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Reducing Customer Churn in Data Science Fashion
The most effective way to reduce churn is to prevent it before it happens. Suppose you know a customer/user will churn next month and know the possible reasons why that customer is about to churn. In that case, you can reach out to that customer and offer some coupons or engage him/her to retain a customer and prevent a possible churn.
Turn your website visitors into customers
Every e-commerce brand attracts massive regular website traffic, and every single of those website visitors is a potential customer. However, the percentage of visitors that end up buying something is very low, to the point where it's almost unbelievable. On average, only 1% o those visitors actually buy something.
A Step by Step Guide to Propensity to Buy Model
By definition, it is the likelihood of a potential customer to purchase something, a.k.a Purchase Propensity. It is applicable to almost any sort of business, however, it's especially applicable to the e-commerce industry.
Breaking the Complexity of the Product Recommendations
With the rise of e-commerce in this era, a new frontier has opened up. It’s called product recommendations. It’s a no brainers, you recommend the right product to the right customers at the right time and your sales just bump up. As much as it sounds sweet and like a cookie-cutter in reality it’s the complete opposite of that.
An All Star Product Recommendations Tool
Almost every online shops have a product recommendation system that is either a very hit or a very miss when it comes to relevancy. It’s like the high school romance gossips; everyone says they did it but we all know only the cool ones actually did it. In reality, these cool kids are Amazon, eBay, Aliexpress, and maybe a few more of such gigantic size. What of the others then?
Physical Perception of Big Data: Enhencer's Multivariate Analysis
The qualitative perspective of the big data discussed a lot for the last few decades. In fact, the stress was being directed onto the qualitative side rather than the quantitative side. If I know something even a little bit about the latest paradigm, it is that nothing is one-sided. Big data is no exception.
How Knowing Demand Movements Helps You
Unlike some other key elements of the market behavior, demand forecasting is pure data analytics. In order to have accurate measurements of the demand in a given timespan, algorithms of items, sales numbers, transactions, incentives, past events, and trends are used accordingly to predict with the highest confidence.
Predicting the Actions of Individuals
At first look, statement looks absurd. Nevertheless, when applied into different fields, anticipating actions of individuals becomes a must for so many of them. Think about an insurance company where asymmetric information is undisputable.
Positioning the Prediction in 21 st Century
As the impact area of data gets larger, the importance of it slowly but steadily found its place in decision-makers. Naming the latest phenomenon of manufacture was the initial stage since all leaps before it goes undetected in their era although their impact was impeccable.
Making Data Science Mainstream
Not being too late is an age-old motto for organizational behavior. Although we had mentioned that being too late is not that important as long as you are being productive, it is best not to leave it to your chance. Hence, whether you make plan beforehand or not, evaluating the possible outcomes and events is certainly helpful.
Analysing and Assessing the Risk Factor
Not being too late is an age-old motto for organizational behavior. Although we had mentioned that being too late is not that important as long as you are being productive, it is best not to leave it to your chance. Hence, whether you make plan beforehand or not, evaluating the possible outcomes and events is certainly helpful.
Benefits of Early Fraud Detection
Our blog has been suggesting the newest ideas and the innovations in the information technology since the beginning. Hence, our inclination towards almost any subjects is automation, self-learning, artificial intelligence and prediction.
Direct Benefits of Enhancing Customer Lifetime Values
When we are evaluating something’s direct benefit, our aim is to define, analyse, and list all outcomes as well as their reasons. Customer lifetime values are no different. In order to implement a health strategy to enhance customer lifetime values, we need to define what it is, analyse its derivations, and list all the projections of its realization.
The Rise of Artificial Intelligence in Service Sector
Big data and machine-learning already paved the way for a smoother operation of economic activities. In fact, the biggest upswings are yet to come since there is a brilliant potential of them.
Instant Gratification & Data Science
We live in a world of instant gratification where old habits are slowly but certainly is fading away. In a world of Netflix, we abandoned the habit of going out and actually buying/renting a movie. Why all the hassle when we can start watching in a click of a button at our home comfort? When we have Spotify and SoundCloud like platforms then why go buy music records?
Churn Prediction in 5 minutes
Today I will show you how to obtain churn predictions before your coffee is ready. Put some coffee on the machine or french press so that when you get all those churn predictions you can enjoy going through them with that hot coffee you just brewed in the meantime.
Why Enhencer is Web Based
In the age of data-driven decision making, the swiftness of the human-data interaction is as important as the reliability of the data. As the data-sets are getting larger and larger, running between sources to make an analysis becomes harder.
