To stand out, you need more than just fantastic items and a top-notch website. Sales and consumer satisfaction have changed dramatically as a result of personalized product suggestions. You may provide product suggestions that appeal to your clients by using AI algorithms and product recommendation software.
We’ll look at some of the top product suggestion software options in this post. From basic rule-based suggestions to sophisticated machine-learning algorithms, these tools have it all. There is a solution for everyone, regardless of the size of your business or online shop.
Best Product Recommendation Software
1. Involve.me
You may develop a variety of surveys, questionnaires, calculators, and product recommendation quizzes with this product recommendation software, a no-code builder, without knowing a single line of code. This no-code builder makes it simple to create embeddable quizzes that allow you to customize product suggestions and assist your consumers in finding the ideal purchase.
Additionally, ‘Involve.me’ ensures easy data movement across the technologies your team utilizes by integrating with email marketing solutions, CRMs, and e-commerce systems. The product suggestion quizzes involve. It allows you to directly sell your goods or services in addition to making recommendations. Responses, payments, completion rate, email open rate, response summaries, and other crucial indicators are available in the analytics dashboard.
Features:
- API.
- Access Controls/Permissions.
- Alerts/Notifications.
- Autofill.
- Behavioral Targeting.
- Campaign Management.
- Campaign Segmentation.
- Categorization/Grouping.
- Collaboration Tools.
- Communication Management and many more.
Price:
- Free plan and trial are available.
- Basic: $29 per month.
- Pro: $59 per month.
- Business: $129 per month.
- Enterprise: Custom pricing.
2. Clerk.io
Over 18,000 websites are presently served by Clerk.io, which assists companies in giving their clients individualized experiences via email, social media advertisements, site searches, and other channels. Fifteen pre-built recommendation logics, such as best cross-sell items, client purchase history, and popular products, are included in its recommendation engine.
Additionally, the system is designed to automatically modify suggestions in response to new trends and seasons. Furthermore, it provides you with unique filters to assist you in customizing your suggestions based on your company’s requirements.
Features:
- A/B Testing.
- AI/Machine Learning.
- API.
- Abandoned Cart Saver.
- Activity Dashboard.
- Activity Tracking.
- Alerts/Notifications.
- Behavior Tracking.
- Behavioral Targeting.
- Campaign Analytics and many more.
Price:
- Search: Starts at $99.
- Recommendations: Starts at $99.
- Email: Starts at $99
- Audience: Starts at $99.
3. Emarsys
With eCommerce accounting for 6% of its user base, this one of the best product recommendation tools is an omnichannel customer engagement platform that is currently utilized by 15,000 websites across various industries.
Its recommendation engine uses offline and online customer data to provide real-time personalization and product recommendations across various channels and devices. Emarsys enables users to incorporate product recommendations into emails, product listings, searches, shopping carts, product descriptions, and advertisements.
Features:
- Behavior Tracking.
- Behavioral Analytics.
- CAN-SPAM Compliance.
- CRM.
- Campaign Analytics.
- Campaign Management.
- Campaign Scheduling.
- Campaign Segmentation.
- Click Tracking.
- Contact Database and many more.
Price: Contact Emarsys for pricing details.
4. Nosto
Nosto’s product recommendation software leverages machine learning algorithms to assess users’ offline and online behavioral data to provide items relevant to them. It provides its users access to many customization options to let them deploy and change tailored suggestions at every part of the customers’ purchase experience.
The system also comes with a range of suggestion algorithms, such as top sellers, trending goods, new inventory, and more, that can be further personalized to suit individual consumers utilizing its segmentation product. Furthermore, its A/B testing and optimizing capability enable customers to try multiple suggestion tactics and gather insights to help them expand quickly.
Features:
- A/B Testing.
- Behavioral Targeting.
- CRM.
- Campaign Segmentation.
- Catalog Management.
- Content Analytics.
- Contextual Targeting.
- Customer Profiles.
- Customer Segmentation.
- Email Management and many more.
Price:
- Free plan available.
- Pricing varies between 2.5 and 4% of Nosto’s revenues.
5. Qubit
Qubit claims to be the first deep learning-based customer-to-product recommendation software in the world. Google Cloud AI powers its deep learning technologies. As a result, it makes use of the same recommendation system that powers YouTube and Google.
At each stage of the client experience, Qubit automatically modifies its suggestion approach in real time to account for any changes. Users may solve problems like missing data points and missing items from all data sources with the use of its automatic health check. Qubit enables new goods to learn from older, comparable items via deep attribute matching, making consumer testing more effective.
Features:
- Fluorescence-based quantification.
- Easy to perform.
- Can measure low abundance samples.
