Great software is about people, not hyper personalisation

The use of AI to create highly personalised digital experiences seems to be the ultimate goal today according to Forbes, who use Netflix as their epitomic example. Digital disruptors like Netflix made super targeted, but not invasive, content the norm. Now, consumers struggle to engage with anything less. 

But we see it from a different perspective. It’s not the hyper personalisation that is driving engagement; it’s the creation of software that is both truly useful and that people truly love. 

Successes like Netflix represent software that has been built for individuals. Not to achieve business goals, or show off a cool piece of tech. Not to gather cookies or get you to sign up to a newsletter. And not even to just provide a service. 

This kind of software is made to deliver a service with a human-led purpose and real-world usefulness. Then, it does so with such an elegance that the person at the other end takes delight in using it.  

While hyper personalisation on its own simply fulfils a person’s wants or needs, a people focus creates software that exceeds far beyond an individual’s expectations. 

Personalisation is more like the outcome of this equation. 

Part 1: Software that people love 

How can you make software ‘loveable’? 

Well, it’s extremely difficult, but it’s absolutely critical. As Harvard Business Review points out, this is much easier for consumer solutions than business ones. 

Software that you love evokes an emotional response. In this sense, how or why we ‘love’ software can mean several things. 

It may be tied to the application. For example, Google, FaceTime and Zoom provide people with ways to connect to their loved ones. This is an inherently emotional function, something which we all felt during the pandemic. When creating software that is woven into our social fabric like this, it’s much easier to create something people will love.  

But not all software is emotional, and so functional services like banking apps or data solutions will have to find other ways to evoke that human connection.  

This leads us into the concept of ‘useful’ software. 

Part 2: Useful software 

For software to be useful, it has to go beyond just fulfilling a function. It has to do this extremely well. Any distractions, clunkiness, or sub-par functionalities will detract from the user experience, sometimes turning something that’s meant to be useful, into something that’s more of a burden. 

They need to find ‘love’ in the beauty of the design. 

Software can be loved in how much it exceeds your expectations, how it seems to understand and reward you, or how much you trust it to make your life easier. 

To achieve this, developers need to carefully consider what any given user is trying to achieve. Even going so far as to delve into the psychology of user engagement, behaviours and motivations. 

Likely what they’ll find when they do is that no two people are the same. Some people want to see their running training progress in charts, while others will respond better to motivational messages. With different needs and likes, what we each define as useful or loveable is entirely different. 

And maybe more importantly, what one person loves another may hate. 

Part 3: Bringing them together 

Looking at usefulness and love together – the individual is at the heart of both.  

Creating a piece of software that a diverse group of users will both find useful and delight in using therefore requires the software to adapt to its individual users. 

Generally, software that really excels does so because the developers have put great pains into trying to understand their individual users. They’ve tried to give them tailored experiences – through personalised recommendations and customisations, or by giving users more than they thought they wanted. 

For example, I can like a standard recipe app. But I would love it if it was able to guide me to local ingredients and recommend relevant recipes accordingly. 

This is why Netflix was Forbes’s example. It is always trying to individualise and enhance the user’s (singular) experience. 

This level of user centricity will quickly upgrade a piece of software from useful, to loveable. From mundane, to emotive. 

How Mindset creates software people love 

We build software that adapts to people, not the other way around. 

For us, this means thinking about two audiences; our customers and theirs. Behind every decision we’re thinking about what will help consultants, coaches, social workers and more, interact with their customers better.  

We ensure every feature is designed to delight both sides of this relationship. For example, using data insights to support business strategies as well as to personalise the end user experience. 

One key method we’ve introduced to ensure that individuals always remain at the heart of our platform is two-way feedback loops. 

Between the experts running their business platform and the users they’re working with, there are continuous lines for communication. Users can directly feed-back, ask questions or rate what they’ve been delivered. The experts can evaluate this, adapt their content, and continue to hone their offering based on human insights. 

They can also cluster users in different ways and evaluate their delivery against this. Businesses can then ensure that every need, user demographic, or personality type, is being accommodated equally. 

This gives everyone in the ecosystem a voice and makes sure every user is catered to. 

Why hyper personalisation isn’t the answer 

We’re also constantly conscious of the pitfalls of ‘hyper personalisation’. If software is too focused on personalisation rather than people, it could introduce several core issues.  

One is overfitting. Hyper personalisation without any randomness or discovery will only give users things that align with their worldview. In knowledge-based sectors like consultancy, this undercuts the user’s intention to learn, develop and grow. 

Another potential issue is bias. Developers and anyone with content input must be aware of their own bias – whether negative or positive, conscious or unconscious. We have to understand that our views may affect the system and try and identify this. We also have to monitor how the system is adapting and why. 

These potential problems with hyper personalisation are another reason why understanding people must always be the focal point of any software. We must first adapt the software to people’s needs, and then make sure the software continues to work in people’s best interest. 

There is a definite relationship between a people-centric approach and the quality of the software. As hyper personalisation continues to take off, it will be interesting to see the difference between those who harness it as a digital tool and those who end up using it as a result of a people-led purpose. 

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