Around 50% of all customer service calls to Internet Service Providers (ISPs) are related to issues with home Wi-Fi. A recent study conducted in UK and USA shows that around 70% of all customers experience problems when streaming or downloading content over Wi-Fi in their homes. Of all customers, 75% expect their ISPs to solve their Wi-Fi related issues, and 54% are willing to pay an extra €4.5 per month if their ISP would provide a premium Wi-Fi service. ISPs respond to around 35.000 Wi-Fi related customer calls resulting in around 3.500 truck rolls per 1 million subscribers per month. Average length of a Wi-Fi related help desk call is 26 minutes. Calls typically cost €0.7 - €1 per minute and truck rolls typically cost between €80 - €150 per visit. Thus, with a modest assumption of €0.7 per minute cost of a call and €80 cost per truck roll, Wi-Fi related customer care cost sums up little over €11 million per year per 1 million customers. Moreover, the customers that call to complain are often only the tip of the iceberg. Many of the dissatisfied customers do not prefer calling for a complaint, instead they silently churn by switching their service to another provider either immediately or when it comes time to renegotiate their service contract. Thus, in addition to the above-mentioned costs, ISPs undertake unnecessary hardware replacement costs, customer churns and lost higher tier upsell opportunities. These findings demonstrate that there is solid need to diagnose and solve Wi-Fi problems remotely.
TEA’s innovative solution, TEApot (predictive optimization technology), comprises embedded (local) and cloud software modules that facilitate predictive maintenance and proactive control of home Wi-Fi networks, thus avoiding customer dissatisfaction. TEApot assures significant cost savings for ISPs by improving QoE of their customers. Moreover, TEApot promises new revenue opportunities for ISPs by its AI-based features such as advanced parental control, per client behavioral analytics, and advanced network setup assistance. The objectives of this feasibility study are summarized as follows:
•Studying technical requirements with potential customers and partners through online and face-to-face meetings before and after field trials. In this study, one of the main objectives is to understand complexity of remaining development activities, such as productization of embedded and cloud controller modules, and the potential impact of these complexities on the overall work plan.
•Analyzing and projecting the scalability of SaaS costs, and validating and/or modifying our cloud infrastructure that relies on Amazon Web Services (AWS).
•Studying data privacy related regulatory issues, such as GDPR, of the target markets.
•Market clearance study for ensuring freedom to operate.
•Studying the market by benchmarking customers and competition, examining trends to validate (and/or modify if necessary) our current knowledge and assumptions.
•Economic comparison study of direct and indirect competition and practices.
•Studying different business models, testing the business model against different customers, and assessing the risk associated with each one.
