In the telecommunications industry, personalised marketing is a strategic component of Marketing and Sales Optimisation, yet it serves as a foundational pillar for Customer Experience (CX) Enhancement. According to the sources, the core of a successful modern CX strategy is making customers feel “known, heard and understood,” a goal that is primarily achieved through AI-driven personalisation.
There are several ways personalised marketing operates within the larger context of CX:
1. Data-Driven Customer Segmentation
AI enables telecom providers to move beyond broad demographics by analysing vast amounts of user data, including demographics, usage patterns, and individual preferences.
- Targeted Strategies: This analysis identifies distinct segments within the customer base, allowing companies to craft promotions that resonate with individual needs rather than relying on the “guesswork” of traditional marketing.
- Propensity Modelling: Startups like Ikue use robotic data automation to build propensity models that adapt to real-time changes in consumer behaviour, ensuring that marketing remains relevant as the customer’s journey evolves.
2. Maximising Customer Lifetime Value (CLTV)
Personalisation is directly linked to a customer’s long-term value to the company. By analysing spending patterns and product loyalty, AI models calculate Customer Lifetime Value (CLTV), which informs the creation of highly targeted campaigns designed to build long-term relationships. This approach helps mobile virtual network operators (MVNOs) and traditional providers alike to drive revenue growth through increased engagement.
3. Proactive Retention and Churn Prediction
A critical intersection of marketing and CX is churn prediction. AI algorithms monitor customer history and engagement to predict when a user might switch to a competitor.
- Tailored Retention: By identifying at-risk customers early, companies can take proactive measures, such as offering personalised retention deals.
- Real-Life Example: T-Mobile utilizes machine learning to analyse engagement data specifically to tailor these retention offers effectively.
4. Enhancing Support through Personalisation
Personalisation extends beyond sales into service and support.
- Personalised Recommendations: AI systems use machine learning to suggest service plan upgrades or tailored troubleshooting solutions based on a customer’s specific usage patterns.
- Empowered Human Agents: AI-driven insights provide contact centre staff with the context needed to offer a more personalised experience during human-to-human interactions.
- Virtual Assistants: Virtual assistants and chatbots use Natural Language Processing (NLP) to provide 24/7 support that feels personal and responsive to the individual’s specific account status and history.
5. Strategic Competitive Adjustments
AI allows for dynamic marketing strategies that respond to the external environment. For instance, if a competitor launches a new promotional price, AI can detect this and recommend immediate price adjustments or targeted counter-promotions to maintain customer loyalty and engagement.
Analogy for Personalised Marketing in CX Imagine walking into a massive department store where every sign, display, and price tag instantly changes based on who you are. Instead of wandering through aisles of items you don’t need, the store’s layout shifts so that your favourite brands are right at the front, and a clerk greets you by name, knowing exactly which pair of shoes you bought last year. In this “living” store, you aren’t just a face in the crowd; the environment proactively adapts to make your shopping trip as effortless and rewarding as possible. This is what personalised marketing does for the digital customer experience.