Big data and AI were buzz words throughout 2017, but, as often the case in the IT world, the hype outstripped actual real-world examples. AI bots that can replicate human conversation grab a few headlines and inspire conversations that inevitably end in references to the Terminator films’ Skynet.
However, machine ‘intelligence’ is real and offers genuine value to enterprises of all kinds, and AI will become a bigger part of how consumers interact with companies.
To Speak to a Real Person Press….
Contact centres are at the forefront of AI innovation because of the need to interact with high volumes of people across multiple media in a cost-effective manner. Automated messages and interactive voice response systems have been commonplace for some time now.
When reaching out to a company online, it is also not uncommon to encounter a bot ‘agent’ asking if you need assistance. It is fair to say that customer response to these automated systems is not always enthusiastic.
However, the same can be said for the response to humans in call centres that are outsourced outside the country the caller is based in. In any case, consumers should feel reassured that although dealing with automated ‘agents’ may become more common, the analytics engines that are powering these interactions are becoming ever more powerful and efficient.
Big Data and AI May Improve Customer Relations
Data analytics tools have also been a feature of contact center solutions for some time. Customers may be doubtful that this is a good thing as big data in the consumer environment often leads to more targeted selling – e.g., advertisements based on one’s browsing/e-commerce history.
The media has depicted a frightening long-term consequence of this trend, i.e., advertisements that will ‘recognise’ and target people individually. Such an outcome is possible, but it is likely that regulation and consumer backlash will limit the most aggressive forms of smart, analytics-powered advertising.
When it comes to the contact centre, consumers have a reason to be reassured when it comes to the use of analytics as one of the most common deployments of analytics tools is for monitoring human agent performance.
The goal is to ensure that customer complaints/queries/needs are dealt with in an efficient manner, although the negative side of this can be that agents are pressured not to spend too long with any one customer.
Similarly, while analytics-driven customer insight may in part be a way to improve sales, it is also a method for ensuring that the person (or the bot) dealing with a customer has the required information to help the customer. In the age of social media, poor customer experiences spread like wild fire – and companies know this.
What About Data Security and Privacy?
Key concerns when it comes to data analytics are about ownership and security of the data collected and analysed, and the customer’s right to privacy. This is often a game of cat and mouse between security experts and hackers, government regulators, and those collecting data.
In Europe, the new General Data Protection Regulation (GDPR), due to be enforced as of May 18, 2018, is part of the move to allow consumers more control over their personal data. The need to comply with the European Union’s new data security/ownership laws may make it harder for providers to utilise analytics solutions.
Certainly, it is making them warier about which information they seek to distil from customer/user behaviour. Those worried about how their data is used should also be aware that under GDPR they have the right to be ‘forgotten’, and that collection of their data will have to happen on an opt-in basis where clear consent is given. No regulation can be perfect, but the rise of the big data machines is not being ignored by governments.