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Sample Strategies for Next Best Action Recommendations (Managed Package)
In Multiplay Subscription Management, a strategy called SFI-NBARecommendationStrategy is used to search for and display the recommended products in the Next Best Action section of the agent console. Here's an overview of the rules that are implemented by this strategy along with suggestions for setting up new rules.
This feature is part of the Communications Cloud managed package.
To access this strategy and view or modify it, see Customize the Criteria for Recommending Next Best Action.
Here are the criteria considered by SFI-NBARecommendationStrategy to decide if a subscriber is eligible for a next best action recommendation.
Recommendation Eligibility Criteria |
For Lock-in Recommendation |
For Retention Recommendation |
|---|---|---|
Churn Score |
Low (less than 20) |
High (60 or higher) |
Tenure |
More than three months |
More than three months |
Payment Frequency Trend |
Not considered |
Trending down (less than 0) |
Last 30 Days Usage (GB) |
Not considered |
Trending down (less than 0) |
If a subscriber meets the criteria for a next best action recommendation, then SFI-NBARecommendationStrategy looks for products that meet the following criteria.
Recommendation Product Criteria |
For Lock-in Recommendation |
For Retention Recommendation |
|---|---|---|
Product Type |
Lock-in Add On |
|
Main Feature Term in Days |
365 |
Not considered |
Main Feature Unit of Measure |
GB |
GB |
Main Feature Quantity |
>= Last 30 Days Usage (GB) * 12 |
>= Last 30 Days Usage (GB) |
In the default implementation, SFI-NBARecommendationStrategy returns the following recommendation products:
Recommended Product |
For Lock-in Recommendation |
For Retention Recommendation |
|---|---|---|
Product Name |
8GB Data for 12 Months |
5GB 500 Minutes & 500 Texts 30 Days |
You can modify the strategy to consider different criteria in determining if a subscriber is eligible for a next best action recommendation. For example, you could create more heavily discounted products for subscribers with a higher churn score. Alternatively, you could consider different trends in determining eligibility for retention recommendations.
Further, you can consider and define different salient features on recommendation products. For example, on broadband products, you might consider upload or download speed rather than data usage, while on monthly subscription products you might consider monthly spend as a search criterion.
You could also extend your strategy to select the best match in the recommended products by filtering the recommendations based on price, quantity, or other criteria.
