Product Recommendation Software Development Services

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 by suggesting relevant products to customers who are already interested in making a purchase. By displaying complementary products and bundles, companies can increase their average order value 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 is also beneficial for inventory and stock level management. By actively promoting products that are not selling well, businesses can clear out their inventory and reduce waste. Furthermore, by highlighting popular products and accurately predicting demand, companies can adjust their stock levels accordingly and 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

VIEW MORE VIEW LESS

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 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