Sales Trend 7 from the Barrett 12 Sales Trends Report for 2020 looks at the benefits, downfalls and ethical issues that arise for businesses from collecting and using data.
This is a condensed version of Sales Trend 7, to read the original version you can download the report for free.
People, particularly in big business and governments around the world, are obsessed with data – big data, surveillance data and especially human data and how they can use it and sell it.
Being obsessed with data is not a new phenomenon, after all most humans are usually wanting to know what the future will hold for them – from our obsession with the weather forecast, to the stock market, to customer demographics, to the latest fashion trends or baby names. Given the way human brains are wired, most of us are looking ahead to anticipate dangers and threats, and anything that may disrupt our status quo – our comfort zone – which is why we love certainty. But be careful what you wish for. This last point is particularly important when we dive into the ethical use of data and data analytics, especially, its intended uses on us, as humans. Therefore we must enter this sales trend with a degree of caution and insight.
Let’s start with data.
Data – Data Analytics and Predictive Analytics
Businesses have always used data in some way or other to make decisions. However, this sales trend shows that the advances in accessible technology, the amounts and types of data at our disposal has grown exponentially and with it what we can do with it. We can now collect data to see what has happened – Data Analytics – and then use that data to predict what might happen in the future – Predictive Analytics.
Most businesses now use Data Analytics to get feedback on a range of areas, for instance: How many views/downloads happened with the new product/pdf/media release? How long do their eye stay on a page? And so on. The data lists are endless. If you are asking the right questions and tracking the right data, data analytics can give you a very clear understanding of what is happening in whatever aspect you choose to peer into which can then inform you about what to do next, giving us some degree of certainty. But is all data relevant data? This is the conundrum. What to capture and assess? Customer interactions, requests and purchases, processing loan applications and detecting fraud are all on the agenda. All of them involve people and their relationship with our businesses and organisations.
How do we use the data for doing better sales and business?
All organisations need to gather certain amounts of data from their clients to be able to provide the right/best services and products, however just having more data does not equate to better service or greater profits. Businesses can be tempted to gather more data than what is strictly needed. With social media and all of the easily downloadable apps we have access to now where we have our behaviours stored, many organisations are mopping up this information and using it to predict our behaviours, even before we have in some instances. This sales trend sees data mining using huge amounts of data that validates, or not, the assumptions made by humans. The more data a business gathers the more ‘certainty’ it will have on the decisions it can make. This is where Predictive Analytics comes into play. It’s helping answer the question ‘What will we, the customer, do next?’
On the plus side, that can help businesses and organisations predict customer behaviours for the future and then curate information, offers, invitations and so on to clients that are customer centric, helpful and supportive, leading to better targeting, better conversion rates, more profit, better retention and more customer loyalty. When computer programs get even better at prediction and can adjust their approach based on the available data we call this Machine Learning. Machine learning is another part of AI. The Google algorithm is based on machine learning and looks to narrow down our options and choices based on our previous preferences. However, is this an unethical use of the algorithm? What’s really making us click on a link and buy?
The ethical dilemma of AI, data analytics and selling certainty
A Reason and Purpose for Data Collection and Use
Businesses, organisations and governments gather data for different purposes. It may be related to accounts and invoicing, service delivery or to be able to provide their service, etc. But the big question is how is that data kept, protected, and used? Is it anonymous? Is it being used for the benefit of the clients? To make their life easier and to help them find solutions, deliver better outcomes, etc.? Or is it for the sole benefit of the organisation keeping the data? There is a very fine line between the data that an organisation needs to deliver their services better and what is ‘nice to have’ or too sensitive to retain.
The Use and Abuse of Data
Even with the data gathered for legal purposes or because it’s necessary for the development and delivery of the product or service, there are issues related to accessing that same data for other uses. Questions need to be asked. Is it ethical to make profit analysing data that was collected for other purposes or to use private data to sell ‘more’ tailored products and services? What’s for certain is that our data is up for grabs and not for good reasons either. Things have got to such an unhealthy and unethical pervasive point that Professor Alan Finkel, Australia’s Chief Scientist, said that AI is crossing a moral boundary. There’s a balance that needs to be achieved between the data a business gathers to provide the service that is expected in an efficient and effective manner and the data that a business would like to have to ‘improve’ this service and sell more. Ethical guidelines and regulatory frameworks are essential in this space. If these are ignored then we have re-entered the world of carpetbaggers and snake oil salesman where anything goes.
Welcome back the human factor
So how can customers feel safe and have some degree of certainty that who they are buying from is legitimate and has their best interests at heart? At a business level, we need to go back to the human factor. Some businesses have already done it. Netflix is testing a section now where people curate content suggestions instead of an algorithm and since 2017 Apple has an Apple News’s editor in chief and employs journalists to decide which stories to promote.
While many will say that the future of business is in AI, this trend sees businesses choosing to put people not only at the centre of what they do, but also at the centre of information. So, whatever data is gathered and use, there can be a human caring about what happens to the other people and communities involved (or affected by) business decisions.
Remember, everybody lives by selling something.
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