Why hyper-personalisation, I hear you ask?
Well, it’s one of the latest trends in marketing. As more AI functions pop up, such as chatbots, generative AI products that you may already use like ChatGPT or Bard or even AI analytics tools, businesses around the globe are automating their ability to communicate with their customers on a whole new level. Gone are the days where cold-calling and random emails are enough to satisfy a client that your business is worth their time and investment.
With the emergence of AI tools, customers have a more powerful example of how to find their voice over customer service journeys; they don’t want to be treated like a transaction, they want to be treated like humans whose pain points are recognised and responded to empathetically by the business they choose to purchase from. In fact, Drift – an AI-based conversational marketing tool – finds that “72% of buyers will switch brands after just one bad experience.
Through this, the importance of understanding your customer as an individual; not even as a demographic, but as an individual, is undeniably important. How do you do that? How do you integrate this into touchpoints for your customer throughout their journey? And how does it improve their experience? Let’s find out!.
What is hyper-personalisation?
Hyper-personalisation is a completely individualised customer experience, based upon the unique needs and pain points (life challenges) of a specific buyer. This is based upon constantly updated data, as well as effective communication between customer and business and the studied analysis of customer choices.As mentioned above, this goes above simply a demographic.
A personalised customer profile might be: women aged 25-35 who work in the software industry, live in Melbourne, perform data analysis, are passionate about empowerment of women within the tech industry, want to organise their data in a customisable way and are challenged by the need to analyse large volumes of data within their daily work responsibilities.
A hyper-personalised customer profile/experience is far more specific.
It could be something like this: Faye, aged 28, works in business analysis at an energy startup. Her tasks include: managing customer data, analysing trends, recording risks in projects and customer relationship management.
She lives in Carlton, works remotely and deals with clients both nationally and locally. Her business is upscaling, so she is searching for a tool that can support transplanting her data across to a more efficient, larger and better-equipped digital storage facility. Her organisation uses social media tools like Instagram, LinkedIn and TikTok to promote their product.
Faye also enjoys travelling herself, and so one of her challenges is finding a tool that accommodates her lifestyle by operating on some AI features in her absence, as well as fostering collaboration with her co-workers.
Notice the difference between the two?
Firstly, the customer has a name, a personality, lifestyle habits and their needs are the focal point of the profile rather than acting as an end-result or simply a PO to be collected.
How do you actually get this information holistically?
We discussed how quickly customers will change their course of action if they feel they’ve encountered a poor quality, disappointing or unsafe experience. That last factor is perhaps the most important – there are huge upticks in cybercrime at the moment, and hacking is at the top of the list for business-risk.
For example, in a report entitled ‘The Future of Retail Banking’ prepared by Deloitte on hyper-personalisation in the banking industry, it was found that: ‘most respondents [in their survey] would share their geo-location, as opposed to more personal data (e.g., life stage events and health data.)’ So, in curating hyper-personalised customer profiles, trust is an integral factor. And trust is centred around transparency – sure, most of the time people click ‘accept cookies’ without a care in the world, but they’re not likely to follow the same trust-process when it comes to actually entering their own details.
Being transparent means answering the following:
- Why are we asking for this information?
- Is this entry field end-to-end-encrypted?
- What do we use this information for?
- Can a customer opt out at any given time?
- Can a customer speak to someone about what we’re doing with this data?
- If I’m buying a product, how does this information better enhance my buying experience?
An Example:
And on that last point, we arrive at how you can ethically and holistically collect customer hyper-personalisation data. Let’s say you’re advertising a software product that Faye is going to buy (see above 👆) to help with her data management, and it uses AI. You might work with your website team to install a feature on your site that allows your potential clients to toggle through to their personal preference for what they’re looking for.
E.g: a field that asks ‘I’m looking for…help with data management‘ that, when filled in, will take your client to the correct product. Additionally, consultation emails or field entries should become far more detailed.
Explaining why you’re asking personalised questions will begin to build the foundations of trust and transparency required to achieve a strong hyper-personalised customer lifecycle. Best of all, once you’ve received the inputs from your client, you can integrate these with whatever AI programs you may have across your tech suite, meaning you will be able to automate some of these steps – all the while keeping up a stellar standard of service. Another way you can provide customers with the option to get to know one another is through gamification; the B2B industry has the potential to employ AI in partnership with gamified applications or programs to help its users.
For example, let’s say Faye needs an alternative scheduling tool that functions to support her concentration and productivity.
A business who provides that product may be able to amplify its features by allowing Faye to track her project progress or task completion through visually inspirational games – maybe each time you finish something, your character progresses onto a new level. As she does so, Faye can be supported by the application’s ability to prompt, recommend and remind her of upcoming tasks so that she doesn’t have to worry about them herself.
The Power of Behavioural Science on Meaningful Customer Interactions
Returning to the Deloitte report, we should consider the impact of ingrained behavioural practices that inform our decisions. As put by Deloitte, it’s the ‘”what”, “how” and “why” of customers’ behaviour.’ It’s integral to note that customers don’t always put their right foot forward (Doyle and Kibble) because of these internal – and indeed external – lifestyle circumstances. Factors such as financial situation, living conditions, family, social setting and interests can determine why customers do or don’t invest in a product. So, if you think about it, your hyper-personalisation efforts have the power to transform the stability of a customer’s investment and improve their quality of work or lifestyle. If you make a customer feel seen, respected and understood, they are more likely to
a) recommend your product to other like-customers who have similar needs,
b) return to buy from you again/renew their subscription or contract and;
c) make smarter choices with their own investment, building their trust within you as a valued part of their work setup.
Need a Helping Hand?
If you’re wondering how to make hyper-personalisation work for your business and how you can get meaningful customer interactions out of your marketing and sales efforts, allow us to introduce ourselves. Hey there, we’re Rovert Digital, a startup marketing agency whose expertise in one-in-a-million customer journeys extends itself to B2B and B2C capacity. We love seeing your customers feel like they’re the only people in the world, and translate that into our work with you. To get started, book a chat with our team today.