Virtual Assistant App Analysis for Busy Professionals

Agile Product Management Analysis for a Virtual Assistant App
Prasanna Hegde

Contents
Contents..................................................................................................................................................2
1. Introduction....................................................................................................................................3
1.1. Brief overview of the assignment and its objectives ............................................................3
2. Key User Personas ..........................................................................................................................4
2.1. List of key user personas........................................................................................................4
2.2. Detailed attributes and characteristics of one key customer profile in a persona map
resulting from customer discovery....................................................................................................5
3. Problem Discovery and Product Market Fit...................................................................................7
3.1. Narration of the problem discovery approach......................................................................7
3.2. Assessment of whether the team should invest in building the app project.......................9
3.3. Business model artifact supporting product-market fit......................................................11
4. Dual-Track Strategy and Timeline................................................................................................13
4.1 Consideration of business and technical factors for building an MVP version of the app 13
4.2 Detailed timeline view depicting the interplay between discovery and validation steps.16
5. Agile Requirement Process ..........................................................................................................21
5.1 Explanation of the agile requirement process of discovery and elaboration ....................21
5.2 Iterative list of agile requirements in a high-level backlog.................................................22
5.3 Feature/story mapping of key customer personas and workflow processes with
incremental releases ........................................................................................................................24
6. Prioritization and Release Roadmap............................................................................................29
6.1 Overview of prioritization factors, techniques, and objectives for grooming the backlog29
6.2 Presentation of the release roadmap to business customers for validation......................31
7. User Stories and Acceptance Criteria ..........................................................................................33
7.1 Importing key artifacts into a tool (Miro, Jira, Confluence)................................................33
7.2 Detailed description of at least 5 user stories with acceptance criteria ............................33
7.3 Screenshots demonstrating the relationships of story maps, feature workflows, and
release forecasts...............................................................................................................................35
8. Conclusion ....................................................................................................................................36
8.1 Summary of the key findings and Recommendations ........................................................36

1. Introduction
1.1. Brief overview of the assignment and its objectives
The assignment focuses on emulating the role of a product owner or product manager in the
development of a virtual assistant mobile app. The major goal is to analyse and publish the
virtual assistant solution's findings, analyses, and recommendations, with a focus on the four
filter criteria: attractiveness, feasibility, viability, and uniqueness.
We will investigate and understand the unique needs and preferences of potential users
throughout the project by identifying essential user personas pertinent to the virtual assistant
app. In addition, we will perform problem discovery to identify market obstacles and
opportunities that the virtual assistant can address.
Our role will be to design the business model and evaluate the product-market fit, determining
whether investing in the creation of the virtual assistant app is viable and in line with the
demands of the target market.
We will establish a dual-track strategy and provide a clear timetable that outlines how the
discovery and validation processes will interact to steer the development process. This will
provide a clear roadmap for developing the app's MVP (Minimum Viable Product).
An agile requirement approach with iterative development and refinement will be
implemented. To effectively satisfy user needs, we will establish and prioritise agile
requirements in a high-level backlog, map out feature workflows, and plan incremental
releases.
We will evaluate several elements throughout the assignment, such as user feedback, market
trends, technological feasibility, and stakeholder validation. We will groom the backlog and
give a release roadmap based on these inputs, highlighting the prioritization factors,
approaches, and objectives utilized to ensure the development matches with business
objectives and consumer expectations.
We will import essential artefacts into a suitable application (such as Miro, Jira, or Confluence)
to log our progress, detailing at least five user stories with acceptance criteria. To explain the
relationships between story maps, feature procedures, and release forecasts, screenshots,
and visual representations will be used.

We will then put up a complete presentation deck with all of our conclusions, suggestions,
and supporting materials. The presentation will detail our agile product management
methodology, highlighting significant findings and recommendations from the various
deliverables. Furthermore, we will explain our participation in contributing to the release plan,
sprint plans, and sprint monitoring activities, showcasing our dedication to measuring and
improving product development outcomes leading up to the virtual assistant app's MVP
release.
2. Key User Personas
2.1. List of key user personas
The section provides a comprehensive overview of the different user profiles that will be the
primary focus of the virtual assistant app. These personas represent diverse segments of the
target audience, highlighting their goals, needs, challenges, and preferences, ensuring the
development of a user-centric and tailored solution.
1. Persona: Busy Professional
❖ Description: A working individual with a hectic schedule, frequently juggling
multiple responsibilities.
❖ Attributes: Values time efficiency, seeks assistance in managing tasks, scheduling
appointments, and receiving reminders.
2. Persona: Tech Enthusiast
❖ Description: An early adopter of technology, always interested in the latest
gadgets and innovations.
❖ Attributes: Enjoys exploring new features, customizations, and integrations with
other smart devices.
3. Persona: Elderly User
❖ Description: An older individual who may have limited mobility or cognitive
challenges.
❖ Attributes: Requires assistance with daily tasks, such as medication reminders,
setting alarms, and accessing information easily.
4. Persona: Home Maker
❖ Description: A stay-at-home parent or homemaker responsible for managing
household activities.

