Recommend Me

How can we help you?

Contact us at the consulting office nearest to you or submit a business inquiry online.

With the increase in number of sensors per machine, we had gathered lot of data and it needed to be churned. Mactores with their analytics experts in IoT did it for us. They have an excellent approach to look at the problem and solve them progressively and effectively. We were able to explore unimaginable insights and gained a lot and lowered our operational costs as well.

Mark Phillips
Senior General Manager, Manufacturing Company

Built to enhance customer experience and drive sales
Drive your customer interactions with the next best action

Recommend Me enables companies to easily and efficiently meet consumer desires and expectations. The result is a win-win for everyone involved: an uptick in sales as well as in customer satisfaction. That’s because Recommend me is a product that helps refine, understand and anticipate a your customers preferences and needs in a way that creates a more personalized experience.

Increase sales and conversion rates

Up-selling and cross-selling is responsible for an average 20% to 30% of online businesses, making them crucial marketing components in the various industries. Recommend Me helps industries to increase sales and conversion rates by providing shoppers with a personalized multi-channel purchasing experience.

Retain and increase customer loyalty

Personalize your customers’ entire shopping experience. As content website continues to explode, on-line retailers are seeking out for more and more ways to provide visitors a dynamically personalized shopping experience. Recommend Me helps enterprises to retain and increase customer loyalty to build brand and business.

Track every activity and recommend relevantly

Tracks every activity shoppers perform on your site from the products they’ve browsed at, added to cart and purchased to their preferred categories. Recommend Me collects this personalized information over time and builds a rich consumer profile and relevantly recommend articles, videos, pictures, content or products by using collaborative filtering.

Reasons why industries prefer Recommend Me over other systems

Increase per
customer revenues
Reduced
sales cycles
Improved
sales forecasting
Improved up-selling
and cross-selling
Improved customer
satisfaction by quicker responses
Complete track of
all your leads and opportunities

Enterprises rely on Recommend Me to enhance customer experience and increase sales

E-commerce

Recommend Me offers an effective form of targeted marketing by creating a personalized shopping experience for each customer. For large retailers our product is scalable over large customer bases and product catalogs, needs only few seconds to process and generate online recommendations, is able to react immediately to changes in a user’s data. It makes compelling recommendations for all users regardless of the number of purchases and ratings. Recommend Me analyzes over 10 billion customers’ data and over 100 billion recommendations every day.

Insurance

Recommend Me uses algorithm based on data science that helps underwriters and brokers identify industry-specific client risks; then, recommend up-selling and cross-selling opportunities by offering access to parallel policies, products, marketing materials, and educational materials. As more products are consumed to an increasing customer base, Recommend Me becomes more mature and reliable, resulting in an exponential increase in revenues and customer satisfaction.

Banking

Every banking firm have sufficient knowledge about customer interests and behavior. Recommend Me uses memory-based collaborative filtering. It processes the data/information sourcing from various banking channels into the services that other customers have used most frequently and recent services that a customer has previously used.

Social media

Recommend Me generates recommendation based on user’s interests, social connections, blog entries, social activities and content analysis. It integrates with advanced machine learning algorithm which aggregates relationships among items, people and tags. It offers user-specific, tags-specific, popularity-based and combinations of these recommendations.

News

Recommend Me integrate news articles/information filtering method with the collaborative filtering method to enable personalized recommendations for easier news access. This combination has proven significant over the traditional collaborative filtering method. User satisfaction, rich experience, easier access to intended news article are some of the benefits gained.

Healthcare

Recommend Me integrate real-time performance monitoring, advanced data analytics, information dashboards. With real-time monitoring, you take right decisions at the right place and time. Our solution accelerators enable you to keep track of cost and quality performance. It helps healthcare organizations transform their businesses by integrating traditional report analysis with organization’s analytics-driven insights.

3 filtering techniques we use to optimize your businesses

Collaborative filtering technique is a domain-independent algorithm for unstructured data such as movies and music. It matches customers with relevant interest and favorites by determining similarities between their profiles to generate recommendations.

Content-based filtering technique is a domain-dependent algorithm and it concentrates more on the processing of the attributes of items in order to generate recommendations.

Hybrid filtering technique integrates various recommendation techniques in order to process different types of data to avoid some shortcomings and issues generating personalized recommendations.

Looking for a First-Class Technology Consultant?

Top