RBM Analytics – Powerful customer intelligence

RBM Analytics – Powerful customer intelligence

RBM Analytics makes Rich Communications Services even richer! With RCS, all players in the ecosystem, whether they be Enterprises, Aggregators, Mobile Operators or End Customers – will benefit not just from growth in their messaging business but also from the huge additional richness and diversity of data points that RBM can deliver.

Anam’s RCS Business Messaging (RBM) Hub provides Analytics features in a multi-dimensional framework ranging from simple messaging traffic and volume analysis to a much deeper exploration of customer journey, brand visibility and interaction patterns. Listed below are just some of the types of insights stakeholders will have access to:

Messaging Traffic Analysis – the ability to manage and analyse messaging volumes and trends over time with enhanced attributes related to RCS like read receipts and customer opt-in response.

Customer Engagement Analysis – Data points related to customer’s interaction and activity feeds into greater insights about sessions trends, active hours, conversations, active customer base and churn rates.

Customer Experience & Journey Analysis – The analysis of customer journey and access points throughout a conversation is a key element in marketing, for example in measuring the success of a promotional campaign. In addition, it supports development of chatbot content enhancements or design / flow improvements. Conversion steps, funnel analysis and customer satisfaction measures are crucial metrics to be considered.

Customer Intent Analysis (P2A) As messaging has been always a two-way platform, it is important to evaluate the visibility and reachability of a brand towards a specific customer segment along with an understanding of customer intent and classification of  conversations based on that intent. For brand owners, it is crucial to get insights on how customers seek out a brand and their intentions.

 

Anam RBM Analytics supports all players in the ecosystem enabling them to make data-driven decisions that can be translated to a value: a direct revenue stream, process efficiency and/or customer satisfaction improvement. Different stakeholders will be able to apply these enhanced capabilities according to their specific use cases and business objectives. Commercial functions might be concerned with conversion rates, campaign design, disconnection points and brand visibility while, Customer Care teams will use it to gather insights about conversation paths, customer intent distribution and user activity trends.

Conclusion

A key feature of an RBM platform is the extent and flexibility of the analytics capability – how it can provide incredible insights on prospect & customer behaviour and ultimately enable stakeholders to increase their business value.


 

Ahmed Elwardany is an Analytics Solutions Manager at Anam.

As part of Anam’s Analytics division, he is involved in driving product development and continued analytics improvements.