This section provides detailed insights into the foundational elements that form the backbone of audience segmentation and campaign management within OptiKPI: Events, Customer Properties, Customer Metrics, and Affinities. Understanding these concepts is crucial for effectively leveraging the platform to analyze customer behavior and personalize marketing strategies.
Events
Event Definition: Events are specific actions taken by your customers that you track within your system. Examples include making a purchase, logging into your site, or playing a game. Each event is recorded in OptiKPI with essential information such as the date and time, event name, event category, unique customer ID, and unique event ID.
Event Attributes: Additionally, events may include event attributes, which are attributes associated with the specific event. For instance, if a customer makes a purchase using a credit card on your mobile app, the event attributes might include “payment method: credit card” and “device: mobile.” The inclusion of event attributes depends on the data associated with the event that is sent to OptiKPI. If certain details are not logged by your system, they will not appear as event attributes in OptiKPI.
Importance of Events: Understanding events is crucial for real-time insights into customer behavior and for triggering targeted actions based on these behaviors. They are essential for dynamic segmentation and activating event-driven campaigns, allowing you to respond promptly and appropriately to customer actions, enhancing engagement and conversion opportunities.
Customer Properties
Definition: Customer properties are specific attributes related to your customers that are captured and utilized within OptiKPI to create detailed customer profiles. These properties are divided into several categories, each essential for building comprehensive customer segmentation and refining marketing strategies:
- User Profile: Basic information including User ID, Username, First Name, Last Name, Date of Birth, Birthday, Email, Phone Number, and Address.
- Demographic Data: Gender, Country, City, Language, and Currency.
- Preferences: Preferences for receiving marketing emails, notifications, subscription preferences, and privacy settings.
- Membership & Status: Tracks VIP Status, Loyalty Program Tiers, and Account Status.
- Acquisition Channel: Captures the Acquisition Source and Partner ID.
- Referred Friends: Referral Link/Code and whether the Referral Limit has been reached.
- Other Industry-Specific Properties: Depending on the industry, additional properties such as Responsible Gaming profiles or Risk and Security measures may be available. These are tailored to meet specific regulatory or operational needs and can be integrated upon request.
Data Dependence: The availability and richness of these properties in OptiKPI depend on whether they are logged and sent from your back office. Only the data provided by your system will be displayed and available for use in OptiKPI. It is crucial for your back office to accurately log and transmit this information to ensure effective customer segmentation.
Importance of Customer Properties: Customer properties are crucial for building actionable profiles that can be precisely segmented for targeted marketing campaigns. They enable a deep understanding of the diverse needs and preferences of your customer base, enhancing customer experience and informing strategic marketing decisions based on solid data insights.
Customer Metrics
Definition: Customer metrics are quantifiable data points that measure various aspects of customer behavior and financial activity. These metrics are critical for assessing customer value, monitoring financial transactions, and understanding engagement patterns. They play a key role in shaping business strategies and marketing decisions.
Types of Customer Metrics:
- Financial Metrics: Include total and average values of transactions such as purchases, refunds, deposits, and withdrawals. These metrics provide insights into the financial behaviors of customers.
- Customer Lifetime Value (LTV): Represents the total revenue a business can reasonably expect from a single customer account throughout the business relationship. Calculating LTV helps in determining marketing spend, segmenting customers based on profitability, and tailoring customer retention strategies.
- Campaign Attribution Value: Measures the impact of specific marketing campaigns on customer behavior, particularly in terms of revenue generation or other valuable actions. This metric is essential for evaluating the effectiveness of marketing efforts and optimizing future campaigns.
- Industry-Specific Metrics: Depending on the industry, additional specific metrics may be tracked. For example, gaming platforms might measure metrics like bet amounts and winnings, while e-commerce sites might track cart abandonment rates and average order value.
- Session Metrics: These include counts or averages of customer interactions or events, such as the number of sessions of specific activities within a certain period. Session metrics help understand customer engagement and usage patterns, which are vital for improving user experience and service delivery.
Data Dependence: The availability and accuracy of these metrics depend on the data that is pushed to OptiKPI. It is crucial that the data sourced from your back office or data management systems is comprehensive and regularly updated to ensure that the metrics reflect current and relevant customer behaviors and financial statuses.
Importance of Customer Metrics: Utilizing customer metrics allows businesses to create a more detailed and data-driven picture of their customer base. By analyzing these metrics, companies can optimize their operational, marketing, and strategic decisions, enhancing overall business performance and customer satisfaction.
Affinities
Definition: In OptiKPI, ‘affinity’ refers to a customer’s preference or tendency towards specific behaviors or attributes, identified through their interaction patterns. Affinities are set based on two primary parameters: predominance and recency of specific events and their attributes.
Parameters of Affinity
- Predominantly Performed Event: This parameter considers the most frequent behavior or attribute exhibited by a customer over a given period. For example, if a customer predominantly uses a mobile app for purchases, their affinity is set towards mobile app usage.
- Most Recently Performed Event: This parameter focuses on the most recent action taken by a customer. It captures the latest event and its attributes, regardless of the predominant pattern. This is useful for identifying and responding to shifts in customer behavior.
Example of Affinity Usage
Consider Customer A who has made 10 purchases on your website. Out of these, 7 were made using a mobile app, and 3 using a desktop, with the most recent purchase made on a desktop. In this scenario:
- Using Predominant Affinity: If you segment customers who predominantly make purchases using desktop, Customer A would not be included because the majority of their purchases were made via mobile app.
- Using Recent Affinity: If you segment based on the most recent purchase platform, Customer A would be included in the segment for desktop users because their last purchase was made on this platform.
Importance of Affinity: Affinity helps in tailoring marketing strategies to match the current or most frequent preferences of customers. By understanding and leveraging affinities, businesses can significantly enhance personalization, improving customer engagement and satisfaction. This targeted approach ensures marketing efforts are more relevant and effective, potentially increasing conversion rates.Data Dependence: The effectiveness of affinities in segmentation and targeting relies on the accurate and timely capture of event data. Continuous updating of customer interactions is crucial to maintaining relevant and actionable affinities.