Analytics and data science business case studies to identify opportunities and inform decisions about products and features. Topics include Markov chains, A/B testing, customer segmentation, and machine learning models (logistic regression, support vector machines, and quadratic discriminant analysis).

In this project, a RFM model is implemented to relate to customers in each segment. Assessed the Data Quality, performed EDA using Python and created Dashboard using Tableau.

Customer analytics has been one of hottest buzzwords for years. Few years back it was only marketing department’s monopoly carried out with limited volumes of customer data, which was stored in relational databases like Oracle or appliances like Teradata and Netezza. SAS & SPSS were the leaders in providing customer analytics but it was restricted to conducting segmentation of customers who are likely to buy your products or services. In the 90’s came web analytics, it was more popular for page hits, time on sessions, use of cookies for visitors and then using that for customer analytics. By the late 2000s, Facebook, Twitter and all the other socialchannels changed the way people interacted with brands and each other. Businesses needed to have a presence on the major social sites to stay relevant. With the digital age things have changed drastically. Customer issuperman now. Their mobile interactions have increased substantially and they leave digital footprint everywhere they go. They are more informed, more connected, always on and looking for exceptionally simple and easy experience. This tsunami of data has changed the customer analytics forever. Today customer analytics is not only restricted to marketing forchurn and retention but more focus is going on how to improve thecustomer experience and is done by every department of the organization. A lot of companies had problems integrating large bulk of customer data between various databases and warehouse systems. They are not completely sure of which key metrics to use for profiling customers. Hence creating customer 360 degree view became the foundation for customer analytics. It can capture all customer interactions which can be used for further analytics. From the technology perspective, the biggest change is the introduction of big data platforms which can do the analytics very fast on all the data organization has, instead of sampling and segmentation. Then came Cloud based platforms, which can scale up and down as per the need of analysis, so companies didn’t have to invest upfront on infrastructure. Predictive models of customer churn, Retention, Cross-Sell do exist today as well, but they run against more data than ever before. Even analytics has further evolved from descriptive to predictive to prescriptive. Only showing what will happen next is not helping anymore but what actions you need to take is becoming more critical. There are various ways customer analytics is carried out: Acquiring all the customer data Understanding the customer journey Applying big data concepts to customer relationships Finding high propensity prospects Upselling by identifying related products and interests Generating customer loyalty by discovering response patterns Predicting customer lifetime value (CLV) Identifying dissatisfied customers & churn patterns Applying predictive analytics Implementing continuous improvement Hyper-personalization is the center stage now which gives your customer the right message, on the right platform, using the right channel, at the right time. Now via Cognitive computing and Artificial Intelligence using IBM Watson, Microsoft and Google cognitive services, customer analytics will become sharper as their deep learning neural network algorithms provide a game changing aspect. Tomorrow there may not be just plain simple customer sentiment analytics based on feedback or surveys or social media, but with help of cognitive it may be what customer’s facial expressions show in real time. There’s no doubt that customer analytics is absolutely essential for brand survival.

A collection of SQL-based data analytics projects demonstrating techniques for data extraction, transformation, analysis, and visualization. These projects showcase practical SQL queries and insights across various domains, including sales, customer segmentation, and employee attrition analysis.

I use various Data Science and machine learning techniques to analyze customer data using STP framework. I preprocessed the data, performed segmentation, hierarchical clustering, k-means, PCA techniques with a lot of visualizations to segment and understand customer data. I have performed Purchase Analytics (both descriptive analysis and predictive analysis). Used deep learning to enhance my model.

LEO CDP is an open-source, AI-first Customer Data Platform for building customizable, self-hosted, privacy-friendly CDP infrastructure. It unifies data collection, enables real-time analytics, audience segmentation, and personalized marketing — powered by big data and machine learning.

An end-to-end data analytics project using SQL, Python, and Power BI to perform customer segmentation

Advanced SQL analytics project extending prior EDA work. Includes change-over-time, cumulative trends, performance benchmarking, segmentation, part-to-whole analysis, and customer/product analytical reporting using window functions and real-world data warehouse logic.

Big data & Data Science: Making smarter decisions through fraud detection, management of customer data, risk modeling, real-time predictive analytics, customer segmentation, etc.