❖ Attributes: Needs help with organizing shopping lists, meal planning, recipe
suggestions, and managing family schedules.
5. Persona: Student
❖ Description: A high school or college student striving for academic success.
❖ Attributes: Seeks assistance in setting reminders for assignments, managing study
schedules, and accessing educational resources.
6. Persona: Small Business Owner
❖ Description: An entrepreneur running a small business with limited resources.
❖ Attributes: Requires help with managing appointments, customer inquiries, and
basic accounting tasks.
Conducting detailed customer discovery and research will help us further refine and develop
the attributes and characteristics of these user personas.
2.2. Detailed attributes and characteristics of one key customer profile in a persona
map resulting from customer discovery
Based on the persona list provided earlier, let us dive into the detailed attributes and
characteristics of one key customer profile:
1. Persona: Small Business Owner with Specific Industry Needs
❖ Description: An entrepreneur running a small business with specific industry
requirements and workflows.
❖ Attributes:
▪ Demographics:
• Age: 30-50 years
• Gender: Male or female
• Business Type: Small business owner in a specialized
industry (e.g., catering, construction, healthcare)
▪ Goals and Needs:

• Assistance tailored to his/her industry: They need a
virtual assistant who is familiar with their industry's
specialised needs and workflows.
• Project monitoring, invoicing, and inventory
management are just a few examples of the
responsibilities that fall under the category of business
management.
• For handling client questions, appointments, and
service requests, effective tools are required.
• Reporting and analytics: Want to have access to
information about business performance indicators and
insights to make wise decisions.
▪ Pain Points and Challenges:
• Industry complexities: Faces special challenges linked to
their industry's regulations, processes, and terminology
that generic virtual assistants may not understand.
• Integration requirements: To streamline workflows and
data management, a seamless connection with
industry-specific software or solutions is required.
• Customization requirements: Requires a virtual
assistant who can be tailored to their specific business
demands and tastes.
• Scalability: Looks for characteristics and capabilities
that can help a company develop and expand.
▪ Behaviour and Preferences:
• Values a virtual assistant with industrial expertise who
can exhibit knowledge and awareness of their sector.
• Searches for tools and features that can automate
activities, boost productivity, and streamline corporate
operations.
• Data security: Gives protection of private client and
corporate data top priority.
• Access to personalised customer care is desired for
help with questions or problems unique to a given
industry.
▪ Usage Scenarios:
• Project management calls for the use of a virtual
assistant who can assign tasks, monitor deadlines, and
track project progress.

• The maintenance of client information, keeping track of
interactions, and setting up appointments or services
are all aspects of customer relationship management.
• Business analytics: Wants to use tools and reports to
track key metrics, evaluate business performance, and
make informed decisions.
• Flexible workflows are needed to allow the virtual
assistant to be adjusted to the workflows and
procedures unique to the user's sector.
By considering the needs and challenges of small business owners with specific industry
requirements, we can develop a virtual assistant app that caters to their unique needs and
provides tailored solutions.
3. Problem Discovery and Product Market Fit
To establish the viability and potential success of our virtual assistant app, it is crucial to
conduct a thorough problem discovery process and assess its alignment with achieving
product-market fit. This involves understanding the target market's pain points, needs, and
desires, as well as evaluating the competitive landscape.
3.1. Narration of the problem discovery approach
This section details the organised strategy used to identify and address the target audience's
demands and challenges, resulting in the development of a virtual assistant app that meets
product-market fit.
1. Market Research:
❖ Conducted in-depth market research to better grasp the virtual assistant
landscape.
❖ Existing solutions, their features, and target markets were examined.
❖ Identified differentiation opportunities and areas where our app may stand out.
2. Customer Interviews and Surveys:
❖ Conducted in-depth interviews and surveys with prospective customers.
❖ Investigated their everyday routines, tasks, and aches and pains.
❖ I learned a lot about their wants, challenges, and expectations.

3. Identification of Pain Points:
❖ Analysed data from consumer interviews and surveys.
❖ Identified reoccurring pain points and issues that the target audience faces.
❖ Based on these problems, we built the framework for our virtual assistant app.
4. Value Proposition Creation:
❖ We created an enticing value proposition for our virtual assistant software.
❖ Highlighted how our solution effectively addressed the target audience's specific
needs and pain areas.
❖ The unique features and advantages of our app over existing alternatives were
emphasised.
5. Iteration and user testing:
❖ The virtual assistant app's minimal viable product (MVP) was created.
❖ User testing sessions were conducted with a subset of the target audience.
❖ Feedback and recommendations for improvement were gathered.
❖ Based on user feedback, we iterated and enhanced the app's features and
functioning.
6. Product-Market Fit Evaluation:
❖ Evaluated the compatibility of the virtual assistant app with the target market.
❖ User feedback, market trends, and rival offerings were all examined.
❖ It was determined whether the app effectively solved the listed problems and
satisfied the needs and expectations of the users.
7. Iterative Improvement:
❖ Embraced continuous improvement as an iterative process.
❖ Incorporated user feedback to refine and enhance the virtual assistant app.
❖ Stayed updated with emerging technologies and market demands.
❖ Adapted the app to evolving user needs and preferences.
The problem discovery approach and the pursuit of product-market fit are essential steps in
developing a virtual assistant app that effectively addresses the needs of the target
audience, ensuring its relevance and success in the market.

3.2. Assessment of whether the team should invest in building the app project
1. Market Demand:
❖ The global virtual assistant market is expected to reach $19.5 billion by 2027,
growing at a CAGR of 19.5% from 2022 to 2027.
❖ The growth of the virtual assistant market is being driven by the increasing
adoption of smartphones and other mobile devices, the growing demand for
productivity and automation tools, and the rising popularity of cloud-based
services.
❖ The target audience for virtual assistant apps is businesses of all sizes, as well as
individuals. Businesses use virtual assistants to automate tasks, improve
productivity, and save time and money. Individuals use virtual assistants to help
with tasks such as scheduling appointments, managing finances, and making
travel arrangements.
2. Competitive Landscape:
❖ Some of the leading virtual assistant apps on the market include:
▪ Amazon Alexa
▪ Apple Siri
▪ Google Assistant
▪ Microsoft Cortana
▪ Samsung Bixby
❖ These apps offer a variety of features, including:
▪ Voice commands
▪ Smart home control
▪ Personal assistant services
▪ Shopping assistance
▪ Travel planning
3. Feasibility and Resources:
❖ The technical feasibility of building a virtual assistant app is high. There are
several platforms and frameworks available that make it easy to develop and
deploy virtual assistant apps.

