Know that AI is the ‘next big thing’ but not sure exactly where and how you might apply it in your business?
Or perhaps your leadership team is worried about missing the boat, as competitors harness its capabilities in powerful but unspecified ways?
The concern is understandable, given the extraordinary hype and headlines AI has generated over the past 18 months, following the unveiling of ChatGPT, the OpenAI chatbot and virtual assistant that allows users to steer and refine conversations in whatever direction they choose.
While AI technology – computer systems or machines designed to perform tasks that would typically require human intelligence – has been around for years, the immediacy and accessibility of this large language model, generative AI platform has triggered an extraordinary wave of conversations, in boardrooms and C-suites up and down the country.
Doing more with your data
Data is the requisite ingredient that enables generative AI programs such as ChatGPT to have quasi-human conversations – and become progressively more ‘intelligent’ over time, as they analyse and learn from those conversations.
In fact, data is the essential fuel for all AI-powered processes and the good news is, your organisation is likely to be awash with the stuff, courtesy of the cloud based digital applications it’s implemented over the past decade.
With any luck, your revenue management platform will be one of those systems. If so, the data it collects and stores could be an unparalleled source of business insights; useful for analysing trends around product usage, sales, revenue and more.
Business insights from the billing function
Detecting fraud is one way ahead-of-the-curve businesses are using AI. Historical billing data can be used to train machine learning algorithms to identify anomalies or suspicious transactions. Those tools can then be used to detect patterns that indicate fraudulent activity in real time.
Historical billing data can also be utilised to predict future financial trends, thereby assisting businesses to make informed decisions that will see them better positioned for whatever is to come.
Meanwhile, granular analysis of the billing process – to a degree that would be well-nigh-impossible for human beings to achieve, and utterly impossible for them to achieve cost effectively and in a reasonable time frame – can enable organisations to identify inefficiencies and bottlenecks.
It’s an exercise that may result in the decision to automate tasks and streamline procedures to boost productivity and reduce error rates across the entire revenue management function.
Cost savings are likely to ensue. In today’s challenging economic times, those are likely to be keenly appreciated, by businesses seeking to protect their margins whilst containing their prices.
Using customer behaviour analysis to create value
Another way to create value is seeing data on how customers are using the product, and then tailoring a more relevant and persona-specific user experience. Insights into their behaviour, preferences and purchasing patterns can be extracted, analysed and leveraged quickly and easily, using generative AI tools.
From the creation of personalised marketing strategies that really resonate, to the enhancement of every touchpoint on the purchasing journey, they can transform billing data into the catalyst for customer experience optimisation on multiple fronts.
Smart technology that can help your organisation get smarter
Of course, utilising generative AI to extract actionable insights from your billing data is only possible if you’ve deployed a revenue management solution that allows it – one with a metadata-driven architecture that allows it to be seamlessly integrated with generative AI tools.
With this framework in place, your users will be able to interact directly with your billing solution by simply voicing their requirements to a trained AI model that understands their language.
They’ll be able to request feature enhancements and data analysis in plain language, without the need for intervention or support from technical specialists.
And by continually analysing user interactions, configuration patterns and business data, GenAI itself will be able to identify hidden opportunities, suggest innovative enhancements and even predict potential issues before they arise.
Tackling the future with confidence
As the technology continues to evolve at bewildering speed, organisations that fail to capitalise on the opportunities and advantages generative AI can deliver will soon find themselves struggling to compete with their more innovative counterparts.
If your enterprise is ready to embark on the generative AI adoption journey in FY2025, the revenue management function is an excellent place to start.
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