Product recommendation is one of the most elusive–and potentially profitable–forms of merchandising online, where consumer behavior can bring in reams of data about the way people shop. But figuring out what to do with that data, and how to present what you learn, is a psychological challenge all its own.
Most e-commerce retailers are familiar with the science of product recommendations. richrelevance has created an addition to its SaaS platform called myrecs, which uses more data to recommend more products per page, and updates customer information to recommend those products in real time.
Trying to best Amazon.com is not an easy task. But that is what richrelevance is aiming to do with the introduction of myrecs, a new component of its richrecs suite of personalization and product recommendations technology.
The myrecs system creates a page filled with product recommendations organized by product type, customer behavior and visit chronology. The page serves as a way to navigate a retailer’s e-commerce site by recommendations.
David Selinger was first recognized as an expert in the field of e-commerce data analytics and personalization for his work on the research and development of Amazon’s data mining and personalization team. He founded richrelevance, a provider of personalized product recommendations.
The dirty little secret of Web 2.0 — the version in which users like you create much of the content — is that companies have been trying for years to “monetize” it, and mostly failing. Facebook, Wikipedia, YouTube, Digg and the like are wildly popular, but they’re not making money the way Google and Amazon did.
All that math brain power that Wall Street is busy shedding: Can it plug into the algorithm economy of profiling, preferences, predictions and recommendations?
I called Darren Vengroff. He’s the chief scientist at RichRelevance, a San Francisco company that helps e-commerce sites figure out what to recommend to their customers. Like Amazon’s, the recommendations are based on the statistical analysis of people’s behavioral patterns. But RichRelevance is trying to take it a step further. Vengroff worked in exotic derivatives at Goldman Sachs before moving his math smarts to Amazon in 2002. He has a phd in computer science from Brown.
We started working with [e-commerce service provider] richrelevance because it was in line with our cutting-edge philosophy. Its platform gives out automated recommendations based on what people have searched for and what is most popular. We can examine analytics from the site and determine which data points will be used.
Forty-eight percent of online shoppers plan to spend less this year, but 61 percent are positively influenced by online shopping resources, according to a new study.
The study was conducted by JupiterResearch, a Forrester Research
company, and surveyed more than 800 consumers nationwide in November and December 2008. It was commissioned by Bazaarvoice