Hot Trends in Chats: Interesting Disruptions Ahead!

Introduction

Chat as a channel is superhot these days and started to explode in terms of its capabilities to entice millennials and Z Gen. Chats personify the brand experiences, enhance e-commerce, and are preferred by digital native apps and users. The chat here includes messengers, webchats, business-purposed chat apps like Apple Business Chat, and specialized chat apps such as WhatsApp and WeChat.

42% of people on the planet have a smartphone and 87% of smartphone owners use messaging apps. Facebook is eyeing to merge the backends of Messenger, WhatsApp, and Instagram to create a proprietary messaging environment with nearly 4 billion users.

Billions of people and their trillions of chat conversations happening each day all around the world will eventually be mined for insights (except a few secured apps). Chats will be further expanded as a strong channel due to its inherent concurrency and relatively easy and effective self-service configurations. Here is an attempt to discuss some of those trends and phenomena that drive the emerging dimensions of conversations. 

Conversation Commerce - cCommerce

This term was coined by Uber's Chris Messina in 2015. It encompasses chats, text analytics, speech analytics, speech recognition, voice biometrics, NLP, NLU, and so on. On the whole, the text-centric analytics approach for better customer understanding by connecting the data dots and targeted selling. Interestingly, smart speakers and voice assistants are crucial parts of such a conversational revolution with speech to text and vice versa.

cCommerce drives eCommerce and digital native apps put forth chat as the first option for anything to be heard from or told to the users. Conversation Commerce is been there for the past 5 years yet holds good considering the traction that eCommerce and ultra-personalization are getting these days. B2C brands are swiftly adopting cCommerce, aptly so. Also, conversations have the highest CSAT score among the other channels, perfectly optimized model for the users and companies.

Payment via Chat Apps and Chat via Payment App

Chat products (like WhatsApp and WeChat) forayed into payment tools on the one side and digital wallets (like GPay) bring in chat as functionality in their payment systems on the other side. WhatsApp Pay in India is waiting for supreme court clearance to launch its service (still a sub judice matter). On a lighter note, there is a joke floating around that employees use GPay chat to socialize among themselves and stay under the radar of their manager who is tracking them in WhatsApp and Skype in these WFH days.

Apple Business Chat has Apple Pay built-in, and Facebook is working on WhatsApp Pay, Facebook Pay and, the most debatable, Libra—its proprietary cryptocurrency. Buying a stuff is a critical step of the conversational customer journey, and it’s about to get more seamless.

As a matter of fact, in-chat payments will power conversation commerce big time.

Chatbots and QR Codes to Sabotage the Exploding Mobile Apps

There are 2.8 million apps in Google Play Store and 2.2 million apps are in App Store. Not all of them are there to solve user problems and most of them solve their respective companies’ problems. We are nauseatingly fed with mobile apps. Side effects such data breaches and theft are severe threats to our physical wealth and mental health. There are some developments of antidotes to reduce nausea:

•  A website with the capability to work on a mobile browser and with a chatbot - chatbots are simpler, cheaper, and smarter than mobile apps in most of the cases
• QR Codes in places such as theaters, malls, and stadia can be used when needed basic (QR code is an old-fashioned technology, remember fashion often resurrects and repeats). Orders can be placed and delivered with “social distancing” without requiring mobile apps.
• Smaller apps will be consolidated into social media, specialized chat platform, or mobile wallet apps. One interface will provide all lifestyle needs in a synergized manner. Similar to restaurants merged onto food delivery apps instead of having own delivery systems. Everybody wants to be in everything and used by everyone! Bots will be super busy in these environments.

This is not to demean the mobile apps but there has to be a strong business case and just-for-the-sake-of-it mobile apps are a headache for both user and maker. Whatever product updates on the website have to be reflected in mobile apps and whenever OS upgrades, specific debugging for specific brands and screen sizes is difficult.

A major retailer or publisher who needs constant connect to sell or deliver is an ideal fit for mobile apps. Whether we like it or not, these changes will pretty much happen.

Uni-Channel “U” Turn?

Interesting dynamics in the world of digital and eCommerce leading to the emergence of chat as the primary touchpoint. Z generation and millennials guys are comfortable with chats than voice, and companies can have one agent handle four chats, unlike voice where one agent is occupied in one voice call (concurrency). Digital native apps such as OLA and Zomato have almost have only chat unless if there is any serious issue, they do not let us reach out to the voice agents. Nowadays, naturally, we tend to text someone before or instead of calling a person or a company.

A uni-channel approach suggests that you find which channels perform most proficiently for you and then invest in going deeper on those channels. It is expected that chat will mostly like be the candidate that will front end all the channels. This does not necessarily mean to sunset the rest of the channels, each has its own users based on age, preference, demographics, and so on.

Pre-emptive Approach – DIY (Do It Yourself, Dude!)

This is a familiar area for most of us. Let us discuss some possible approaches, ticket/issue analysis is comparable to a blood test for humans when they are ill. Whatever may be the health issue, it reflects on the basic blood analysis as a first step. Analyzing the tickets from the reports pulled from ticketing tools and call logs will give the pointers of the pain points. Further grouping and number crunching will reveal the candidates for all sorts of automation, such as RPA (agent-centric), self-service (via IVR, chatbots, etc.), and IPA (approving a complex credit card or claim or suggesting alternative surgery or treatment, of course, the final decision rests with doctor).

Over a period, CX, CRM, and ITSM players develop their own benchmarks and golden standards of such data and update them continuously with the influx of internal data in a permissible and anonymized manner. Some of them share these benchmarks (like Zendesk) and some have it in a secret vault. These are the key metrics that influence their decisions on the functionality roadmap. 

Reality Check on the Adoption

Meta-analysis is a statistical methodology used predominantly in epidemiology to aggregate results in the form of data from various clinical trials and studies to get more statistical power and derive corroborating conclusions.

The above image has similar data collected from different studies, if we look at the trust percentage of chatbot it is 20% and another discrete survey shows 80% of sales decline if the user knows there is a bot at the other end. This data must be very close to reality.

83% of users are ready to use chat if the real-time response is promised and 87% of companies want to educate the users on the digital channels, both these are from different survey studies. Thus, both are parties are pretty much interested in engaging via chat and there is some gap that has to be filled in terms of effective FAQs and other DIY manuals and visual materials. Naturally, such data can be interpreted in many different meaningful ways by different people.

This is just superficial, meta-analysis has statistical research methodologies along with hypotheses that can be emulated in such studies.

Final Thoughts

Outwardly it looks initial euphoria of bots is subsided and it will remain static. But that is not true just like any other AI endeavors, noisy datasets, expensive human resources, technical and functional debts, and so on, cause failures. Emerging trends such as relying on proved AI-SaaS solutions and using own (of course anonymized) and realistic data sets will lead to eventual success.

Chat has already surpassed email and marching towards catching up with voice and go beyond in the near future. Users want answers in real-time and less invasive manner due to the increased level of demand for instant gratification. Chat (including messengers) and apps (both mobile and apps) have become inextricably entwined. Innovations around chats will weigh more, Fear of Missing Out (FOMO) is gripping us to not to miss this ‘futuristic chat” boat. We can always transform the fear into fuel and fast forward the growth.

Disclaimer: The views and opinions expressed in this article are the personal views of the author and do not in any way represent the views and opinions of any organization.