Glory Okoli’s Post

🚀 Hey LinkedIn Community, I am excited to share my new project on Coffee Shop Sales Analysis using MS-Excel. 🚀 Objective: The main objective of this project is to analyze retail sales data to gain actionable insights that will enhance the performance of the Coffee Shop. Analysis to do: How do sales vary by day of the week and hour of the day? Are there any peak times for sales activity? What is the total sales revenue for each month? How do sales vary across different store locations? What is the average price/order per person Which products are the best-selling in terms of quantity and revenue? How do sales vary by product category and type? Key Metrics 1) Total sales-$698,812.33 with a total footfall of 149,116 customers. Average bill per person is $4.69, and the average order per person is 1.44. Quantity Order by Hours: 2) Peak order quantity is observed between 8 AM and 10 AM, with a significant drop after 10 AM. 3) Sales Distribution: Coffee constitutes the largest sales category at 39%. Bakery items and Branded products follow at 28% and 12% respectively. 4) Order Size Distribution: Regular and small-sized orders dominate at 31% and 30% respectively. Large-sized orders constitute 30%. 5) Footfall by Store Location: Hell's Kitchen has the highest footfall at 236,511.17, followed closely by Astoria and Lower Manhattan. 6) Top 5 Products on Sales: Barista Espresso leads with sales of $91,406.20. Brewed Black Tea, Brewed Chai Tea, Gourmet Brewed Coffee, and Hot Chocolate also feature in the top five. 7) Orders by Weekdays: Orders are fairly consistent across weekdays with slight variations. 🌟 Conclusion: The coffee shop experiences the highest sales and customer footfall in the morning, particularly between 8 AM and 10 AM. Coffee is the top-selling product category, with regular and small-sized orders being the most common. Hell's Kitchen is the most popular store location. Barista Espresso is the best-selling product. Sales and footfall remain steady throughout the week, indicating a consistent customer base. GitHub link: https://lnkd.in/diD5GyMV Check out the dashboard and explore the data to gain insights. I would greatly appreciate your feedback and thoughts on the work I've put into it. #EXCEL #5DASHBOARD #PIVOTTABLE Ayushi Jain

📣 📣 Practical Post Alert #2 📣 📣 It was great to see so many people appreciated my Marketing Math post, so here's another for all my friends in the restaurant industry 🥙 🥞 🍲 Almost all restaurants (QSR, full service, fast casual) grade themselves on sales, traffic and check comps. You might also see these comps referred to as the below acronyms. 📈 Sales comps = SSSG (same store sales growth) 📈 Traffic comps = SSTG (same store traffic growth) 📈 Check comps = SSCG (same store check growth) 🔑 PRO TIP: Sales is a bi-product of two things TRAFFIC & CHECK. 🚨 Same store sales growth = traffic growth + check growth Example: ⚡ This week your restaurant delivered 4 points (+4) of traffic growth ⚡ It also saw a 3 point DECLINE (-3) of check growth ❓ What is your sales growth/SSSG for this week? ⚡ Simply (Add the numbers from traffic and check): +4 + (-3) = ~1 point of sales growth ++++ You can also use this in the inverse: ⚡ Sales up 4 ppts ⚡ Check up 6 ppts ❓ What is your traffic for that week? ⚡ Use the equation above and solve for traffic. Traffic would be -2. Christina Pedison Marisol Alviso Christine Guiang Bailie Bridges Andrew Greenberg Arushi K. Erica Hicks Anderson, MBA Dora Yvette Ortiz Georgeanne Erickson Mary Ellen Scott Daniel Fingerote Danny Klein

Hello LinkedIn community, I'm excited to share the details of my recent project on Coffee Sales Analysis by using MS EXCEL. The project dives into key sales trends to boost customer engagement and revenue. Here’s a quick summary: Key Insights: Sales Trends: Peak sales occur from 7 AM - 9 AM on weekdays, but drop off sharply after 10 AM. Weekends show reduced sales- Suggesting an opportunity for family promotions or brunch specials. Monthly Revenue: Steady growth from January to June, peaking at $166,485. February is the lowest-performing month, suggesting a need for winter promotions. Store Performance: Astoria location leads in sales, but Hell’s Kitchen and Lower Manhattan show strong potential for targeted marketing. Top-Selling Products: Barista Espresso, Brewed Black Tea, and Gourmet Coffee are driving revenue-perfect candidates for promotion through loyalty programs or combos. Category Dominance: Coffee makes up 38% of sales, followed by Bakery (12%). Bundling offers could drive even more revenue. Check out the full project details on GitHub: https://lnkd.in/eECjBWv8