9 Email Marketing Tips For Content Marketers Even “agnostics” regarding email marketing can't hash out the following evidence - the average ROI from this promotional practice is close to 3,800%. Measureless opportunities to scale up and relative cheapness, compared to other reaching-out channels, are the two reasons why the email marketing is fair-haired by businesses. However, this is not about the price and physical extent alone. The chief advantage is a better alignment of communication with customers. If you hope a certain content strategy brings desirable results, overlooking the quality of mailing messages will be a sorry pitfall. Always keep in mind that newsletters, welcome, retention, and other emails are not just a brand's facade - but a powerful tool for generating conversions. By joining sides of email and content strategies, you can come up with synergy from both. In this guide, we’ll cover a few recommendations for content marketers on how to write email messages that work. Tips for email marketing Segment your list Split the batch of email recipients into smaller groups based on chosen criteria, and mail distinct relevant messages - for each. You can use recipients' GEO, demographic characteristics, or purchase history to distinguish homogeneous clusters and proceed with the content planning. Segmentation is the basic premise for personalization, and if you still doubt why bothering about the latter - here are just a few numbers we took from Instapage: 52% of customers claim they do care if the message was tailor-made or not 82% of marketers say that mail personalization increases the open ratio custom emails have 41% more unique clicks than mass-produced ones. To avoid a fragmented approach, use data from CRMs, website analytics tools, and other sources to define segments. Concerning phrasings, a good idea is to create Buyer personas profiles. Thus, you'll be able to choose the appropriate message length and wording. Say, design a newsletter to promote paid subscription for an email validator service. You've decided to distinguish corporate clients based on their company size and determined the following groups: #1 - B2Bs and #2 - sole entrepreneurs. Possible messages for the two: #1. Our "XXL" plan is perfect for agencies and enterprises. One can add unlimited users and conduct up to 100,000 checks per month. #2. With our "S" you get 1,000 credits and 5,000 unique recipients - for only $33 per month. Plus - a 7-days free trial. Use interactive content The best content marketers know that interactive content came into vogue a long time ago. As to emails, here are the most common examples: CSS animated buttons If you include CTAs buttons (that we hope you do) - liven them up a bit. Add an animated hover effect, so that every time a recipient puts a cursor on a button, it changes shape, shade, color, or text. “Add hover to emphasise objects”, source This shouldn’t necessarily be something dramatic - add tiny accents that will yet grab the user's attention. starring “Add a star rating component to engage readers with content”, source Including ranking or reviewing widgets in the email body is one of the most working ways to engage the reader with the message. Ask recipients to assess your product or service with stars. Add the link to Google Forms if you want to receive an extended opinion on overall customer satisfaction. pictures' rollovers “Use animated images to describe goods better”, source The effect is eagerly used by the ones who promote online stores. Using The rollover allows to show goods from different angles or even play with recipients, if relevant. Take into account that this feature only works on desktops - mobile mail users will see the very first picture only. images carousel “Add pieces of text directly on images”, source If you want to enhance goods cards with descriptive content, say - price and shipping details, use a carousel instead of a rollover. As so, you can add more info pictures to the email body and, hopefully, convert more recipients into customers. a countdown “Countdowns work well for limited in time offers”, source Again, this type of interactive content fits the online shopping niche. Animated clocks amplify urgency and theoretically increase conversions. But it's important to stay extremely careful and not to sound desperate - otherwise, the newsletter will end up in the recipient's "Spam". Improve design The attractiveness of an email is something granted on certain terms, indeed. Not all emails need to be flashy or include expensive designs. However, there are some prevailing common trends in the matter. By following them, you seem to show the recipient that your company is moving in step with the times, and not stuck in the 2000s. Here's the shortlist from the TOP email design trends list that a 99designs provides - as of 2021: magazine-styled “Make newsletters to look a bit editorial”, source More and more newsletters tend to look like a centerfold from good old printed media. With a strict following to the "Less is more" principle - clear fonts, short phrases, HD-quality images with a few objects on them, and short CTAs. hand-made illustrations “Unique pictures create a distinct flavour of your brand”, source Tailored icons or sketchy images - whatever fits your mailing purpose, just make sure it's not too bright, contrast, or overloaded with details. Give preference to clean colors. skeuomorphic objects This is when