Transform your Customer Support Portals & Internal Operations with Generative AI

At Parallax we have worked with a range of global organisations creating and optimising digital products, services and support portals. Our expertise across delivery, digital strategy, experience design and engineering perfectly aligns with being able to uncover and understand the needs of customers, as well as a deep understanding of what businesses want to achieve by building them.

The customer experience is paramount. Can they access and log in easily? Are the functions and features what they expect? Did they find a resolution to their issue quickly? Did they see that you offer a complimentary service or product to what they already have? It’s a fine balance between offering key functions and assistance, but also a perfect opportunity to cross-sell and up-sell, increasing awareness of your product or service portfolio.

‍

Where Generative AI Can Help

Unless you’ve been hiding under a rock, you’ll be aware Generative AI is evolving rapidly. The opportunity it brings to enhance user experiences, streamline internal operations and boost revenue are massive. 

Generative AI goes beyond chatbots — it's a powerful technology that works through a combination of advanced learning techniques, primarily involving large language models (LLMs) and neural networks. ChatGPT is just one very popular example; the potential applications are vast and varied. 

Some of the opportunities we’ve spotted in the digital product, service and support portal space are: 

Dynamic Content Creation

Generative AI can use natural language processing (NLP) to understand the context and intent behind customer queries. As well as being trained on vast amounts of customer interaction data, it can recognise patterns and common issues to generate coherent and contextually appropriate responses based on the input they receive.

Interesting use cases include:

• The ability to generate and update FAQs based on trending queries and customer feedback
• Creating tailored product descriptions that highlight benefits relevant to individual customer preferences 
• Suggesting relevant products, services, or content based on customer behaviour and preferences

Superior Support & Customer Insights

Machine learning algorithms can analyse historical customer support data to identify common problems and solutions. By recognising these patterns and using predictive analytics, AI can provide accurate and relevant insights to forecast future trends and potential issues.

To help customers you can:

• Automatically create and update knowledge base articles based on new product features or common customer issues
• Implement AI-driven visual recognition tools that help customers diagnose issues by analysing photos or videos of their products
• Prioritise and route support tickets based on issue severity, customer value, and historical data using AI
• Summarise customer feedback from various channels and generate actionable insights for improving products and services

Proactive Alerting

By using machine learning models to continuously monitor system performance, data points and user behaviour in real-time, deviations can be detected and AI can generate various forms of alerts.

We can use this to:

• Predict potential issues customers might face based on usage patterns and notify them before problems arise
• Predict peak times and optimise the allocation of support staff to ensure efficient handling of queries
• Generate personalised schedules and reminders using AI for products that require regular maintenance

Hyper-Personalisation

AI can build detailed profiles of each customer by analysing their interaction history, preferences, and behaviour patterns. This ongoing learning process enhances personalisation over time and can tailor its responses and recommendations to fit the specific needs and circumstances of each customer.

Some experiences can take the form of:

• Custom step-by-step guides and tutorials that adapt to the user's level of expertise and previous interactions
• Monitoring customer interactions to gauge satisfaction levels and adjust support tactics accordingly
• AI-driven virtual assistants can walk customers through troubleshooting processes, reducing the need for human intervention

‍

Business Benefits

These use cases and application of technology shouldn’t be perceived as daunting tasks. We always take a sensible approach and look to create proof-of-concept pilot schemes to test and learn before scaling. This allows us to work closely with our customers you and iron out any issues that arise, whether it be internal staff concerns or customer feedback regarding accuracy. The other benefit is understanding the impact, so you can calculate return on investment (ROI) and plan future optimisations.

We’re already seeing businesses:

• Increase revenue by enhancing customer satisfaction and offering personalised recommendations, businesses are driving higher sales and customer retention

• Improve staff efficiency and productivity through automation and intelligent routing by freeing up support staff to handle more complex issues, improving overall efficiency and reducing operational costs

• Provide faster and more accurate support leads to happier customers, fostering loyalty, positive reviews and support feedback scores and ultimately increased customer satisfaction

‍

To collaborate on spotting opportunities, propel your business strategies forward, or test pilot schemes with these cutting-edge technologies, reach out to us.

‍