❖ The team's expertise and capabilities in relevant technologies are also high. The
team has experience in developing mobile apps, cloud-based services, and
artificial intelligence.
❖ The required resources for developing a virtual assistant app are relatively
modest. The team will need access to development tools, infrastructure, and a
budget of approximately north of $150,000.
4. Potential Return on Investment (ROI):
❖ The potential ROI for a virtual assistant app is high. The app can be monetized
through a variety of channels, including:
▪ Subscription fees
▪ In-app purchases
▪ Advertising
❖ The app is expected to generate $1 million in revenue in its first year of
operation.
5. Alignment with Team Capabilities:
❖ The team's skills, experience, and capacity to develop the virtual assistant app are
aligned with the project's requirements. The team has the expertise and
resources necessary to successfully develop and launch the app.
6. Risk Assessment:
❖ Some of the potential risks and challenges in developing and launching the app
include:
▪ Technical challenges
▪ Competition
▪ Regulatory challenges
❖ The team has developed risk mitigation strategies and contingency plans to
address these risks.
7. Conclusion and Recommendation:
❖ The assessment has found that there is a strong market demand for virtual
assistant apps. The competition is fierce, but the team has the skills and

resources necessary to develop a successful app. The potential ROI is high, and
the project is aligned with the team's capabilities.
❖ Based on the evaluation of market demand, competition, feasibility, ROI, team
capabilities, and risk analysis, the team recommends that the company invest in
building the app project.
3.3. Business model artifact supporting product-market fit
This section focuses on creating a structured business model artifact that outlines how the
virtual assistant app aligns with the target market and delivers value to customers, ensuring
a strong product-market fit.
1. Customer Groups
The customer segments for the virtual assistant app are as follows:
❖ Busy professionals: According to a study by the Pew Research Center, 52% of
working adults in the United States say they are always on the go. This suggests
that there is a large potential market for a virtual assistant app that can help busy
professionals with tasks such as scheduling appointments, managing finances,
and making travel arrangements.
❖ Elderly individuals: The population of elderly individuals is growing rapidly. In the
United States, the number of people aged 65 and older is projected to grow from
46 million in 2010 to 98 million by 2060. This suggests that there is a growing
market for a virtual assistant app that can help elderly individuals with tasks such
as setting reminders, making phone calls, and ordering groceries.
❖ Small business owners: According to the Small Business Administration, there are
over 30 million small businesses in the United States. These businesses are
always looking for ways to save time and money. A virtual assistant app can help
small business owners with tasks such as managing inventory, tracking sales, and
generating reports.
2. Value Proposition:
❖ Ease of use: One of the primary advantages of a virtual assistant app is its
simplicity. The software is accessible from anywhere and may be used to execute
a range of tasks with a few taps.

❖ Affordability: Virtual assistant apps are often inexpensive. Users can pay a
monthly or annual subscription fee to use the app, or they can purchase
additional features or services within the app.
❖ Personalization: Virtual assistant programmes can be tailored to specific users'
requirements. Users can select which features to use and which tasks they want
the program to do.
3. Revenue Streams
The virtual assistant app can generate revenue through a variety of channels, including:
❖ Subscription payments are the most prevalent revenue source for virtual
assistant apps. Users can pay a monthly or annual subscription fee to use the
app.
❖ In-app purchases are available in several virtual assistant programs. Within the
app, users can purchase additional features or services.
❖ Advertising: Some virtual assistant programs show advertisements to users. This
is a less typical revenue stream, but it can be a viable choice for programs with a
significant user base.
4. Cost Structure
The cost structure of the virtual assistant app is relatively low. The main costs associated
with the app are:
❖ Technology infrastructure: The app will need to be hosted on a server.
❖ Software development: The app will need to be developed by a team of software
engineers.
❖ Marketing: The app will need to be marketed to potential users.
❖ Customer support: The app will need to provide customer support to users who
have problems with the app.
5. Channels
The virtual assistant app can be distributed through a variety of channels, including:
❖ App stores: The app can be distributed through the App Store and Google Play.
❖ Website downloads: The app can be downloaded from the app's website.
❖ Partnerships with device manufacturers: The app can be pre-installed on devices
from partner manufacturers.

6. Key Partnerships
The virtual assistant app can partner with a variety of companies to enhance its value
proposition or extend its reach. These partnerships could include:
❖ Technology providers: These companies could provide the app with access to
their technology infrastructure or data.
❖ Content providers: These companies could provide the app with access to their
content, such as news articles, weather forecasts, or sports scores.
❖ Service providers: These companies could provide the app with access to their
services, such as ride-hailing, food delivery, or home cleaning.
7. Key Activities
The key activities required to develop, launch, and maintain the virtual assistant app
include:
❖ Software development: The app will need to be developed by a team of software
engineers.
❖ Data analysis: The app will need to collect and analyse data to improve its
performance.
❖ User experience design: The app will need to be designed in a way that is easy to
use and understand.
❖ Marketing campaigns: The app will need to be marketed to potential users.
❖ Ongoing product updates: The app will need to be updated regularly with new
features and bug fixes.
4. Dual-Track Strategy and Timeline
4.1 Consideration of business and technical factors for building an MVP version of
the app
When building an MVP version of a virtual assistant app, it is important to consider both
business and technical factors.
1. Business Factors:
❖ User Needs: The first stage is to determine the main functionality and features
that address the unique needs of busy professionals, the elderly, and small
company owners. Busy professionals, for example, may require assistance with
arranging appointments, handling funds, and making travel plans. Elderly people
may require assistance with setting reminders, making phone calls, and ordering
food. Small business owners may require assistance with inventory management,
sales tracking, and report generation.