a design resembles a real object. To see an example - just open a reader App on your smartphone. “A skeuomorphic bookshelf”, source HD photographies “If you operate in the luxury segment, do not skimp on email visuals”, source These are expensive content, but if you work in fashion or other chick industries - it may be worth the effort. animated content Yeap, we've covered this in a previous tip. single scroll “Looks especially good on smartphones”, source Place the entire email content, including buttons, on the endless-looking long frame. Focus on conversions Stay focused on what's your mailing purpose. Don't forget that everybody expects to see a good ROI from email actions at the end of the reporting period. Craft effective CTAs - perceive these not as a sole button with a "Download now" text or so, but as an entire sense of a message that you write. To create a captivating CTA copy, adhere to the below advices: include win-win propositions Even though you’re not providing a customer with a discount or cash refund at the moment, your proposition may include a non-monetary incentive. New arrivals, selection of the latest news, free copies, advice from experts - the only rule here is to offer what’ll hold in high esteem. trigger on emotions Don't long-windedly list benefits. Instead, simulate a life situation and show how your product or service can help. use several CTAs throughout the email Email body may be viewed in several scrolls, especially when via small mobile devices’ screens. If you add a call to action at the beginning of the message, a mere number of users will get back to it after finishing reading the content. Thus, you may lose potential conversion. Include several buttons throughout the email body, but don’t sound repeatedly - change calls’ forms and wording. Encourage readers to reply Driving recipients to reply is challenging yet able to be done. First, choose the proper writing tone. According to an extensive study of emails that didn’t get a response, the most preferable is a 3rd-grade reading level. “Too elementary or too proficient tone may scare away readers”, source Of course, you must apply this recommendation with an eye on the recipient. If you mail to a professor or a government agency, a “3rd-grade” rule isn’t applicable. But all else being equal - simplify the lexicon to the level a schoolchild can understand it. Another trick is to sound overall happy. Emails that are enhanced with positive emotions get 10-15% more replies, on average than neutral ones. The best manner is to choose a slightly warm tone. Exaggerated excitement may look weird and even suspicious, especially when reaching out to business partners. And don’t forget about courtesy. A rare person will respond if you address him or her with a hair-raising “To whom it may concern” phrase. Make it personal Personification shouldn’t be confused with personalization. The second is rather about mailing fitting content from a commercial perspective, while the first term - about addressing the recipient as a one-off personality. Personal emails start with the recipient’s name - and no other way. They include references to the user's interests or past actions. For example, if your tourist agency’s client is interested in island vacations - you shall approach him or her with respective offers. They also shall contain personalized promotions, if any. The best way to expand this approach on hundreds or thousands of recipients is to launch trigger-based email campaigns. Create delivery scenarios for different segments or stages of a sales pipeline. Then prepare a fitting sequence of relevant content - for every single scenario. To give a human face to mailing, one can practice greetings, as well. Birthdays, state holidays, anniversaries, a new status in the loyalty system - there are a lot of examples of what one may congratulate the customer with. Keep your emails out of spam folders It is better not to launch mailing at all than to use an untrustworthy emails’ database. The risks are much higher than a slew of undelivered messages - from harming a sender's reputation to being banned by mailing systems. So it's better to stay proactive: tidy away broken, misspelled, temporary, or other worrisome emails from the database - either manually or with the help of software collect a valid email address only - through email finders avoid spam-trigger words establish a double opt-in validation set the correct mailing frequency. Make sure your emails look clean and crisp Newsletters shall afterall bring revenues - whether you want it or not. But in a bid of quantity, don’t lose the overall content integrity and sense: a subject line, pre-header, header, email body, and calls shall be consistent with one another the copy must be of the proper size; although the length depends on many factors, stick to an “ideal” interval - 50 to 125 words if can, don’t attach too many files or links to external websites - mailing filters are suspicious to these adapt the layout to fit smaller screens - nothing looks worse than broken email elements when you open it on mobile. Wrapping up It doesn't make much difference whether you create mailing content for personal or business purposes - these email marketing tips will serve both. No strains here - the recipient’s interest should be at your forefront. If you can hook him or her with the content by using tricks we've covered, you’ll never fail with enough conversions.

