Product Recommendation Software
Retail businesses use product recommendation software to suggest goods to company’s customers based on their past behavior. This system aims to better serve customers and increase the average order value.
About E-commerce Product Recommendation System
In a nutshell, this system predicts and displays the goods a user would like to buy based on their preferences and previous interactions. An e-commerce product recommendation engine works by using algorithms that customize your customers’ shopping experience. This tool can make use of one of three types of filtering: customer-based, content-based, or combined.
The tool can help increase sales. It suggests relevant products to customers who are already interested in placing an order. Displaying complementary products and bundles helps companies increase their average check and boost revenue. Additionally, an e-commerce product recommendation system can help increase customer loyalty and retention, as users are more likely to return to a website that provides relevant and personalized suggestions.
Personalized product recommendation in e-commerce also benefits inventory and stock level management. Businesses can clear out their inventory and reduce waste by actively promoting products that have low sales. Highlighting popular products and accurate demand prediction help companies adjust their stock levels. Thus, they avoid running out of stock or overstocking certain goods.
If the suggested goods are tailored to an individual customer, businesses can reduce bounce rates and increase engagement. That’s because users spend less time searching for the items they’d like to buy. This all contributes to building brand loyalty. Tools for product recommendation e-commerce can be integrated with marketing automation tools and CRM software to offer a more seamless experience.
Features
Product recommendation system for e-commerce
- Web behavior tracking
- Customer behavior analytics
- User feedback analysis
- Integrations with third-party tools
- Concurrent editing
- A/B testing
- Cross-device recommendations
- Custom filters
- Reporting
- Location-based recommendations
- Email marketing analytics
- Requirements management
- Content-based filtering
- Customer data platform
- Social media analytics
- Discounts and special offers
- Cross-channel data exchange
- User segmentation
- Demand predicting
Work Process
Product recommendation software development consists of several stages, each involving its own team of specialists. As a rule, teams pay special attention to data analysis and Big Data.
1
Project planning
We estimate tasks, plan our resources, and set priorities.
Team:
- Project Manager
2
Business analysis
We analyze the client’s current platform, data quality, and quantity, and create task specifications.
Team:
- Project Manager
- Business Analyst
3
UI/UX design
We develop convenient interfaces for different groups of users.
Team:
- Project Manager
- Business Analyst
- UI/UX Designer
4
Back-end development
We build the server side of a web solution.
Team:
- Project Manager
- Business Analyst
- UI/UX Designer
- Back-end Engineers
- Manual QA Engineers
5
Front-end development
We build the user side of a web solution.
Team:
- Project Manager
- Business Analyst
- UI/UX Designer
- Front-end Engineers
- Manual QA Engineers
6
Integrations
We analyze the systems we need to integrate and implement two-side integrations.
Team:
- Project Manager
- Business Analyst
- UI/UX Designer
- Front-end Engineers
- Back-end Engineers
- DevOps Engineers
7
Testing
We perform manual, automated, unit, and integration testing.
Team:
- Project Manager
- Manual QA Engineer
- QA Automation Engineer
- Back-end Engineers
8
Implementation and training
We develop training materials and implement the solution in the client’s company.
Team:
- Project Manager
- Technical Writer
- DevOps Engineers
- Support Engineers
Our Clients
We develop large projects for clients across 27 countries, a significant number of which are featured on the Fortune 500 list.
Our company specializes in projects for
Retail & E-commerce
Why Do You Need It?
Businesses in the e-commerce industry strive for personalization because their audiences are more likely to buy from those who understand their needs, and suggest relevant goods. Listed are some of the cases during which product recommendation engine development would be helpful.
Conversion optimization
Your online store has low conversion rates and high levels of cart abandonment
Inventory issues
You constantly deal with overstocking or out-of-stock items in your inventory
Low website engagement
Your potential customers don’t spend much time on your website
Acquisition costs
The costs of customer acquisition are very high
Customer insights
You have difficulties identifying customer interests and preferences
Marketing effectiveness
Your marketing strategies don’t achieve the desired results
Deeper audience analysis
You want to analyze the audience’s behavior and preferences better
Clear sales forecasts
You lack accurate sales predictions
Low average check
Your average check and repurchase rates are low
Wide range of products
You have a wide assortment of goods with many substitutes
A/B testing
You want to perform A/B tests to increase user engagement
Our Standards
In our work, we follow international approaches and standards such as:
Management: | PMP |
Design: | ISO 9241-210 |
Programming: | Coding conventions, MDN Web Docs, Naming convention |
Python: | PEP 8 |
JS/TS: | ECMA, JavaScript Standard Style, Google TypeScript Style Guide, ESLint |
PHP: | PSR |
С#: | ReSharper |
HTML/CSS: | W3C |
Security: | GDPR |
Testing: | ISTQB |
Technologies
We specialize in specific technologies, with the technology stack chosen based on the project’s purpose and requirements
Programming languages:
Web / Frameworks:
Databases / Data storage:
DevOps containers:
DevOps automation:
DevOps CI/CD:
DevOps monitoring:
Testing:
Clouds: