- Amazon Web Services Webinar: Leverage data sets to create a customer-centric strategy and improve business outcomes - Oct 14, 2021.
Register now for this webinar, Oct 28, to learn how using third-party data enhances applications to better prioritize your target customer - helping you build a more customer-centric business.
AWS, Business, Customer Analytics, Webinar
- How I Built A Perfect Model And Got Into Trouble - Oct 12, 2021.
Data-driven decisions, actionable insights, business impact—you've seen these buzzwords in data science jobs descriptions. But, just focusing on these terms doesn't automatically lead to the best results. Learn from this real-world scenario that followed data-driven indecisiveness, found misleading insights, and initially created a negative business impact.
Analytics, Business, Customer Analytics, Finance, KPI, Metrics
- How to Effectively Obtain Consumer Insights in a Data Overload Era - Sep 17, 2020.
Everybody knows how important is understanding your customer, but how to do that in an era of Information Overload?
Analytics, Customer Analytics, Data Science
- 3 Key Data Science Questions to Ask Your Big Data - Jun 3, 2020.
The process of understanding your data begins by asking 3 questions at the highest level, and then iteratively asking hundreds of cascading questions to get deeper insights.
Big Data, Business, Customer Analytics, Data Science, Metrics
- Customer Churn Prediction: A Global Performance Study - May 13, 2020.
This article details an automated machine-learned approach to predict customer churn and its results across selected communication service providers around the globe.
Churn, Customer Analytics, Predictive Analytics
- How To Build Your Own Feedback Analysis Solution - Mar 12, 2020.
Automating the analysis of customer feedback will sound like a great idea after reading a couple hundred reviews. Building an NLP solution to provide in-depth analysis of what your customers are thinking is a serious undertaking, and this guide helps you scope out the entire project.
Customer Analytics, NLP, Text Analytics
- Passive Data Collection and Actionable Results: What to Know - Feb 21, 2020.
There are plenty of ways to get actionable results by using passive data. However, such an outcome will not happen without careful forethought. Data analysts must consider several crucial specifics, including what questions they want and expect the information to answer, and how they'll apply the findings to aid the business.
Analytics, Customer Analytics, Data Curation, Datasets
- Random Forest® vs Neural Networks for Predicting Customer Churn - Dec 26, 2019.
Let us see how random forest competes with neural networks for solving a real world business problem.
Churn, Customer Analytics, Neural Networks, random forests algorithm
- Customer Segmentation Using K Means Clustering - Nov 4, 2019.
Customer Segmentation can be a powerful means to identify unsatisfied customer needs. This technique can be used by companies to outperform the competition by developing uniquely appealing products and services.
Clustering, Customer Analytics, K-means, Python, Segmentation
- Customer Segmentation for R Users - Sep 26, 2019.
This article shows you how to separate your customers into distinct groups based on their purchase behavior. For the R enthusiasts out there, I demonstrated what you can do with r/stats, ggradar, ggplot2, animation, and factoextra.
Customer Analytics, R, Segmentation
- Customer Churn Prediction Using Machine Learning: Main Approaches and Models - May 14, 2019.
We reach out to experts from HubSpot and ScienceSoft to discuss how SaaS companies handle the problem of customer churn prediction using Machine Learning.
Altexsoft, Churn, Customer Analytics, Machine Learning
- Audience Segmentation - Jun 6, 2018.
The process of audience segmentation is not about just statistics, it’s about finding your ideal clients and choosing the right way of interaction with them.
Clustering, Customer Analytics, Segmentation
- Calculating Customer Lifetime Value: SQL Example - Feb 15, 2018.
In order to understand how to estimate LTV, it is useful to first think about evaluating a customer’s lifetime value at the end of their relationship with us.
Customer Analytics, Lifetime Value, SQL, Statsbot
- A Guide for Customer Retention Analysis with SQL - Dec 19, 2017.
Customer retention curves are essential to any business looking to understand its clients, and will go a long way towards explaining other things like sales figures or the impact of marketing initiatives. They are an easy way to visualize a key interaction between customers and the business.
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Analytics, Customer Analytics, SQL, Statsbot
- The danger in comparing your campaign performance against an average - Oct 26, 2017.
Performance measurement is only meaningful when compared against a benchmark. While “average” is a good, and easy to understand metric, it could be very deceptive.
CleverTap, Customer Analytics, Metrics
New-Age Machine Learning Algorithms in Retail Lending - Sep 13, 2017.
We review the application of new age Machine Learning algorithms for better Customer Analytics in Lending and Credit Risk Assessment.
Credit Risk, Customer Analytics, Deep Learning, Fintech, Machine Learning, Recurrent Neural Networks
- Do We Need Balanced Sampling? - May 4, 2017.
Resampling is a solution which is very popular in dealing with class imbalance. Our research on churn prediction shows that balanced sampling is unnecessary.
Customer Analytics, Data Mining, Data Science
- Beginner’s Guide to Customer Segmentation - Mar 9, 2017.
At the core of customer segmentation is being able to identify different types of customers and then figure out ways to find more of those individuals so you can... you guessed it, get more customers!
Clustering, Customer Analytics, Histogram, K-means, Yhat
- The Challenges of Building a Predictive Churn Model - Mar 8, 2017.
Unlike other data science problems, there is no one method for predicting which customers are likely to churn in the next month. Here we review the most popular approaches.
Churn, Customer Analytics, Datascience.com, Survival Analysis
- What is Customer Churn Modeling? Why is it valuable? - Mar 1, 2017.
Getting new customers is much more more expensive than retaining existing ones, so reducing churn is a top priority for many firms. Understanding why customers churn and estimating the risks are powerful components of a data-driven retention strategy.
Churn, Customer Analytics, Datascience.com
- The Top 5 KPIs to Consider When Measuring Your Campaign - Feb 28, 2017.
When it comes to measuring marketing campaign performance or analysing customers in any business, below top 5 Key Performance Indicators (KPIs) needs to be used to strategically drive the business.
Churn, Customer Analytics, KPI, Metrics, ROI, Social Media
- Doing the Data Science That Drives Predictive Personalization - Sep 9, 2016.
Agile collaboration within data science teams is essential to the vision of customer analytics and personalization. Attend IBM DataFirst Launch Event on Sep 27 in New York City to engage with open-source community leaders and practitioners.
Clustering, Customer Analytics, IBM, New York City, NY
- Data Science of Reviews: ReviewMeta tool Automatically Detects Unnatural Reviews on Amazon - Aug 23, 2016.
ReviewMeta is a tool that analyzes millions of reviews and helps customers decide which ones to trust. As the dataset grows, so do the insights on unbiased reviews.
Amazon, Analytics, Customer Analytics, Data Mining, Trends
- How to Use Cohort Analysis to Improve Customer Retention - May 2, 2016.
Cohort analysis is a subset of behavioral analytics that takes the user data and breaks them into related groups for analysis. Let’s understand using cohort analysis with an example of daily cohort of app users.
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Churn, CleverTap, Customer Analytics, Customer Behavior
- What is the influence of Big Data in Medicine? - Mar 14, 2016.
The 360-degree customer view is the idea, that companies can get a complete view of customers by aggregating data from the various touch points that a user. And, big data is helping to materialize this idea, which will revolutionize the healthcare.
Big Data, Customer Analytics, Healthcare
