Many eCommerce industries use artificial intelligence for predicting buyers' intent based on the shopping patterns, and target them with more personalized offers.| Express Analytics
Here are some of the common pitfalls to avoid as you go about implementing it: 1.Lack of appropriately scoped objectives 2. Lack of required skills 3. The size of Big Data 4. The quality of Big Data| Express Analytics
Predictive analytics make use of data along with techniques like statistics, analysis, and machine learning to create a perfect prediction related to the future.| Express Analytics
Predictive Analytics in insurance industry is becoming the “weapon of choice” of insurance firms. It is because of advances in AI & ML deployment.| Express Analytics
Curious about how to improve your customer experience? Dive into the world of customer journey analytics and discover 5 strategies to create memorable interactions.| Express Analytics
Studies show that unstructured data weighs in at as much as 80% of the total data available today. It is to be found in social media networks, news, chat services, messaging services, niche magazines, government reports, and white papers.| Express Analytics
Data cleaning is process of deleting incorrect, wrongly formatted, and incomplete data within a dataset, which later leads to false conclusions, making even the most sophisticated algorithm fail.| Express Analytics
Data analytics retail sector allows retailers to create personalized offers and achieve a better return on investment.| Express Analytics
A customer behavior analysis uses actionable intelligence to improve retention. With the power of data analytics though, businesses are now able to predict consumer behavior by analyzing past purchases, search history, or even social media profiles.| Express Analytics
There are two ways to look at Customer Lifetime Value — Historic CLV and Predictive CLV. The historic method analyzes past data to judge how valuable a customer is. In this case, we don't try and predict the future value of that customer's purchases.| Express Analytics
Does your business use emotion-based customer segmentation? allow marketers to create groups of potential customers segmentation, aligned with their wants.| Express Analytics
How to Build a Customer Profile Database? Build a customer interactions database. This is the first of the six important steps in operationalizing analytics for any company| Express Analytics
Retail and Consumer Data Analytics Case Studies, Blogs, eBook, Guide, Videos, Webinars, and WhitePapers for Retail and Consumer Industry.| Express Analytics
Customers leave behind an enormous amount of data. We are analyzing how Machine Learning can use this data to get ahead of the competition.| Express Analytics
A recommendation engine is nothing but an information filtering system composed of machine learning algorithms that predict a given customer's ratings or preferences for an item.| Express Analytics
Big Data Analytics may have been coined recently but the act of collecting and analyzing data is decades old. Simply put, it denotes the large volumes of structured and unstructured data that flows into your business every hour, and every day.| Express Analytics
Artificial Intelligence (AI) is back in the headlines as most companies like Amazon, Google, Facebook, and Microsoft have started to use it.| Express Analytics
The use of machine learning in data analytics can help decision-makers automatically evaluate data and boost business outcomes.| Express Analytics
Operationalizing Data analytics can be done cost-effectively if you implement the right practices and the right people. That’s so true. Know the what, why and how of operationalization analytics.| Express Analytics