Mall Customers Clustering Project Unleash the power of K-means clustering to decode mall customer behavior! From data exploration to 3D visualizations, we navigate through demographics and spending patterns. Join our journey into customer segmentation for strategic insights. Let's redefine retail analytics! 🛍️📈

Customer segmentation🛍️😄 task includes RFM model, data analytics and Machine Learning.

📊 Data analytics project exploring patterns in return behavior across e-commerce transactions. Includes visual insights, customer segmentation, and actionable trends.

Explore the E-commerce Customer Segmentation Analysis project! Dive into data analytics with an e-commerce dataset, aiming to understand customer behavior, identify segments, and glean insights for targeted marketing. This repository covers data cleaning, statistics, clustering, and visualization, offering a hands-on journey into data analytics. 🚀

Three business analytics case studies were undertaken, encompassing market basket analysis, customer segmentation, and campaign management. SAS Visual Data Mining and Machine Learning on SAS Viya was utilized to explore data and provide insights. A comprehensive report addressing both technical and business aspects was delivered.

In this project, we explore the sales data for a retail company and generate various analytics and insights from customer's past purchase behavior. I used SQL to analyze sales revenue. We also perform customer segmentation analysis using the RFM technique.

The aim of this data analytics project is to perform customer segmentation for an e-commerce company. By analyzing customer behavior and purchase patterns, we aim to group customers into distinct segments using clustering algorithms.

End-to-end project on customer segmentation and retention strategy built on transactional data, combining RFM-based analytics, churn modeling, deployment, and monitoring to support data-driven retention decisions.

eCommerce Sales Interactive Dashboard Overview: 📊 Sales Overview: Visualize overall sales performance with interactive charts and graphs. 🛍️ Product Analytics: Dive deep into product-level data to identify top-selling items and optimize inventory. 👥 Customer Segmentation: Understand customer behavior through segmentation and purchasing patterns.

I use various Data Science and machine learning techniques to analyze customer data using STP framework. I preprocessed the data, performed segmentation, hierarchical clustering, k-means, PCA techniques with a lot of visualizations to segment and understand customer data. I have performed Purchase Analytics (both descriptive analysis and predict…

End-to-end retail analytics with PostgreSQL KPIs, CLV/RFM segmentation, and JSON data exports. Interactive dashboard built using HTML/CSS/JS and Chart.js. Covers sales trends, customer value, store ranking, and product performance.

This study is about performing the Stock Segmentation and Customer Congregation for an online retail service using analytics data. Almost a year’s data has been collected by the retail which needs business strategies to increase their sales, deliver customer requirements, plan the inventory, and increase sales by widening the horizon.

Predictive Analytics : Project on customer data from a store that answers : 1.Segmentation - Can we find the Holiday Shopper or Discount Freak clusters among customers using latent class or k-means analysis? 2.Price Sensitivity - What effect does increasing price have on the revenue generated by a segment? 3.Market Basket - Which products can be sold together? 4.Churn - When will a customer leave us? 5.Survival Modelling - Can we predict the lifetime value of a customer? and much more using predictive analytics in SAS

📊 Enterprise Power BI sales dashboard with advanced KPIs, customer segmentation, and interactive analytics - Complete template with sample data

A comprehensive business intelligence project analyzing retail performance with predictive analytics, customer segmentation, and interactive dashboards for data-driven decision making

End-to-end SQL-based analytics project for a simulated SaaS product. Includes data cleaning, transformation, KPIs, churn analysis, customer segmentation, and reporting views.

This project analyzes a Customer Segmentation Dataset (commonly known as the Mall Customers dataset) to derive business insights through exploratory data analysis and clustering techniques. A practical application of Data Analytics and Machine Learning for customer behavior understanding and targeted marketing.

Retail analytics platform with sales forecasting (Prophet), customer segmentation (K-means), and interactive dashboards. Built with Python, SQLite, and Streamlit for end-to-end data analysis.

A comprehensive data analytics project for GenX E-Commerce Company aimed at boosting revenue through customer segmentation. This repository features RFM analysis and interactive Power BI dashboards to identify high-value customer behaviors and provide actionable growth strategies.

This is an end-to-end Data Analytics project focused on analyzing a European e-commerce fashion dataset. The primary goal was to process complex transaction and customer data to derive actionable business intelligence, focusing on sales performance, customer segmentation, and product trends across European markets