Discover how cutting-edge technology is revolutionising customer personalisation, making every interaction unique and impactful.
Customer personalisation has come a long way from the days of simple email salutations and basic segmentation. Today, personalisation involves understanding the intricate needs and preferences of each customer, often predicting what they will want before they even realise it themselves. This blog illustrates how peronsalisation is taking shape and what the future beholds through the following topics:
The journey began with the collection of basic customer data such as purchase history and demographic information. For example, early loyalty programs like those of grocery chains would track purchases to offer discounts on frequently bought items. Over time, this evolved into more sophisticated methods, including behavioural tracking, social media interactions, and real-time data analysis. A notable example is Spotify, which analyses listening habits to create personalised playlists like Discover Weekly. Similarly, Starbucks uses its mobile app to track customer preferences and offer tailored promotions. This evolution has been driven by the increasing availability of data and the advancement of technology, enabling businesses to offer increasingly tailored customer experiences.
As a marketer, customer-centricity is more than just a couple of words; it’s an obsession. This mindset helped me achieve conversion rates of over 70% while working as a solutions sales consultant in the payment industry. I see each customer as not merely looking to purchase a product, but rather "hiring" a product to accomplish a specific job in their lives. It's my responsibility to help them make the progress they need. If I do my job well, then the next time a customer has a similar job, they'll hire us again.
One of my customers, Trish, a luxury art dealer, came to me when her boss tasked her with setting up an EFTPOS machine for their gallery. Instead of providing a standard solution, I sought to understand the underlying job she needed to accomplish. I discovered that Trish had been under pressure for not hitting sales targets. Her specialty was selling at exclusive events and outings, but she faced a recurring issue: clients would frequently back out of deals the next day. This led to pressure from her boss for not meeting sales targets, so she began to compensate with odd jobs such as organizing EFTPOS machines.
The events were high-end, and Trish did not want to arrive all dressed and holding an EFTPOS machine. This would send the wrong idea and cramp her fashion style. Understanding the functional, social, and emotional dimensions of her needs, I proposed that in addition to the office EFTPOS, converting her latest iPhone into an EFTPOS machine. This allowed her clients to tap their cards on her phone to make payments seamlessly. She was reluctant at the idea of punching in numbers on her phone at a party.
I took her through some examples of other clients who saw success with the solution and gave her a demo. She realized the solution was cutting-edge and completely subtle, allowing her to carry it 24/7 and whip it out whenever she needed to take a deposit to lock in a deal.
While she initially intended to gain her boss's favor by doing odd jobs, the final solution did the job of gaining her boss's favor in a far better way. Her sales went through the roof, and she impressed her boss so much that she was promoted to top art dealer.
What I didn't tell you is that I never actually spoke to Trish and nor did she ever know that I existed. This was my work as a marketer personalising Trish's experience to help her career aspirations. With clever segmentation and predictive algorithms I was able to make sure Trish was able to achieve both her job to get the office payment terminal and her other job to land more sales.
Personalisation is now scalable and it's taking shape now for businesses large and small. With the help of powerful technology, your business could be benefiting from our personalisation strategies right now.
Data analytics plays a pivotal role in personalising customer journeys. By analysing vast amounts of data collected from various touchpoints, businesses can gain deep insights into customer behaviour, preferences, and pain points. This data-driven approach allows for the creation of highly targeted marketing strategies that resonate with individual customers.
For instance, Woolworths uses predictive analytics to understand shopping patterns and recommend products to customers through their Rewards program. Similarly, Qantas leverages sentiment analysis to monitor customer feedback on social media, allowing them to make real-time adjustments to their services and improve passenger satisfaction. The key is to leverage data to create a seamless and engaging customer experience that feels uniquely tailored to each individual.
Artificial Intelligence (AI) and Machine Learning (ML) technology are revolutionising the way businesses approach personalisation. Before the advent of AI and ML, technology personalisation efforts were largely manual and limited in scope. Businesses relied on basic data analysis and segmentation to tailor their offerings, which often resulted in generic and less effective customer interactions. These traditional methods lacked the ability to process large volumes of data in real-time, making it difficult to provide truly personalised experiences.
With the introduction of AI and ML technology, the landscape of personalisation has transformed dramatically. These technologies enable real-time data analysis and decision-making, allowing for dynamic adjustments to customer interactions based on current context and behaviour. AI and ML technology can process vast amounts of data from various sources, identify patterns, and make predictions with a level of accuracy and speed that was previously unattainable.
Take Netflix as a notable example. The streaming giant employs AI and ML technology to analyse vast amounts of customer viewing data, including what users watch, how long they watch, and even when they pause or rewind. This data is then used to create highly personalised content recommendations. By understanding individual viewing habits, Netflix can suggest shows and movies that align with each user's preferences, keeping them engaged and subscribed. This integration of AI and ML technology into personalisation efforts ensures that customers receive relevant and timely interactions, enhancing their overall experience and driving loyalty.
The shift from traditional personalisation methods to AI and ML-driven approaches has significantly enhanced the ability of businesses to deliver customised experiences. AI and ML technology not only streamline the process but also provide deeper insights and more precise personalisation, ultimately leading to higher customer satisfaction and loyalty.
Several businesses have successfully implemented personalisation strategies that have significantly improved their customer engagement and conversion rates. One notable example is Netflix, which uses sophisticated algorithms to recommend content based on individual viewing habits. This level of personalisation keeps users engaged and subscribed to the service.
Another example is Amazon, which leverages customer data to offer personalised product recommendations and targeted promotions. This approach not only enhances the shopping experience but also drives sales and customer loyalty. These real-world examples highlight the power of personalisation in creating a competitive edge and fostering long-term customer relationships.
The future of personalised customer experiences is promising, with emerging technologies set to take personalisation to unprecedented levels. Imagine a world where AI and machine learning algorithms can anticipate human needs before we even recognise them ourselves. For instance, these advanced systems could predict our desires and preferences, such as calculating our libido based on the time we woke up and our correlated behaviours. It could then anticipate that the individual it's serving is likely to go and get a massage and make a booking before the individual knows they even want to go. That way, when they realise they want to go, it's already booked, ensuring they don't miss the appointment.
Another trend is the integration of Internet of Things (IoT) devices, which can provide valuable data on customer behaviour and preferences. This data can be used to create seamless, context-aware interactions across multiple channels. As technology continues to evolve, businesses will have even more opportunities to refine their personalisation strategies and deliver exceptional customer experiences.