In this post we highlight factors that might influence how conversational interfaces (CIs) are viewed, used, and interacted with across emerging markets in the future.
It is often easier and less costly for CI providers to white label their conversational interface to a revenue partner rather than go direct to customer.
This is post number 4 of the Conversational Interfaces Blog Series and has been prepared by Teller Technologies, Inc., with whom some of our research was conducted, based on their pilot with Orange Money Madagascar.
Conversational interfaces (CIs) are currently being deployed to help extend access to financial education and services across emerging markets with strong results. In one pilot in Tanzania, CGAP found that farmers who used Arifu’s interactive learning platform saved at rates five times that of farmers who did not use the platform. Although these findings are preliminary, they suggest these tools have a significant potential to change behavior.
As mentioned in the primer, using CIs to interact with customers through freeform African languages can be challenging given the limited amount of localized digital content to source.
Though functionally similar, it’s important to understand how SMS and messaging applications differ prior to engagement.
As the cost of accessing the latest in machine learning and artificial intelligence drops, more and more organizations are depending on technology to reduce the cost and improve the quality of core business functions. By leveraging this technology in interactive conversations via conversational interfaces (CIs), customers across different demographics can now receive current, guided assistance, whether they want to know more about the latest agricultural practices or new financial services.
This blog is authored by Ashley Lewis, Investment Officer, West Africa and South Africa, Accion Venture Lab with support from Tunde Kehinde, co-founder of Accion Venture Lab portfolio company Lidya.
The FiDA partnership launched version 2.0 of the Digital Finance Evidence Gap Map (EGM) in October 2018. With 55 studies examining 60 products, there are many insights to navigate. To show the types of analysis the EGM makes possible, we published a number of impact insights on a range of topics.
In previous insight pieces on savings, credit, and, Person-to-Person (P2P) transfers, we synthesized what we learned from studies in the Digital Finance Evidence Gap Map (EGM) using a product lens. However, the product lens is just one perspective, and the digital finance impact landscape is more varied and layered than this. Here we share four factors that digital finance researchers should consider when testing the impact of a digital finance product.