$190M in revenue per month with AI

  • 9M B2C customers
  • 75+ Offers
  • 25+ AI/ML models

Telefónica Argentina, a subsidiary of Telefónica Group, operates one of the largest mobile and fixed broadband connectivity services in the HispAm region. Combine those offers with integrated information and communication technology (ICT) solutions and media and TV services reaching an additional 24M access points through Movistar, Vivo, and Virgin Media O2 (VMO2) brands. This telecom and media powerhouse is creating hyper-contextualized experiences exploiting its differentiation in a competitive and challenging marketplace.

Argentina’s telecommunications and media markets are experiencing challenging dynamics and disruptions:

  • Hyperinflation is redefining pricing strategies and leading to cuts in consumer spending
  • Mergers and acquisitions (M&A) consolidation is shifting the competitive landscape
  • Changing consumer behaviors, like cord cutting and exponential over-the-top (OTT) growth, and digitization are creating fierce competition to retain and expand consumer relationships.

With these market forces in play, Telefónica Argentina is transforming its company using artificial intelligence (AI), analytics, and data.

“Telefonica has a mission to make our world more human by connecting lives,” says Horacio Mansilla, director of marketing at Movistar.


$190M in incremental monthly revenue using AI models for Next Best Action

Alejandro Salevsky, director of the chief information office at Telefonica Group’s VMO2 UK and former chief analytics officer at Telefonica HispAm, explains that “being able to trigger offers to every single customer, across every single channel and challenge, is super important. When people aren’t demanding or wanting the newest and best iPhone, personalization becomes absolutely necessary. You need to decide the specific product and discount, when to offer it, and in which channel.”

Differentiating customer experiences can increase loyalty and grow average revenue per user (ARPU). To accomplish this, Telefónica Argentina seeks to know its customers, cater to their needs, and provide hyper-personalized communications and offers in the moment of decision. The company has a vision and process for AI to support commercial omnichannel operations.

“Our commercial strategy is based on a next-best-action (NBA) engine that calculates the best offer for each customer, and then we deliver that knowledge through our commercial strategic campaign delivery,” shares Mansilla.

The NBA engine has grown to over 75 offers, serving 9 million business-to-consumer (B2C) customers. Machine learning (ML) models leverage 1,500 feature variables and continuously optimize and improve monthly, weekly, daily, and near real time. NBA insights permeate across the enterprise to enrich customer experience. Whether a customer engages through Telefónica’s apps, online store, call centers, retail stores, chatbots, or other voice-supported channels, hyper-personalization and hyper-contextualization provide every customer with tailored offers and messaging as a result of scaling AI/ML models.

“We have more than 25 ML models. The engine calculates the most valuable action we can take with the customers and the channel to deliver the offer, based on their propensity to buy specific products and the maximum value we can get,” explains Mansilla.

Propensity models calculate the probability of positively increasing ARPU and factor in variable and fixed costs. These insights feed the recommendation engine to serve the best recommendation per client for a business user, chatbot, campaign, or website promo to offer to the customer.


Teradata VantageCloud on Azure delivers harmonized data and trusted AI/ML

Telefónica Argentina is solving large-scale analytics challenges using VantageCloud on Azure, the complete cloud analytics and data platform for AI, by unlocking data, activating analytics, and scaling AI. 

“VantageCloud is the heart of our analytics and data platform, where we have integrated and harmonized data to run our campaigns, know our customers, and make decisions. We have also built a multidimensional model based on Teradata’s Telecommunications Logical Data Model that helps us act on both aggregate and disaggregate information,” adds Mansilla.

Through this AI-led strategy, Telefónica Argentina transforms its marketing technology to be analytics and data driven. Now, more than 1,100 self-service users gain insights into how to best engage and serve customers. 

“When a company delivers a proper communication—one that’s trusted, reliable, and makes sense—even if it’s advertising a value proposition, I’m going to feel OK as a consumer,” Salevsky continues. “We truly believe that we will make our consumers much happier when we are able to communicate with a proper offer, at the right moment and with the right channel.”

Telefónica Argentina generates over $190M USD in incremental monthly revenue by creating and delivering hyper-contextualized offers to its millions of customers. 


Generative AI advances high-value recommendation and personalization use cases

Generative AI is poised to massively impact enterprise value with nearly $26T in total AI economic potential. Emerging use cases powered by AI include:

  • Improving business performance through operational efficiencies
  • Advancing hyper-contextualized customer experiences
  • Accelerating product innovation

Telefónica Argentina looks to further innovate with AI and transform its enterprise with generative AI. The company sees opportunities to integrate generative AI for:

  • Customer care. Adding generative AI capabilities to its existing chatbots will further personalize and contextualize customer engagements.
  • Innovation in business operations. Using generative AI to augment software coding will boost productivity.

To accelerate AI value, enterprises must manage data growth with high-quality, trusted data that is both integrated and harmonized. A data platform that provides a flexible, open, and connected ecosystem can empower organizations to use public or custom large language models (LLMs) or other preferred tools and technologies of their choice. Scaling trusted AI demands strong data governance to deliver accountability, security, and trust of AI models, insights, and actions.

“Because we have a centralized data stack in VantageCloud, we have strong data governance and proper integration with our data governance decisions,” concludes Salevsky.

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