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Businesses need to satisfy their customers’ needs. Since companies are innovating rapidly due to for example Artificial Intelligence, Big Data and Machine Learning, they need to keep up with this innovation to be ahead of competitors. In order to do this they need to know what the customers want. A new concept of crowd-based Requirements Engineering is mentioned in literature where a large group of users are continuously involved in the developing process. This crowd provides user feedback through feedback-channels. The crowd needs to be intrinsically motivated. Data from users is also collected from monitoring systems and provides context and usage data. This can be used to get insights in users’ behavior and what they want.

As mentioned, this concept is new and mainly mentioned in literature. In practice this type of Requirements Engineering is not acknowledged yet. Although it might seem promising, there are some challenges that arise. For example, the users must be able to decide what level of privacy they want. Therefore the monitoring systems must take into account what, where and how data can be collected. Besides, analyzing this data and gaining insights out of them is a lot of work. Automated data mining techniques can be used, but they need to be accurate. Another challenge is highly involving users into the developing process. Once users can give their input, they start to have expectations. These expectation need to be lived up to, otherwise users will feel like their participation was pointless and they will get disappointed. As last, motivating the users to give feedback is a challenge. Each user needs a different approach to get motivated, because you want them to be genuinely interested in helping the products’ success. But motivating the users can quickly affect the feedbacks’ usefulness and truthfulness. Therefore it is not quite clear whether investing your time and money into crowd-based Requirements Engineering is worth it in the end. Feedback can also be collected through a simple feature that asks the users for a rating or comment on an application. But is that enough to get insights in customers’ needs?

References:

Eduard C Groen, et al. The crowd in requirements engineering: The landscape and challenges. IEEE software, 34(2):44–52, 2017.

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Every business needs customer service to answer customer questions and help resolve issues. This will improve the relationship between the business and the customer. 84% of organizations that tries to improve their customer service see an increase in their revenue. (Rosen, 2021) A happy customer results in a good reputation and returning customers.

This Customer Relationship Management is becoming more automated due to the rise of Artificial Intelligence. Nowadays the best customer experience involves fast service at any time.  The role of Artificial Intelligence is getting bigger in creating this customer experience. For example, the rise of chatbots enables a customer service that is available 24/7. Besides, chatbots decrease the workload of call centers, because it can handle multiple customers at once. This also means the wait time of the call centers decreases which also result in a better customer experience. Artificial Intelligence also creates a more personal experience, because it can reach the customer data. For example,  a customer might want to know the status of their order. Since the chatbot interacts with the customer data it can quickly answer to these type of questions. If a question is too complicated for a chatbot to answer, it will direct the customer to a human agent for service. Therefore Artificial Intelligence helps customer service to be more efficient. (Salesforce)

Although the combination of Artificial Intelligence and Customer Relationship Management seems promising. It is still a challenge for these chatbots to understand what a person is saying and interpreting it correctly at a deeper level. If a chatbot is unhelpful because it doesn’t understand the given problem, it can result in a bad customer experience.  (MIT Technology Review Insights, 2020)

Therefore, we can say that Artificial Intelligence can improve the customer experience, if it performs correctly. It will deliver a 24/7 service to customers and makes the Customer Relationship Management more efficient. In the end, it will be worth the investment since satisfied customers correlate with the business revenue.

References:

Melissa Rosen, 2021, https://www.groovehq.com/blog/why-customer-service-is-important

Salesforce, https://www.salesforce.com/products/service-cloud/best-practices/how-ai-changed-customer-service/

MIT Technology Review Insights, 2020, https://www.technologyreview.com/2020/09/17/1008148/from-support-function-to-growth-engine-the-future-of-ai-and-customer-service/