Filed under: Behavioural Targeting, Optimisation | Tags: Amazon.com Recomendation Engine, Josh James, Omniture Recommendations
Omniture Recommendations features a marketer-friendly user interface and a portfolio of pre-built algorithms that display relevant products or content such as popular and similar items, to drive maximum conversion, customer engagement and revenue.
In addition, site and product affinity algorithms can determine which products or content to present based on a combination of criteria including: page views, cart adds and removes, and overall site activity.
Marketers can also drill down to granular levels of control, modifying the recommendation algorithms based on certain parameters, such as price ranges, product categories and other variables. As a result, marketers can balance recommendations between customer behavior insights and current business needs.
The application also includes built-in testing and reporting capabilities.
Filed under: Web Analytics | Tags: Josh James, Omniture, On-Demand, SIIA
To put things into perspective in the web analytics space….
Through its 15,000 servers, Omniture processes almost 1 trillion transactions per quarter.
Listen to Josh James, Omniture CEO speaking at the SIIA On-Demand conference: http://www.siia.net/ondemand/2008/video/1.asp
Recently, Josh James, the CEO of Omniture said something similar during the Q&A portion of the company’s Q3 earnings call in response to a question about whether businesses saw web analytics as discretionary:
“Every dollar that a marketer has, I think everyone has in every organization is under pressure right now and certainly marketing spend is where CFOs like to look and see if they can cut. But, what we’ve seen with our customers is their online channels are the ones that are performing the best. Their online channels are the ones that are giving the most direct impact within that quarter that spend is also taking place.
In terms of the way that they think about Omniture, even if they cut let’s say 10% of their marketing spend, they’re going to use us to a) identify the 10% they’re going to cut and b) use us to optimize the other 90% to try to get back up to the same results as they had with the 100% the year before. These kinds of times actually drive usage of our product.
When things are good it’s a lot easier when you want more sales just to throw more money at the top of funnel and to generate more leads and go through the process. When things get bad people try to focus on of everyone that’s already coming to our store, what can we do to keep them more attracted? What can we do to get them to look at other things? What can we do to get them to read additional articles? All of those behaviors drive uses of our product.”