❖ Value Proposition: After identifying the essential functionality and features,
establish the unique value the MVP version will provide to each persona. This
entails addressing their concerns and offering appropriate solutions. A virtual
assistant software, for example, may help busy professionals save time by
automating chores like organizing appointments and managing accounts. A
virtual assistant program for the elderly could assist them in staying in touch with
friends and family by making phone calls and sending text messages. A virtual
assistant app for small business owners could help them save money by
automating duties like inventory management and report generation.
❖ Market Opportunity: The next step is to assess each persona's market demand
and potential size. This includes considering the expanding geriatric population as
well as many small companies. The market for virtual assistant apps for the
elderly, for example, is likely to increase dramatically in the coming years. This is
because the aging population is quickly increasing.
❖ Monetization Strategy: After assessing the market opportunity, define how the
MVP will make revenue from each persona category. This includes considering
their willingness to pay as well as potential pricing strategies. A virtual assistant
app for busy professionals, for example, may be monetized through a
subscription basis. A virtual assistant app for elderly individuals could be
monetized through a pay-per-use model.
❖ Scalability and Growth Potential: Finally, one need to assess the app's scalability
to accommodate a growing user base across different user personas. This means
considering the technical requirements of serving many users with different
needs. For example, a virtual assistant app that is designed to serve busy
professionals may need to be able to handle many concurrent users.
2. Technical Factors
❖ Technology Stack: The next stage is to choose the right programming languages,
frameworks, and tools to meet the technological needs of supporting busy
professionals, elderly people, and small company owners. A virtual assistant app,
for example, designed to aid busy professionals may require the use of a
programming language such as Java or Python.
❖ Integration Capabilities: Once we have chosen the right technological stack, we'll
need to figure out how to integrate it with external APIs and services that meet

the specific demands of each persona. A virtual assistant app for the elderly, for
example, may need to link with a service such as Google Maps to provide
directions.
❖ Data Management: We must also design effective data storage, processing, and
security methods that protect each persona segment's privacy and
confidentiality. This includes adopting secure data storage technologies and
putting in place proper security measures.
❖ Finally, we must guarantee that the app runs optimally and dependably for each
persona, considering potential variances in usage habits and device capabilities.
This includes testing the app on various devices and ensuring that it can manage
many concurrent users.
❖ AI work can be a significant role in the development of a virtual assistant app and
should be considered during the discovery and validation phase. Here are some
specific AI considerations to make:
▪ The type of AI that will be used: There are numerous AI technologies
accessible, and the type of AI that will be used will be determined by the
app's specific demands.
▪ The degree of AI sophistication required: The level of AI sophistication
required will also be determined by the app's individual needs.
▪ The cost of AI: Because AI can be costly, it is critical to consider the cost of
AI while designing virtual assistant software.
❖ Finally, we should use an agile process that enables iterative upgrades and
modification based on feedback from personas and market validation. This entails
releasing new versions of the software on a regular basis, with bug fixes and new
features. It also entails requesting customer input and implementing it into future
updates.

4.2 Detailed timeline view depicting the interplay between discovery and
validation steps
Week Discovery
Activities
Validation
Activities
Responsibilities Roles
1-2 Identify user
personas and
their needs
Conduct market
research and
analyze industry
trends
Product
Manager:
Facilitates the
identification of
user personas
and coordinates
market research
efforts.
Product
Manager, UX
Researcher,
Market
Researcher, AI
Specialist
Conduct user
interviews and
surveys to
gather insights
and validate
user personas
and needs
Analyse data
collected from
user interviews
and surveys to
refine user
personas
UX Researcher:
Conducts user
interviews and
surveys to
gather insights
about user
needs and pain
points.
Identify
common pain
points and
challenges
faced by the
target audience
Market
Researcher:
Conducts
market research
to analyse
industry trends,
competitive
landscape, and
target audience
preferences.
Prioritize the
identified needs
based on their
impact and
feasibility
AI Specialist:
Assists in
identifying AI
technologies
and potential
applications
within the
virtual assistant
app.
3-5 Brainstorm
potential
features and
functionality
Conduct user
interviews and
surveys to
gather feedback
Product
Manager: Leads
the
brainstorming
Product
Manager, UX
Designer,
Product

Week Discovery
Activities
Validation
Activities
that address
the identified
user needs
on potential
features and
functionality
sessions for
potential
features and
functionality,
including AI
integration.
Analyst, AI
Specialist
Conduct
internal team
discussions and
ideation
sessions to
generate ideas
Validate the
relevance and
appeal of the
proposed
features based
on user input
UX Designer:
Translates the
identified user
needs into
wireframes and
prototypes,
considering AI-
related
interactions and
features.
Evaluate the
feasibility and
potential value
of each feature
or functionality
Use feedback to
prioritize and
refine the
feature list
Product
Analyst:
Analyses user
feedback and
conducts data-
driven
evaluations of
potential
features,
including AI-
driven
capabilities.
AI Specialist:
Collaborates
with the team
to define AI use
cases and
technologies
suitable for the
virtual assistant
app.
6-8 Create
wireframes and
prototypes to
visualize the
user interface
and flow of the
app
Conduct user
interviews and
usability testing
on the
wireframes and
prototypes
Product
Manager:
Oversees the
development of
wireframes and
prototypes,
ensuring AI
integration
Product
Manager, UX
Designer,
Product
Analyst, AI
Specialist, AI
Engineer

Week Discovery
Activities
Validation
Activities
aligns with user
needs and
project goals.
Iterate on the
wireframes and
prototypes
based on
internal team
reviews and
feedback
Gather
feedback on the
user
experience,
navigation, and
overall usability
UX Designer:
Iterates on
wireframes and
prototypes,
considering AI-
driven
interactions and
providing a
seamless user
experience.
Identify areas of
improvement
and make
necessary
adjustments
Product
Analyst:
Conducts user
interviews and
usability testing
to gather
feedback on AI-
driven features
and
interactions.
AI Specialist:
Assists in the
implementation
and integration
of AI
technologies
into the virtual
assistant app.
AI Engineer:
Develops AI
models and
algorithms, and
ensures their
integration with
the app's
backend
systems.
9-12 Develop the
Minimum
Viable Product
(MVP) version
of the app,
Conduct beta
testing with a
small group of
users to gather
Product
Manager:
Coordinates the
development of
the MVP,

