Data Science and Analytics Projects

I'm a dedicated data science and analytics consultant. Being that I've based my career off of collecting, organizing, analyzing and presenting insights. Below you'll find a selection of some of my most recent projects that showcase the type of clients I’ve work closely with.

Computer Manufacturing Company - Propensity Modeling

Overview: Our Computer Manufacturing Client is a leading manufacturer specializing in high-end computer systems for businesses and individuals. They have a wide range of products, but their high-end systems are their most profitable. Therefore, they approached us to help them identify which customers were more likely to purchase a high-end computer in the next 30 days.

Objective: To increase sales of high-end computer systems by using a propensity model to predict which customers are more likely to purchase them in the next 30 days.

Approach: We analyzed the client's customer data, including purchase history, demographics, and psychographics. We also conducted market research to understand the competition and industry trends. Our analysis identified several variables that were predictive of high-end computer purchases, such as previous purchase history, income level, job title, and website behavior.

Propensity Model: We developed a propensity model that used logistic regression to predict the likelihood of a customer purchasing a high-end computer in the next 30 days. We trained the model on a subset of the client's customer data and tested it on a holdout set to ensure accuracy.

Using the propensity model, we assigned each customer a score that indicated their likelihood of purchasing a high-end computer in the next 30 days. Customers with higher scores were considered more likely to buy a high-end computer, while customers with lower scores were considered less likely to purchase one.

Marketing Strategy: We recommended that the client use the propensity model to target their marketing efforts toward customers with higher scores. Specifically, we suggested that the client launch targeted email campaigns and social media ads to promote their high-end computer systems to customers with higher scores.

Results: The client implemented our recommendations and targeted their marketing efforts toward higher customer scores. As a result, they saw a significant increase in sales of high-end computer systems. Here are some specific results:

1. Increased sales: The client saw a 25% increase in sales of high-end computer systems compared to the previous 30-day period. This increase in sales was attributed to the targeted marketing efforts toward customers with higher scores.

2. Improved targeting: The client was able to target their marketing efforts more effectively using the propensity model. They could focus their resources on customers who were more likely to purchase a high-end computer, which resulted in a higher ROI on their marketing spend.

3. Increased customer satisfaction: Customers who received targeted marketing messages were more likely to purchase and were generally more satisfied with their experience. This led to an increase in positive reviews and customer loyalty.

Overall, the client was pleased with the propensity model and targeted marketing campaign results. As a result, they were able to increase sales of their high-end computer systems and improve their targeting of marketing efforts, which resulted in a higher ROI on their marketing spend.

Online Fashion Company - Customer Segmentation

Overview: Our client is a fashion brand that sells clothing, shoes, and accessories online. They have a wide range of products to cater to different styles and fashion preferences. They have been in business for a few years and have a loyal customer base, but they need help to increase their revenue and market share. Therefore, they approached us to help them find a way to grow their business.

Objective: To increase revenue and market share by customizing product offerings for different customer segments.

Approach: We analyzed the client's customer data, including purchase history, demographics, and psychographics. We also conducted market research to understand the competition and industry trends. Based on our analysis, we identified several customer segments with distinct needs and preferences.

Customer Segments:

1. Fashion-forward trendsetters: These customers always look for the latest trends and styles. They are willing to pay a premium for exclusive and high-end products.

2. Budget-conscious shoppers: These are customers who are looking for good deals and discounts. They are price-sensitive and value-conscious.

3. Classic and timeless shoppers: Customers prefer classic and timeless styles that never go out of fashion. They are willing to pay a premium for high-quality and durable products.

Customized Product Offerings: Based on our customer segmentation analysis, we recommended that the client customize their product offerings for each segment to meet their unique needs and preferences. Here are some examples:

1. Fashion-forward trendsetters: We recommended that the client introduce a new line of limited-edition products that are exclusive and high-end. These products would be marketed as "must-have" items for fashion-forward trendsetters.

2. Budget-conscious shoppers: We recommended that the client introduce a new line of affordable products that offer good value for money. These products would be marketed as "budget-friendly" options for customers looking for good deals and discounts.

3. Classic and timeless shoppers: We recommended that the client introduce a new line of high-quality, durable products with a classic and timeless design. These products would be marketed as "investment pieces" worth the price for customers who value quality and longevity.

Results: The client implemented our recommendations and customized their product offerings for each customer segment. They also launched targeted marketing campaigns to promote each product line to the relevant customer segment. As a result, they saw a significant increase in revenue and market share. Here are some specific results:

1. Fashion-forward trendsetters: The new line of limited-edition products was a huge success. It sold out within a few weeks of launch, and the client received positive feedback from customers excited to own an exclusive and high-end product.

2. Budget-conscious shoppers: The new line of affordable products was also a success. It attracted new customers who were previously hesitant to purchase from the client due to their premium pricing. The client also saw increased repeat purchases from budget-conscious shoppers who appreciated the excellent value for money.

3. Classic and timeless shoppers: The new line of high-quality and durable products was well-received by customers who value quality and longevity. These products became best-sellers, and the client saw increased revenue from customers willing to pay a premium for a timeless and durable product.

Overall, the client was pleased with the results of the customer segmentation analysis and customized product offerings. As a result, they saw a significant increase in revenue and market share, and they could attract new customers while retaining their existing loyal customer base.

Health Care Company - Funnel Analysis

Overview: Our client is a large healthcare company providing various medical products and services. They have a significant online presence and sell many products and services through an online sales funnel. However, they needed higher conversion rates on their online sales to funnel and approached us to help them increase their conversion rates using digital analytics.
Objective: To increase conversion rates on the company's online sales funnel using digital analytics.

Approach: We started by auditing the company's website and online sales funnel. We analyzed website traffic, user behavior, and conversion rates to identify areas for improvement. We also conducted market research to understand the competition and industry trends.

Digital Analytics: Using digital analytics, we identified several areas of the online sales funnel that were causing low conversion rates. These areas included slow page load times, confusing navigation, and poor user experience on mobile devices.

To address these issues, we recommended several improvements, such as optimizing page load times, simplifying navigation, and improving the mobile user experience. We also recommended adding tracking codes and implementing A/B testing to measure the effectiveness of the improvements.

Marketing Strategy: We developed a targeted marketing strategy to drive more traffic to the website and improve conversion rates. Specifically, we recommended that the company use targeted social media ads and search engine optimization (SEO) to drive more traffic to the website. We also suggested that the company use retargeting ads to re-engage customers who had abandoned their shopping carts.

Results: The company implemented our recommendations and saw a significant increase in conversion rates on their online sales funnel. Here are some specific results:

1. Increased conversion rates: The company saw a 40% increase in its online sales funnel after implementing the recommended improvements and marketing strategy.

2. Improved user experience: Customers reported a much better user experience after the improvements were made. Page load times were faster, navigation was more straightforward, and the mobile user experience was significantly improved.

3. Increased revenue: The company saw a significant increase in revenue due to the increased conversion rates. They could sell more products and services through their online sales funnel, which resulted in a higher ROI on their marketing spend.

Overall, the company was pleased with the digital analytics and targeted marketing campaign results. They increased conversion rates on their online sales funnel and improved the user experience, which resulted in a higher ROI on their marketing spend.

TECH COMPANY - CONSUMER SEGMENTATION

We used K-means clustering to segment our clients buyers based on both demographic and transaction variables. Customer Segmentation allows our clients to target both buyers and acquisition groups based on like attributes.