- Vodafone’s data analytics strategy continues to focus on both internal and external opportunities to harvest data (including aggregated, anonymized customer data) for increased efficiency and monetization.
- Its update briefing for analysts was notable more about its progress in the latter.
Vodafone provided an update to analysts on its big data and advanced analytics activities, which are focused both on internal data optimization for Vodafone’s own business outcomes and on external data for use in products and solutions. The briefing also included three demos: an internal solution for intelligent pricing as well as customer solutions for visitor traffic analytics and IoT connectivity analytics.
Vodafone reiterated its specific position as a mobile network operator, which results in generating a massive amount of internal operational data and customer data. It mentioned only briefly its partnership with Google Cloud, announced this year, to collaborate on taming and optimizing its overwhelming volume of data in a strategic way, noting its importance without much further elaboration. The focus was rather on what’s new and what’s working with its internal and external data analytics initiatives.
Vodafone’s data strategy is to maximize value creation from data and analytics to become more data-driven internally as an organization and to monetize external data to enhance core services and create new products for customers. The partnership with Google is key to creating a platform and framework for creating and maintaining quality, reliably consistent internal data and applying artificial intelligence (AI) at scale, while gaining a complete view of the customer based on both operational and customer data. When it comes to the external element – monetizing data to drive business outcomes for customers – Vodafone stressed that the focus today is on executing an already-established strategy. It noted growth in its capabilities from its beginnings as a team of just a few data scientists to what it has now: a large team of data specialists with multiple professional disciplines, as well as an extended, group-wide community of people with a stake in data analytics across different internal domains. It has also grown its customer base from just a handful to about 120 enterprises and public sector organizations across several European markets, with imminent plans to expand to other regions.
What impressed was the number of real live examples provided to back up Vodafone’s ambitious and well-established product strategy, which includes solutions for six verticals (media, travel & tourism, financial services, energy & utilities, government & health, and transportation), and three horizontal domains (sales & marketing, customer service, and logistics & operations). A few years ago, multiple telcos mapped out similarly extensive plans for what could be done with aggregated and anonymized mobility and location data, and rolled out innovative solutions, but it wasn’t always evident that the offerings had found much traction in the market. Vodafone shared new customer references including the European Space Agency, UK Network Rail, Lisbon City Council, Istat, Banca D’Italia, and INE Tourism in Spain, demonstrating how solutions for out-of-home advertising, footfall analysis, smart retail, and smart lighting are being utilized across Europe. The demo it provided for footfall traffic analysis showed how different verticals can use insights to make decisions from the massive dataset, including audience measurement for advertising campaigns, real estate valuation, and smart signage based on traffic and demographics.
Another theme which helped explain the progress Vodafone has enjoyed in its data analytics strategy is the creation of multiple data assets that can be re-used for different use cases, depending on the product and customer segment. By standardizing internal product taxonomies across the business and using a common framework, data-driven initiatives – whether internal or external – can be launched within days rather than months. Internally, it ensures data consistency for any project, enabling all teams to access the same dashboard. Externally, it makes it much simpler to integrate existing data assets into targeted and scalable solutions. Vodafone has also taken a framework approach to figuring out whether or not its role in the data monetization value chain can justify each potential analytics initiative. Understanding where and when it may have a role as a data provider, or as an analytics-as-a-service provider, should result in additional wins as it assesses new opportunities in this emerging market.