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RCS: Mobile’s Next-Gen Customer Interaction Platform: Page 2 of 3

Pizza Anyone?

The concept of using RCS, which is already on your phone, as a rich brand interaction engine has real promise. Customers can initiate the interactions using RCS from an application or directly from the RCS client included on the mobile device. The RCS client would contain a list of contacts, including brands the customer regularly interacts with, as well as offer the ability  to search for new brands. This is fundamentally different from SMS, which doesn’t really provide a way for consumers to initiate an interaction with a brand.

With Mavenir’s RBM, the consumer can easily initiate an interaction with a brand with which it hasn’t previously had any interactions. In demos, Mavenir even showed the ability to include paid advertising in the contacts list for an interaction. A major issue in SMS and voice is the amount of spoofing and lack of trust. In RBM, the RCS client includes a “verified” icon that lets the consumer know the brand (or entity) running the RBM interaction can be trusted. Mavenir verifies a brand’s trustworthiness during the onboarding process.

With RBM, Mavenir said the goal is to have an AI (artificial intelligence)-based bot manage most if not all initial interactions. Because RCS includes a rich media experience, that interaction can include a full range of media to enhance the interaction. For example, a restaurant can send pictures to a customer who wants to order a pizza but isn’t sure what kind. Being able to see the different kinds of pizza should help the customer make a quick choice.

In listening to the concepts and the Mavenir implementation strategy, I’ve come to believe that this technology may address a major shortcoming of the mobile application experience.  In the figure below, the relationship between a consumer and a brand is defined based on two factors. As shown on the horizontal axis, the first is the depth of the relationship defined by trust level and frequency of interactions. Brands with which a consumer either has a high trust relationship or regular/frequent interactions are to the right, while brands that are infrequent or basic are to the left. A bank relationship would be on the right, while ordering a pizza while traveling would be to the left.  The second dimension is the complexity of the interaction and the range of choices presented. Ordering a pizza can be a simple task, while transferring funds between multiple bank accounts is much more complex, leading to application use.

Chart showing relationship between consumer and brand

Mapping the relationship between a consumer and a brand

Given the overwhelming number of apps available, consumers will generally only commit to download applications for relationships that have a combination of high trust/frequency and/or complexity. These are the relationships that fall at the upper right in the chart. For the others, if the combination of trust, frequency, and complexity of the relationship doesn’t meet the consumer barrier to download the applications, interactions must take place in the message domain or using the mobile browser. This is where Mavenir is focusing its business messaging service.

As shown in the figure below, the number of brands with frequent (and trusted) interactions is small, but the number of interactions is large. This follows the traditional asymptotic adoption curve. The majority of brands fall to the right, with infrequent interactions and often lower trust requirements. Application downloads would likely be concentrated in the brands to the left. A key observation is the volume of interactions that can be best served using a messaging concept like RBM instead of a bespoke application may be 25% to 50% of all interactions. Further, deploying a bot in a bot framework as an interaction is significantly less expensive than developing a comprehensive native mobile app or an optimized mobile browser app. An application would require support for a range of platforms and continual upgrades, whereas a bot framework with RCS takes a simple interaction definition with minimal change or upgrade required.

Chart showing relationship between brands and interactions

The number of brands with frequent (and trusted) interactions is small, but the number of interactions is large.

Using RBM to access the potential volume of interactions pushes the doors wide open for MNOs looking to tap into the $54 billion mobile applications advertising market analyst firm IHS Markit projects for 2020.  Mavenir shared results of a GSMA analysis of the RCS rollout in Japan.  Potential advertising and other opportunities RCS makes available to MNOs are six times greater than the basic A2P value, the analysis showed.

Mavenir currently has 18 partners in its RBM ecosystem and is conducting RBM trials in four countries (not the U.S. at this point).

While Mavenir is active in the RCS transformation, some MNOs like Vodafone are doing trials with their internal RCS deployments, and trial customers are seeing excellent results. The challenge is that if each MNO has a totally separate system, brands will have to build relationships with each MNO tht has its customers.