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Predictive Analytics

Discover your Data’s destiny with Predictive Analytics

Introduce visionary force of predictive analytics to transform uncertainties into strategy advantages and unlock doors to new opportunities.

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Transform the Customer Experience with Predictive Analytics

If you have an eye toward the future, it’s high-time to boost data and analytics capabilities and harness the power of predictive insights with the ultimate objective to connect more closely with the customers, anticipate behavior, identify issues associated with customer experience and opportunities in the real world. With the help of predictive analytics, companies are better understanding the interactions with customers, predict problems in customer journeys, and reaping benefits like never before.

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Types of Predictive Analytics

Popular predictive analytics include Classification model, regression model, clustering model, and time series model.

Classification Models

This model falls under the category of supervised machine learning models. These machines are known to categorize data entirely based on historical data, while describing intricacies within a dataset. It is helpful in putting data into categories based on the sources and other sort of features it possesses.

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Clustering Models

Customer segmentation is one of the common use cases for clustering. Being a part of unsupervised machine learning, the primary purpose is to group data points based on similar attributes. These models further help in revealing hidden patterns by utilizing data and organizing into meaningful groups.

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Regression Models

Another model that comes under the branch of supervised machine learning. These models employ different techniques of correlation, distribution evaluation, and outlier detection which altogether predict continuous data by establishing between a dependent variable and one or more independent variables.

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Time Series Models

This model is the mixture of supervised and unsupervised techniques to predict patterns in data points over time. The distinct attribute of this model is associated with taking data from previous periods likewise, monthly or quarterly sales and employing this technique to estimate future outcomes.

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Benefits of Services

Reaching the audience, the right one, at the right time and selling products or services is the only mantra for any business. However, businesses deal with humongous volume of data and analyzing it will allow them to stay ahead of the curve in this fierce competition.

Security

Data Security is one of the main concerns of every modern business. Undoubtedly, if the combination of automation and predictive analysis can be attained, it would improve data security. Peculiar patterns associated with suspicious or unusual end user behavior can trigger specific security procedures.

Risk Reduction

Like businesses are working day and night to keep the data secure, businesses must also consider reducing the risk profiles. For instance, insurance companies can use predictive analytics to better understand if the insurance coverage is adequate. This helps with the best of the tactics for lower risk & higher ROI.

Operational Efficiency

Undoubtedly, efficient workflow improves profit margins. For instance, when a vehicle used for delivery is going to need maintenance before it’s actually broken on the side of the road. Predicting this implies delivery made on time without the additional cost of having the vehicle towed and complete the delivery.

Improved Decision Making

Running any business is synonymous with making calculated decisions. That being said, any expansion or addition to a product line requires balancing the inherent risk along with the potential outcome. Predictive analytics offer measurable and actionable insights and can grab competitive advantage.

Create go-to Market Strategies

Predictive data analytics helps some of marketing and sales pros to unlock new opportunities, unearth new trends and anticipate customer behavior. By using these insights, you can customize relevant content, create targeted ads and even send personalized product recommendations to increase engagement.

Optimization of Resource Allocatio

Operational leaders can take proactive measures to optimize existing business processes with the help of sales forecasting and annual financial predictions to make better adjustments to their respective procurement and production methods. In the long run, these insights can help to reduce operational costs.

Our Services

Fluper offers expert consulting services in predictive analytics which assists businesses to make important choices. With the help of our specialized team, they use data insights to support businesses in gearing up for emerging trends and new problems. Our Predictive analytics offerings include:

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Formulate informed decisions and get ready for future events with predictive analytics.

  • Full suite of analytics service
  • Easy access to real-time data
  • AI-assisted insights
  • State-of-the-art techniques and methods
  • Top-tier data security
  • Round the clock availability

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How is predictive analytics performed in Fluper?

At Fluper, we offer a typical process followed when data analytics is performed. The whole process of predictive analytics has 6 steps.

  • Defining Business Problem

The first step starts with identifying business problems that can be solved using predictive analytics. This step includes identifying stakeholders, understanding issues and parameters on the basis of which outcome of the predictive model will be evaluated on ceratin basis.

  • Data preparation

This step pertains to data cleansing and exploration. These data-based operations follow the concept of GO-GA (Garbage-In-Garbage-Out). This step holds significance of data cleansing before feeding it into a predictive model.This typical task is inclusive of cleaning data.

  • Model deployment

The operations team makes sure to use the model developed by the team of data scientists. Here data engineers come to the picture in order to access, store, clean and feed into the model at scale. The output of the predictive analytics is used to automate the tasks.

  • Defining required data

The next step is collaborating with data analysts to observe the data type for impactful data analysis. Undoubtedly, identification of data sets will provide a complete picture of the situation. The necessary data encompasses factors right from timeframe and level of aggregation.

  • Predictive modeling and model evaluation

The step is associated with the development of data models. This data model is backed by identifying the most suitable algorithms based on the business problem, cleanliness, and quality of the data available. This data is further fed into the model to unlock predictions.

  • Model monitoring

One of the most common problems associated with the process of predictive analytics is model degradation that teams face due to the dynamic world. Some common aspects like business climate, customer behavior, and economic situation are responsible for decreasing performance.

Applications of Predictive Analytics

The following are some use cases that are transformed with the introduction of predictive analytics:

Benefits

Embrace Predictive Analytics for smarter decisions.
  • Boost Operational Efficiency

  • Drive Revenue Growth

  • Mitigate Risks

  • Gain Competitive Edge

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Our Awards & Achievements

Our unwavering commitment to quality support, team of predictive analytics experts, skillfully adhering to stringent standards and compliance has earned us prestigious awards for digital transformation, and predictive analytics consulting service from industry leaders and experts.

Frequently Asked Questions

Still, Have Queries? Know More About Us by Going Through the Following FAQs.

How does Fluper perform Predictive analytics?

Our experts first identify business problems, followed by defining the required data, data preparation by using the concept of Garbage In-Garbage Out. The next step is developing predictive modeling and model evaluation, model deployment, and model monitoring.

Tools and Technology We Use for Predictive Analytics

Here is the list of some tools and technologies that our predictive analytics team adhere to while delivering customized predictive analytics.

Caffe

Chainer

Deeplearning4j

Keras

Microsoft Cognitive Toolkit

PyTorch

TensorFlow

Torch

DeepArt

DeepDream

GPT-3

GPT-4

Pix2Pix

WaveGAN

AlexNet

DenseNet

Inception

ResNet

Xception

TensorFlow

Caffe

OpenAI Gym

Keras

PyTorch

FastAI

MXNet

Scikit-learn

OpenAI GPT

AllenNLP

DeepMind Sonnet

Hugging Face Transformers

NVIDIA StyleGAN

Autoencoders

DRLN

GAN

LSTM Networks

RNN

Predictive Analytics Blogs

Please find expert insights through our industry experts’ lens predictive analytics, and digital transformation, latest industry trends, innovation and detailed use cases. Explore Digital Strategy Consultancy and predictive analytics consulting services to get a grab a quick understanding of software and application.

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Lorem Ipsum is simply dummy text of the printing and type

Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.

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Lorem Ipsum is simply dummy text of the printing and type

Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.

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