Unlocking the Potential of Generative AI for Subscription Businesses
By : Rajkumar Solanki
General Manager - Customer Success
Picture this scenario. John, a Product Manager at a large Telco, has to optimise tariff plans for subscription-based products. Despite his experience and diligent efforts, he faces challenges – the complexities of market dynamics, evolving consumer preferences, and real-time competitive pressure. In addition, striking the right balance between attractive plans that resonate with customers and maximising profitability for the company can be a cumbersome process. Typically, it takes months of creative thinking and data analysis for John and his team to produce the right plans or products.
Now, what if John has an AI that can mitigate these pain points, automate price optimisations, and finetune the benefits associated with new product designs for customers to ensure a higher expected value in the marketplace?
This is where a Generative AI (GenAI) solution comes into play – one that can create novel product innovations and assist John’s team in meeting their business goals faster.
How is GenAI different?
Subscription businesses have traditionally deployed discriminative AI to meet their business KPIs. Discriminative approaches use existing observed data to assign a finite set of labels to the data. For example, Telcos use such AI techniques to analyse large sets of customer data, predict churn, and segment customers based on demographics, usage patterns, etc., to create hyper-personalised experiences.
In general, discriminative AI is beneficial for predicting a repeat event or grouping data by similarity.
On the other hand, GenAI is driven by Large Language Models trained with many volumes of data sets. Unlike discriminative AI, GenAI focuses on generating new original data in the form of images, videos, or text responses that are not chosen from existing data. It is this capability that assists Telco product managers like John to come up with out-of-the-world digital product designs faster and imagine what would have been missed otherwise.
In general, GenAI is best suited to problems that involve the exploration of new designs for plans, programs, processes, etc., going beyond the remit of discriminative AI.
GenAI can boost several business KPIs
Given the creative capabilities and massive potential of GenAI, digital businesses can boost several KPIs such as revenue, profitability, and customer lifetime value.
Here is a list of various use cases of GenAI in the subscription business:
- New Product Design: GenAI can automate the design of high-performing digital products with automated price optimisation, benefit tuning, and quick experimentation. This capability helps product managers optimise tariff plans and quickly create new products.
- Promotional Content Generation: GenAI can create tailored offer promotion content that resonates with the target audience. This feature assists marketers in maximising customer engagement and uptake rates.
- CX Program Design: GenAI can design a tailored customer experience program. It helps CX teams design a customer care process to resolve a specific issue faster or an omnichannel campaign to meet marketing goals.
- Agent Conversation Assistance: GenAI can guide human and chatbot agents to handle complex queries and provide accurate responses in simple language.
- Network SLA Remediation: GenAI can detect breaches of network SLA and generate remediation or upgrade plans and even compensation offers to proactively address shortcomings in desired network experience.
- On-demand BI Report Generation: GenAI can produce visual and textual insights, reports, and dashboards in response to user queries in natural language.
In conclusion, GenAI offers more than merely analysing data; it is capable of generating new content across text, images, and video. The potential use cases for digital subscription businesses are promising, whether designing novel digital products or enhancing chatbot interactions to seem more human-like. Product managers could maximise a product’s anticipated value before launch. Customer service leaders might find the right balance between investment in customer support and improvements to customer satisfaction and value. Marketing and customer experience teams could accelerate experimentation and innovation, thereby improving efficiency and revenue generation. Explanation of artificial intelligence decisions in straightforward natural language could provide a further benefit of transparency. For digital subscription businesses seeking to remain at the forefront, investing in GenAI technology appears the prudent course of action.
