Predictive Analytics


Predictive analytics is a form of advanced analytics that helps define the probability of a certain action or event happening using current and historical data.

The aim of predictive analytics consulting is to make accurate predictions through the enablement of statistical analysis and AI-driven techniques. DarkRockMountain builds tailored predictive analytics solutions for companies to increase their bottom lines with valuable insights.

Key applications of predictive analytics solutions

Churn prediction

Detect at-risk customers, uncover the reasons for customer churn, and optimize your retention strategy.

Smart recommendations

Deliver personalized product suggestions to maximize cross-selling and upselling and expand your product exposure.

Predictive segmentation

Predict the likelihood of customers making repeat purchases, abandoning the shopping cart or stopping buying from you to assign them to segments and target them with relevant marketing campaigns.

LTV modeling

Predict customer lifetime value to accurately identify your target audience and nurture long-term relationships with them.

Demand forecasting

Anticipate demand fluctuations to eliminate inventory shortages or overstock and decrease operational costs.

Financial risks forecasting

Predict the creditworthiness of your contractors to minimize the probability of loss.

Pricing personalization

Optimize your pricing strategies and adjust them in real time based on customer buying patterns and market conditions.

Predictive maintenance

Accurately predict equipment failures to reduce breakdowns, increase productivity, and reduce maintenance costs.

Our predictive analytics development framework

DarkRockMountain’s specialists develop predictive analytics software from scratch and can take up your project from any stage, from solution planning and analysis to its deployment. As a predictive analytics service provider, we also render long-term support services for the implemented solutions to ensure their smooth functioning and on-demand scaling and improvement.

  • 1

    Requirements definition

    • Identification of business needs and objectives, user expectations and concerns
    • Assessment of the customer’s technical environment
    • Definition of functional and non-functional requirements of the solution
  • 2

    Data analysis

    • Assessment of current data management workflows
    • Exploratory analysis of available data sources, both customer-owned and from public databases, to ensure it meets project goals
  • 3

    Design

    • Solution architecture design
    • Definition of the implementation strategy, algorithms, and techniques
    • Selection of the optimal technology stack
    • Project timeline and budget setup
  • 4

    Implementation

    • Data preprocessing, including cleaning, annotation, and transformation
    • Definition of the solution evaluation criteria
    • Solution development in line with the selected implementation strategy
  • 5

    Integration and deployment

    • Solution integration into the customer’s infrastructure
    • Solution launch into production
    • Transfer of technical and business documentation to ensure the correct operation and maintenance of the solution.
  • 6

    Support and maintenance

    • Retraining and functional enhancement based on user feedback and new data from the production
    • Support of system operation under varying load

Techs & Tools we are proficient in:

Programming languages

  • .Net

  • C++

  • Golang

  • Java

  • JavaScript

  • Kotlin icon

    Kotlin

  • Php

  • Python

  • Qt

  • Rails

  • Rust

  • Scala

  • Swift icon

    Swift

Cloud

  • AWS - Amazon Web Services

    AWS

  • Microsoft Azure

    Azure

  • DigitalOcean

    DigitalOcean

  • Google Cloud

    Google

  • IBM Cloud

    IBM

Databases

NoSQL Databases
  • Apache HBase

  • Apache Nifi

  • Cassandra

  • MongoDb

  • Neo4j

  • Redis

SQL Databases
  • MicrosoftSQL

  • MySql

  • Oracle

  • PostgreSQL

Big Data

  • Apache Spark

  • Apache Storm

  • Confluent

  • Databricks

  • Hadoop

  • Hive

  • Kafka

  • Snowflake

Machine learning & Data Science

  • Alteryx

  • Apache Mahout

  • Keras icon

    Keras

  • Mathworks icon

    MatLab

  • OpenCV

  • PyTorch icon

    PyTorch

  • logo--r-script

    R

  • Scikit-learn

    Scikit-Learn

  • SpaCy

  • TensorFlow icon

    TensorFlow

  • Theano

DevOps

CI/CD & Automation
  • Ansible

  • CircleCI

    CircleCI

  • file_type_cloudfoundry

    Cloud Foundry

  • GitHub Actions

    GH Actions

  • Git

  • GitHub

  • GitLab

  • Jenkins

  • Packer

  • Tekton

    Tekton

  • Terraform

  • Travis CI

Containerization
  • Apache Mesos

  • Docker

  • Kubernetes

  • logo--openshift

    OpenShift

Monitoring
  • Datadog icon

    DataDog

  • Grafana

  • Prometheus icon

    Prometheus

Security & Testing
  • Gremlin

    Gremlin

  • HashiCorp Vault

  • selenium

    Selenium

  • Snyk icon

    Snyk

Blockchain

Platforms
  • EOS

  • Ethereum

  • Graphene

  • Hyperledger

  • Solana

Development tools & languages
  • OpenZeppelin

    OpenZeppelin

  • file_type_solidity

    Solidity

  • Vyper

  • Waffle

Front & Back End Frameworks

  • angular

    Angular

  • Astro

    Astro

  • django

    Django

  • Flask

  • Flutter

  • Gatsby

  • GraphQL

  • Hugo

  • Next.js

  • Node.js

  • React

    React

  • Vue.js

    Vue