Decoding Customer Experience Post Covid-19 | Peak-End Rule & Return Of The Chatbot
A popular online delivery store has a message right at the top of their website which says this:
Understandable, of course, given the unprecedented need for home deliveries during the extended lockdown and the fact that supply chains have not scaled up, in line with the unmet demand.
What’s hard to comprehend is the fact that this message has been constant, regardless of which customer has logged in for the last few weeks.
No customization for updated inventory.
No customization for customers’ urgency or previous buying patterns (Frequent buyer/one-time buyer and more).
Meanwhile, you might have, like many of us, booked an airline ticket to go somewhere. A summer holiday to an exotic destination, say. Forget the holiday; if you even tried calling the call center, you will get no response. In this case, some airlines have been able to use a blanket message on the website by saying any tickets booked during the period will be automatically routed to a credit-shell account.
Phew.. some answer at least.
Now, wait, did you order medicines online? Another popular online medicine store sends constant messages on SMS: Every message, pushing the delivery date out by a few more days. If you asked for clarity, well, that’s too much to ask for, in most of these cases.
Of course, COVID-19 has also shown us some brilliant innovations and experiences.
Right from the neighborhood grocery shops that stayed open to serve customers with whatever inventory they have, to food delivery apps like Swiggy and Zomato, that took to delivering groceries. From Dunzo trying to deliver anything to your doorstep to applications like Price Club aggregating deliveries at local apartments – the lockdown has shown many examples of companies trying to innovate on their digital delivery models to serve customers better.
And for every order served, there is the promise, delivered or undelivered, of customer experience. Let’s bring an aspect of behavioral science, which explains this in the current context.
The rule says that our memory often does not depend on average positive or negative feelings during an experience but relates to the most extreme point and the end. Daniel Kahneman explains it as remembered utility being more important than actual utility.
When applied to the current context, it means our memories of these times, are being shaped by the intense peaks of our experiences and by their ending. Neither of these are very positive in some of the cases mentioned at the beginning of the article.
So, what’s the solution?
We know customer service representatives are impacted by the lockdown and may not be in a position to answer customer’s queries from whichever location they are in. Many may not even have up-to-date knowledge about the situation.
We know that supply chains are impacted but, we also do know that every such interaction is generating data. Data which can be understood, assessed and modelled into answers based on machine learning.
Yes, precisely what chatbots have been doing since the last few years. Studies, even a couple of years back, said that over 80% of businesses would depend on chatbots for automating their customer queries. A well-defined chatbot, according to Haptik, a company that has been focusing on conversational AI and recently developed a WhatsApp chatbot to help the Government of India raise COVID-19 awareness, believes that over 80% of the queries can be automated.
If chatbots had been used in the scenarios above, some of the commonly repeated queries could have been answered. There could have been customizations built-in based on purchase data and behavior, and more importantly, customers would not have felt under-served.
While chatbots and voice bots have been around for some time now, there were always questions about how accurately they could address questions and how they could support multiple languages and accents. That, to some extent, had stalled their scorching early progress.
Will COVID-19 become a watershed for the conversational AI interfaces across sectors and bring more investment and acceptance? We certainly think so.
Even before the crisis hit, estimates showed the following:
In sectors like retail, Microsoft Voice Report expects 54% of customers to use digital assistants in the next five years.
2019 SalesForce report predicted a 241% growth in conversational interfaces in travel and hospitality by 2020.
The number of digital voice assistants estimated to be in use by 2023 is 8 billion.
Post the summer of 2020, if the current uncertainty persists, these numbers may no longer look like future predictions but a startling reality!