- Can distinguish between DNA and RNA.
- Onboard calculators.
- Assay design tool.
- Compatible with a broad range of assays.
- Can measure as little as 1 µL of sample.
Price: Contact sales for pricing.
6. Dynamic Yield
Dynamic Yield predicts clients’ upcoming purchases and makes appropriate product recommendations by using statistical engines, cross-channel assistance, merchandising control, and deep learning algorithms.
The remarkable segmentation capabilities of Dynamic Yield’s recommendation engine, AdaptML, enable you to apply the appropriate suggestion approach according to the prospect’s stage in the sales funnel (home page, product description page, checkout, etc.). Additionally, it enables you to apply the proper approach according to user characteristics, such as new vs returning customers.
Additionally, Dynamic Yield lets you combine many recommendation techniques into a single widget or let the machine learning engine choose the optimal combination of strategies for you.
Features:
- Monitoring Targeting.
- Templates.
- Customization Optimization.
- Recommendation Content.
- A/B Testing.
- Multichannel.
- Web & Mobile.
- Segmentation.
- A/B Testing.
- Personalized Content.
- Recommendation Engine.
- Reports & Analytics.
- Experimental Design.
- Mobile Testing.
Price: Contact Dynamic Yield for pricing.
7. Criteo
Criteo helps organizations build individualized online display advertising experiences for prospects by combining artificial intelligence with commerce data. Facebook, Google, Taboola, and other ad networks are among its partners.
Criteo’s retargeting capabilities are its best-selling point. By using its Dynamic Retargeting feature, users may provide suggestions that are most likely to result in a conversion to site visitors at various phases of their sales funnel.
Features:
- AI/Machine Learning.
- Ad Inventory Management.
- Audience Targeting.
- Behavioral Targeting.
- Campaign Analytics.
- Campaign Management.
- Conversion Tracking.
- Cross Channel Attribution.
- Customer Segmentation.
- Data Blending and many more.
Price: contact sales for pricing information.
8. Bloomreach
Bloomreach is a complete digital commerce platform designed to improve your online business, not just one of the best product recommendation tools. Bloomreach’s robust features and integrations enable you to provide outstanding customer service and promote long-term success.
Features:
- 2-Way Messaging.
- A/B Testing.
- AI Content Creation.
- AI Writing Assistant.
- AI/Machine Learning.
- API.
- Abandoned Cart Saver.
- Access Controls/Permissions.
- Account-Based Marketing.
- Accounting Integration and many more.
Price: Contact Bloomreach for pricing.
9. Recombee
A recommendation engine called Recombee focuses on providing precise and tailored product recommendations. It uses cutting-edge algorithms and machine learning to provide clients with pertinent suggestions.
Features:
- ML Algorithm Library.
- Machine Learning.
- Mobile App.
- Model Training.
- Multi-Language.
- Multiple Data Sources.
- Natural Language Processing.
- Performance Metrics.
- Predictive Analytics.
- Predictive Modeling and more.
Price:
- Free version and free trial available.
- Standard: $99/month.
- Plus: $999/month.
- Pro: $1,499/month.
- Premium: $2,499/month.
How To Choose The Right Product Recommendation Software
It might be difficult to choose the best product recommendation software, but you can make an educated choice by taking into account the following elements:.
Your Particular Requirements: Which features are necessary for you? Do you want sophisticated customizing features or simple recommendations? Do you need comprehensive statistics to monitor how well your suggestions are working? Does the program work with the marketing tools and e-commerce platform you currently have?
Usability: Select a program that is easy for you and your team to use and has a straightforward UI. A complicated tool may make it more difficult for you to get insights rapidly.
Combining Your Current Tools: To expedite data collection and analysis, make sure the software works in unison with your existing marketing and analytics systems.
The cost: Examine the price structures of several tools to determine which one best suits your needs. Think about the benefits that the software’s capabilities and insights will provide.
User Evaluations: To learn more about other users’ experiences with the program, read their reviews. Check for reviews on overall value, customer service, and convenience of use.
FAQ
Q: Which method is used while recommending products?
A: Conventional product recommendation systems provide recommendations based on rules derived from the known preferences of a consumer or a group of customers using three different approaches: collaborative filtering, content-based filtering, and hybrid.
Q: How do product recommendation engines operate?
A: These algorithms use vast volumes of client data, such as search history, preferences, and purchase history, to allow predefined procedures to automatically provide relevant suggestions based on the data.
Q: What does location-based product recommendation mean?
A: In an effort to provide customers with more relevant suggestions, recommender systems that include location data—such as that from a mobile device—into their algorithms are known as location-based recommendation systems.