It’s not new news and not surprising that a 2023 McKinsey research found that 71% of consumers expect their brand interactions to be personalised. But somehow many brands assume that adding ‘Hi Sarah’, ‘To Jerry’, or “Hey Ryan!” is enough to pass muster. We are in the era of hyper-personalisation and this simply isn’t going to cut it anymore.
Consumers expect more. They want to feel seen, heard and understood and expect to receive personalised offers, recommendations for products and services that are relevant and interesting to them, customised pricing, and tailored services that make their lives easier.
But how can brands be expected to know every customer, understand their true behaviours, and meet their individual needs? Even if they did have access to all of the information, how would they be able to see it all and act on it at the right time to achieve the best outcome? It can feel overwhelming. But it is possible.
Harnessing AI and decision intelligence platforms makes hyper-personalisation very achievable. It’s already very much a reality for some of the world’s leading brands. Those who have started on the digital hyper-personalisation journey are achieving startling results, in some cases 10% -15% ARPU improvement, a 20% reduction in churn, and a four-fold increase in customer lifetime value.
Internationally, Vodafone is a leader in this field; they follow the learnings from digital native brands like Spotify and Netflix and adapt these for the telco domain. In Australia, TPG which operates 11 different brands (including Vodafone and Lebara) are leading the way. When brands incorporate hyper-personalisation into their marketing and CX strategy, they achieve results that were far superior to anything they’d ever achieved before. Like many other leaders around the world, TPG recognised they needed to leverage data to supercharge how they were delivering value to specific customer segments. Harnessing the power of AI and decision intelligence, they were able to implement a data strategy built to deliver hyper-personalisation backed by insights. This is a strategy they still rely on today.
At the centre of hyper-personalisation strategies is decision intelligence, a domain of AI (or, more specifically, machine learning). It enables people to make smarter decisions based on accurate data-backed insights and deliver individualized experiences that align with unique customer needs. For example, SourseAI’s decision intelligence platform, Atlas, works to turn huge volumes of data, pulled from a wide range of sources, into valuable insights. These insights are then translated into predictions, which gives teams the information they need to take action when it matters most.
Using pre-determined AI models trained on specific industry data (for example, telco), decision intelligence platforms help teams to maximise retention and acquisition outcomes. What’s more, these solutions are scalable, running hundreds of different variations of CVM campaigns to find the sweet spots for success. One of the biggest benefits of AI and decision intelligence in acquisition use cases is its ability to predict the lifetime value, tenure, and cost to acquire and yield potential of a customer. This means it is possible to create sets and subsets of segments to a degree that’s not been possible before. In turn, more personalised campaigns can be developed and deployed, boosting engagement, loyalty and revenue.
For example, a decision intelligence platform will identify everything about the best lifetime customers. Drawing on these insights, it is then able to predict what makes a good, high-yield, loyal customer and devise plans to acquire them. In short, it helps to ensure the base is fit for future growth. Retention is no longer the gross additions headache it once was, and knee-jerk price promotions and giveaways (which can be costly!) can become a thing of the past.
MVNOs are well placed to realise hyper-personalisation sooner than most. Their youth, relative to the incumbents is also an advantage. There are no legacy systems for a start and their focus on digital products and services makes them inherently agile. Not to mention, they have well-organised data thanks to the value their MVNEs place on it.
MVNOs are also targeting specific segments, which gives them a boost when it comes to using AI to understand the micro-segments in their base. These attributes combined, put MVNOs in a better position to outpace their competitors within three to five years of adopting a data strategy built for hyper-personalisation. Of course, this relies on investment in data and SaaS tools. However, such solutions deliver results quickly. Typically, SourseAI customers realise the value of Atlas within 90 days of adoption, and without any need for specialist data scientists. If you’re an MVNO and want to discuss decision intelligence in your business, get in touch.
There is trepidation from some leaders about integrating AI within their business. How will AI fit into the business model? Will it disrupt our operations and processes? Do we have the necessary skills and resources in place? How accurate and reliable is the data? There’s also the ever-present question: how can there be any level of certainty that this will improve the business?
The fact is, there are already pioneers you can learn from. They are leading their markets and in control of their data with plenty of evidence that partnering is better than a do-it-yourself model. Read more about that here.
Now is the time to embrace a culture where data is the currency. Because the value of data-driven decision-making cannot be overstated. By applying AI to their own acquisition strategies, SourseAI customers are seeing:
As awareness and understanding grow around the value of data-driven hyper-personalisation, more businesses will be actively looking to incorporate the technology that makes it possible. Early adopters are already powering ahead. Now is the time to act – or risk getting left behind.
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To discuss how hyper-personalisation and decision intelligence can optimise your business performance, get in touch with the SourseAI team today.
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