Thrilled to share my latest project: the “Coffee Shop ☕and sales🚀 Dashboard”! 📊📈 In this Excel-based masterpiece, I’ve meticulously dissected sales trends, scrutinized customer engagement, evaluated product performance, and explored regional dynamics✧ Short Analysis of the project: Sales Products: Barista espresso☕, Brewed chai tea, the dashboard reveals them all. Product Categories: Coffee, Drinking Chocolate, Tea , Bakery🍪. Profit Pathways: Which products are our top products? And which product will give us more profit. Geographic Insights: Examined the sales distribution across different regions and identify key markets with best coffee sales. Discounts vs. Profitability: Understanding how discounts will affect overall profitability and identify optimal discounting strategies. Sales Metrics: From daily transactions to Monthly aggregates, it shows all sales patterns.

I'm super excited to share a milestone moment with all of you - I've just wrapped up my latest project, diving deep into Coffee Shop Sales Analysis! With the guidance and support of my amazing mentor, Zain Ul Hassan, I've been on a journey to unravel the secrets hidden within coffee shop data. We've uncovered fascinating insights, from the hustle and bustle of peak sales hours to the favorite picks of our customers. It's been an adventure! 1. Exciting sales insights uncovered! Our analysis reveals a surge in coffee shop sales during weekends, peaking at 10 am. Mornings, especially from 8 am to 10 am, witness heightened activity. Perfect timing for that morning brew! 2. Discovering prime sales time! 10 am emerges as the peak hour for customer activity, offering valuable insights for staffing and resource optimization. Ready to seize the day and serve up those delicious cups of coffee! 3. Monthly sales trends uncovered! From January to June, sales see a progressive rise, offering strategic foresight for planning and forecasting. Understanding seasonal trends is key to staying ahead in the coffee game! 4. Location insights unveiled! Hell's Kitchen shines with the highest weekly sales. Analyzing location-specific data guides tailored strategies for maximizing revenue across our coffee shop chain. 5. Understanding customer spend! The average price per person is $4.50, with an average order per person of 1.44. Valuable insights for pricing strategies and menu offerings, ensuring every sip is worth it! 6. Top sellers revealed! Coffee takes the lead, closely followed by Tea. Identifying these favorites enables targeted marketing and inventory management, keeping our customers caffeinated and happy! 7. Recognizing our best sellers! Barista Espresso leads the pack, closely followed by Brewed Chai Tea. Acknowledging these top performers allows for focused promotion and product optimization. Cheers to our winning brews! A massive shoutout to Zain Ul Hasan for being an incredible mentor every step of the way. Your wisdom and encouragement have truly made all the difference! I'd love for you all to peek into the world of coffee shop analytics with me. Check out the snapshot below to see what we've discovered! And hey, your thoughts and ideas are always welcome. Let's keep the conversation going! #CoffeeTalk #SalesStories #MentorMagic #Gratitude #InsightsThatMatter

After selling over 2 million cocktails in the last 5 years, I’ve realised that forecasting is one of the most important factors in running a successful FMCG business. In previous years, as we’ve headed into November and the run-up to Christmas - what I call the chaos quarter - we’ve always under-forecast. For example, last year, e-commerce really caught us off guard. We had no idea how popular the cocktails would be, and we didn’t anticipate the demand at all. But in hindsight, I shouldn’t have been surprised - our cocktails are a very giftable product: 🍸 The price point is perfect for people who are hard to buy for (aunts, uncles, brothers, sisters… almost everyone really!). 🍸 It’s a thoughtful gift—unique compared to just a bottle of wine. 🍸 You can choose cocktails based on the recipient’s taste, which makes it a more personal gift. While high demand is a great problem to have… Under-forecasting, ultimately, caused us problems like: 🍸 Missed sales opportunities during peak times. 🍸 Increased pressure on our production team. 🍸 Longer delivery times than we’d like. This forced us to play catch-up. But this year: 🍸 We’re more prepared, starting production in October ready for the rush. 🍸 We’ve improved our processes, allowing us to pack and ship more efficiently. 🍸 We’ve hired more temps, meaning I’m not packing boxes until 11pm every night (I hope!) So we’re far better equipped to tackle demand. However, one advantage has remained the same for us since we started: Making the products ourselves. Using a third-party manufacturer would leave us stuck when we run out of stock. But since we control production, we can just work longer hours to fulfil orders. TL;DR: Effective forecasting is key to managing demand and keeping customers happy, especially during busy seasons.

