AI based Recommendation Engine
AI-Based Recommendation Engine
When it comes to the digital world, A recommendation engine serves the purpose of personalization. A recommendation engine is a system that suggests products, services, information to users based on the analysis of data. The recommendation engine can derive personalized suggestions from a variety of factors such as the history of the user, market trends, the behavior of similar users, etc.
Common industry challenges
Is it challenging to drive traffic on your website?
Are you losing business in the absence of personalized relevant content?
Do you have a high Churn Rate?
Struggling to Increase the number of items per order?
Benefits of Recommendation engine
Increase in revenue
Higher Customer Satisfaction
Ease of Making Decisions
Synctactic.AI as Recommendation Engine
Synctactic.AI engines leverage cognitive filtering, Item-to-item filtering, collaborative filtering and hybrid information around user profiles around preferences, past data, similar demographic data, transactional data, deals, social profile, interests, etc to recommend to the user’s items which suits them the most. This directly increases customer satisfaction because of the relevance in terms of recommendation and its high probability to be accepted by the users.
If you are a company wanting to be at the forefront of the industry, then an accurate, enhanced and reliable recommendation engine is a must-have technology in your business arsenal. Synctactic.AI systems are designed to bring AI results and return on your investment in the record 2-6 weeks.
Upselling & Cross-Selling based on Customer needs, Demographic and Behavioral patterns
Upselling is an opportunity to educate your customer about a better available option of product or service which best meets their needs and satisfies them in the long run. This is only possible if your recommendation is competent enough to learn about the customer needs, demographic and behavioral patterns to precisely recommend your customer and convert the opportunity into business. Similarly, Cross-selling is adding a separate, though typically related, product to a sale.
Ease of Integration & to Go-Live with AI Recommendation Engine
Synctactic.AI recommendation engine framework ensures that it understands the existing client data, client business and inter-relation between thousands of business and non-business attributes in existing client’s database in such manner that Synctactic.AI data engineering team along with their AI tools like Sync discover, Sync learn , Sync data, Sync analyze are easily integrated into a client system in record time.
Data & Goal Driven Algorithm
Synctactic.AI recommendation engines play a critical role to bring in a decision-making framework in which the logic is derived by an algorithm that is constantly fueled by data, rather than explicitly programmed by a developer or implicitly conveyed via a person’s intuition.
Speed & Accuracy
Synctactic.AI recommendation engines are designed to deliver speed and accuracy. They learn from its successes and failures with speed and sophistication that humans usually cannot match any of this user behavior analytics-based recommendations, upselling recommendations and cross selling recommendations. Thereby ensuring businesses to constantly meet their key business KPI i.e, increase in revenue.
Personalized content based on Historical Buying Patterns & Demographics
Doctors take advice from doctors, lawyers from lawyers. We all love to hear from our friends on their recommendation because we share common interests and disinterests. We are always taking recommendations from our friends and family because we are committed to each other and we trust each other’s opinions.
This is precisely where recommendation engines come into play, it leverages all the past data based on user browsing history, buying patterns, order value, brand inclination, demographics, age and constantly tries to give the most suitable option from the endless portfolio of the product. This enables customers to make faster and more satisfying decisions around their shopping.