Predictive Analytics

Predictive Analytics

Predictive analytics refers to using historical data, machine learning, and artificial intelligence to predict what will happen in the future. This historical data is fed into a mathematical model that considers key trends and patterns in the data. The model is then applied to current data to predict what will happen next.

Customer 360 (graph database)

A simple definition: Intelligent call routing systems identify the caller and the reason for the call to assign her to right agent. Though we mentioned phone call routing in the definition, intelligent routing can take place regardless of where the customer contacts the company. Routing is also important for email or chat queries.

  • Customer 360 provides a holistic view of the customer by integrating the information an organization already holds on them, such as demographics, buying behavior and history, across many channels.
  • Data silos pose a big challenge for many organizations. Customer touchpoint data – website activity, emails, transaction logs, social posts, reviews, etc
  • Graph visualization tools, like KeyLines, make it possible to pull this information into a single consolidated view.
  • Delivering value to customers, maintaining relationships, and proactively addressing their needs are paramount to succeeding in this highly competitive vertical.
  • Customers using Customer 360 insights with DataStax Enterprise.
Intelligent Call Routing

Intelligent Call Routing is a term for routing done by software that attempts to identify the caller and direct them to an appropriate agent. ... The Genesys platform performs this intelligent routing using criteria such as agent skills, caller priority, and DTMF entered by the caller.

  • Intelligent call routing systems identify the caller and the reason for the call to assign her to right agent.
  • Intelligent skill-based routing systems use agents’ track record, their trainings and skills to ensure that caller is routed to the most capable agent.
  • Intelligent Call Routing is a term for routing done by software that attempts to identify the caller and direct them to an appropriate agent.
  • Intelligent call routing automatically routes calls to the most appropriate employee and prevents loss of business in first time and repeat callers.
Ad Optimization

Ad text optimization (ATO) is the process of improving the performance of a text Pay Per Click (PPC) Advertisement on search engines by improving its Click Through Rate (CTR) performance both in terms of volume and quality of response, that is “more buyers, less browsers”.

  • PPC Ads are triggered to appear on search engine pages when Users search with keywords which match those selected by the PPC Advertiser.
  • There are many metrics that PPC advertisers should focus on to ensure a strong ROI from their campaigns. Click-through rate, or CTR, is among the most important.
  • At the heart of Ad Text Optimization (ATO) lies a specialist type of direct response copywriting which can be augmented by an Ad Text Optimization (ATO) algorithm that measures the response effectiveness of Ad Text copy.
Revenue Optimization

Revenue management is the application of disciplined analytics that predict consumer behaviour at the micro-market level and optimize product availability and price to maximize revenue growth.

  • Revenue optimization is the strategic management of pricing, inventory, demand and distribution channels to maximize revenue growth over the long term.
  • The primary aim of revenue management is selling the right product to the right customer at the right time for the right price and with the right pack.
Customer Lifetime Value

In marketing, customer lifetime value, lifetime customer value, or life-time value is a prediction of the net profit attributed to the entire future relationship with a customer.

  • In marketing, customer lifetime value (CLV) is a metric that represents the total net profit a company makes from any given customer.
  • CLV is a projection to estimate a customer's monetary worth to a business after factoring in the value of the relationship with a customer over time.
  • CLV helps you make important business decisions about sales, marketing, product development, and customer support.

Forecasting is the process of making predictions of the future based on past and present data and most commonly by analysis of trends. A commonplace example might be estimation of some variable of interest at some specified future date. Prediction is a similar, but more general term.

  • Forecasting is the process of making predictions of the future based on past and present data and most commonly by analysis of trends.
  • When a forecast is showing, future values for the measure are shown next to the actual values.
  • Forecasting is determining what is going to happen in the future by analyzing what happened in the past and what is going on now.
Churn Models

A Predictive Churn Model is a tool that defines the steps and stages of customerchurn, or a customer leaving your service or product. Having a predictive churn model gives you awareness and quantifiable metrics to fight against in your retention efforts.

  • Churn is defined slightly differently by each organization or product.
  • Generally, the customers who stop using a product or service for a given period of time are referred to as churners.
  • As a result, churn is one of the most important elements in the Key Performance Indicator (KPI) of a product or service.
  • Ideally, when building a churn model, you want to produce a model that can predict the discrete churn event that best describes the system without overfitting.
Customer Segmentation

Customer segmentation is the practice of dividing a customer base into groups of individuals that are similar in specific ways relevant to marketing, such as age, gender, interests and spending habits.

  • Customer segmentation is the process of dividing customers into groups based on common characteristics so companies can market to each group effectively and appropriately.
  • The patterns in the data are used to identify / group similar observations.We will use are k-means clustering for creating customer segments based on their income and spend data.
  • At its most basic, customer segmentation (also known as market segmentation) is the division of potential customers in a given market into discrete groups.
  • Cross-selling identifies products that satisfy additional, complementary needs that are unfulfilled by the original item.
Customer Journey Mapping (touchpoint optimization,Root cause analysis)

Although posts often talk about customer journey mapping as a powerful way of visualising the customer experience, many find the idea of creating a customer journey map intimidating. But, that shouldn’t be the case.

  • The reason people feel intimidated by customer journey mapping is they have the wrong view of it.
  • A better way to think of it is like a person. It is representative of a typical experience.
  • There is nothing magical about the process, and it is something that can be done by anybody.
  • This guide aims to talk you through the process of mapping the customer journey from beginning to end.
  • Customer journey map illustrates the relationship of a customer with a business over a period of time using storytelling technique and visual cues.
Marketing Campaign Optimization

Marketing campaign optimization is key for turning your strategy into a powerful marketing machine. They continually evaluate and optimize marketing campaigns to ensure that every dollar of their hard-earned budget is being spent wisely.

Price Optimization

Price optimization is the use of mathematical analysis by a company to determine how customers will respond to different prices for its products and services through different channels.

  • Price optimization starts with a segmentation of customers. A seller then estimates how customers in different segments will respond to different prices offered through different channels.
  • Given this information, determining the prices that best meet corporate goals can be formulated and solved as a constrained optimization process.
  • Price optimization practice has been implemented in industries including retail, banking, airlines, casinos, hotels, car rental, cruise lines and insurance industries.
Financial Risk Modeling
  • Financial risk modeling is the use of formal econometric techniques to determine the aggregate risk in a financial portfolio.
  • Risk modeling is one of many subtasks within the broader area of financial modeling.
  • Financial risk modeling is back in the limelight these days because of its place at the intersection of two hot trends.Fintech and big data.
  • Financial risk modeling is the process of determining how much risk (measured in volatility) is present in a particular business, investment, or series of cash flows.
Scenario Optimization

The scenario approach or scenario optimizationapproach is a technique for obtaining solutions to robust optimization and chance-constrained optimization problems based on a sample of the constraints. It also relates to inductive reasoning in modeling and decision-making.

Simulations (markov chain)
  • Many stochastic processes used for the modeling of financial assets and other systems in engineering are Markovian, and this makes it relatively easy to simulate from them.
  • A Markov chain is a probabilistic model describing a system that changes from state to state, and in which the probability of the system being in a certain state at a certain time step depends only on the state of the preceding time step.