‘Very often data is rich but the insights are poor‘
By N Jayalakshmi | May 15, 2023
Malcolm Koh, Director of CX Practice at Zendesk, the global CRM company, tells Retail4Growth why AI tools like ChatGPT will drive up the experiential quotient in retail, provided retail brands can leverage them well.
Being part of a global service-first CRM company like Zendesk, how exactly do you see AI tools like ChatGPT helping retailers in their business?
In retail, it all boils down to understanding customers - improving engagement and reducing stress points. So the better you are with your customers, the better the loyalty, and the stickiness. This is where AI tools help, especially in areas like returns processes or other points in the customer journey that can get stressful. These are opportunities where we can engage better with AI capability, which essentially helps in understanding the context of the customer and their buying behaviours and thus help in lowering friction.
What are some of the specific pain points that retailers face, which AI tools can help address?
As I was mentioning earlier, the return process is one area that can get very challenging, because this is also one area that customers tend to be quite sensitive about. This can be better managed with a shift in the engagement by leveraging AI, through better understanding of the customer and the incidents. AI also enables segmentation of customers, based on which the engagement can be tweaked and automated. Essentially AI capabilities allow you to engage with the customer intuitively, like the predictions on Google or on your Apple watch and thus help create more value for the customer. Obviously, as we get further into AI, it will get more complex. But right now, these are some real life examples of AI application in retail/customer engagement.
But how do AI tools work for brick and mortar retailers?
End of the day, it’s all about understanding the customer and being more efficient in the engagement process, whether it’s offline or online retail. AI tools particularly help when there's an online - offline model. When sales agents are face to face with the customer, they have an intuitive understanding of the customer and there is a lot of EQ involved. This can be augmented better with AI capabilities. For example, using AI they can do better profiling of the customer, as opposed to doing it on the fly when the customer walks in. So retail staff can use AI capability to understand the customer’s order history, their preferences, etc., and accordingly engage with them. Now that we have the ability to run massive amounts of data and do predictions based on them, we can get smarter in the way we do personalization and customization and improve the relationship with the customer, whether it be online or offline.
Is there a specific process or a checklist by which retail brands can get the best from AI tools like Chat GPT?
It all depends on the kind of personalisation that they are looking at and understanding the application. A lot of the time, data is rich but the insights are poor. So, while we have lot of information on the customer and the customer expects us to create value for them, we often don't do that. This is because we look at personalisation in a segmented manner in terms of age, demographics. We need to filter data correctly and move towards the right kind of personalisation, though that’s easier said than done. But to come back to the question, retail brands can get the best from AI tools by a better understanding of the customer journey and by applying some of the tested theories. End of the day tools like ChatGPT are still relatively generic and not gone down to specific use cases. We are still in the stage where we are testing out the model. So we still need to create the parameters that we want in terms of customer engagement using these tools.
I suppose the adoption of these tools has also got a lot to do with a retail organization’s tech culture and adaptability to change?
Yes of course. I think there is some amount of fear that AI tools will replace humans, but we have found the opposite to be true - they will actually augment and level up human productivity. If you look at the evolution of humans, we tend to step up and handle more complex areas every time we have the opportunity to leverage anything new. A classic example is that of bank ATMs. Instead of replacing bank tellers, as it was feared, ATMs enabled them to go beyond tasks like dispensing money and focus on other things like loan applications, wealth management etc. It’s the same with any other customer facing industry like retail. AI tools can perform simple tasks more efficiently, leaving humans free to perform more complex tasks and deliver better, value added customer engagement.
How do you anticipate the growth of AI in retail moving on?
AI experiences will become more evolved and seamless. We have predictions in terms of the adoption and the outlook looks very positive, with the evolution expected to cross expectations. About 87% of that is in India, much higher than the APAC average, which is 66%. Also 84% of customers in India want bots to provide the same level of experience as humans. So there is a great degree of expectation and perception driver. India is also invested heavily in technology, and this reflects in the numbers and in the customers’ expectations of AI.
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