Overview
Proactive Assistant is an AI-powered assistant that provides marketers with valuable insights to enhance their marketing efforts. MoEngage meticulously gathers comprehensive data from diverse sources, harnesses the capabilities of AI and robust algorithms to transform it into actionable insights, and presents these insights in a streamlined, unified interface.
- Proactive intel at fingertips: PA does not need instructions or queries from you to run and produce insights. But proactively combs through all of the data and generates actionable insights.
- One-click actionable insights: The performance-boosting insights suggested by the assistant are actionable with a few clicks. You can send out a campaign immediately or save them as segments to analyze them further
- High-impact insights delivered first: The system creates plenty of insights but showcases to customers the ones most impactful to boost performance. The system uses intelligent algorithms to evaluate the impact of every insight and prioritizes them accordingly.
- Unlock hidden business opportunities: PA processes a wide array of data related to users, events, campaigns, devices, etc. to mine valuable performance-boosting insights, which customers couldn’t have uncovered otherwise.
- Limited intel on key segments: A marketer-driven segmentation is often elementary and helps uncover only primary segments based on predefined values of attributes. Brands often miss out on discovering more sophisticated, outcome-driven segments, which only algorithms can help recommend. Understanding and targeting these segments could be paramount to business growth.
-
Manual efforts to mine segments: Extracting target customer segments at present requires manual efforts. Understanding the creation of micro-segments requires configuring variables such as user and event attributes, time duration, and so on. This could be time-consuming and overwhelming for some users.
Accessing Proactive Assistant
Use one of the following:
-
Click on the Assistant button in the header to access the assistant.
Segment Insights
The Proactive assistant surfaces insights based on customer segments. There are two types of segment insights the assistant would be suggesting:
- Segment Based on RFM: RFM (Recency, Frequency, and Monetary) Model provides auto-segmentation and bucket users into categories such as Loyal, Promising, At Risk, and so on based on user behavior.
- Auto Segmentation: Sherpa automatically generates user clusters or segments using proprietary AI. Specify any event and attribute used for generating these clusters.
RFM Insights
RFM Insights proactively provide valuable information to Marketers about the user base. Use MoEngage Sherpa AI engine to get the most important users and uncover insights about user behavior on your product. For more about RFM (Recency, Frequency, and Monetary) segments, refer to What is RFM analysis.
Engage with users belonging to the RFM segment based on the defined Recency, Frequency, and Monetary attributes. For example:
-
An audio streaming company would like to know which of its customers are About To Sleep and how to re-engage them.
(Recency - App Opened, Frequency - Song Played & Monetary - Subscription Price) -
An online retail store might want to know which of its customers Needs Attention and how can they be nudged.
(Recency - Website Opened, Frequency - Order placed & Monetary - Price)
On the other hand, a brand would like to understand which of its customers have transformed from one RFM segment to another and what should be the strategy to engage with them.
-
A credit card company would like to know which of its customers have transitioned from Champions to Needs Attention, to re-engage them before losing forever quickly.
(Recency - App Opened, Frequency - Transaction Completed & Monetary - Payment amount) -
An OTT platform might want to know which of its customers have transitioned from Lost to Can’t Lose Them to understand what worked and keep them further engaged.
(Recency - App Opened, Frequency - Content Watched & Monetary - Subscription Price)
Setting up RFM insights
Navigate to Settings > Proactive Assistant > RFM Insights. Specify the events and revenue attributes you would like to use for RFM analysis. Sherpa will provide the relevant insight and alerts for any sizable movement of users across the RFM segments.
You can set up up to 5 different RFM Metrics that will be used as input to Sherpa. By Default, Recency and Frequency Events will be set up as App/Site Opened and Monetary Event will be picked from Settings (Settings>General>Key Metrics Parameters). These inputs will be analyzed over the duration added in “Analysis Duration” (Analysis Duration is recommended to be above 7 Days for meaningful insights).
Actions on Insights
Users will be able to create a custom segment or a campaign directly from an insight. Navigate to the insight that you want to use for a campaign or segment creation, and click on Actions on the bottom right.
Name the Custom Segment, save it and you will be to create a campaign with it.
- Segments created from the RFM Insights will be dynamic, which saves the RFM segment definition, not the exact users. The next time when a campaign with an RFM segment is sent, one time or periodically, that RFM segment gets calculated and the newly generated RFM segment will be used in the campaign.
- Segments created from the Auto Segmentation cluster will be static, the users in the segments will be saved and will remain the same whenever it is used for analysis or a campaign.
Share: To share insight, navigate to the insight card on the top right and click on copy insight.
Pause: If an insight type is not relevant to you right now, you can pause it for 30 days.
Feedback: You can also share any specific feedback that you have for any insight to MoEngage using the feedback button.
Proactive Assistant insights have a life of 60 days before they expire.
Key Insights
Let's look at some examples:
- A movie streaming company would like to know the monthly active user count and the reasons for the expected drop in the user count.
- An e-commerce website might want to know the Daily active user count and best-performing factor in the user count growth
Examples of Key Insights:
- Example 1:
- Example 2:
- Example 3:
Setting up Key insights
Navigate to Settings > Proactive Assistant > Key Insights.
Specify the App Open Event, Conversion Event, and revenue attributes you would like to use for Key insights. Specify the Deviation Interval and Analysis Duration based on your need.
Proactive Assistant will provide the relevant insight and alerts for any sizable movement of users for DAU and MAU Metrics.
Conversion Rate Insights
Let's look at some examples:
- A fintech company would like to know the monthly transaction completion as conversion and the reasons for the expected increase in the conversion rate.
- An e-commerce company in the fashion business might want to know the conversion rate on their website and the key factors in the conversion rate increase.
Examples of Conversion Rate Insights:
- Example 1:
- Example 2:
Setting up Conversion insights
Conversion insights will be generated using the Conversion Event, and revenue attributes set in the Key Insights settings, as mentioned in the above section.
Retention Insights
Customer retention insights are crucial for businesses as they contribute to further growth and help stabilize profitability. These insights play a pivotal role in key decisions such as customer acquisition cost, generating opportunities for sustainable growth, and redefining the customer experience.
Retention Insights provides critical D7 and D30 insights that are indispensable for any business. At D7, users demonstrate advanced engagement with the core platform, serving as a valuable indicator for mid-term user retention. Subsequently, by D30, users transition into the highly valued category.
Let's look at some examples:
- In an e-commerce business, what percentage of users visited a specific product on the app, returned to the app, and made a purchase?
- In a lending business how many users are applying for the loan after signing up?
Examples of Retention Insights:
- Example 1:
- Example 2:
- Example 3:
Setting up Retention insights
Navigate to Settings > Proactive Assistant > Retention Insights.
Specify the First Event, Return Event, Retention type attributes you would like to use for Retention insights. Specify the Deviation Interval and Analysis Duration based on your need.
Proactive Assistant will provide the relevant insight and alerts for any sizable movement of users for D7 and D30 Retention Metrics.
|
Important Note: MoEngage uses statistical and ML algorithms to define the correlation with the most important Contributing attributes and uncover insights about user behavior on your product.
Most importantly, we allow you to customize your Deviation interval range and configure your alert based on your business needs. To identify the causing factor, we focus on the impact of the following areas:
|
Reach out to us directly from your MoEngage Dashboard -> Need Help? -> Contact Support or send an email to support@moengage.com.