Project Management: Implementing an AI-Driven Chatbot for OnBuy's Customer Service

BUS6018

Project Management

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Table of Figures

1. Background

This project is from a company that was founded in 2016, the fast-growing OnBuy, based in the UK is a company that allows its customers to buy products online. OnBuy is unique in its positioning as a fair and ethical platform, opting to place the main focus on fair and ethical businesses and transparent listing. The platform is customer first but there are many products across multiple categories including electronics, fashion, home goods, and many more (Laitala et al., 2021, p. 2). The model that OnBuy has built is based on developing a marketplace that is both beneficial to independent sellers and the consumer one that has a suitable product offering and the best possible pricing. OnBuy directly competes with big competitors such as Amazon, eBay, and others globally known for being able to throw resources and a large customer base at any given problem. Yet, thanks to its unique positioning as an ethical, transparent marketplace, OnBuy is well positioned particularly as consumer preferences increasingly skew away from favoring bigger, less transparent companies. Even as limited concerning its resource deficit compared to the competition OnBuy has managed to establish the company as a rapid growth position for both user base and revenue. OnBuy also remained innovative, growing, and most recently has focused on expanding its customer service operations to accommodate growing customer demands.

Challenges

To stand out from the other e-commerce giants, OnBuy follows a business model where it puts customer service at the forefront of its philosophy. Given the volume of customer inquiries product queries, order updates, and return processes the volume will grow as the company’s user base grows. The growth in customer demand is a problem for OnBuy's relatively limited customer service team who have fewer resources to carry out tasks like this at other e-commerce platforms. Increasing pressure is being placed on OnBuy’s customer support infrastructure which largely relies on manual responses to resolve customer issues rapidly. Customer query delays can affect rates of satisfaction and, in turn, brand loyalty (Rane et al., 2023, p. 429). OnBuy is working around this challenge by testing automation via an AI-driven customer service chatbot. The goal of this chatbot was the automate a lot of typical queries, giving the customers swift and effective answers without much human intervention.

Figure 1 Customer Loyalty with Brand Loyalty

Source: (Rane et al., 2023, p. 430)

SWOT Analysis

A SWOT analysis gives a better idea of how this chatbot project goes along with OnBuy’s strategic goals and challenges.

Strengths

OnBuy is different in an industry where professionalism is often lacking in its reputation as an ethical marketplace. The foundation of high customer retention and trust through fair treatment of buyers and sellers is what it is committed to.

Weaknesses

OnBuy, compared to its competitors is much smaller and has fewer resources to scale operations, especially in customer service. High inquiry volumes are managed by the company through manual processes which restricts the company’s ability to handle high and efficiently.

Opportunities

OnBuy has an opportunity to become more efficient and increase customer satisfaction with the increasing adoption of AI and automation in the customer service space.

Threats

The constant threat of intense competition from established massive e-commerce platforms because of that companies can allocate more resources for automation and customer service, which will result in higher expectations of the consumers.

2. Project Aim and Objectives

Every organization needs to make some changes in their working process to make the services better and get more business from different communities so OnBuy needs to make a change in their system to help their customers so they can get their queries solutions in less time and take all the benefits of the company’s policies and products.

Project Aims

Its main aim is to help streamline OnBuy’s customer service processes. The chatbot will use AI-driven automation to respond to frequently asked questions and common inquiries all by themselves, freeing the customer service team to focus on complex customer service issues (Lon et al., 2023, p. 3). The majority say this efficiency boost will increase customer satisfaction as to many customer queries, they have to wait for a response that will be nearly instant and it will overall improve customer experience with OnBuy.

Project Objectives

To achieve the project’s aim, the following SMART objectives have been identified:

• Grow customer query resolution rates by 20% within six months. The aim of this objective is about how well the chatbot answers queries correctly which directly contributes to faster issue resolution.

• Within the first three months of deployment, reduce the response times for common inquiries by 40%. If frequently asked questions the customers will receive prompt answers and meet their expectations for quick assistance in e-commerce settings.

• Handle repetitive inquiries and reduce the workload of the customer service team by 20%, letting team members do what they do best which means focusing on complex or high-value tasks. The objective of this improves morale within the team and also increase efficiency in catering to specifically a customer need.

• In these cases, the goals are SMART (Specific, Measurable, Achievable, Relevant, and Time-bound) so that the chatbot project targets real things and fits correctly within OnBuy's long-term objectives.

• Every goal is focused on certain performance indicators that are easy to measure resolution rates and response times and it’s possible to measure how the chatbot was successful.

Composed Scorecard Arrangement

This project supports OnBuy’s broader objectives across the Balanced Scorecard framework:

Customer: Driving faster responses to improve satisfaction.

Financial: Reducing operational costs of manual inquiries by decreasing volume.

Internal Processes: To automate the repetitive tasks to improve efficiency.

