Bml munjal chatbots

Coping with chatbot service failure
Dr. Ana Isabel Canhoto
Brunel University London
September 15th 2020
www.anacanhoto.com ; @canhoto

AI-powered customer service bots
• 2 out of every 3 digital customer interactions
involves a bot
• More than 300,000 active chatbots on
Facebook
• Big adopters: finance, healthcare, education,
travel, and real estate
• And…
© Ana Isabel Canhoto, 2020

AI-powered customer service bots
• Public sector…

Definition
A computer program that automates certain
tasks, typically by chatting with a user through a
conversational interface.
The most advanced are powered by AI.
Understands complex requests, personalizes
responses, and improves interactions over time.

A (very brief) history of (chat)bots
For more: https://futurism.com/images/the-history-of-chatbots-infographic

A (very brief) history of (chat)bots

The promise
• Cost savings
• Customer insight
• Better customer experience

The reality

Research gap
• How do customers perceive failures in chatbot-
enabled customer service?
– What is lost?
– What are the perceived causes for those losses?

Research gap
• Experiences of interacting with customer
service (chat)bots
• Understanding the “usage climates” of a
technology is essential for its future
development and expansion (Wang, Yuan, Turel & Tu, 2015)
• Negative emotions have a disproportionate
effect on consumers’ evaluation of the
exchange, and their subsequent behaviors
(Demoulin & Willems, 2019)
– Very difficult to recover from (Van Doorn & Hoekstra, 2013)

The study
• Interviews with chatbot users in Malta
– Finance, IT support, Retail
• With Ms Daniela Castillo and Professor
Emanuel Said
• Results:
– https://www.tandfonline.com/doi/full/10.1080/02642069.
2020.1787993

Findings – Expectations
• Customers view chatbots as substitutes for
humans, not self-service technologies.
• They expect high (human-like) service levels.
• Vs. (AI-enabled) chatbot capabilities
Source: Huang and Rust (2018)

Findings – Losses
https://anacanhoto.com/2020/07/06/sources-of-customer-dissatisfaction-in-ai-powered-service-interactions/
Customers are unsure whether they are interacting with a chatbot or a human
customer service assistant.
It is a source of dissatisfaction because the customer feels deceived, and is unsure
about how to approach the interaction, and how much effort is expected.

Findings – Losses
The chatbot struggles to interpret what the customer needs or wants, and progress is
slow.
It is a source of dissatisfaction because the customer feels that they can’t control the
interaction and this generates a number of negative emotions, such as frustration, anger,
agitation or upset.

Findings – Losses
Unlike human customer support assistants, the chatbot lacks empathy.
It is a source of dissatisfaction because the impersonal interaction leaves the customer
feeling undervalued, and detached.

Findings – Losses
The chatbot can only assist with a restricted range of issues and types of queries and, thus,
is deemed as being of limited assistance.
It is a source of dissatisfaction because it is seen as a waste of time, as the customer either
needs to repeat the query in alternative ways to try and get an answer, or needs to try and
get the information elsewhere.

Findings – Losses
There is loss of information during an interaction with the chatbot, or during the handover
to a human customer support assistant.
It is a source of dissatisfaction because it causes frustration, it is seen as a waste of time,
and the lack of traceability and transaction memory causes anxiety.

Findings – Reasons
Problem
Who’s to
blame?
Firm, because: Customer, because:
Functionality Firm, only
Failure to invest in features
valued by customer [care]
—
Affective
Firm,
mostly
Failure to invest; Unsuitable
use of chatbot [care]
Diminished presence of
mind, during emotional
situations [emotional]
Integration
Firm,
mostly
Poor organizational
procedures [incompetence]
Failure to proactively save
information [behaviour]
Cognition Both
Lack of attention during
development of the chatbot
[incompetence]
Failure to use simple
language and check spelling
[cognitive]
Authenticity Both
Deliberate misrepresentation
of chatbot via naming, script
and other features [deceit]
Failure to notice cues – e.g.,
speed of reply [cognitive]
https://anacanhoto.com/2020/07/13/perceived-blame-matters/

Findings - Outcomes
• Avoidance
– Revert to human support
– Refuse to reuse chatbot
• Confrontation
– Terminate service (specially
new customers)
– Switch to competitor
– Engage in negative WOM
(specially Twitter)
• Waste of
resources
• Unhappy
customers
• Lose
customers
• PR crises
• Difficult to
acquire
new
customershttps://anacanhoto.com/2020/07/13/perceived-blame-matters/

Implications
• Tangible losses – e.g., time, information
• Compensation
• Intangible losses – e.g., trust, deception…
• Negative impact on brand’s image
• When measuring the success of a chatbot, look
beyond “cost savings” or “convenience”

Implications
• Recognise the technology’s limitations
https://anacanhoto.com/2019/10/11/the-potential-of-ai-for-customer-facing-applications/

Implications
• Manage customer expectations
• Make clear that customer is being serviced by
chatbot
• Do not anthropomorphise chatbot

Bml munjal chatbots

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