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AI for Customer Service

Categories Customer Services

Essay, Pages 8 (1839 words)

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Essay, Pages 8 (1839 words)

2. LITERATURE REVIEW

The Customer Experience Professionals Association (CXPA) (2018. p. 5) utilized the Oxford word reference in characterizing AI as a begin. It is characterized as “the hypothesis and advancement of PC frameworks ready to perform assignments typically requiring human knowledge, for example, visual observation, discourse acknowledgment, basic leadership, and interpretation between dialects.” In their whitepaper, the CXPA underscored that implanting AI all through the client adventure yields numerous advantages for the association. The beneath figure demonstrates the means over a client purchasing venture (CXPA, 2018):

During the mindfulness arrange, prescient examination (an AI subfield) distinguishes the fascinating perspectives for the client and propose item or administration suggestions.

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In the thought stage, AI can help sites in incorporating huge information, allowing clients the chance to pick up learning and think about related items.
In the acquiring procedure, AI finds out about the interesting purchasing behavior of the client through contemplating information designs and gives proposals in like manner.
In the help stage, AI can likewise think about the clients’ conduct, and track any indications of disappointment to make the suitable move towards the particular client.

Such techniques convey very customized client administration.
Last yet not least, AI figures out how to draw in a two-manner discussion to give the proper client support. The CXPA (2018. p. 11) kept on clarifying the normal difficulties both the association and the client may face dependent on a top to bottom writing survey. For instance, utilizing chatbots can be useful more often than not, yet can likewise build the danger of losing individual associations with clients.

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Jeffs (2018. p. 4) recommends the requirement for AI in the organization by utilizing quantitative information. The investigation of 362 firms found that while 80% of CEO’s accepted they were conveying incredible client experience, just 8% of their clients concurred. This demonstrates there’s a gigantic hole in conveying a better encounter than the client, and one fundamental explanation for this marvel is the trouble to comprehend what clients truly need. This is the place AI should be received. In addition, Jeffs (item advertising chief of Pegasystems) proposes that clients should be available to these new procedures. By reviewing 6000 grown-ups, he reasoned that lone 28% said that they would be “awkward with a business utilizing AI to improve associations,” which shouldn’t stress over the undertakings from the outset. As per Jeffs (2018. p. 6) the organization that is happy to convey unrivaled administrations should utilize AI in handling the issues that have the best effect on client experience. He recommended three instances of such systems: 1) Using chatbots or other computerization advancements to free client holding up time, just as lessen the weight on the representatives. 2) Using client information to foresee which parts of the organization are well on the way to impact the client, and permitting salesmen to concentrate on that angle. 3) Using client information to publicize important advancements dependent on their needs, permitting higher consumer loyalty.

Dahlhoff et al. (2018. p. 6) utilized a case of applying AI in automatons as conveyance strategies. The outcomes were promising to the analysts, as practically 40% of buyers would think about the automaton as a conveyance technique, taking client experience to another level.

Debecker (2016) to demonstrate the requirement for chatbots. “With chatbots, information and AI unite to expand a constantly open arm of your client administration group and use information to tailor the experience,” express the creators. They express that 51% of clients accept that a business ought to be opened to help constantly (every minute of every day). What’s more, by utilizing wise chatbots, organizations have the chance to offer client human-like help 24 h daily, 7 days seven days. Such mechanical techniques will convey more astute encounters to clients.

While a few investigations like IBM (2018), Forbes, and Gartner recommend that “by 2020, 85% of all client connections will be dealt with without a human specialist,” Moore (2018. p. 104) have accentuated that the client administration delegates today will move into errands that bots can’t do. For instance, managing unique clients can be the undertaking of a real human.

Klein et al. (2017. p. 25) played out an investigation on driving retail officials to consider the impact of AI innovation on the change of client commitment. Utilizing quantitative information, the creators recommend that “computer based intelligence fueled client administration is the retailer’s new reality. Shopping isn’t trusting that retailers will get up to speed, they essentially move their reliability to a contender with a predominant encounter.” They utilized Zendesk (2018) to accentuate that 87% of brands need to put more exertion into giving a steady encounter. Despite the fact that AI doesn’t understand each test, yet we discover no lack of the positive effect AI has on conveying predictable client experience.

III.Objectives of the study:

  • To analyze the empirical relationship between AI and customer experience
  • To analyze the empirical influence of AI on customer experience.

Hypothesis of the study

  • There is no empirical relationship between AI and customer experience.
  • There is no empirical influence of AI on customer experience.

IV. Methodology:

In pursuance of the above mentioned objectives and the hypotheses, the following methodology was adopted for conducting the study. The study is an empirical one based on both primary and secondary data.