Learning and Growth: It allows the more complex queries to be routed to the customer service team and spend their time building their skills.

3. Commercial Case Framework

The integration of an AI-powered chatbot solution can help OnBuy adapt to its customer service challenges, positioned well on the company’s character of efficiency, customer satisfaction, and ethical company practices. The options available for this are outlined, a cost-benefit analysis is performed and the recommended approach is given.

Options Analysis

Two primary options are available for implementing the chatbot project such as

In-House Expansion

Developing the chatbot within OnBuy’s team allows for a highly customized tool aligned with the company’s unique customer service needs. The in-house expansion provides full control over design, features, and updates, ensuring the chatbot reflects OnBuy’s brand identity and adapts precisely to customer requirements (Skuridin and Wynn, 2024, p. 6).

Contract out Progress to a Provider

This option involves partnering with an established chatbot service provider to deploy a ready-made or customizable chatbot solution. Outsourcing offers rapid deployment, lower upfront costs, and access to expertise without overstraining OnBuy’s internal resources.

Cost-Benefit Analysis

Options	Cost	Benefit
In-House Expansion	High initial investment in development and maintenance, extended project timeline, and need for ongoing internal support.	Greater customization, alignment with brand identity, and seamless integration with internal systems.
Outsourcing	Limited customization options and reliance on third-party support for upgrades and troubleshooting.	Faster deployment, reduced initial costs, access to specialized expertise, and lower maintenance burden.

Justification and Recommendation

Based on this comparison, outsourcing is the most viable solution for OnBuy. The outsourced development option provides a quicker, cost-effective path to deployment which is essential given OnBuy’s immediate need for improved customer service capabilities (Bayyapu, 2022, p. 16). Most third-party chatbot solutions offer enough flexibility to align with OnBuy’s brand and customer service objectives. The reduced reliance on internal resources also makes this option sustainable for OnBuy’s budget and resource constraints.

Theory Application

Applying CBA (Cost-Benefit Analysis) highlights that the benefits of outsourcing outweigh those of in-house development for OnBuy’s immediate needs. Additionally, the payback period for outsourcing would be shorter, as quicker deployment allows the company to benefit from operational efficiencies and customer satisfaction improvements earlier.

4. Project Management Methodology

For the implementation of OnBuy’s AI-driven chatbot project, an Agile project management methodology is recommended due to its flexibility, iterative development, and ability to incorporate continuous feedback. Agile’s adaptability makes it particularly suited for projects involving new technologies like AI, where testing, refinement, and adjustments based on user feedback are essential.

Rationale for Agile

Agile’s iterative structure allows the project to progress through multiple sprints or short development cycles each focused on specific chatbot features or functions. This approach supports rapid development and testing, enabling the team to identify and address issues early (Rehman et al., 2020, p. 2). As OnBuy’s customer service needs may evolve during development, Agile’s flexibility allows the team to adapt the chatbot’s functionalities based on real-time feedback from stakeholders, including the customer service team and end-users. This continuous improvement ensures the final chatbot aligns closely with OnBuy’s objectives of efficiency and customer satisfaction.

Key Agile Practices

Sprint Arrangement

The project will be divided into sprints each lasting approximately two-three weeks. During each sprint, specific functionalities such as FAQ handling, and order tracking responses will be developed and tested.

Regular Stand-ups

Short daily meetings will keep the team aligned on progress, challenges, and immediate tasks, ensuring accountability and open communication.

Sprint Assessments and Demonstrations

At the end of each sprint, reviews will assess the completed functionalities, and retrospectives will identify areas for improvement, allowing for continuous adaptation.

Theory Application

Agile’s principles align with OnBuy’s need for flexibility and rapid iteration. Scrum is a popular Agile framework that provides structured processes like sprint arrangement, regular stand-ups, and sprint assessments, fostering consistent progress and adaptability. By using Agile, OnBuy’s chatbot project will benefit from a responsive, user-focused approach that can quickly adapt to evolving requirements and customer needs.

5. Stakeholder Management Plan

The success of the Onbuy chatbot project is based on the effective management of the stakeholders of the project. The list of key stakeholders is the management team, the IT department, the customer service team, the chatbot provider, and end users (Malik et al., 2023, p. 2). There are different interests, levels of influence, and roles that each stakeholder such as:

Stakeholder	Role	Impact	Responsibility
Project Manager	Manage complete Project	High	The project manager needs to know everything about running the project and the activity of the work.
Management Team	Control the working process	High	They approve the project’s budget, timeline, and overall strategic alignment with OnBuy’s goals. Regular project milestones and customer satisfaction improvements are what they need.
IT Department	Check everything on Chatbot	Medium	The chatbot will be integrated into OnBuy’s existing systems to be technically compatible and secure from a data protection perspective.
Customer Service Team	Verify Queries and Arrangement	Low	As this team handles routine inquiries, their insights into designating the chatbot questions as well as common customer troubles are crucial to what the chatbot is programmed to respond.
Chatbot Provider	Fulfill the need for OnBuy	High	they supply the technology and support for the chatbot with customize, roll out, and maintain the chatbot.
Users	Product user	High	Although they will not influence directly project decisions, customer feedback will be necessary to assess the chatbot’s success and refine it.