Coffee Shop Sales Analysis Here is an in-depth sales analysis for a coffee shop covering January to June 2023. Objective: The objective of this analysis is to provide valuable insights for stakeholders in the coffee shop market by examining metrics; Total Sales, Total Orders and Total Quantity Sold within the period. The analysis will help inform inventory management, promotional strategies, and operational efficiency improvements. Key Findings: Total Sales: June 2023 saw the highest sales at $166,487, with the lowest in February at $76,145. Total Orders: June also had the highest orders at 35,352. Quantity Sold: June's 50,942 items sold reflect high customer demand. Daily Sales: Average daily sales were $5,056, with variability on certain days. Weekday vs. Weekend: Weekdays outperformed weekends in sales. Store Location Performance: Sales were balanced across Astoria ($232,244), Hell’s Kitchen ($236,511), and Lower Manhattan ($230,057). Product Categories: Coffee and tea led sales, while blended chocolate lagged. Top Product Types: Favorites included Barista Espresso, Brewed Chai Tea, and Hot Chocolate. Hourly Sales: Peak sales were from 7:00 to 10:00 AM. Recommendations: Replicate June's success by optimizing peak sales periods (7:00 - 10:00 AM). Boost weekend sales with targeted promotions. Strengthen offerings in high-performing categories and improve lower-performing ones. Implement location-specific promotions to leverage balanced sales performance. Data Visualization: https://lnkd.in/d2yBAVAJ My Special thanks goes to Swapnjeet S for his guidance on this project. #DataAnalysis #CoffeeShop #SalesStrategy #PowerBI #BusinessInsights #DataVisualization

The Power of Engagement and Quality Lets read a short story Once upon a time in a vibrant village, there were two merchants, X and Y, who both sold fruit. X was known for his loud and persuasive sales pitches, promising that his fruit was the freshest and tastiest. Y, on the other hand, had a quieter approach. He would set up a small table, slice his fruit, and offer samples to passersby, often engaging them in conversations about their favorite fruits and recipes. One day, a royal chef visited the village in search of the best fruit for a grand feast. Attracted by X's enthusiastic claims, the chef purchased a large quantity from him. However, when the fruit was delivered to the palace, it turned out to be average, and the chef was disappointed. Curious about the other merchant, the chef then approached Y's stall. Y welcomed him warmly, offered samples, and asked about the dishes the chef was planning to prepare. He suggested specific fruits that would complement the dishes perfectly. The chef was impressed by Y's knowledge and the quality of his fruit, and he made a purchase. The feast was a tremendous success, and word spread about the delicious fruit from Y's stall. People started flocking to his stall, drawn not just by the quality of his fruit, but also by the personalized experience he offered. Y's business flourished, while X's loud claims began to fall on deaf ears. Key Learnings: 1. Engage Authentically: In sales and marketing, genuine engagement and understanding customer needs can create a lasting impact. Y's personal touch made customers feel valued and understood. 2. Quality Speaks for Itself: Delivering high-quality products consistently builds trust and loyalty. Y didn't need loud claims; his quality fruit did the talking. 3. Customer Experience Matters: Creating a memorable and positive customer experience leads to word-of-mouth referrals and repeat business. Y's approach made customers feel special and informed. 4. Sustainable Success: Long-term success is built on integrity, quality, and strong relationships, not just on immediate, flashy sales tactics. Y's steady and thoughtful approach ensured sustainable growth and customer loyalty. Please Like, Repost & Follow Aditya Raj for more such content Subscribe our newsletter: https://lnkd.in/gBM8P2hU #Sales #Marketing #Story #SalesManagement #Client #Relationship #Success #Growth

