The challenges of the telecommunications industry: If you are on that tense playing-field of new technologies, ever-changing customer requirements and growing competitive and costing pressure and want to make you mark, you will have to implement "Big Data" as efficiently as possible. A modern data platform perfectly equips your company for any challenge - from the optimisation of your operational structure to securing long-term customer loyalty with tailor-made yet profitable products.
Integrating customer, tariff and marketing information opens up whole new realms of possibility for calculating profit margins. A multi-level calculation within each partial block can account for a number of different characteristics. This means that you are in possession of a clearly differentiated basis for decision-making in relation to potential improvements in efficiency, in regard to the profitability of individual user groups and complex tariff models or designing advertising budgets and commissions. It also generates a substantiated profit and loss sheet.
And in addition, with the help of your own Prediction Model, you can reliably predict the profitability of a new customer at the signing the contract. The services provided can thus be specifically evaluated the moment the account is activated rather than after several months.
Who is successful? Who isn't? Detailed data on various sales channels facilitate a substantiated comparison of individual branches and distributors. Further findings can be generated by additionally linking demographic and socio-demographic information. In this way, sales promotions or publicity expenses subsidies can be planned and positioned in a targeted fashion. Similarly, regional campaigns can be undertaken separately.
Modern BI-solutions provide detailed usage profiles which provide a transparent overview of the use of products and options per day. Customers can be categorized again and again on the basis of different behaviour patterns and provided with tailor-made offers. Customers who are potentially opting out are also included: they can be identified early on based on their habits. One can also research and test the attractiveness of specific tariff models.
On basis of previous user behaviour, new offers can be developed for each client individually. For example, in the event of the extension of a contract, the staff of a shop can generate a variety of options which are attractive to the customer while promising an increase in revenue.
The integration of Webshop data into the analysis process can contribute to the differentiated categorisation of the customer. Which web pages deliver potentially interested parties? What can be expected of customers with a specific set of online behaviours? Who will generate the highest revenue in the future? These questions and others can be clarified in this context. The results are more accurate prognoses and an even more specific customer approach.
The sales structure of telecommunications companies is complex - meaning the commissions of traders and affiliates are also complex. A high-performance BI-system ensures that commissions and premiums can be administered more reliably and be accounted for more precisely. In addition, points systems calculations also take into account individual shops as well as customer acquisition.
Radio masts constantly produce information regarding the extent of utilization and quality of the network. This data can also be analysed and used by telecommunications companies to optimise their services. For example, everything from the network coverage to the post code can be broken down so that any weaknesses in the system can be specifically identified. Even a differentiation between day-time and night-time populations can be programmed for analysis. You can identify the different levels of network traffic and thereby determine the user's behaviours at different times of the day.
It is an unfortunate fact that attempted fraud by traders and customers is part and parcel of the telecommunication business. Whether it is an irregularity in the return of a smartphone or pre-activation without a usage pattern - a reliable controlling system can be integrated into your data platform based on typical usage patterns, so that you can immediately identify anything out of the ordinary and react accordingly.
Opinions from social media can be easily processed by your analysis model too, despite the enormous influx of data. This is a measure which makes sense for everyone because in the arena of social media, customers are extremely open in how they express their opinions on products, services or the general image of a company. This means that you will receive important indications for the optimisation of strategic initiatives in marketing, sales and customer service.