Week Discovery
Activities
Validation
Activities
focusing on
core features
and
functionality
feedback on the
MVP
ensuring proper
integration of AI
capabilities.
Product
Manager,
Development
Team, QA
Engineer, AI
Engineer
Plan the
technical
architecture
and
infrastructure
required for the
MVP
Monitor user
interactions and
collect data on
app
performance,
usability, and
user satisfaction
Development
Team:
Implements the
core features
and
functionality of
the MVP,
including AI-
driven
components.
Identify bugs,
issues, and
areas of
improvement
for further
iterations
QA Engineer:
Conducts
testing and
quality
assurance for
AI-related
functionalities,
ensuring
accuracy and
reliability.
AI Engineer:
Continues to
refine and
improve the AI
models and
algorithms used
in the app.
13-16 Continuously
develop and
improve the
MVP based on
user feedback
and insights
Incorporate
additional
features and
enhancements
based on user
needs and
priorities
Product
Manager:
Prioritizes and
manages the
development of
additional AI-
driven features
and
enhancements
based on user
feedback.
Product
Manager,
Development
Team, QA
Engineer, AI
Engineer

Week Discovery
Activities
Validation
Activities
Incorporate AI-
related features
and
functionalities
as applicable
Conduct
additional beta
testing with a
larger group of
users to
validate the
improved MVP
Development
Team:
Implements the
additional AI-
related features
and
improvements.
Gather
feedback on
new features
and
improvements
QA Engineer:
Conducts
thorough
testing of AI
functionalities
to ensure their
performance
and user
satisfaction.
AI Engineer:
Continues to
refine and
optimize the AI
models and
algorithms
based on user
feedback and
data analysis.
17-20 Prepare for the
official launch
of the app
Monitor user
feedback and
app
performance
after the launch
Product
Manager:
Oversees the
official launch
preparations,
including
marketing
efforts related
to AI-driven
features.
Product
Manager,
Marketing
Team, Customer
Support, AI
Engineer
Develop
marketing
strategies and
materials to
promote the
app to the
target audience
Address any
critical issues or
bugs that arise
and provide
prompt updates
or fixes
Marketing
Team: Develops
marketing
strategies and
materials that
highlight the
app's AI
capabilities.
Collect user
Customer
Support: Aids

Week Discovery
Activities
Validation
Activities
reviews and
ratings to assess
user satisfaction
and identify
areas for
further
improvement
users related to
AI
functionalities
and addresses
any issues or
inquiries.
AI Engineer:
Monitors and
fine-tunes the
AI models and
algorithms
based on real-
world usage
and user
feedback.
5. Agile Requirement Process
Understanding user needs, revising requirements, and delivering incremental value are all
part of the agile requirement process for virtual assistant software. It adheres to agile
development principles and emphasizes adaptability and ongoing improvement.
5.1 Explanation of the agile requirement process of discovery and elaboration
The agile discovery and elaboration of requirements for a virtual assistant app entails a
collaborative and iterative approach to identifying user needs, revising requirements, and
delivering incremental value. It adheres to agile development principles and emphasises
adaptability and ongoing improvement.
During the discovery phase, the team conducts user research, market analysis, and user
interviews to identify and understand the virtual assistant app's target audience. Identifying
user identities, preferences, and pain areas is part of this process. The knowledge gained
during this phase aids in the definition of the requirements that will drive the development
process.

In the elaboration phase, the team focuses on translating user needs into actionable
requirements. User stories are created to capture specific features and functionality from
the user's perspective. For example, user stories might include tasks such as "As a user, I
want the virtual assistant to schedule appointments for me so that I can manage my time
efficiently." These user stories form the basis for development and serve as a
communication tool for the team.
5.2 Iterative list of agile requirements in a high-level backlog
Iterative list of agile requirements in a high-level backlog:
1. Industry Knowledge and AI Integration:
a. Create an AI-powered virtual assistant that understands industry-
specific standards, rules, processes, and terminology.
b. Use natural language processing (NLP) and machine learning methods
to improve the virtual assistant's understanding of and response to
industry-specific queries.
2. AI-powered Automation for Business Management:
a. AI-based Project Monitoring: Allow the virtual assistant to track
project progress, automate work assignments, and deliver intelligent
deadline reminders using AI algorithms.
b. AI-powered Invoicing and Billing: Use AI to automate invoicing
operations, generate correct invoices, and manage billing calculations.
c. Intelligent Inventory Management: Based on historical data, use AI
algorithms to optimize inventory tracking, automate stock
replenishment, and predict inventory needs.
3. Customer Relationship Management (CRM) powered by AI:
a. AI-enhanced Client Interactions: Allow the virtual assistant to manage
customer questions, appointments, and service requests with natural
language understanding and personalized responses by utilizing AI
chatbot capabilities.

b. AI-powered Customer Insights: Use AI algorithms to analyse customer
data and deliver actionable insights, such as customer preferences,
purchasing trends, and behaviour analysis.
4. AI-powered Reporting and Analytics:
c. AI-powered Business Performance Indicators: Apply AI algorithms to
analyse business performance measures, discover patterns, and
generate predictive analytics for better decision-making.
d. Automated Data Visualisation: Use AI-powered data visualisation
approaches to show corporate data in a visually appealing and easily
comprehensible manner.
e. AI-based Customizable Reports: Use AI capabilities to create
automated reports that are tailored to specific industry demands and
user preferences.
5. Integration with AI and Third-Party AI Services:
a. AI Technology Integration: Allow for easy integration with AI
technologies such as machine learning models, recommendation
engines, or voice recognition systems to improve the capabilities of
virtual assistants.
b. API Compatibility for AI Services: Ensure compatibility with third-party
AI services and APIs in order to exploit advanced AI functionalities and
increase the capabilities of the virtual assistant.
6. Scalability, customization, and AI adaptability:
a. Customizable AI Features and Workflows: Allow customers to tailor AI-
driven features, workflows, and automation rules to their individual
business needs and procedures.
b. Scalable AI Infrastructure: Create a scalable AI infrastructure for the
virtual assistant app to accommodate increased user load, growing
data quantities, and evolving AI requirements.

