In a highly competitive market, telecommunications companies that prioritize customer experience (CX) have a distinct advantage. And telcos are well-positioned to provide a superior customer experience by capitalizing on the vast amounts of data they collect, including a goldmine of information on customer behavior, preferences, and location. Providing customers with real-time personalized offers based on their location data is one powerful way telcos can improve customer experience—and, in turn, help boost profitability.
Real-time personalized offers are tailored to an individual's specific needs, preferences, and location and delivered in the moment as they interact with a product, service, or platform. The idea is that by providing customers with content and services that are highly relevant to their immediate needs and interests, businesses can enhance customer satisfaction, drive engagement, and ultimately achieve better outcomes, whether that's increased sales or improved customer loyalty and retention.
Businesses can achieve this level of personalization by processing data and applying algorithms to instantly adapt the content, recommendations, and experiences they deliver to the user's current context and behavior. Customers' smartphones constantly transmit location data, which can be collected and analyzed to provide real-time insights. Location data is a particularly powerful tool in the hands of telcos. By combining location data with customer profiles, including demographics and usage patterns, telcos can create a comprehensive view of each user, which they can use to deliver highly relevant and timely offers and services. Integrating data from third-party sources, such as weather data, traffic patterns, and information about local events, can provide additional context for personalized offers. Real-time data analytics plays a crucial role in turning all this data into actionable insights. Advanced analytics tools can process and analyze the information at lightning speed, allowing telcos to make quick decisions and deliver tailored offers in real time.
Real-time personalized, location-based offers can significantly impact customer behavior by making the user experience more relevant and engaging. Here are some examples of the ways telcos can provide highly individualized, contextually relevant customer experiences using a combination of historical user data (such as past interactions, purchase history, and preferences) and real-time data (including location, device type, and current actions).
Mobile marketing, while effective and potentially profitable, can be risky; however, personalization can help reduce the risk. Relevant marketing messages that contain useful information can enhance the customer experience; but irrelevant, untargeted messages become spam and can lead to customer fatigue and churn.
By providing real-time personalized offers based on customer location data, telcos can create a win-win situation, enhancing customer satisfaction and helping to drive revenue growth. This proactive approach simplifies the customer's experience and reduces the risk of unexpected charges, leading to higher satisfaction and loyalty. For telcos with narrowing margins and significant capital investments to make, improving the customer experience with data-driven personalization and location-based offers can also help significantly impact profitability. Location-based personalization can drive revenue growth in several ways.
When using customer data to deliver real-time personalized offers, telcos must, as always, handle that data responsibly, comply with regulatory requirements, and communicate transparently about data usage. Striking the right balance between personalization and privacy is key to a successful implementation. To achieve this, telcos need a data platform that’s able to deliver consistency, scalability, and performance while ensuring security and providing service and deployment flexibility.
By ingesting, curating, processing, and analyzing data, telcos can provide their customers with real-time personalized offers based on their location. This involves leveraging location data from users' devices, processing it in real time, and then triggering personalized offers.
The architecture presented here demonstrates how we can combine recommended Oracle components to build an analytics architecture that covers the entire data analytics lifecycle and is designed to help telcos and digital service providers deliver real-time contextual offers to their customers and achieve the wide range of business benefits described above.
Connect, ingest, and transform data
Our solution is composed of three pillars, each supporting specific data platform capabilities. The first pillar provides the ability to connect, ingest, and transform data.
There are four main ways to inject data into an architecture to enable telcos to deliver real-time personalized offers.
Persist, process, and curate data
Data persistence and processing is built on three components. Some customers will use all of them, others a subset. Depending on the volumes and data types, data could be loaded into object storage or loaded directly into a structured relational database for persistent storage. When we anticipate applying data science capabilities, data retrieved from data sources in its raw form (as an unprocessed native file or extract) is more typically captured and loaded from transactional systems into cloud storage.
Analyze data, learn, and predict
The ability to analyze, learn, and predict is facilitated by three technology approaches.
With support for the entire data analytics lifecycle, Oracle Modern Data Platform gives telcos the tools, performance, security, and flexibility they need to provide customers with real-time personalized, location-based offers. This marketing approach can yield significant benefits for both the customer and the telco, including the following:
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