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Lychee Boba Shop | Growth Strategy Analysis
California, U.S
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TIMELINEJune, 2024
MY ROLE & CONTRIBUTIONBusiness Analyst (Strategy & Operation)
TOOLS & SKILLSExcel | Google Sheet
Data Cleaning | Data Wrangling| Pivot Tables | Advanced Formulas | Data Visualisation
BACKGROUND 👣Lychee Boba Shop has 3 stores in different cities (Cit A,B,C) in California. Customer order through the app and pick up in store.
OBJECTIVE
Increase total sales revenue across all location🧋
Menu prices for the year have been set. Based on one week of app data, provide recommendations to increase total sales revenue.
FRAMEWORK
Increase Li-Chi Boba Shop’s total sales revenue (menu prices for the year have been set already).
Sales Revenue ($)
=
=
# of Units Sold
x
Avg. Selling Price
Business OpportunitiesIncrease customers (acquire new customers + retain existing customers)Increase order frequency (more orders per person per week)Increase order size (more drinks per order)
As menu prices for the year have already been set, we can’t increase the selling price
ANALYSISBUSINESS OPPORTUNITY 1 Increase Customers
BUSINESS OPPORTUNITY 2 Increase Order Frequency
BUSINESS OPPORTUNITY 3 Increase Order Size
INCREASE CUSTOMER
Increase advertising and marketing effort in City A (Highest revenue & order; Frequent & Small transaction) to acquire new customer, while leveraging City B’s premium engagement (higher average order value) through tailored loyalty incentives.
By average order value: City A $44.3, City B: $46.9, City C$44.7.
City A has the highest total orders and revenue at $358 and $15K, respectively, followed by City C (354, $15K), and City B (337, $15K).
City B, despite having the fewest order, has the highest amount spent per transaction ($46.9), followed by City C($44.7), and A($44.3).
Despite City A has highest number of orders (358), its lowest average order value indicates frequent but smaller purchases. While City B's fewer orders with higher spending per transaction suggests a preference for premium purchases.
RECOMMENDATION
Leverage City A's high demand (total orders and revenue), capitalize on the existing momentum by increasing marketing and advertising spend, and introduce a referral program to acquire new users.
Given that City B has the highest average spending, enhance the premium experience with targeted marketing activities, and establish a loyalty program with tiered benefits to encourage repeat purchases.
INCREASE CUSTOMER
Drive traffic to City C's store (Best operational excellence) to build customer loyalty and retention, while conducting research in City A's store (Least operational excellence) to diagonise and enhance customer experience.
City C has the best operational excellence (highest average rating, lowest refund, shortest avg. prep time), while City A has the least operational excellence (lowest avg. rating, highest refund, and highest avg. prep time).
City A's high revenue and order volume coincide with longer prep times and higher refunds. This suggests that operational strain may be affecting customer satisfaction and spending behaviour.
City C’s faster service and fewer errors correlate with higher customer satisfaction, which likely contributes to greater customer loyalty and repeat business.
RECOMMENDATION
City C's best operational excellence has potential to build customer loyalty. Recommend drives traffic (e.g. Online marketing, SEO etc) and implement marketing campaign (e.g. Loyalty program) for customer acquisition and downstream retention.
City A's has least customer satisfaction, hypothesise that high order volume may be overwhelming operational efficiency, leading to longer prep times, more errors, and lower satisfaction. Recommend conducting qualitative research (e.g., customer journey mapping, user interviews, in-app surveys) to identify root causes and develop targeted strategies such as staff training and equipment upgrades to enhance customer retention.
INCREASE ORDER FREQUENCY
Leverage the social nature of peak times (6-10 PM; 12-3 PM) and high-traffic days (Friday-Monday) through targeted emails and promotions (group discounts, Bxuy 2, Get 1 Free offers) to increase engagement.
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Order volumes are highest from Friday to Monday, with Saturday as the peak day.
There's a noticeable decrease in order volumes on Tuesdays and Wednesdays across all cities.
Order volume has two peaks. Highest peak occurs from 6PM-10PM at night, another from 12PM-3PM in the afternoon.
RECOMMENDATION
General demand peaks at two key periods: 6 PM-10 PM and 12 PM-3 PM, coinciding with lunch and dinner times, suggesting social activity. Enhance engagement by sending targeted emails and push notifications before the peaks. Promote offers that encourages social dynamics (e.g. Buy 2, Get 1 Free, percentage discounts on larger orders) to capitalise on the social context.
Implement weekend-exclusive promotions that cater to social gatherings during quieter hours, (e.g. special discounts on bulk purchases).
Weekday demand dips, highlighting opportunities for targeted promotions to stimulate activity during these typically quieter periods (e.g., happy hour specials, group discounts, and local business lunch deals).
INCREASE ORDER SIZEIncentivize low spenders (44% of customers ordering below 5 drinks per order) with upsell opportunities, benefits, and promotions to increase the number of boba sold per order, driving revenue growth.
Avg order size = 5 unit per order.
44% of users falls below the average order size of 5 drinks per order.
Customer Segment
High Spenders: >5 units per order, 45.3% of customers; Average Spent = $65.2.
Medium Spenders: = 5 units per order, 10.7% of customers; Average Spent = $44.4.
Low Spenders: <5 units per order, 44% of customers; Average Spent = $23.7.
Positive correlation between order size and spending
Customers who order more than 5 units per order spend significantly more, with average spending increasing from $23.74 (<5 units) to $65.17 (>5 units).
RECOMMENDATION
