interactions of customers or users, including real-time. METRIC enables system stakeholders to enhance their understanding of their customers via actual behavior on particular pages in the online systems, including the focus and interaction with sub-elements on a page within that system.

METRIC's unique approach enables collecting to be done both onsite and remotely. METRIC conducts the measuring automatically, reducing the complexity for the end user. METRIC offers guided processes for the analysis of these measures.  Finally, METRIC provides sophisticated reporting features throughout the collecting, measuring, and analyzing process.

Observing customer interactions with web systems offer important insights for the design and application of such systems, along with critical insights into customer needs, tasks, and pain points. Via an easy to employ embedding of METRIC into existing systems, customer behavior and interaction with online pages, content, and interfaces can be collected with high precision, addressing the scarcity of behavioral user studies and ensuring relevant and valid analysis. This high-quality data collection, measurement, analysis, and reporting ensure the most accurate and glandular information to make better business decisions to obtain better business results.

METRIC provides the manageability of customer user studies for the stakeholders’ online systems via simple yet nuanced and sophisticated methods. METRIC end users can create a customer study for a target page (or other artifacts) on their online system. Then, the METRIC user study link can be shared and the engagement of the study participants can be tracked via the METRIC service. The user study may require a follow-on survey after interaction with the target page from the participant, so METRIC provides the customization feature for the case. This METRIC survey enables immediate and fresh customer cognitive insights to enrich the behavioral data collection process and analysis.

The customer’s attention may not correlate with mouse movement even if it is an unobstructed form of tracking natural user behavior. METRIC adopts the webcam-based eye-tracking that is a javascript library and integrates it into METRIC architecture to monitor the customer’s real visual attention during interaction with the online system. METRIC end users can enable the eye-tracking feature for their particular user study,  and METRIC encompasses a process for the participants of the user study to calibrate their eye movement for the user study session.

METRIC records the engagement of customers on pages, content, and interfaces of most online systems. This recording includes where the customer’s mouse hits and the order the mouse hits. Additionally, it records where the customer’s mouse clicks and what order the mouse is clicked on the page. METRIC enables its end users to designate the elements of a page and track the elements precisely for further and increasingly sophisticated and more accurately granular behavioral analysis. The eye-tracking also records the eye hits and eye gaze with its order when the user studies enable eye-tracking, measuring most of the industry eye (and mouse) measurements.

The mouse movement and eye gaze are possible to visualize in a heatmap chart provided by METRIC. METRIC employs a heatmap chart javascript library and enables the tracked mouse movement and eye gaze to plot on the heatmap. From this, the METRIC end users can have a better understanding of the interaction of their customers.

In sum, METRIC enables its end users to conduct studies for the users’ target artifacts of online systems. METRIC enables stakeholders to understand their customers' interaction on their online systems by measuring engagement to a level of granularity, accuracy, flexibility, and speed not previously available. Thus, METRIC provides important insights for the decisions by providing the analysis based on the engagement of customers' as expressed via the integration of mouse movement, eye gaze, and survey data.