5 of the Biggest Challenges Making Chatbots to Work For Your Business

Among the main pain points for consumers when interacting with any business two
prominent complaints are not being able to get a response. For those who get one, many
report not getting satisfactory answers to their questions. At least 31% of consumers have
reported this problem. Another 28% experienced difficulties finding the essential (but
simple) details about a business like the hours of operation and contact details.

All businesses value customer relationships and these issues are major factors that stress
that bond. That apart, in the digital age does this impact an online business? Unfortunately,
the truth is this impacts the customer experience in many ways including higher bounce
rates from websites or users abandoning shopping carts when shopping.

Chatbots are being seen as an excellent tool for online businesses that want to bridge this
gap and enhance the user experience. Based on the concept of Artificial Intelligence (AI), a
chatbot can engage in natural conversations with users just like any other human being and
answer their questions.

Several businesses are already using chatbots to simplify and elevate the interaction
between consumers and computers. The global chatbot market is expected to grow
exponentially by 2023 and beyond.

Having said that, businesses face more than one challenge in implementing chatbots. Read
on to understand some of the biggest challenges in making chatbots work.

1) Gaps in understanding user intent

Over 60% of consumers now prefer to communicate with brands using chatbots. Chatbots
are now being deployed to enhance the customer experience. The challenge that comes
with this is that of interpreting customer interactions and responding accordingly.
Online users have different ways of conveying a message – through a short sentence, or a
long explanation, or maybe even an emoticon. For example, a message like “Why do I see
this weird transaction on my credit card?” does not fully convey user intent. Are they
disputing the transaction, or do they need more information? How can the chatbot
understand the intent and convey a proper response?

Chatbots have to be much more nuanced in their understanding of such interactions. This
calls for greater contextual understanding. They need smarter algorithms that can decode
the hidden meaning in users’ messages and compare them with possible variants before
responding.

2) Privacy and security issues

Privacy awareness is one of the most significant challenges that can pose challenges to
making chatbots work. A Cisco Consumer Privacy Survey revealed that 84% of respondents
care about privacy and their data and want to exercise control over how their data is being
used online. With so many data breaches and security issues in the recent past, it has
become imperative for online businesses to assure their customers of data privacy.
Chatbots have acquired a sort of reputation that they could be prone to hacking. Obviously,
if hackers get access to users’ sensitive data, it can be easily misused and damage your
company’s reputation. Among the known cases is that of Delta Airlines – where hackers
were able to modify the chatbot’s source code and retrieve the credit card information of
the airline’s customers.

3) Limitations with Natural Language Processing

In simple terms, Natural Language Processing (or NLP) enables machines to understand
human language. Spoken language is complex – with a mix of synonyms and local
languages.
Despite the advancement in Artificial Intelligence (AI) technology, NLP is still in an evolving
form as it tries to incorporate the ever-changing human language. Improper
implementation of NLP in chatbots can also result in miscommunication with users. For
instance, in response to the client query about how to register as a user, the chatbot could
provide an accurate step-by-step response, but which is practically useless for the user.
As a plausible solution, Advanced AI models have made it possible to translate a language,
summarize text, and even analyze sentiments. There’s a long way to go but solutions like
IBM Watson are showing the way forward.

4) Understanding the emotions and sentiments of users

There is no denying the fact that conversational AI platforms have evolved a lot from their
earlier days. From just typing messages, voice bots can now recognize human emotions and
sentiments. That said, misinterpretation of language tones and sentiments can have
negative consequences for your business.

How effectively can your chatbot identify consumer emotions from their voices and
messages and respond accordingly? Here are some points to consider:
– How to determine the current mood of the consumer?
– How soon do they want a remedy for their problem?
– Is it the right time to recommend a new product or service?

5)Lack of context

Among the key challenges, chatbots can be more effective when they can provide
meaningful responses after understanding the context of customer conversations. The
challenge for chatbot developers is to build their memory – to remember previous
conversations and provide personalized responses.
Among the latest developments, Contextual chatbots can analyze the entire flow of
interacting with consumers and figure out the overall context. For instance, when a
consumer is making a random statement about pizzas (as an example) – or is ordering the
pizza. Similarly, chatbots can self-train to learn from the user’s online journey and recent
actions.

Conclusion

Many of the challenges outlined in this article can be addressed using advanced NLP
capabilities and sophisticated models. That’s why IBM Watson is the right tool that can
answer questions put forward in natural language within fractions of a second. It can also
analyze human speech and help chatbots make meaningful conversations. Unlock the
power of data and AI and resolve chatbot challenges with the technical expertise of
Veracitiz. Contact us today with your queries.