Everyone who has ever produced something for people has had chances to get his head spinning around this question. How can I draw their attraction? What can I make to catch up with their current interests?
There’s nothing special in asking those questions as long as you’re trying to make better service. The only thing is that formula can be universal but implementation should be very individual for your case.
Nowadays the excessiveness of widely available tools for creating everything in a very aesthetic and user-friendly way drives to the dangerous similarity of what surrounds you in online space.
(To explore more on the topic of the place of beauty in technology, check this article) That’s why personalization issue becomes more relevant and even acute. Finally, authentical becomes everything that has at least something standing out from the crowd.
In the minds of thousands of specialists personalized way of interaction with customer becomes almost a key to drawing attention.
In fact, those from entrepreneurship and marketing concerned with the reaction of users always have the feeling (and not even once) that there should be a key to the customer loyalty and client retention somewhere around. Once they realize what it is, they face the same personalization issue.
There’s a lot of services that you can leverage for improving your customer service. However, you may not be interested in the scope of existing opportunities but in the one that can make you exclusive.
It exists! It’s a conversational interface, virtual assistant, or chatbot. The best thing about it is that you can make it the very special thing for the special needs of your company.
Later on, in this article, we will try to find the answer to the question of how to increase client retention with the help of the chatbots and why they should help.
How to get ready to increase customer loyalty with chatbot
The goal of increasing customer loyalty is a way more serious thing than you may expect. If you decide to take up this task and set up the aim of improving the interactions with customers you need to be ready to revolution. Things don’t change without triggers. And if triggers are insufficient they also don’t make any difference.
The conversational interface is a very powerful tool that you need to take into consideration right now (if you haven’t before). When you have clear purpose and plan of leveraging it, you will figure out all its usefulness on the evaluation of the results (they won’t disappoint).
However, for many people, it still remains difficult to grasp that at the first instance users would interact with not a real person actually. They would ask something and get some answers. What if something goes wrong?
This is the first rule: There is always something that goes wrong. It happens more often with humans than with the programs. So relax. You are going to test it.
You have to get used to the idea that computer program can be much more efficient than a human assistant. So for the sake of common sense, learn how to distribute the tasks.
The smart combination of human and computer power is one of the premises for success in modern times. The earlier you grasp the idea – the sooner you’re going to benefit from it.
There’s a bunch of services that combine chatbots (on the first line) with the human workforce on the background. Sometimes it’s the best solution. Especially it’s relevant when it comes to the complicated tasks that chatbots are not capable of performing yet or when there’s a high risk of error.
At the same time, you can come across a lot of services that use chatbots as the only customer service assistant. It doesn’t mean that you can’t contact any human being from the company (such cases also exist but it’s a bad example) but it’s supposed that chatbot is capable of assisting you with the majority of the tasks.
This is where next rule arises: Be aware of what chatbot is capable of and balance its use. Don’t overestimate chatbot capabilities but also try to distribute all the automation work to it.
Remember that chatbots can be different. They can be very complicated systems. There can be huge companies that work on their development. But also it can be a one-person project that doesn’t imply AI breakthroughs and overstuffed structures.
To make it right (or to get right people to make it so) you need to know what exactly you need and what you can demand along with the price you’re ready to pay.
It’s a huge confusion spreading around that building bot is something very simple and accessible for almost everyone. Of course, if we talk about plain pre-programmed bot conversation flow that would abrupt after few pairs of questions and answers, then you can get it done even by a beginner in programming.
However, what you want is definitely more complicated stuff that requires databases of information, bot ability to store and retrieve data, options to teach bot and improve it as new inputs arrive.
You would need your bot to understand human language and recognize visual information. To make it all work exceptionally as you want to, you would need a knowledgeable specialist.
One more rule from me: Understand what you really want from the chatbot and be ready to pay for it as much as it really costs. You can compromise on your needs but don’t compromise on the quality.
Chatbots are becoming an essential part of modern commerce. Here and there you can face different retail bots that are deployed for marketing purposes.
They have served the basis for conversational commerce that is rapidly developing now. Indeed, chatbots can appear the great time- and money-savers in every case as long as it meets an overall strategy.
