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?
According to HubSpot's State of Inbound 2017, "marketers today find generating traffic and leads to be their biggest challenge". Companies are constantly struggling to meet their website visitor traffic targets and losing them to their competitors.
Are you losing business in the absence of personalized relevant content?
One of the most reputed research companies- Gartner survey shows Industrial brands risk losing 38 percent of customers because of poor Marketing Personalization Efforts. By 2025, Gartner predicts that 80% of marketers who have invested in personalization will abandon their efforts due to a lack of return on investment.
Do you have a high Churn Rate?
A failure of your existing recommendation engine to deliver personalized information around the product and services, not only leads to loss of an opportunity to make more revenues but also leads to a persistent depletion in the customer traffic pool and increasing churn.
Struggling to Increase the number of items per order?
Who wouldn't love to increase the average deal size of every sales transaction keeping all the cost constants? On top of that, every business wants to make the most revenue per transaction so that they have a higher top line with a minimal operational burden. This is only possible when businesses have an efficient and reliable system to upsell and cross their clients.

Benefits of Recommendation engine

Increase in revenue
An increase in Revenue is the utmost critical aspect of any business. It is extremely satisfying if one's company's website is as promising and appealing as Amazon, Flipkart or Target that the users directly land on their business site to strike their shopping list. This is when a promising recommendation engine comes into play which strives to deliver the best and memorable customer experience. Such a delightful experience compels users to revisit business websites frequently while maintaining loyalty and periodically increasing business revenues.
Personalized Content
When was the last time you walked into your favorite store and the owner of the store greeted you with your name and remembered the last event at your home you did the shopping. Personalization is a basic necessity in sales and business. It enables businesses to provide personalized services and products, best meet user demands and provide the most friendly buying experience.
Higher Customer Satisfaction
A promising recommendation engine provides customers frequently contextualized product options. With such a personalized pool of options, a customer with minimal effort gets maximum out of their invested time. Such a magical experience gives customer tools to make immediate decisions and give them a unique shopping experience & customer satisfaction.
Ease of Making Decisions
Countless magazines, advertisements, blogs and forums are clear proof of how challenging it is when it comes to selecting a choice of product or service that best suits one's needs. Recommendation engines are extremely competent to run through the sea of information and choose what most suited for customers. This saves a lot of time and energy of the user and also keeps users delighted on any business's website and e-stores. To immediately leverage this power of AI on your existing data and system please connect with one of the data scientist members of the Syntactic.AI team.

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.

To immediately leverage this power of AI on your existing data and system please connect with one of the data scientist members of the Syntactic.AI team.

Talk to our team!