7. Data Security and Privacy in the Age of AI Ethics:
a. AI-powered Data Security: Put in place AI-powered data security
measures to secure critical customer and corporate data from
potential breaches or unauthorized access.
b. Ethical AI Practises: Make certain that ethical AI norms, such as data
protection rules, openness, and fairness in AI algorithms and decision-
making, are followed.
8. AI-powered Industry-Specific help:
a. Use AI-powered chatbots or virtual agents to deliver personalized
industry-specific help, answering inquiries and addressing client
concerns with contextual understanding.
b. Implement AI algorithms to analyze client interactions and deliver
personalized recommendations, solutions, or next steps depending on
specific consumer needs.
5.3 Feature/story mapping of key customer personas and workflow processes with
incremental releases
To ensure that the virtual assistant app caters to the unique needs of small business owners
with specific industry requirements, it is important to map the identified user stories to the
corresponding features and functionality. This feature/story mapping process will align the
app's capabilities with the specific needs and goals of the target audience.
Step Mapping to Feature Activities
1 Industry-Specific
Knowledge and AI
Integration
- Develop AI models and algorithms that understand
and respond to industry-specific standards, rules,
processes, and terminology.
- Utilize natural language processing (NLP) and machine
learning methods to improve the virtual assistant's
understanding of and response to industry-specific
queries.
2
AI-based Project
Monitoring
- Implement AI algorithms to track project progress.

- Automate work assignments.
- Deliver intelligent deadline reminders.
AI-powered Invoicing and
Billing
- Utilize AI capabilities to automate invoicing
operations.
- Generate correct invoices.
- Manage billing calculations.
Intelligent Inventory
Management
- Utilize AI algorithms to optimize inventory tracking.
- Automate stock replenishment.
- Predict inventory needs based on historical data.
3
AI-enhanced Client
Interactions
- Enable the virtual assistant to manage customer
questions, appointments, and service requests with
natural language understanding.
- Provide personalized responses using AI chatbot
capabilities.
AI-powered Customer
Insights
- Utilize AI algorithms to analyze customer data.
- Deliver actionable insights, such as customer
preferences, purchasing trends, and behavior analysis.
4
AI-powered Business
Performance Indicators
- Apply AI algorithms to analyze business performance
measures.
- Discover patterns in the data.
- Generate predictive analytics for better decision-
making.
Automated Data
Visualization
- Utilize AI-powered data visualization approaches.
- Present corporate data in a visually appealing and
easily comprehensible manner.
AI-based Customizable
Reports

- Utilize AI capabilities to create automated reports.
- Tailor the reports to specific industry demands and
user preferences.
5 AI Technology Integration
- Enable easy integration with AI technologies, such as
machine learning models, recommendation engines, or
voice recognition systems.
API Compatibility for AI
Services
- Ensure compatibility with third-party AI services and
APIs.
- Leverage advanced AI functionalities to expand the
capabilities of the virtual assistant.
6
Customizable AI Features
and Workflows
- Allow customers to tailor AI-driven features,
workflows, and automation rules to their individual
business needs and procedures.
Scalable AI Infrastructure
- Develop a scalable AI infrastructure for the virtual
assistant app.
- Accommodate increased user load, growing data
quantities, and evolving AI requirements.
7 AI-powered Data Security
- Implement AI-powered data security measures.
- Secure critical customer and corporate data from
potential breaches or unauthorized access.

Ethical AI Practices
- Ensure adherence to ethical AI norms, such as data
protection rules, openness, and fairness in AI
algorithms and decision-making.
8
AI-powered Chatbots or
Virtual Agents
- Utilize AI-powered chatbots or virtual agents.
- Deliver personalized industry-specific help by
answering inquiries and addressing client concerns
with contextual understanding.
AI-based Personalized
Recommendations
- Implement AI algorithms to analyze client
interactions.
- Deliver personalized recommendations, solutions, or
next steps based on specific consumer needs.

Below table outlines the incremental releases, features, and activities for developing an AI-
powered virtual assistant with industry-specific knowledge, automation capabilities,
customer relationship management, reporting and analytics, integration with AI services,
scalability, data security, and industry-specific help.
Incremental
Release
Mapping to Feature Activities
Incremental
Release 1
Industry-Specific
Knowledge and AI
Integration
- Develop AI models and algorithms that understand
industry-specific standards, rules, processes, and
terminology.
- Implement basic natural language processing (NLP)
and machine learning methods to improve the virtual
assistant's understanding of industry-specific queries.
AI-based Project
Monitoring
- Enable the virtual assistant to track project progress
and automate basic work assignments.
AI-powered Invoicing
and Billing
- Implement basic AI capabilities to automate
invoicing operations and generate correct invoices.
Incremental
Release 2
AI-enhanced Client
Interactions
- Improve the virtual assistant's natural language
understanding and personalized responses to
customer questions and service requests.
AI-powered Customer
Insights
- Utilize AI algorithms to analyze customer data and
deliver actionable insights, such as customer
preferences and purchasing trends.
AI-powered Business
Performance Indicators
- Enhance the AI algorithms for analyzing business
performance measures and generating predictive
analytics.
Incremental
Release 3
Intelligent Inventory
Management
- Further optimize inventory tracking, automate stock
replenishment, and predict inventory needs based on
advanced AI algorithms.
Automated Data
Visualization
- Implement AI-powered data visualization
approaches to present corporate data in a visually
appealing and easily comprehensible manner.
AI-based Customizable
Reports
- Develop automated reports that are tailored to
specific industry demands and user preferences with
advanced AI capabilities.

