It has been six years since telcos began introducing data and analytics products into their portfolio of enterprise services. This report assesses the potential value of data monetisation across 13 verticals, and by type of data analytics product.
Data revenue opportunities are variable
Monetisation of telco data has been an area of activity for the last six years. However, telcos’ interest levels have varied over time due to the complexity of delivering and selling such a diverse range of products, as well as highly variable revenue opportunities depending on the vertical. Telcos’ appetite to pursue data monetisation has also been heavily impacted by the fortunes of other new telco products, in particular IoT, owing to the link between many data/analytics products and IoT solutions.
This report assesses the opportunity for telcos to monetise their data and provide associated data analytics products in two parts:
- First, we look at the range of products and services a telco needs to create in order to deliver financial value.
- Then, we explore the main use cases and actual financial value of telco data analytics products across 12 verticals, plus horizontal solutions that apply to multiple verticals.
Telco data monetisation: Calculation methodology
The methodology used to model the financial value of telco data analytics is outlined in the figure below.
- The starting point for this analysis is 210 data or data analytics use cases, spread across 12 verticals and the horizontal solutions applicable to multiple verticals.
- We then assess how difficult it is for a telco to address each use case, based on pre-requisite supporting platforms and solutions, regulatory constraints, etc. (shown in red). This evaluation enables us to assess how likely telcos are to develop products for each use case.
- Thirdly, we assess which types of telco are able to develop the use case (in yellow). For example, telcos in a market with particularly restrictive regulation around use of personal data are simply not able to create certain products.
- Finally, it is necessary to understand whether the data/analytics products created for a use case can be offered as an independent, standalone product, or more likely to be provided as a bolt-on service to another, pre-existing solution. This question is primarily pertinent in the IoT space where basic data/analytics are likely to be included in the price of the IoT service.
- For products that we expect to be sold independently, we calculate the potential revenue based on estimated pricing for the type of data product, where known, and likely volumes that a telco will sell in a year.
- For data analytics products closely linked to IoT, we attach no monetary value.
Calculation methodology for the feasibility and value of telco data monetisation use cases
Source: STL Partners, Charlotte Patrick Consult
Viewing the data
Underlying the analysis in this report is a database tool including a detailed assessment of each of the 210 data monetisation use cases we have identified, with numerical analysis and charting capabilities. We know many of our readers will be interested to explore the detailed data, and so have made it available for download on the website in the form of an Excel spreadsheet.
Full use case database and analysis available on our website
Source: STL Partners
Table of Contents
- Executive Summary
- Calculation methodology
- What is this market worth to telcos?
- Creating products for data monetisation
- Telco products for the ecosystem
- Data and analytics for IoT
- Use of location in data monetisation
- Maximising value in different verticals
- Advertising and market research
- Real estate and construction
- Telecom, media and technology
- Horizontal solutions for all verticals
- Conclusion and recommendations
- How to pick a winning project