Making personalisation work

Most businesses have been investing in tools to personalise services and setting up ultimate best experiences based on your preferences. This obviously serves them to have you spend more because they understand how to target you better. We all at this stage also know that this kind of targetting can also stimulate very narrow behaviour and drive us to a path of being easy to manipulate based on what we read, consume or like or emote on.

There is an opposite movement coming forward and originating from the dark web circles where anonymisation or pseudonyms are the norm. I was having a conversation recently and someone suggested that it would be great to have an organisation made up of people you don’t know delivering for your business or purpose. Which made me think and write this post. Would we really like a society or business where you didn’t know who worked on something but jobs got done?

The good and bad of personalisation

Personalisation of products and services are and have been popular for some time; most software tools now include it or at the very least have it on their roadmap. For a lot of companies, this means having an algorithm with or without an element of machine learning under the hood, or a recommendation engine or at worst being able to pick up a persons’ first name and track what they have done on your site or software.

From a business perspective, it is how Amazon and Netflix make a lot of money, by recommending us things based on our user behaviour. A lot of business tools such as learning systems are adopting similar approaches. Where based on what you have already consumed you are presented with similar courses.

From an engagement perspective, the more you appeal to what people are truly looking for, the better they will feel about your service delivery and engage with it.

On the flip side, we are sent down a specific track either based on what the trained algorithm thinks is great or in the now publicly know case of Facebook (and I am pretty sure they are not the only one) we can be manipulated to think and act a certain way. One really wonders if there had been no deliberate interference whether certain politicians would have been elected or whether Brexit would have even ever happened. Manipulators will always find a way, but personalisation algorithms and recommendation engines have a lot to answer for.

The other point I see which is relevant to business tools, is where you have recommendations of learning for example taking you down a specific track to the exclusion of a whole bunch of other things which would also serve you. I think there should be an anti-recommendation list which presents to you all the things you never read or visit. I also believe a reset button to clear the recommendations and start over.

Either way, don’t pretend to personalise!

Making personalisation work

If you have ever been in a sales conversation, you may have heard the comment “I know you do this for that company, now we want something like that ‘but we are quite different'”.  In the eyes of the customer they are giving you a clue ‘they are different.’ In my learning and development work even with teams in the same organisation heard this every single time. My first response is always, to follow up with a question namely “what makes you different?”. This both acknowledges the fact that you may appreciate the difference and then allows the person to explain exactly what they find important as a differentiator.

Listening to the explanation and then ignoring it for future reference is basically equivalent to dismissing their request and unfortunately, this happens more often than not. In the learning and HR space, I have often seen new buzzwords added with only minimal change to the overall system and that then allegedly is personalised. From simply addressing the person with their first name to tick the box of being personalised. I am cynical about some of the antics in our technology space. But really if you are going to make a claim then go all in. Simply welcoming me by my first name is cute but let’s be real it doesn’t make a system personalised.

By using the information that was volunteered to you, you are actually making the client feel valued and special because you took on board their message. It is remarkably uncommon in business and it is often the client knowledge the salesperson forgets to pass along as part of the processing of an order. Make it personal to them or their way of working, so that they feel heard. Ask them what they want and within the realms of possibility make that happen for them. If you can’t then also be honest about it.

Preferences and opt-outs

In my view preferences and opt-outs or opt-ins are part and parcel of creating an inclusive personalisation strategy. I also believe it is up to the individuals’ free will to choose a specific path. Allowing individuals to tailor a path their way based on their preferences can go some way of creating a feeling of autonomy and personalisation. Both are close allies. Not only should I be able to change the cosmetical look of something from light to dark mode or any flavour in between, but I should also be able to reset my preferences, erase my consumption history and start over.

As a simple example, when I travel some websites especially the search engine variety want to then change all the commands into the local language. Whilst this can be great for a native speaker, it is also really annoying when you are not and you are consistently confronted with things that you simply don’t understand. As an e-learning and course designer, I often had to delve deep into a topic, only to find that all the social media channels now thought I needed more of that content. Once the projects were closed I would have preferred to be the controller of that setting or algorithm and reset it to something that does actually appeal to me outside of work.

Openness about your artificial intelligence

With Facebook announcing that they are going to go all metaverse on us, I couldn’t personally think of a worse development. When we know that VR and reality are such close friends for our minds and we then put this in the hands of a company whose ethics and track record are not pure. That is when I draw the line of the acceptable.

I think for all of us working on software projects, we need to be open about the purpose of our artificial intelligence and let the consumer decide if it is in their best interest. I don’t mean another set of ignored statements when you sign up for something, but much more concrete friction to ask for permission. Do I want to be targeted by ads or recommendations of a certain type? Do I want to organise my content in certain topics? Then have an explainer as to what happens if you opt-in or out. Simply stating that you will not have the same experience is not good enough. If I opt-out then what do I miss, if I opt-in then what do I receive instead of what I already have.

Currently, I see most software providers with employee-facing tools hide behind fancy terms and technical lingo, which most end-users and often HR decision-makers will not understand. Then I also see management teams setting up systems that only suit their objectives and not that of their employees. Both practices need to be out in the open. If you are doing something because it will make you more profit, then say so unashamedly. If you are doing something to comply with certain laws of your country, equally say so. An educated employee can then help spot more opportunities and will most likely aim to do the right thing for both them and the company.

All I can say for sure is that human beings operate on many more complex levels than most of the deployed algorithms do. Eventually, they may catch up with us, but to enable us, humans, to choose our path we need to allow for choice, resets, preferences as well as the typical recommendation engines that are covered with this catch-all term. Trust that your people will do the right thing when given the choice especially when you have bothered to educate them why certain practices are in place. Don’t underestimate a human that feels heard, valued, and respected.

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