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DATAFOREST Services for the E-Commerce Industry

Optimize business performance, enhance customer engagement, and drive innovative growth in the digital marketplace with AI-adopted technologies.

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Data Engineering Services Satisfy Needs

Scale infrastructure effectively, optimize user experience and supply chain, improve customer service with AI, and derive actionable insights.
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The Core Essence
of Data Science

Harness advanced analytical techniques and AI/ML algorithms to interpret complex data. Analyze user behavior and preferences, forecast demand, and use intelligent chatbots.
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Data Scraping and Customer
Service Automation

Gather customer feedback and queries from various platforms to train and improve AI models.
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Managing Large-Scale
Infrastructure with DataOps

Optimize data workflows, making scaling more responsive to fluctuating demands.View page
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Data Integration for Informed

Aggregate and harmonize data from diverse sources, providing a comprehensive view. Combine big data from various supply chain sources.
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Web Development for
User-Friendly Trading

Create dashboards and reporting tools that are accessible through a website or an intranet.

Better Products and Experiences

Benefits of e-commerce using our services and solutions:
Enhanced decision-making
Optimized inventory management
Customer segmentation for
targeted marketing
Efficient supply chain management
Personalized customer experiences
Fraud detection and prevention
Predictive analytics for
future planning
Competitive advantage
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Boost Work Efficiency and Accuracy with Expert Machine Learning Support.

Get in Touch Now!

Cases of Using Artificial Intelligence and Machine Learning

Check out a few case studies that show why DATAFOREST will meet your business needs.

The Service Platform for Food Distributors

The client had an idea for a food service platform to collect the leads for the food suppliers and distributors. The main idea was to collect the info about the restaurants and then use the data to calculate the possible contract values. Dataforest created the web solution using complicated data parsing and processing logic alongside the backend development of the solution itself.
1 mln

USA restaurants data


connections with external data sources

The Service Platform for Food Distributors preview
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First Bite is a food service data, CRM, and selling tool in one solution.

Lead-collecting Web Solution

Leadmarket is the lead-collecting web tool made by Dataforest. We’ve built a solution that provides a fast and precise lead search from various sources like Google Places, Facebook Business Pages, Yelp, and Yellowpages in one place. The collected lead bases from the USA's e-commerce, insurance, retail, and finance industries can be set to auto-update as quickly as every 10 minutes!

minutes auto-update


Search categories

Leadmarket preview
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Leadmarket is the lead-collecting web solution made by Dataforest.

Cargo Documents Digitalisation

In logistics, every carrier relies on documentation, especially paper. Numerous paper documents are prone to frequent misplacement and erroneous signatures, while strict submission requirements exist. Dataforest has innovated a web application to streamline paper-intensive processes into an entirely digitized one with just a few clicks, significantly enhancing efficiency and accuracy.

seconds for doc generation


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Andy Tomka

VP of Product, MVMNT
View case study
Cargo Documents Digitalisation preview
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If you are looking for a strong product manager who takes the time to become enmeshed in your business and industry, then Maryna is the person for the job.

E-commerce Data Management

An e-commerce business uses reports from multiple platforms to inform its operations but has been storing data manually in various formats, which causes inefficiencies and inconsistencies. To optimize their analytical capabilities and drive decision-making, the client required an automated process for regular collection, processing, and consolidation of their data into a unified data warehouse. We streamlined the process of their critical metrics data into a centralized data repository. The final solution helps the client to quickly and accurately assess their business's performance, optimize their operations, and stay ahead of the competition in the dynamic e-commerce landscape.

DB entries daily


sources integrations

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Lesley D.

Product Owner E-commerce business
View case study
E-commerce Data Management case image preview
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We are extremely satisfied with the automated and streamlined process that DATAFOREST has provided for us.

Entity Recognition

The online marketplace for cars wanted to improve search for users by adding full-text and voice search, as well as advanced search with specific options. We built a system application using Machine Learning and NLP methods to process text queries, and the Google Cloud Speech API to process audio queries. This helped greatly improve the user experience by providing a more intuitive and efficient search option for them.

faster service


CX boost

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Brian Bowman

President Carsoup, automotive online marketplace
View case study
Entity Recognition preview
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Technically proficient and solution-oriented.

Show all Success stories

Towards Good Development

These data engineering development stages ensure that solutions are well-designed, thoroughly tested, and aligned with business objectives.
How we help companies?
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Step 1 of 7

Initial Project Assessment 
and Definition

In the early phases of our data engineering development process, we engage in a free consultation to gauge project compatibility. During the discovery and feasibility analysis, we adapt to your needs, whether it's high-level requirements. We gather information to define project scope through discussions, including feature lists, data fields, and solution architecture. We craft a project plan to guide our progress, reflecting our dedication to achieving project goals and delivering effective data engineering solutions.
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Step 2 of 7


So, you have finally decided that you are ready to cooperate with DATAFOREST.