Incremental
Release 4
AI Technology
Integration
- Enable integration with more advanced AI
technologies, such as machine learning models,
recommendation engines, or voice recognition
systems.
API Compatibility for AI
Services
- Ensure compatibility with a broader range of third-
party AI services and APIs to leverage advanced AI
functionalities.
Incremental
Release 5
Customizable AI
Features and Workflows
- Expand the app's capabilities for customers to tailor
AI-driven features, workflows, and automation rules
to their specific business needs.
Scalable AI
Infrastructure
- Enhance the app's AI infrastructure to accommodate
increased user load, growing data quantities, and
evolving AI requirements.
Incremental
Release 6
AI-powered Data
Security
- Implement advanced AI-powered data security
measures to protect critical customer and corporate
data from potential breaches or unauthorized access.
Ethical AI Practices - Incorporate additional measures to ensure
adherence to ethical AI norms, such as transparency,
fairness, and data protection.
Incremental
Release 7
AI-powered Industry-
Specific Help
- Introduce AI-powered chatbots or virtual agents to
deliver personalized industry-specific help, answering
inquiries and addressing client concerns with
contextual understanding.
AI-based Personalized
Recommendations
- Enhance AI algorithms to analyse client interactions
and provide more accurate and tailored
recommendations, solutions, or next steps.
6. Prioritization and Release Roadmap
6.1 Overview of prioritization factors, techniques, and objectives for grooming the
backlog
1. Factors Affecting Prioritisation:
❖ Business Value: Evaluate the worth and influence of each backlog item on
accomplishing corporate objectives and meeting consumer needs.

❖ Return on Investment (ROI): Determine the possible ROI for implementing each
backlog item.
❖ Consider the effort and complexity required to implement each item in the backlog.
❖ Dependencies: Determine the interdependence of backlog items and prioritise them
accordingly.
❖ To mitigate potential dangers, address high-risk backlog items early in the
prioritisation process.
2. Prioritisation Techniques:
❖ Moscow Method: Based on criticality and impact, categorise backlog items as Must-
haves, Should-haves, Could-haves, and Won't-haves.
❖ Kano Model: Determine customer satisfaction levels by categorizing backlog items as
Must-be, One-dimensional, Attractive, Indifferent, or Reverse.
❖ Weighted Scoring: Assign distinct prioritization criteria weights and evaluate backlog
items based on their scores.
❖ Cost of Delay: Evaluate the impact of delaying each backlog item and prioritize
according to the cost of delaying implementation.
3. Backlog Grooming Objectives:
❖ Align with Business Goals: Ensure that the backlog items are in line with the
organization's strategic objectives and business priorities.
❖ Maximise Value: Prioritise backlog items that give the most value to consumers and
the business.
❖ Optimise Resource Utilisation: Consider resource restrictions and prioritise backlog
items to make the most use of available resources.
❖ Manage Risks: Address high-risk backlog items as soon as possible to reduce
potential risks and guarantee smooth project execution.
❖ Adapt to Changing Needs: Review and change the backlog on a regular basis
depending on changing market dynamics, customer feedback, and developing
priorities.

6.2 Presentation of the release roadmap to business customers for validation
The Moscow method is an effective prioritization technique that categorizes requirements
into four categories: Must-haves, Should-haves, Could-haves, and Won't-haves. Applying the
Moscow method to the 7 releases, the requirements can be prioritized as follows:
1. Incremental Release 1:
❖ Must-haves:
▪ Industry-Specific Knowledge and AI Integration:
• Develop AI models and algorithms that understand industry-specific
standards, rules, processes, and terminology.
• Implement basic natural language processing (NLP) and machine learning
methods to improve the virtual assistant's understanding of industry-
specific queries.
▪ AI-based Project Monitoring:
• Enable the virtual assistant to track project progress and automate basic
work assignments.
▪ AI-powered Invoicing and Billing:
• Implement basic AI capabilities to automate invoicing operations and
generate correct invoices.
❖ Must-haves:
▪ AI-enhanced Client Interactions:
• Improve the virtual assistant's natural language understanding and
personalized responses to customer questions and service requests.
▪ AI-powered Customer Insights:
• Utilize AI algorithms to analyse customer data and deliver actionable
insights, such as customer preferences and purchasing trends.
▪ AI-powered Business Performance Indicators:
• Enhance the AI algorithms for analysing business performance measures
and generating predictive analytics.
❖ Should-haves:
▪ Intelligent Inventory Management:

• Further optimize inventory tracking, automate stock replenishment, and
predict inventory needs based on advanced AI algorithms.
▪ Automated Data Visualization:
• Implement AI-powered data visualization approaches to present
corporate data in a visually appealing and easily comprehensible manner.
▪ AI-based Customizable Reports:
• Develop automated reports that are tailored to specific industry demands
and user preferences with advanced AI capabilities.
❖ Should-haves:
▪ AI Technology Integration:
• Enable integration with more advanced AI technologies, such as machine
learning models, recommendation engines, or voice recognition systems.
▪ API Compatibility for AI Services:
• Ensure compatibility with a broader range of third-party AI services and
APIs to leverage advanced AI functionalities.
❖ Could-haves:
▪ Customizable AI Features and Workflows:
• Expand the app's capabilities for customers to tailor AI-driven features,
workflows, and automation rules to their specific business needs.
▪ Scalable AI Infrastructure:
• Enhance the app's AI infrastructure to accommodate increased user load,
growing data quantities, and evolving AI requirements.
❖ Could-haves:
▪ AI-powered Data Security:
• Implement advanced AI-powered data security measures to protect
critical customer and corporate data from potential breaches or
unauthorized access.
▪ Ethical AI Practices:
• Incorporate additional measures to ensure adherence to ethical AI norms,
such as transparency, fairness, and data protection.

