AI-Based Segments
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Netmera employs event-based AI analysis as the backbone of its AI-based segments. This approach involves employing artificial intelligence algorithms to dynamically analyze and interpret the user events in Netmera such as purchases, clicks, or notifications, allowing Netmera to uncover patterns and correlations in real-time user behavior. By continuously learning from these interactions, Netmera's system adapts, providing a nuanced understanding of user engagement.
Netmera features two distinct AI-based segment categories: Conversion and Churn.
A conversion event refers to a specific user interaction or behavior that signifies a successful outcome or desired action for a business. This could include actions such as making a purchase, signing up for a service, completing a form, or any other predefined goal that aligns with the business's objectives. The AI algorithms employed by Netmera within the Conversion Segments identify patterns and trends in user behavior associated with successful conversions.
AI-based Conversion Events:
In Netmera's AI-based Conversion Events, businesses have the flexibility to select the most relevant conversion event and customize the associated time period according to their specific needs. This empowers businesses to define the criteria that indicate a successful conversion in their context.
Churn, in general, refers to customer disengagement or loss. Netmera's AI-based Churn Segments represent a category within the platform dedicated to customer churn predictions. The AI algorithms embedded in the Churn Segments analyze user behaviors and interactions to identify potential indicators of churn.
Default AI-based Churn Segment Event:
In Netmera's default AI-based Churn Segment, the designated event is "OpenApp." This means that if a user has not opened their app within a specified timeframe (customizable by the business), the AI segment will predict that the user is at risk of disengaging or being lost in the near future. Both the default event and the time period is customizable and can be designed according to your needs.
In Netmera's AI-Based Segments, the AI system operates by conducting a detailed examination of users' historical interactions over a specified 'past x time.' This involves analyzing patterns, frequencies, and recency of events to gain a comprehensive understanding of user behavior. The AI then predicts future actions 'in the following y time.'
This predictive functionality is entirely customizable, allowing businesses to define the specific timeframes relevant to their objectives. By systematically analyzing past events and forecasting future user actions, Netmera's AI empowers businesses with concrete, data-driven insights.
In Netmera's AI-Based Segments, the temporal analysis operates in a triad – past (p1), present (p2), and future (p3). The AI system diligently examines users' historical interactions in p1, analyzing patterns, frequencies, and recency to derive meaningful insights into user behavior. Leveraging this understanding, the AI seamlessly transitions to predicting future actions in p3.
Several key calculation metrics play a pivotal role in understanding user behavior in the 'past x time (p1) and optimizing engagement strategies. These metrics include:
Duration Between Events: This metric involves calculating the time intervals between successive events, providing insights into the duration of user activities or inactivity. Analyzing the duration between events helps businesses understand the pacing of user interactions and can be instrumental in identifying patterns related to engagement and potential churn.
Frequency: Frequency refers to the rate at which specific events occur within a given timeframe. By calculating the frequency of events, businesses can gain a quantitative understanding of user engagement patterns. This metric is valuable for identifying active users, determining popular features, and assessing overall user involvement with the platform.
Recency: Recency focuses on measuring the time elapsed since a user's last interaction or event. This metric is crucial for assessing the freshness of user engagement. Businesses can use recency calculations to identify users who have recently engaged with the platform and tailor targeted strategies, such as promotions or personalized content, to re-engage users who may be at risk of churn.
In summary, these calculation metrics—Duration Between Events, Frequency, and Recency—serve as fundamental tools within Netmera's AI-based segments, providing businesses with quantitative insights into user behavior, engagement patterns, and potential churn indicators.
Precision Level is a metric that assesses the accuracy of a segmentation model in correctly identifying and categorizing instances within a specific group. Precision, in this sense, is a measure of the model's ability to avoid false positives within a segmented group. It provides valuable insights into the reliability of the segmentation model, indicating how well it distinguishes instances that truly belong to the targeted group.
Higher Precision Level Leads to Smaller Focused Group:
Precision is calculated as the ratio of true positives to the sum of true positives and false positives. True positives are instances correctly identified as belonging to the group, and false positives are instances incorrectly included in the group. As the precision level rises, the model becomes more cautious about assigning instances to the group, aiming to reduce the likelihood of including items that do not truly belong.
Therefore, a higher precision level indicates a higher degree of confidence that the instances identified as part of the group are indeed representative of the characteristics or behaviors targeted by the segmentation model. However, this may also result in a smaller, more focused group, as the model becomes more conservative in its categorization.
The optimal precision level can vary based on the specific goals and requirements of each business and the purpose of the segmentation. The choice of precision level depends on the trade-offs a business is willing to make between the accuracy of the identified group and the potential exclusion of some relevant instances. It's essential for businesses to carefully assess their specific needs and objectives to determine the most suitable precision level for their AI-based segmentation models.
The AI-based segments in Netmera undergo nightly updates, ensuring that the segmentation model is refreshed and recalculated on a daily basis. This frequent updating mechanism allows the system to integrate the latest data and adapt to evolving user behavior patterns. By keeping the segments current, businesses can leverage up-to-date insights for strategic decision-making and enhance the effectiveness of their customer engagement strategies in real-time.
To create a new AI-Based Segment, please reach out to your dedicated Customer Success Manager (CSM). They will guide you through the process and ensure that your new AI Segment aligns seamlessly with your business objectives and requirements. Contacting your CSM is the first step to initiate the creation of a tailored AI-Based Segment that optimally serves your customer engagement needs.