The discovery stage involves delving into the details of the project. Data engineers gather requirements, analyze existing systems, and understand the needs of the business. This step is crucial for laying the groundwork for development, as it ensures that the project aligns with business goals and user needs.
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Step 3 of 7

Tech Design and Backlog Planning

In this stage, the technical architecture and design of the solution are formulated. Data engineers plan how data will be collected, stored, processed, and presented. Simultaneously, the project backlog is created — a list of tasks and features to be developed. This backlog is prioritized, ensuring that high-priority items are addressed first.
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Step 4 of 7

Development Based on Sprints

Development takes place in iterative cycles known as sprints. During each sprint, the development team tackles tasks from the backlog. The team focuses on coding, testing, and integrating the components. At the end of each sprint, a functional part of the solution is ready for review.
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Step 5 of 7

Project Wide QA

Quality Assurance is an ongoing process that permeates the entire project development lifecycle. It ensures rigorous testing, identification, and resolution of any bugs or issues to guarantee the solution's smooth operation, compliance with requirements, and alignment with quality standards. The solution is prepared for release as QA activities persist and necessary adjustments are continuously implemented.
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Step 6 of 7

Deployment and Rollout

The deployment phase involves releasing the solution to the production environment, making it accessible to users. It requires careful planning to ensure a seamless transition and minimal disruption. After deployment, the rollout phase begins, involving training for users and ongoing support to address any hiccups.
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Step 7 of 7

Support and Continuous Improvement

In the final stages, we ensure ongoing excellence. We guarantee optimal performance and swiftly address any issues. Simultaneously, our feedback process empowers us to continuously enhance the solution based on user insights, aligning it with evolving needs and driving continuous innovation.

What Data Science technologies do we use?

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SciPy icon
TensorFlow icon
Numpy icon
ADTK icon
DBscan icon
G. AutoML icon
G. AutoML
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Natural L. AI icon
Natural L. AI
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Pillow icon
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FB Prophet icon
FB Prophet
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Related articles

All publications
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19 min

Digital Transformation Trends in Insurance — Customer Expectations

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Data Science in Insurance: A Healthy Person Approach

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Still have questions about data science services?

Can you handle large volumes of data from various sources, including sales, inventory, and customer interactions?
We can handle large volumes of data from diverse sources such as sales, inventory records, and customer interactions, allowing for comprehensive analysis and actionable insights to inform decision-making and improve business operations. Using data processing services, e-commerce increases in size.
How does your Ecommerce Data Processing service integrate with our existing systems and processes?
Our E-commerce Data Processing service seamlessly integrates with your existing systems and processes by employing compatible data formats, APIs, and connectors, ensuring smooth data flow between platforms. This integration optimizes data accuracy, enhances operational efficiency, and empowers you to make well-informed decisions based on comprehensive, up-to-date information. This is also true for big data in e-commerce.
How can DATAFOREST help us personalize our marketing strategies and improve customer experiences?
DATAFOREST, as an e-commerce data services company, can significantly enhance your marketing strategies and customer experiences through its robust data analysis and segmentation capabilities. By analyzing customer preferences and purchase history, DATAFOREST can identify distinct customer segments and tailor marketing messages and offers to resonate with each group's preferences. It boosts engagement and conversions while creating for your e-commerce company more meaningful interactions with your customers.
How long does it typically take to process and analyze our e-commerce data?
The time it takes to process and analyze your e-commerce data varies based on factors like data volume and complexity, but it can range from hours for fundamental analysis to several days for more in-depth insights. It is regardless of the e-commerce data architecture.
Can you tailor your E-commerce Data Processing solutions to our business needs and industry?
DATAFOREST is an e-commerce data engineering company, and our E-commerce Data Processing solutions are customizable to align with your unique business needs and industry requirements, ensuring a tailored approach that addresses your specific challenges and goals. It is in basics for e-commerce data services and also true for b2b e-commerce.
What types of reports and visualizations do you offer to help us monitor and measure the impact of your services on our business growth?
Our comprehensive reports and visualizations provide insights into sales performance, customer behavior, conversion rates, and other key metrics, helping you monitor and measure the direct impact of our services on your business growth.
How can we get started with ordering E-commerce Data Processing services from DATAFOREST?
To start ordering e-commerce data processing services from DATAFOREST, contact our team through our website form or channels to discuss your specific needs and initiate the tailored solution process.
Do you offer ongoing support and assistance after implementing your data processing solutions?
We provide continuous support and assistance post-implementation of our data processing solutions to ensure seamless operation, address any concerns, and optimize the solutions as your business evolves.
How can DATAFOREST help us optimize our inventory management and supply chain operations?
DATAFOREST, as an e-commerce data management company, can optimize your inventory management and supply chain operations by analyzing real-time demand patterns, historical data, and market trends to ensure optimal stock levels, reduce stockouts, and enhance overall supply chain efficiency. We fulfill all e-commerce data management services.
How do you ensure the processed data is accessible and easily interpreted for our team?
We ensure accessibility and ease of interpretation by providing user-friendly dashboards, visualizations, and reports that present processed data clearly and intuitively for your team or other e-commerce companies.
What is the role of big data in general and big data analytics in particular for data engineering in e-commerce?
E-commerce big data serves as the foundational resource in data engineering. E-commerce big data services encompass vast and diverse datasets that facilitate personalized customer experiences, informed decision-making, and operational optimization. E-commerce big data analytics services further refine this role by extracting actionable insights from the data, enabling tailored strategies for demand forecasting, pricing, supply chain management, and customer engagement in the landscape, ignoring the e-commerce big data architecture complexity.

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We will carefully check and get back to you with the next steps.

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Contact us to discuss
your project goals.