Companies have more data than ever. At the same time, retailers have less and less time to collect and process this data and to think about market changes. It is not surprising that artificial intelligence could be a promising solution to today's retail challenges.
Machine learning analyzes data to the next level. Using massive amounts of product and price data, sophisticated algorithms learn different pricing and sales patterns. Using an endless number of simulations, the algorithm identifies patterns that are beyond human reach. Machine learning algorithms have been proving to be effective over other methods for years now.
Machine Learning Solutions
Help algorithms to understand human speech and text to find the right information quickly, automate customer service, create chatbots for different departments, and easily find topics in text documents.
Understand your data from the past to predict the future for eCommerce warehousing or Supply Chain. Build forecasts to understand how your company can get more profits.
Improve your conversion rate with more relevant recommendations. Create the most personalized experience for your customers.
Patterns and Forecasting
Find patterns in your historical data and dig deeper to predict trends and seasonal changes. Forecast demand for your products. Create a pricing strategy to beat competitors.
NLP (Natural Language Processing)
Analyze customers’ behavior and build segmentation models. Optimize targeting, personalization, and overall customer experience.
Recognize goods to control their availability for on-time stock replenishment. Use biometrics, AR, and face recognition for automating tasks and gathering more information.
What You Can Achieve Using Machine Learning
- Forecasting the demand for discounted goods.
- Identify abnormal behavior to detect fraud, security issues, information breaches, medical problems, structural defects, and other malfunctions.
- Identifying and using patterns of customer behavior in the past to predict their actions in the future.
- Offering certain groups of buyers (segments) of certain products at the moment of greatest need
- Replacement of sales assistants with an automated system for the selection of goods based on the experience of previous buyers and individual preferences of a particular client.
- Determination of the optimal number of staff for high-quality customer service at a specific point at a specific time (during seasonal sales, marketing campaigns, etc.)
- Optimization of product placement in the store (taking into account customer behavior patterns, seasonal changes, trends, etc.).
- Optimization of warehouse storage - every centimeter of storage space will be used profitably.
- A virtual assistant to monitor the shopping schedule and remind the buyer of the need to place a new order or select the best product based on their preferences.
- Demonstration of targeted (depending on gender, age) digital content at points of sale to stimulate demand and increase sales.
Data Acquisition & Understanding
- Building data pipeline
- Setting up environment
- Data wrangling, exploration & cleansing
- Feature engineering
- Model training
- Model evaluation
How We Work
Our main value is to deliver valuable and cost-effective solutions to our clients. That’s why we developed an approach to R&D projects that allows us to see the progress at every stage and deliver solutions incrementally, allowing clients to decide if additional efforts are worth investment or a change of direction is required.
- Research applicable datasets in terms of data volume and set of fields; create ETL
- Test different ML models, algorithms, libraries
- Chose most appropriate dataset, model and model parameters
- Prepare ML model for a simulation with production data
- Elaborate on a suitable integration approach
- Prepare and integrate a production ready ML model
- Optimize and improve the model with new production data, weights, parameters
- Improved model rollout
- Support and minor enchancements
- Effectiveness monitoring
- Increase sales and optimize pricing
- Increase in conversion and average check
- Increase response from marketing campaigns
- Reduce production, logistics, and other costs
- Increase customer loyalty
- Optimize warehouse and distribution
- Improve customer experience
- Manage customer behavior
10 Years of Collaboration: Meeting Client Needs for the Long-term
For almost ten years, DataArt has complemented Ocado’s in-house engineering talent resources, enabling business agility and rapid innovation.
Designing for Business Agility with a Custom WMS
DataArt co-developed a custom Warehouse Management System for Utkonos ONLINE, a large online grocer, enabling the company to launch new warehouses and automate business processes.
Helping Doddle Build a White Label Customer Fulfillment Technology
From Doddle’s beginnings as a UK start-up to its evolution as a global e-commerce tech provider, DataArt played an integral role in the development of the company’s platform and product offerings.
Online Education Platforms
The client is one of the biggest online education platforms in North America with over 4 million enrolled students. The marketplace provides an opportunity for tutors and education service providers to sell their paid courses and connect to various users and corporations looking for learning materials online.
Online Travel Marketplace
The client is a global leader in world travel and tour provision, offering 200+ vacation choices on all seven continents including land tours, river cruises, rail journeys, small group tours, family trips, garden holidays and more. The client works primarily with tour managers helping them to promote and sell their offerings to travelers.
Online Grocery Marketplace
The clients platform provides customers with the ability to search for and purchase food and beverage products as well as providing home delivery services. In contrast to its main competitors, the company has no chain of stores and performs all home deliveries from warehouses.
Online Healthcare Marketplace
The clients platform removes the friction from everyday health related tasks and allows users to seamlessly search for and review medical institutions, book appointments online and connect to medical practices via their patient portals.
Travel Distribution Network
The client is a leading tours & activities distribution network with headquarters in the US. By providing APIs and direct marketing tools to online travel companies, the company helps its customers to create and catalyze financial opportunities through a wide, yet targeted selection of tours and activities.
Solution for Analyzing and Estimating the Queue Size
When customers wait in line, it’s bad for morale. It reduces customer loyalty and profits while impeding productivity. It also impacts working processes. In one local office of a global company, a growing workforce resulted in long lines in the company cafeteria at peak times. As a result, employees wasted time and experienced declining productivity.
Machine Learning to Predict Sales and ROI at Points of Sale
The client is one of the world’s most famous tobacco companies. The Company distributes tobacco products across a set of geographically distributed Points of Sale (POS). To increase their net sales volume, the company uses a set of marketing techniques to increase the visibility of their products.
Increasing Daily Number of Orders by 5x with a Custom Transport Management System
Our client is one of the leaders in the online grocery market, was making 10 000 deliveries daily and aspired to increase that number to 50,000 within the next three years. However, the client’s transport management and route calculation system could not keep up with existing delivery demands and was stifling business growth.
Why Work with Us
Artificial Intelligence and Data Science project methodology is significantly different from traditional research for software delivery projects.
It requires companies to:
- Develop new data science and AI skills (such as NLP, computer vision, machine learning, deep learning, etc.)
- Build new infrastructure for big data and model deployment (often cloud based)
- Adopt new culture of collaboration between the business and data scientists
DataArt can help to bootstrap AI capabilities, or fill data and analytics gaps for companies that do not have the expertise internally or do not want to hire new talent until the benefits of AI are proven.
DataArt focuses not only on research, but also on delivering end-to-end solutions starting with solution design and ending with deployment of ML-model and integration into the existing or newly developed client environment.