Power-Interest Matrix

Figure 2 Power-Interest Matrix

(Source: Author, 2024)

Engagement Strategy

An effective Power Interest Matrix will guide engagement to ensure effective collaboration. High-interest stakeholders who will test phases and give feedback will be given access to this more detailed phase and will provide input into progress reports, which will be given to high-power stakeholders such as senior management, and the IT department.

Theory Application

This structured approach is supported by the Power-Interest Matrix and the Stakeholder Theory so that each stakeholder’s needs are addressed. OnBuy can focus on key stakeholders, reduce resistance, encourage engagement, and align the chatbot with organizational goals.

6. Project Team

OnBuy’s chatbot project stands or falls on the operation of a team fully organized, with clear roles and responsibilities. A RACI Matrix (Responsible, Accountable, Consulted, Informed) is used to define each team member's role to act efficiently and communicate well with other members for the task execution (Hirmer et al., 2021, p. 3).

RACI Matrix

Task	Project Manager	Management Team	IT Development	Employees
Design and Planning	R	A	C	C
Customization	R	R	A	I
Testing	A	A	R	C
Monitoring	R	A	A	I
Deployment	A	R	R	I

Key Team Role and Responsibilities

Project Manager (Accountable)

A project manager is entrusted to manage the whole project and work between departments, monitor the progress, and see that the whole project comes to an end as expected and within the budget.

Management Team (Responsible)

From stakeholders, mostly the customer service team, the Business Analyst gathers and interprets requirements to understand common questions and what yields customer pain points.

IT Development (Consulted)

OnBuy’s IT Specialist makes sure that the chatbot plays well with OnBuy’s existing systems and causes no tech problems during development. Data security, server capacity, and any associated technical changes to implement occur.

Customer Service Lead (Consulted)

The Customer Service Lead is the primary interface with end users and a good source of understanding about which queries they receive the most responses to which in turn helps determine chatbot script and response content.

Theory Application

RACI Matrix solves the team responsibilities ambiguity problem: it clearly states who does what mitigates overlaps and gaps in accountability. In addition, Belbin’s Team Roles theory also makes whole team dynamics balanced by assigning roles that match the individual’s strengths so that work satisfaction and collaboration go on in a way.

7. Project Schedule Development

To ensure that OnBuy’s chatbot project is proceeding efficiently and meeting desired timelines, a clear and well-defined project plan is required. This schedule shows them how to break down tasks into timelines, dependencies, and dependencies into a Critical Path to continue keeping the project moving without delays (Hartmann and Briskorn, 2022, p. 8).

Task Breakdown and Timeline

S. NO.	Task	Duration
1	Initiation Phase	28 Days
1.1	Gathering Requirement	12 Days
1.2	Forming Objectives	16 Day
2	Scheming Phase	28 Days
2.1	Planning	10 Days
2.2	Design	18 Days
3	Progressive Phase	56 Days
3.1	Development	40 Days
3.2	Customization	16 Days
4	Monitoring Phase	28 Day
4.1	Testing	12 Days
4.2	Handling Errors	7 Days
4.3	Improvements	9 Days
5	Documentation	14 Days
5.1	Examine Influences	6 Days
5.2	Complete Development	8 Days
6	Deployment	14 Days
6.1	Post- launch Assessment	14 days

Gantt Chart

Critical Path

Developing, testing, and deploying are the key phases of the Critical Path that have huge consequences when delayed. The schedule for the project will be visualized with a Gantt chart showing task durations, dependencies, and milestones that all team members should consume over to stay synchronized.

Theory Application

The use of the Critical Path Method (CPM) identifies critical tasks that need to be completed on time and the use Gantt chart offers a clear visual timeline with which the team can monitor progress and take corrective actions against any possible delays. An understanding of what exactly the needs will be comes orderly, helping OnBuy to plan ahead in order to deploy the chatbot in a timely way and to improve customer service overall.

8. Risk Register Creation

OnBuy’s chatbot project might be Mancini, King, and Forest’s greatest set of assets or liabilities and therefore requires a Risk Register to proactively deal with potential risks that could harm the ability of the set to be a success. The team identifies, analyses, and ranks it out so that they can implement strategies to reduce risks, thus ensuring disruptions are minimized leading to a smooth deployment (Rodríguez-Rivero et al., 2020). The table below describes the key risks written along with their likelihood, impact, and mitigation strategies.