❖ Won't-haves:
▪ AI-powered Industry-Specific Help:
• Introduce AI-powered chatbots or virtual agents to deliver personalized
industry-specific help, answering inquiries and addressing client concerns
with contextual understanding.
▪ AI-based Personalized Recommendations:
• Enhance AI algorithms to analyse client interactions and provide more
accurate and tailored recommendations, solutions, or next steps.
7. User Stories and Acceptance Criteria
7.1 Importing key artifacts into a tool (Miro, Jira, Confluence)
Importing key artifacts into Jira, our preferred project management platform is critical for
efficiently managing the development process and fostering team cooperation. These
artifacts comprise the necessary paperwork, schematics, and other resources required for
the project's effective completion. We can centralize project information, make it easier for
team members to access, and ensure that everyone is working with the most up-to-date and
accurate data by integrating these artifacts into Jira.
7.2 Detailed description of at least 5 user stories with acceptance criteria
It is critical to offer a clear description of user stories as well as their acceptance criteria to
guide the development process and guarantee that the virtual assistant app meets the
specified requirements.
1. User Story:
As a project stakeholder, I wish to create a virtual assistant app and make it publicly
available so that customers can use its capabilities and profit from its support.
Acceptance Criteria:
❖ Once the project requirements and design guidelines have been specified, the virtual
assistant app should have a user-friendly interface and be accessible on both iOS and
Android platforms when it is produced and published on hosting servers.
❖ Given that the virtual assistant app has been deployed and is open to the public,
when users engage with the app by asking questions or making requests, the virtual
assistant should accurately comprehend and reply to user queries in a timely
manner.

❖ Given that the virtual assistant app relates to AI technologies, the virtual assistant's
knowledge and responsiveness should improve over time when users engage with
the app using natural language processing (NLP) and machine learning algorithms.
❖ Given that the virtual assistant app has been deployed and made available to users,
when users submit feedback via user acceptance testing, the development team
should collect and analyse the feedback in order to make necessary app adjustments
based on user preferences and needs.
❖ Given that the virtual assistant app is open to the public when users visit the app, it
should have a secure architecture to protect user data and assure privacy.
❖ Given that the virtual assistant app has been installed and made available to users,
additional features and improvements should be planned and executed in response
to user input and developing technology.
2. User Story:
As a virtual assistant user, I want virtual assistant to use basic natural language processing
(NLP) and machine learning methods to improve its understanding of industry-specific
queries so that it can provide accurate and relevant answers to my specific industry-related
questions.
Given that the virtual assistant is active and that NLP and machine learning methods are in
place when I ask the virtual assistant industry-specific questions, the virtual assistant should
be able to understand and interpret the queries correctly, as well as provide accurate and
relevant responses tailored to the specific industry context.
3. User Story:
As a project manager, I want the virtual assistant to track project progress and automate
basic work assignments so that I can efficiently manage and delegate tasks.
Given a project with assigned tasks,
When the virtual assistant is enabled,
Then it should be able to track the progress of each task,
And it should be able to automatically assign basic work tasks to team members based on
predefined rules or criteria.

4. User Story:
As a virtual assistant developer, I want to create AI models and algorithms that comprehend
industry-specific standards, norms, processes, and terminology, so that the virtual assistant
can respond to industry-specific queries accurately and relevantly.
Given a set of industry-specific standards, rules, processes, and terminology, the virtual
assistant should demonstrate an understanding of industry-specific concepts and be able to
respond appropriately to related queries once the AI models and algorithms are developed
and implemented.
5. User Story:
As an accountant, I'd like to use basic AI skills to automate invoicing activities and generate
accurate bills, allowing me to speed the invoicing process and decrease manual errors.
When given a set of invoice data, the virtual assistant should be able to automatically
extract relevant information from the data, generate invoices accurately based on the
extracted information, and provide a validation mechanism to ensure the correctness of the
generated invoices.
7.3 Screenshots demonstrating the relationships of story maps, feature workflows,
and release forecasts
Screenshots of the story maps feature workflows, & release forecasts have been provided
below.
Screenshot of the story map:

Feature workflows:
Release forecast:
8. Conclusion
8.1 Summary of the key findings and Recommendations
We have discussed several assignment-related topics in this document that are connected to the
creation of the virtual assistant app. Here is an overview of the main conclusions and suggestions:
Key Findings:
❖ Identification of the main user personas and comprehension of their traits.
❖ Identifying the issue and evaluating the product-market fit.
❖ Creating an MVP version of the software while taking technical and commercial aspects into
account.
❖ The development of an iterative backlog and the agile requirements process explanation.

❖ Considerations, methods, and goals for setting priorities while grooming the backlog.
❖ Presenting the release roadmap to corporate clients for approval.
❖ Developing thorough user stories with approval criteria after importing important artifacts.
❖ Relationships between story maps, feature workflows, and release projections are shown.
Recommendations:
❖ Engage with important user personas frequently to get their feedback and confirm the
functionality of the app.
❖ To keep up with market and competitive trends, conduct regular market research.
❖ To promote successful app development and delivery, encourage a collaborative and flexible
working atmosphere.
❖ Review and improve the backlog on a regular basis to account for shifting customer and
market demands.
❖ Ask business clients for feedback and confirmation at every stage of the development
process.
❖ Develop a thorough testing and quality assurance procedure to guarantee an app that is
dependable and user-friendly.
❖ Encourage efficient cross-functional teamwork and communication throughout the
development process.
❖ Analyse performance metrics frequently to gauge the app's effectiveness and pinpoint areas
for development.
❖ Relationships between story maps, feature workflows, and release projections are shown.

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