(In case if you are asking yourself what conversational commerce is, check the topic here.)
The key premises of leveraging chatbot for your business
1. Understanding human language
This is a broad field that can involve natural language processing (NLP), natural language generation (NLG), speech recognition, and machine learning. The more complicated virtual agent is supposed to be – the more it needs to get built-in.
However, this issue is usually sold by plotting requirements and looking for the most efficient way to meet them while building the structure.
Definitely, you would want chatbot to understand more of people talks than only what you have once fed it. Imagine that while building chatbot you decided on certain possible bot conversation scenarios with the customers.
But you can’t know for sure how they are going to be articulated. While talking we usually change the places of the words, use short and informal forms. All that can make pre-programmed dialogues useless. This is where the need for NLP arises.
With NLP and NLG you can teach the chatbot to correctly relate the words and generate textual output from existing data. (Look at the example of simple application of NLP by using Microsoft LUIS).
Also, you may want to develop your chatbot to the point where it would be able to understand not only text but speech also. First, it’s way easier to communicate by means of voice. Second, it would make possible communication with your service for people with the bad eyesight.
To make your chatbot understand voice inputs and translate them into the language understandable by the machines you would need to use speech recognition. NLP and speech recognition is getting more popular and spreading across the enterprises and fields of application.
The reason is that language understanding is the basis for conversational commerce.
2. Retrieving and storing data
I’m convinced that when you’ve once chatted with someone and next time he completely forgets about it and starts chatting from a scratch, you would get irritated and, perhaps, want to never talk to him again. This is logical.
We put the part of ourselves into our interactions with the world. But this happens with chatbots that are not programmed to properly retrieve and store the data about a bot conversation.
In fact, to make interactions more human-like every chatbot system should rely on the database. But most often it’s not enough. If you think that you can teach the chatbot once and then it would work perfectly, you’re wrong.
The best way is to periodically teach chatbot with acquired inputs. It’s the best way to make conversations natural.
3.Reading visual inputs
Nowadays we are coming to expect more and more complicated abilities from the chatbots. It makes sense as the speed and intensity of the research and development are only growing. So you may not want to measure your chatbot abilities by the language and speech understanding only. Instead, you would want to extend functionality closer to what humans are capable of.
Consequently, next goes image recognition.
Image recognition isn’t already something new. Moreover, it’s one of the most widespread practices among AI-related fields. Thanks to the numerous services that are free of charge and open-source research projects image recognition has become relatively easy in implementation.
The first three items that we have discussed so far are definitely not the easiest in implementation but if you need a smart virtual assistant that can really take up to 80% of work and help you to increase customer loyalty, then those three are a must. However, you can go further and try more advanced stuff that isn’t yet in a wide practice.
One of the first things that come to the mind is deep learning. It’s a field in machine learning that implies building multilayer artificial neural net. Deep learning is very helpful when you have a lot of unstructured data and you want to find patterns.
In turn, the latter could help you to teach the system in a more efficient way and, therefore, vastly improve the performance.
Another interesting field is reinforcement learning. You may have heard of how computer programs have recently beaten human champions in Go (earlier – in chess and other intellectual games). And you definitely know about self-driving cars that are predicted to become an absolute majority and change a lot in the nearest ten years.
All that has become possible with the deep reinforcement learning.
Reinforcement learning itself makes possible for the program to learn from the feedbacks it receives from the environment (inputs). When you combine deep learning and reinforcement learning techniques you get the self-learning system that can continually improve its interactions with the environment.
This kind of systems is very complicated and requires true specialists of the field.
Nowadays, the increase of customer loyalty and client retention can be approached in a hundred different ways. All the technological advancements are here for you. But this is not something that can be done with a few efforts from your side. No, it should be purposeful and structured.
If you want to improve customer service take a long look at virtual assistants (chatbots) and explore how complicated and smart they can be. However, don’t underestimate the complexity of the system that would have to be placed behind. Therefore, don’t compromise on the quality of work that is needed to be done.
The world of conversational interfaces is rapidly expanding and changing modern commerce. Consider it when building or improving your business strategy as its audience is growing.
Consequently, the relevance for the businesses is going to become nearly absolute in the observable future. You won’t gain such results in any other possible way.