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Petal & Vine flower shop scenario

WGU academic capstone · completed case study

Transforming fragmented customer records into one controlled CRM.

Petal & Vine is a fictional five-person flower shop created for my B.S. Information Technology capstone. I planned and documented a cloud-based HubSpot implementation using a structured Waterfall approach.

5business users
7tracked milestones
8 / 8deliverables met
100%modeled user adoption
Interactive process viewBefore and after the CRM
Sticky notesAllergy: liliesEasy to misplace
SpreadsheetCustomer_List_Final_3.xlsxDuplicates and missing fields
Email inboxWedding order detailsKnown by one employee
Paper orderDelivery instructionsNot visible to the full team
!

Core risk: customer history, preferences, and order status were spread across individual memory and disconnected sources.

Petal & VineCustomer Relationship Dashboard
Centralized
Open opportunities14
Orders this month38
Follow-ups due6
New inquiry 6Quote sent 4Deposit paid 2Confirmed 1Delivered 1
AR
Alex RiveraWedding · Peonies · No lilies · Delivery notes saved

Target state: one searchable source for customer records, deal stages, activities, ownership, and reporting.

Business problem

Manual records made routine work reactive.

Employees searched handwritten notes, spreadsheets, email inboxes, and receipts to reconstruct customer history. That created lost information, duplicated effort, inconsistent service, and poor scalability.

Selected solution

HubSpot CRM Free Tier.

A cloud platform provided contact management, customizable deal stages, activity history, user access, and reporting without requiring Petal & Vine to purchase or maintain local server infrastructure.

Delivery method

Structured Waterfall implementation.

Requirements, design, configuration, migration, testing, training, deployment, and support were sequenced with explicit milestones and sign-off points.

Implementation walkthrough

Five phases from requirements to operational handoff

Select a phase to see the work, the control being applied, and the artifact produced.

Phase 01

Requirements & analysis

Map the current workflow and define what the new system must preserve, improve, and make measurable.

    Primary output Documented requirements baseline

    Customer fields, workflow needs, roles, permissions, and acceptance criteria become the reference point for every later decision.

    Control appliedScope clarity before configuration

    Schedule performance

    Planned duration versus modeled actual duration

    Two phases expanded for real project reasons: source data took longer to locate, and additional training improved user readiness.

    Planned Actual Schedule variance
    −1 dayDesign completed ahead of plan
    +4 daysMigration paused while missing records were located
    +3 daysTraining extended to improve manager proficiency

    Modeled post-implementation results

    Success was tied to measurable operational outcomes

    These figures are from the academic post-implementation scenario, not claims about a real client deployment.

    3 → 0

    Weekly data-management errors

    The scenario reports a 100% reduction within one month of deployment.

    10–15 → 6–9

    Hours spent searching each week

    Centralization surpassed the planned 25% reduction in manual information retrieval.

    100%

    User adoption

    All five modeled users were active within two weeks of training.

    < 1 min

    Customer-history access

    Every team member could retrieve a complete profile from front-desk computers within the target time.

    Goals and deliverables

    Every documented deliverable was marked complete.

    The capstone connected technical outputs with adoption work. Configuration alone was not considered success; migration, training, UAT, and post-launch support were part of the finished system.

    CRM configuration and design planProperties, modules, roles, and workflow structure

    Cleaned and migrated customer dataMapping, duplicate handling, import, and verification

    Functional CRM and automationsContacts, activities, deal stages, and email integration

    Training materials and full-team sessionsRole-focused guides and practical scenarios

    User acceptance testing and sign-offIntegrity checks, permissions review, and feedback

    Post-deployment support planAdministration guide, monitoring, and optimization path

    Project lessons

    Risk becomes manageable when assumptions are made visible early.

    The biggest variance came from assuming source records were readily available. A stronger real-world plan would include an early data-discovery gate, minimum-data readiness criteria, and contingency tasks before the migration calendar begins.

    Data readinessVerify availability before committing migration dates.
    AdoptionTrain by role and allow for different learning speeds.
    ControlsKeep sign-off gates at requirements, UAT, and launch.

    What this demonstrates

    Requirements, migration controls, documentation, UAT, and operational handoff.

    The project shows how I organize a technical implementation around business risk and user adoption.