New Mechanism of Marketing
In many places, we mentioned on Machine Learning, Artificial Intelligence, and relative data sciences that are newly gained influence with the fourth industrial revolution. Using those tools to discover new patterns and/or predicting what is going to happen with certain inputs is now invasive enough find its place among various sections of any sector.
Does Startup Mean Less Data?
The terms “startup” has been turning around for a few years in various sectors. From a multinational logistic company that carries passenger on demand or a transnational company that accommodates millions of people without even having any hotel room. All those examples at least one point of their existence had been called startup.
How Do You Make Churn Analysis?
The conventional methods of keeping sales high consist of multiple actions that are mostly originating from the same place; gut of campaign holder. Although this method holds for decades, global spread of the companies caused them to run into a lot of customers at once. That is, the potential of the companies is exponentially rising in terms of their customers.
Key Benefits of Simple Modelling
Ideas behind the core concepts of analysis world are complex as their implementation and area of descriptions are multifaceted. In its simplest form analytical models are models, generally, prescribed in mathematics that have form of explanations to the solution matrix i.e. changes in equations can be described in said formulation with the help of expressed mathematical analytic function.
Why Do We Calculate Product Propensity
Customers’ propensity to change their direction of purchasing has been a huge problem for decades as seller cannot anticipate the correct move for the best strategy particularly in case of larger demands. In fact, as time passes, not implementing the correct move becomes as harmful as implementing a wrong move.
A Statistical Approach To ML Full Automation
Machine learning principles are thoroughly stressed in our blog for every other day. The reason behind is simpler than it seems. The last few decades proved that the AI mechanics and other “tech” related fields needs an improvement in terms of their capacities as well as their physical borders.
Enhencer's Live Outputs
As Enhencer, we are, as a 21st century organism, following the latest trends in the data and management closely. Therefore, the consumer needs and the practical formations of the data science fields direct us to more user-friendly solutions. Those solutions are basically arising due to practical needs and other developments in the fields.
Is Data Analysis Simple?
When a basic question on a complex matter is asked, the answer is always multifold. That is, question’s ability to spot light on the matter becomes obsolete. Thus, a single response cannot answer the question even from a tiny extend. However, there is always a solution to even the darkest problems.
What Is Predictive Storytelling?
Even the most distinguished scientists sometimes have problems, there is a very common one when it comes to share their findings with the rest of the world. The lack of telling what did happen, what is happening, and what will happen is the ultimate curse of scientific advance.
How To Calculate Purchase Propensity With Machine Learning
Marginal propensity of consumers toward a product or a service is generally guessed by suppliers, so demand shifts, market movements, and financial alterations, although they have an impact, are overlooked. In fact, not being able to keep records and data causes so many problems in terms of calculations of these metrics that providers are left to guess only.
The Analytic World Of Big-Data
Regarding to the limited abilities of data storage, data transformation and data analysis processes of traditional analytic platforms on big data, new concepts are developed in the analytic world. The design of analytic processes on big data, and as well as automation processes are substantial parts of newly developed big data discipline.
Fully Automated Work Flow With Enhencer
Big Data was mentioned thousands of timesthroughout our however, we cannot over-stress the importance of it in the context of new-industrial era.
Statistics is Reborn
The science of statistics is one of the key instruments to derive significant information from our tally data sheets to complicated database system.
How to Forecast Demand with Machine Learning
Utilizing human experts on demand forecasting does no harm. However, if there is enough data to train a model, machine learning is the best alternative you may have.
In-depth analysis of Machine Learning as a Service
Programming suites and some AI applications in the sector proved that utilizing machine learning gives you the higher ground. However, neither applying nor conveying it is not easy due to a couple of technical factors. Thus, a new segment – new paradigm of machine learning arose from the need of the market: Machine learning as a Service, MLaaS.
Cross Sell / Up Sell Probability Calculation with Enhencer
Changing the direction of a sale or upgrading it with a bundle is the ultimate goal of every retailer. Thing is that probability of these are tender to calculate even with enough data.
In-depth Analysis of AutoML
Running on its own, automated machine learning algorithms are the latest thing that digital transformation age offered. This smooth observation will point out the value proposition of the AutoML products in general.
How Machine Learning Algorithms Spot Anomalies
We cannot escape the failures arising from the data applications no matter what we try; however, applying sound measures to spot the anomalies is the best way to go.
Churn Calculation Enhances with Machine Learning
Convincing a new customer to buy your product is harder than retaining the old ones. However, how would you know who is going to leave and who is not? Check below to see how machine learning helps you in this matter, too!
Benefits of Transparent Analysis
Stating your strategic moves before you even take the initial steps is not looking clever in business world. However, things are not as they may seem in 21st century business paradigm. Transparency hold a huge space in today’s day-to-day operations in almost every sector.
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