  • Data Collection: The primary data for the study is collected by using a questionnaire for consumers. The aspects on which the data are sought to be collected from the sample respondents include socio-economic status of the respondents, preferences and satisfaction about attributes, price and promotion for the dairy products in Bhubaneswar. The secondary data has been drawn from various publications and also from personal discussions with the officials in milk dairies, Dairy India etc.
  • Sampling: Customers in Bhubaneswar city has been taken into consideration for the present study. The sample is drawn from the consumers which are spread over in Bhubaneswa city. A total 500 sample respondents have been chosen by using convenience random sampling technique. The sample comprises of 50 respondents from each area.
  • Statistical Tools Used: The primary data have been interpreted with the help of simple statistical tools such as percentages, Chi-square test of significance and F-test are administered.

Authors used correlation test to examine the relationship between AI and customer experience; according to the results, there is a direct and moderate positive relationship between the two variables. Regarding the moderate relationship between the variables, it was expected from the authors’ side, as it was mentioned before the application of AI in the Palestinian enterprises hasn’t significance presence due to the high cost of implementing AI systems.

H0-2: There is no empirical influence of AI on customer experience.

Authors used R-square and ANOVA tests to reveal the results associated with the above hypothesis; from the Table 2 it shows that a significant value of 24.669 for the F-distribution with 1 and 89 df. F-test used as an indicator to assess the significance of the regression, with a P < 0.05; so, the results show that there is a significant relationship exists between AI and customer experience. AI predicts 26.4% of the variance in Customer Experience, as R?=0.264 Whereas the correlation coefficient R=0.514 indicates a moderate positive linear relationship between the variables.

The authors explained the influence of AI on the customer experience two dimensions (personalized customer service, aftersales customer support), the below two tables show the R-square and ANOVA summary statistics.

AI explained 22.9% of the variance in personalized customer services, while Table 4 shows that AI explained only 7% of the variance in after-sales customer support. According to these expected results, it indicates that AI is weakly explained the variance in these two dimensions (personalized customer service and after-sales customer support), these results aligned with the results of the interviews that will be discussed in the next sub-section; enterprises have limited access to apply AI systems and solutions to enhance customer experience especially in the applications of after-sales customer support.

The use of AI to enhance the customer experience requires the high adoption of technology and the suitable information technology infrastructure to deploy these technologies to enrich the customer experience through the usage of these innovated tools and solutions.

5. Conclusion

This investigation expanded our comprehension of what AI truly is, and how it influences the business, client, and the entire society by and large. The point of this investigation was to contemplate the effect of utilizing AI to upgrade the client by and large experience. All through the examination, the client experience was isolated into two separate factors: Customer administration and after-deal support. A few kinds of examinations were utilized on both subjective and quantitative information to quantify the relationship in the best estimations accessible.

In the wake of contrasting the consequences of the investigation executed, the creators see that the examination theories coordinate their outcomes. To start with, the aftereffects of the correlational and relapse investigations demonstrate that there is a constructive connection among AI and client experience and that there is an immediate connection between giving customized client administration and after-deal client backing, and AI. What’s more, by utilizing illustrative examination alongside the investigations referenced before, creators demonstrate that giving customized client administration all through the client’s purchasing voyage greatly affects the client experience. Likewise, utilizing AI in call focuses and other after-deals bolster administrations will diminish the clients’ holding up time, and subsequently improve the clients’ understanding. To wrap things up, the topical investigation of the meetings demonstrates that not all organizations in Palestine can completely embrace the innovation of AI because of staggering expenses and absence of aptitudes in the Palestinian culture.

At last, we presently understand that AI is a quick moving train, and it is creating inside our homes and working spots. It will in the end assume control over each gadget we use and will turn into an unavoidable piece of our lives. We all, including the designers of such innovation, should ensure that we just enable it to comfort people, not supplant them.

6. Impediments AND RECOMMENDATIONS

Despite the fact that the outcomes were fulfilling contrasted with the theory, a few constraints were experienced all through the examination. First and most significant, the information was gathered from a little example in the Palestinian area. Just two organizations for subjective research and 90 Palestinian Internet clients for the quantitative research were accessible. Likewise, the organizations being met are just intending to set up an AI division, implying that the majority of their information depend on speculations and projections.

The creators prescribe endeavors to upgrade the client experience all through the clients purchasing venture particularly the mindfulness organize. Undertakings prompted offering increasingly customized administrations for clients which it impacts their general involvement with a superior comprehension of the administrations and items to accomplish positive informal exchange about the general involvement with this venture. Similarly, it’s profoundly prescribed to utilize AI in call focuses and the other after-deals bolster administrations to shortening the clients holding up time all through the most utilized data innovation instruments accessible in the market.

Cite this essay

AI for Customer Service. (2019, Dec 08). Retrieved from https://studymoose.com/ai-for-customer-service-essay

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