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Before discussing the Chatbot challenges, let's start with understanding what are chatbots and what could be the potential chatbot challenges while making one for yourself. We must have heard of and even used Chatbots in recent times. But for those who don’t know what Chatbots are, here’s a little insight. Basically, Chatbots are short for “Chat Robots.” It’s a computer program that simulates human conversation with a user in natural language, through artificial intelligence. So what could be the challenges in building a chatbot?
Chatbots are widely used by different industries today, from banking to business, healthcare to agriculture, and education to airlines. Its primary purpose is in the marketing aspect and providing quick and automated solutions to customer inquiries. The concept seems to be very beneficial, reducing time and resource consumption, but is making a chatbot just as simple as it seems to be?
Programming these bots is complex and needs tech teams to work on updating them constantly. It requires a collective effort of both, human knowledge and artificial intelligence such as NLP, NLU, machine learning, deep learning and etc. Let’s discuss some of the challenges that come with processing a chatbot and look into different strategies to overcome them the right way.
Challenge 1: “Bot-speak” and cold exchange
As we know, we’re conversing with software fuelled by artificial intelligence, which brings forth a sense of loss of human touch in the conversations. The interactions could come off as cold and robotic, lacking personality and conversational flow. It could deliver the customer a clunky and even frustrating experience, resulting in less user attention where the customer loses interest midway through an interaction. Hence, your Chatbot's personality is vital.
To overcome such chatbot challenges, the developers must look at different strategies before coding their context. A few measures to add a human touch to your Chatbots could be -
Challenge 2: Developing chatbots can be costly
Even though Chatbots can be cost-cutting in their operation and labor, developing it could be costly as it requires a high level of coding.
We use all platforms like websites, apps, etc. Now, if you want to implement different types of chatbots in all those platforms, it will require even more coding, which adds to the cost.
Instead of investing large amounts of time and money, just use a low to a no-code platform like Engati to build AI-powered chatbots that can be deployed over WhatsApp, Messenger, your website, and 10+ other channels.
Challenge 3: Appropriate use of NLP and Machine Learning
First, let’s start by understanding what NLP means and does in a chatbot. NLP stands for Natural Language Processing, an AI technology that interprets, recognizes, and understands user requests in free language.
Sometimes it happens that certain chatbots have fixed NLP selection, which might not have all the requirements that you look for. In order to overcome such chatbot challenges, while you plan to leverage machine learning to create your NLP, you must decide upon the model prior to building the chatbot. It is essential to weigh all sorts of models, ranging from generative to retrieval-based models in order to create the intelligent chatbot that you require.
Challenge 4: Making data secure
Usually, all your web data is secure, but adding certain chatbots to it, you can’t be certain that the API will be secure or not.
Data leak and hacking are prone to happen if proper security measures are not taken up. Each enterprise has to focus on encrypting its channels so that no data is leaked through its mediums; Especially when dealing with sensitive data.
While encryption can play a safe role in protecting your data, you can also take up the following measures to further secure your company data. They are:
Challenge 5: Chatbot testing
This makes the whole process of independently developing chatbots even more complex. Chatbots are continuously evolving due to up-gradation in their Natural Language means. Hence, it's necessary for you to keep testing your Chatbot to check for its accuracy and legibility. Purchasing chatbots from vendors reduces this additional responsibility, thus saving your time, labor, and energy.
Challenge 6: Viability of data
Cluttering your Chatbot with excessive data or even inflicting technologically advanced systems will yield no results if your chatbot does not capture the USP for your enterprise. It is not only necessary for your Bot to be enriched with relevant data but also to equip the capability of reaching out to your target audience through brand identity and awareness. To overcome this, you could follow up on the questions below to keep regular check-ins:
Chatbots are a gift from AI to the customer service function of businesses.
- Medium article on chatbot adoption.
It definitely is a great idea to involve chatbots in your digital marketing, yielding efficient results in less amount of time. But creating one that meets all the expectations of your organization can be pretty challenging. Measure and implement effective and well-planned strategies before presenting your audience with your Chatbot.
The Engati chatbot is the ultimate solution to all your worries