Risk Register Table

Risk	Probability	Influence	Moderation Approach
Budget Invades	High	High	Notice every amount, especially a contingency fund. If necessary, adjust features other than necessary.
Practical Incorporation Problems	Medium	Medium	Invite IT Specialists at the early stage of the design process. Test OnBuy systems for compatibility with your system.
User Disappointment	High	Medium	Then test all your chatbot responses with Customer Service. Customer feedback post-launch.
Data Safety Break	Medium	Low	Chatbot will have to follow strictly to get the data. Keep security measures, and the corresponding audits, up to date.
Overdue Arrangement	Low	Medium	The project schedule should be strict and progress should be checked frequently. Have set buffer periods for unexpected things.
Provider Reliance	Medium	High	Keep the track of SLA agreement with the vendor and maintain clear communication. Put your plan in place for ongoing support post-launch.

Risk Matrix

Figure 3 Power-Interest Matrix for Risk Analysis

Source: (Author, 2024)

Risk Analysis and Mitigation

The priority of mitigation efforts has been determined by the assessment of each risk in terms of likelihood and impacts. Preventive measures for high-priority risks include regular budget reviews and early involvement of IT. Buffer time is provided in the project timeline so that if any delays occur those are taken care of and testing phases are detailed enough to avoid chatbot quality resulting in customer dissatisfaction.

Theory Application

The Risk Register will be used regularly throughout the lifetime of the project to review and update the Risk Register to continue to establish new risks and keep old risks under control.

9. References

Bayyapu, S. (2022) ‘OPTIMIZING IT SOURCING IN HEALTHCARE: BALANCING CONTROL, COST, ANDINNOVATION’, International Journal of Computer Applications (IJCA), 3(1), pp.14-20. https://iaeme-library.com/index.php/IJCA/article/view/IJCA_03_01_003

Hartmann, S. and Briskorn, D. (2022) ‘An updated survey of variants and extensions of the resource-constrained project scheduling problem’, European Journal of operational research, 297(1), pp.1-14. https://doi.org/10.1016/j.ejor.2021.05.004

Hirmer, S.A., George-Williams, H., Rhys, J., McNicholl, D. and McCulloch, M., 2021. Stakeholder decision-making: Understanding Sierra Leone's energy sector. Renewable and Sustainable Energy Reviews, 145, pp. 1-12. https://doi.org/10.1016/j.rser.2021.111093

Laitala, K., Klepp, I.G., Haugrønning, V., Throne-Holst, H. and Strandbakken, P. (2021) ‘Increasing repair of household appliances, mobile phones and clothing: Experiences from consumers and the repair industry’, Journal of Cleaner Production, 282, pp. 1-13. https://doi.org/10.1016/j.jclepro.2020.125349

Lin, C.C., Huang, A.Y. and Yang, S.J. (2023) ‘A review of ai-driven conversational chatbots implementation methodologies and challenges (1999–2022)’, Sustainability, 15(5), pp. 1-13. https://doi.org/10.3390/su15054012

Malik, S.H., Fu, W., Rasool, S.F., Wani, G.A., Zaman, S. and Wani, N.A. (2023) ‘Investigating the Impact of Communication Factors and stakeholders Engagement on renewable Energy projects in Pakistan’, Sustainability, 15(14), pp. 1-14. https://doi.org/10.3390/su151411289

Rane, N.L., Achari, A. and Choudhary, S.P., 2023. Enhancing customer loyalty through quality of service: Effective strategies to improve customer satisfaction, experience, relationship, and engagement. International Research Journal of Modernization in Engineering Technology and Science, 5(5), pp.427-452. https://www.researchgate.net/profile/Nitin-Rane-2/publication/370561455_Enhancing_customer_loyalty_through_quality_of_service_Effective_strategies_to_improve_customer_satisfaction_experience_relationship_and_engagement/links/645612ad97449a0e1a7f308a/Enhancing-customer-loyalty-through-quality-of-service-Effective-strategies-to-improve-customer-satisfaction-experience-relationship-and-engagement.pdf

Rehman, A.U., Nawaz, A., Ali, M.T. and Abbas, M. (2020) ‘A comparative study of agile methods, testing challenges, solutions & tool support’, In 2020 14th International Conference on OpenSource Systems and Technologies (ICOSST), pp. 1-5. https://ieeexplore.ieee.org/abstract/document/9332965/

Rodríguez-Rivero, R., Ortiz-Marcos, I., Romero, J. and Ballesteros-Sánchez, L. (2020) ‘Finding the links between risk management and project success: Evidence from international development projects in Colombia’, Sustainability, 12(21), pp. 1-19. https://doi.org/10.3390/su12219294

Skuridin, A. and Wynn, M. (2024) ‘Chatbot Design and Implementation: Towards an Operational Model for Chatbots’, Information, 15(4), pp. 1-28. https://doi.org/10.3390/info15040226