Who is the first person you think of when you are in trouble? Probably a friend or a family member. So, when it comes to seeking business solutions whom would you want to trust – An executive who is taught to learn a script and follow it no matter what, or a conversational chatbot that is trained, and not programmed, to become your friend and help you out? In this article, we are talking about a training a conversational e-commerce chatbot that is robust, cognitive & a quick digital solution for customers.
The first chatbot was built at MIT in 1966 and it certainly has a rich history. But, over the last 10 years the chatbot technology has increasingly become visible to organisations as well as customers.
Today, over 2,000,000,000 (2 billion) people are using messaging apps.
- 37% of the world’s population is using messaging apps & the use is growing faster than social networks.
- 40 million people own a smart speaker and by the end of 2019, 2.5 billion people are expected to walk around with a smartphone.
Therefore, if you are planning to build an e-commerce chatbot, you know which path to follow. Also, it’s not a shocker that most people find AI pretty much hard to understand as of now. However, it is only advancing in its time and in the future it will become more responsive and interactive, and therefore easy to use.
Imagine how convenient it would be to prepare for a party with a chatbot or a virtual assistant, specially when you are alone. As per your previous shopping history, the chatbot will provide you with suitable recommendations.
“Black suits you the best”
“You should buy this jacket, it will look good on you”
“You look really pretty in that dress”
“This week’s top recommendations for you”
Simple. Personalised. Sorted.
Chatbot automation is key in e-commerce
A chatbot is like a digital colleague that can deliver more business value than any other average human assistant. It will take on repetitive, mundane tasks by combining an intuitive UI with robotic process automation (RPA), which is the new-age rage in town. Look at the rate at which the chatbot market is growing for e-commerce.
For example: An IPsoft client automated the off-boarding process for roughly 200 workers each month. This eliminated the need to make more than 2,400 individual requests. Further, the mean time to resolution was brought down by 81%. Chatbot interactions have improved dramatically over the last 12 months.
With the abundance of human knowledge recorded in writing, and more and more of it being digitized every second, there is immense value in integrating this knowledge with systems that go by automation.
Reordering a product that’s almost over, sharing feedback for a product that you really like, all of it must be consumed under the power of automation. Developers must keep closer tabs on the consumer relationship with a chatbot. Companies are making increased investments in deep learning technology and they have to tackle every obstacle that comes in the way of consumer acceptance.
An article published on towardsdatascience.com talks about building a chatbot called ‘Robo’ capable of checking in on people’s mood and taking the necessary actions to cheer them up. It will also be deployed to Slack and will be a fully functional Slackbot capable of listening and responding to requests.
Training chatbots to be conversational
Chatbots have to be conversational, they have no other choice. Otherwise, they will fail.
Colleagues learn from each other. You get better by using the knowledge of your colleagues. You get better by sharing with them what you know. The same rule applies to chatbots, which are basically our digital colleagues. Humans and chatbots interact on a regular basis. Chatbots provide information while humans correct them in case there is any error.
It’s like doing some random search on Google such as-
How many languages are there in the world?
What is the purpose of life?
Does God exist?
What am I doing here?
And Google algorithms are trained to entertain your random request. Otherwise, people will go to some other platform and do random searches. Especially in today’s age of information explosion, when new knowledge is generated in excess every day, it is crucial for machines to read large amounts of text and answer questions for us. It is one of the many practical tasks in the field of NLU (Natural Language Understanding).
You want to drive sales and you also want your customers to be happy, what other way is better than having a conversation with them? GenZ and the latter part of GenY are anyway used to on-demand services, like Uber, Zomato, etc.
Conversational commerce is powerful not only because it makes the automated interactions more human, but because it reduces the number of steps the customer has to take to get to a desirable result. Easier the approach, better the consumer traction.
- Want feedback? Share just one email with CTA asking for feedback
- Need a platform to collect complaints? Create a web page that only talks about the easy of sharing complaints
- Capture in-depth customer behaviour? Launch a push notification that contains a survey with to-the-point relevant questions
In-depth analysis of an available dataset
As per a survey conducted by ai.stanford.edu,
- Nearly 27.2% of the questions require pragmatic reasoning such as common sense and presupposition.
- Only 29.8% of the questions can be answered with simple lexical matching, which is directly mapping words in the question to the passage.
- 30.5% of the questions do not rely on coreference with the conversational history and are answerable on their own.
- For the rest, 49.7% of the questions contain explicit coreference markers.
- And the remaining 19.8% of questions refer to an entity or event.
More specifically, while more than 80% of the higher-ranking paragraphs can be found in the Top 10 IR results, only less than 30% of the lower-ranking ones can be found in the same range. This is with 25% of the questions being comparison questions, where the names of both entities are specified in the question itself. That’s where chatbot training for e-commerce comes in the picture.
Benefits of implementing conversational chatbot by an e-commerce store
- It enables a 2-way communication with the customer. It doesn’t just tell them things or guides them, but also learns from them, hears their questions, and builds a relationship.
- The conversational bot interacts with 2 to 5 times more customers than previously possible over email.
- Stores using conversational commerce, in the right way, are increasing annual revenue by 7 to 25%.
These stats are amazing, and they are only the beginning. The future of conversational commerce is very bright.
E-commerce chatbot popularity among millennials
As per LivePerson April Survey 2017, 67% candidates suggested that they would reach out to a chatbot for customer support. This was the highest and most popular selection amongst purchasing, productivity, fun & others. In fact, millennials are the most accepting generation when it comes to interacting with a chatbot. Hence, training becomes more important than ever.
Credence Research recently predicted that enterprises would transmit 2 trillion messages a year by 2017 to create a market worth $78m by 2022. Facebook reports that there are over 10,000 developers on their platform who are developing chatbots. Slack, world’s fastest growing business tool is supposedly investing $80 million in slack-bot startups. This is majorly because chatbots allow customers the flexibility to use an app without actually installing it on their phone.
From the smallest to the largest enterprise, they are all vouching on chatbot technology.
Chatbots are going to get a lot smarter with more training. They will run millions of algorithms in real time and with analytics, will devise a strategy to convert every prospect individually. The world that we live in today is polarised and sensitive. Therefore, it will take considerable trial and error before AI chatbots master the art of polite conversation.
15 key metrics when determining the effectiveness of e-commerce chatbots
According to Applied AI’s report, apart from training an e-commerce business must tend to the-
- Total number of users
- Number of active users
- Percentage of engaged users
- Total new users
- Messages that start a conversation
- Frequent bot messages
- Messages received by the bot
- Missed messages
- Total conversations
- New conversations
- Rate of retention
- Goal completion rates
- Number of times the interactions failed
- User satisfaction with the chatbot
- Virality of the chatbot conversation
Conclusion of chatbot training
Chatbots provide instant support and are a highly efficient tool to provide instant customer assistance. Therefore, it is really important to invest in their training and make them more interactive and conversational.
Indeed, it is not easy to add a human element to a technical chatbot but the practice is still ongoing. If you want your e-commerce chatbot to add more value to your business by bringing in more conversions, then keep up the hustle. Keep up the training!