Sprout Home is a small business focused in the plant market. There are two departments: the floral store, and the plant nursery. The company has been established since 2003, in the West Town neighborhood of Chicago IL. All employees are knowledgeable with plant care and aesthetic balance. It is expected to be able to consult with clients on how a product can fit in their personal space and how to visually enhance a room.<\/p>\n
In recent years, a website has been created where clients are able to purchase store products on the internet. Analyzing their current system carefully, our team, team _____, noticed a potential tool that could be implemented to improve the user experience and increase sales. <\/p>\n
CHAT is a project that implements an AI chatbot into Sprout Home\u2019s website. This AI is specifically targeted to help clients achieve their desired vision over the internet. Essentially, it\u2019s an upgraded and interactive search bar. In a visual synopsis: when visiting the site, a small avatar pops up on the bottom right corner of the screen asking if you\u2019re finding everything alright and if there\u2019s anything it can do to help. <\/p>\n
The AI interacts with the customer to find the specific requirements and constraints the client gives. Using some examples, we can see how interactions and relationships play out.<\/p>\n
Let\u2019s use the situation of buying a plant and pairing it with a planter. Starting off, the customer asks the chatbot to suggest plants in varying light conditions. CHAT then provides a list of options that accommodate the client\u2019s lighting situation. After the client makes a selection, the chatbot pulls a list of planters fitting the size of the plant selected, including the ones that are best-selling and most popular. The customer is delighted at the robot’s selection and makes a purchase.<\/p>\n
Implementing this chatbot can be an arduous task. Within the scope, it may take days or even weeks for this project to be completed. The first step is understanding the objectives and functionalities that we want the chatbot to satisfy. Then, connections between the questions asked and inventory available must be idealized to the real questions that clients may ask. Establishing this knowledge base is fundamental as it\u2019s what the AI is pulling data from. It also requires a trial phase where a beta is issued for clients to test out (though deployment of this beta needn\u2019t be announced). Bugs will then need to be corrected during this testing phase, only lengthening the duration of the project. Chatbotmagazine.com notes that depending on the complexity of the project, creating a chatbot can range from hours to a \u201cmaximum of 2-3 weeks\u201d (Mansuri, 2018). Inbenta, a globalized leader of AI and NLU production, boasts a fully functional interactive AI in the scope of 8 weeks (Verani, 2020).<\/p>\n
Taking a peak outside of the scope, we propose a learning AI system that is more interactive and playful. After recording and understanding the client\u2019s wants and needs, it can specifically cater to the user\u2019s style preferences pulled from the user\u2019s existing cart and other finer details. The AI, upon completion, should be able to connect users to their desired product, and provide rudimentary suggestions for similar items that are in the store. After its conception and deployment, programmers should look to preserve and maintain the AI as issues are corrected through trial and error. However, the constant maintenance could get costly.<\/p>\n
Depending on the complexity of the system, the rough estimation of pricing varies. A basic system can be achieved with just $10,000. However we aspire to create a top-of-the-line system with advanced learning capabilities, which could bring the final total to $340,000 (Beirne, 2018). This technology is certainly not cheap. Because the company is a small business, it would be impossible to finance an AI with exceptional intelligence. However starting off with a \u201coff the shelf\u201d chatbot would be a start in implementing this system onto the website. With a strong e-commerce presence as the period of covid continues, this added user experience would pay itself. It may not be feasible to start initially with a complex system, but overtime it may be achievable as sales continue to grow. <\/p>\n
Because of its expensive nature, the initial investment may be a risk to the small company, especially if the project is delayed. This would only further add to the cost. Should it fail to work altogether, it could be potentially devastating to the company finances. It is also uncertain if a basic AI system is even worth implementing, as most clientele already know the brands and aesthetic they\u2019re seeking. To compensate for this, a compromise must be found to create a system that is just enough to incentivise a purchase to occur. We can mitigate the risk of delays by creating a strong decision tree and work breakdown structure. <\/p>\n
Beirne, L. (2018, September 14). What are Ai Chatbots and how much do they cost? Modern Retail. Retrieved October 6, 2021, from https:\/\/modernretail.co.uk\/what-are-ai-chatbots-and-how-much-do-they-cost\/. <\/p>\n
Mansuri, S. (2018, October 10). How much time goes into developing a messenger chatbot. Medium. Retrieved October 6, 2021, from https:\/\/chatbotsmagazine.com\/how-much-time-goes-into-developing-a-messenger-chatbot-ce86afdfb969. <\/p>\n
Verani, E. (2020, July 1). Why most AI chatbot projects fail: 7 mistakes and how to avoid them. Inbenta. Retrieved October 6, 2021, from https:\/\/www.inbenta.com\/en\/blog\/ai-chatbot-project-timeframe\/.<\/p>\n","protected":false},"excerpt":{"rendered":"
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