Hello Linkedin community, I am excited to share new project on Coffee Shop Sales analysis using MS Excel. Kindly visit my Github account for detailed Analysis. https://lnkd.in/gZXgZRKY 👉 Key Findings: ➡️ Maximum sales occur on Fridays, with sales reaching their lowest point on weekends. This indicates that the majority of our regular customers are office-going individuals. ➡️ Peak sales hours are from 8 to 10 a.m., with a decline in sales after that. ➡️ The sales trend is positive, showing a consistent increase month over month, with June reporting the highest sales. ➡️ Hill's Kitchen location has generated the highest sales and orders compared to other locations. ➡️ The coffee shop's average price per person is $4.69, with an average order per person of 1.44. ➡️ The Barista Espresso coffee is the top-selling product in terms of both quantity and revenue. ➡️ Coffee contributes the highest percentage (39%) of revenue among all categories. ➡️ Regular-size coffee cups are the best-selling product. 👉 Insights: ➡️ Implementing special offers or discounts in the evening could help boost sales after peak hours. ➡️ The focus should be placed on the main revenue-contributing categories, which are: - Coffee (39%) - Tea (28%) - Bakery (12%) - Drinking Chocolate (10%) - Coffee Bean (6%) Consider eliminating categories such as packed chocolate, loose tea, and flavored beverages, as they contribute only around 1% to revenue. Thank you, WsCube Tech and Ayushi Jain, for your support and guidance. #dataanalytics #dataanalyst #dataanalysis #insights #salesanalysis #salesinsights #excel #dashboard #exceldashboards#CoffeeShopBusiness #DataAnalytics #SalesInsights #Marketing #CoffeeLovers.

"Delighted to announce another launch of an exciting new project "Coffee Shop Sales by Power BI" Coffee_Shop_Sales_Dashboard Power BI Dashboard on Coffee Shop Sales Analysis Introducing my latest Project: The Coffee Shop Sales Project. 🔍 Project Objective: This initiative focuses on analyzing retail sales data to derive actionable insights aimed at boosting the Coffee Shop's performance. 🔍Project Overview: The Coffee Shop Sales Project is an in-depth analysis of retail sales data aimed at uncovering actionable insights to boost the performance and profitability of the coffee shop locations. By examining various aspects of sales, we strive to understand customer behavior, optimize operational efficiency, and enhance overall sales strategies. Insights:  🟢Total Sales: Total sales amount to $698.8K. 🟢Total Orders and Quantity: Total orders: 149.1K. Total quantity: 214.5K. 🟢Sales by Weekday: Weekdays account for 72% of sales. Weekends account for 28% of sales. 🟢Sales by Store Location: Hell's Kitchen: $236,511 Astoria: $232,244 Lower Manhattan: $230,057 🟢Sales by Hour: The document includes detailed hourly sales data for each day of the week, with peak sales hours generally around the morning (8 AM to 10 AM) and early afternoon (12 PM to 2 PM). 🟢Sales by TOP 5 Product Category and Store Location: Product categories include Barista Espresso,Brewed Chai,Hot Choclate,Gourmet brewed Coffee and Brewed Black Tea. Sales data is broken down by each store location. 🟢Monthly Sales by Store Location: The report shows monthly sales figures for different store locations. Conclusion The Coffee Shop Sales Project reveals that total sales reached $698.8K from 149.1K orders and 214.5K items sold. Weekdays dominate with 72% of sales, highlighting their significance. Hell's Kitchen, Astoria, and Lower Manhattan each contribute significantly to total revenue. Peak sales occur during morning and early afternoon hours. Key product categories such as Barista Espresso and Gourmet Brewed Coffee perform strongly across all locations. Monthly sales data provides valuable insights for identifying trends and optimizing operations. These findings can guide strategic improvements and targeted marketing efforts to enhance overall performance. Explore the Project here: https://lnkd.in/gtqdpyCZ Your Feedback and Suggestions are welcome!! #PowerBI #DataVisuvalization #SalesAnalysis #Dashboard