Using predictions, marketers can create targeted campaigns for their users and influence the outcome. Some of the outcomes are as follows:
Personalize and create curated content for different segments of users based on their propensity. For example, users with low propensity to convert (order successful)
Throttle the sent time and frequency of communication with the users
Send contextual campaigns to the specific segment of users based on their propensity.
Reduce overall campaign cost and enhance customer experience by targeting only selective set of customers
Sample Prediction Uses
The following are a few sample use cases marketers can create using MoEngage Prediction
Predict a particular outcome or conversion goal
User conversion refers to performing a particular business objective or outcome as defined by the marketer. Using predictions,
- Identify the propensity of users to perform a particular objective or goal.
- Identify segments of users who have high compared to low propensity and create targeted campaigns.
For example, users with a low propensity to convert are targeted with contextual offers and discounts. The users have more timely campaigns with higher frequency than users who have a higher propensity to convert.
Churn Rate Prediction
Churn rate refers to the percentage of users who stop using the app or service in a specified time period. Businesses must focus on ensuring a higher growth rate with lower churns. With predictions, marketers can pre-empt the loss of a customer and design necessary follow-up or nurturing proactively before it is too late.
For example, users with a high propensity to churn are targeted with contextual offers and discounts. The users have more timely campaigns compared with more timely campaigns with higher frequency than users who have a higher propensity to convert.
Lifetime Value Prediction
Customer Lifetime Value (CLV) refers to how much a customer is worth to the business and the average revenue generated throughout the entire span of the relationship with them. With predictive analytics, marketers can predict the future engagement with the users along with the revenue the engagement is likely to bring in.
Predict and plan marketing campaigns upfront
With predictions, marketers can clearly predict and pre-empt user actions and outcomes. Marketers create a suitable plan for the kind of campaigns required for the users. Risks are significantly reduced as decisions are made based on data, not based on assumptions that rely on instincts and some educated guesses.
The right type of content is identified for certain customers. Customize content creation and distribution based on user preference for content, channel, and time. When customers receive higher-quality communication increasing the probability of sales conversion.
Similarly, based on the user propensity and the number of users likely to perform or not perform an action. Marketers can suitably predict customer acquisition and overall retention costs needed to incur in the coming week or month and budget accordingly.
Upselling and Cross-Selling Opportunities
Predict and identify what customer needs and wants are. Identifying products are selling and the affinity of users towards a particular brand or product category. By predicting user propensity, marketers can target and create contextual campaigns to recommend suitable product categories to the user.