Inferlytics
Facilitating Disruptive Value to e-Retailers

The ecommerce sector has been witnessing significant transformation in the recent years. One critical aspect of online retail that has not evolved as much as it should have is the search and browse experience. Inaccurate search results, no results found pages, and lack of understanding of search context on most websites leave a lot to be desired.

Retail search implementations for most retailers are focused on helping people who know specific products that they are planning to buy. But if you want to buy say a camera and are not sure about the exact model then you are overloaded with tons of information, irrelevant filters and choices that are cumbersome to weed through.

The result –customers cannot decide which is the right product for them, and do not convert. Shopping carts fill up, and are dropped out at different parts of the checkout journey. Customers keep questioning their decision, unsure about their product choice.

Answering these concerns is Inferlytics, a Mountain View, CA based firm focusing on providing a Search and Browse experience for retailers through their focus on Unstructured Data Analytics, Sentiment Analysis and Machine Learning based recommendation algorithms.

The company enables disruptive value to e-Retailers searching for ways to enhance end-consumer experience. The product brings in improvements in online product discovery and makes online product based social content more effective. Further, Inferlytics improves shopping cart conversions and helps merchandizers understand customer’s views on their products.

Inferlytics, led by Amit Jnagal, CEO has found that they can deliver exceptionally better search for most retailers and are running prototypes with some of the top players in the retail sector.

The Inferlytics Product Suite

The Inferlytics suite is made up of three components – a powerfultext processing engine with sentiment analysis capabilities, a

recommendation engine that works based on user behavior based product clustering,as well as sentiment based product contextualization and search & browse engine offering keyword and faceted search capabilities.

Inferlytics is an enhanced customer experience product, with highly advanced text analytics and sentiment analysis engine at its core. It converts raw content into meaningful classifications of product features, and analyzes the relevance of the content.

It also includes an end-to-end social conversations management platform for initiating, collecting and managing social conversations on online products. This module comes with standard features such as ratings and reviews widgets, Comments widgets, Ask questions widget and many others. It also offers detailed analysis and dashboards for all captured social conversations.

Inferlytics is a unique and specialized product for e-tailers, which churns through Internet scale data for a product and makes insights available directly to the consumer, thereby enhancing their experience and assisting in purchase decisions.

On the differentiating factors, Jnagal informs, “If you look at the retail search and browse experience today, it is based on three main dimensions – product merchandizing data, social opinion and user behavior based recommendation engines. However, search engines do not have any clue of social conversations,the recommendation engines do not look at search analytics and social conversation analytics do not even know that the other two exist. Inferlytics is the first engine of its kind providing an integrated search experience.

Inferlytics also has built-in domain specific search knowledge. Our search engine is not a generic keyword-matching robot. So the search results for an apparel retailer is a lot different and relevant than for a wine merchant.Nothing today comes even close to this product discovery experience”.

What Lies Beyond

Inferlytics currently offers out of box solutions for around 10 retail domains. The company’s plans are centered on increasing this number to about fifty by the next quarter. There are plans to deploy more customer insight widgets. Improvements and enhancements to sentiment analytics engine and feature classification engine for a wider natural language support, spanning multiple languages are the other goals.