Comments on: For Online Recommendations, One Size Doesn’t Fit All http://gigaom.com/2009/05/27/one-size-doesnt-fit-all-when-it-comes-to-online-recommendations/ Trusted Insights and Conversations on the Next Wave of Technology Wed, 25 Nov 2009 16:39:17 +0000 http://wordpress.com/ hourly 1 By: Todd Pearson, Chief Customer Officer, richrelevance http://gigaom.com/2009/05/27/one-size-doesnt-fit-all-when-it-comes-to-online-recommendations/#comment-961568 Todd Pearson, Chief Customer Officer, richrelevance Wed, 22 Jul 2009 18:06:10 +0000 http://gigaom.com/?p=51558#comment-961568 <p>I find Patricia’s post very interesting. As chief customer officer, I’ve seen every deal that has passed through richrelevance, and I can say that every retailer who has tested our product suite against our competitors has gone on to select us as their partner. Also, an important point of clarification – we only offer only pay-for-performance pricing and have never offered a rate anything like that described in Patricia’s comment.</p> I find Patricia’s post very interesting. As chief customer officer, I’ve seen every deal that has passed through richrelevance, and I can say that every retailer who has tested our product suite against our competitors has gone on to select us as their partner. Also, an important point of clarification – we only offer only pay-for-performance pricing and have never offered a rate anything like that described in Patricia’s comment.

]]> By: Patricia Linford http://gigaom.com/2009/05/27/one-size-doesnt-fit-all-when-it-comes-to-online-recommendations/#comment-959718 Patricia Linford Tue, 14 Jul 2009 17:15:40 +0000 http://gigaom.com/?p=51558#comment-959718 <p>"Sites like Sears and Burton, which use more than one recommendation technique, have been able to boost sitewide sales by up to 30 percent over the long term".</p> <p>As part of the e-commerce team of a large retailer, we decided we wanted to implement automated recommendations on our site. We looked at a number of players, among which Rich Relevance. We didn't select them because we did some bucket testing to compare their solution with two other vendors and felt they were better at marketing than at ecommerce.</p> <p>If Mr. Vangroff's assertion is correct, (their solution increases sales by 30%) then why did they quote us a monthly price of $1,500? For an increase in sales by 30%, we'd be happy to pay 10 or 100 times that price.</p> <p>My intention is not to criticize Rich Relevance, (their impressive client base indicates that there must be some substance behind their claims), I just want to make sure that other ecommerce managers think carefully when selecting a recommendations vendor, and do not rely on promotional postings of this nature.</p> “Sites like Sears and Burton, which use more than one recommendation technique, have been able to boost sitewide sales by up to 30 percent over the long term”.

As part of the e-commerce team of a large retailer, we decided we wanted to implement automated recommendations on our site. We looked at a number of players, among which Rich Relevance. We didn’t select them because we did some bucket testing to compare their solution with two other vendors and felt they were better at marketing than at ecommerce.

If Mr. Vangroff’s assertion is correct, (their solution increases sales by 30%) then why did they quote us a monthly price of $1,500? For an increase in sales by 30%, we’d be happy to pay 10 or 100 times that price.

My intention is not to criticize Rich Relevance, (their impressive client base indicates that there must be some substance behind their claims), I just want to make sure that other ecommerce managers think carefully when selecting a recommendations vendor, and do not rely on promotional postings of this nature.

]]> By: Recomendações online: nem tudo é perfeito! « Artificial Intelligence Applications http://gigaom.com/2009/05/27/one-size-doesnt-fit-all-when-it-comes-to-online-recommendations/#comment-950031 Recomendações online: nem tudo é perfeito! « Artificial Intelligence Applications Thu, 04 Jun 2009 18:23:59 +0000 http://gigaom.com/?p=51558#comment-950031 <p>[...] Para mais detalhes sobre segmentação, colaboração, personalização e similaridade, leia o artigo do autor clicando aqui. [...]</p> [...] Para mais detalhes sobre segmentação, colaboração, personalização e similaridade, leia o artigo do autor clicando aqui. [...]

]]> By: Analytics Team » Blog Archive » Different methods for online recommendation http://gigaom.com/2009/05/27/one-size-doesnt-fit-all-when-it-comes-to-online-recommendations/#comment-949118 Analytics Team » Blog Archive » Different methods for online recommendation Mon, 01 Jun 2009 18:51:37 +0000 http://gigaom.com/?p=51558#comment-949118 <p>[...] Darren Vengroff, chief scientist from RichRelevance, explains some of the components of a recommendation system in a GigaOM article. [...]</p> [...] Darren Vengroff, chief scientist from RichRelevance, explains some of the components of a recommendation system in a GigaOM article. [...]

]]> By: amazingamazon http://gigaom.com/2009/05/27/one-size-doesnt-fit-all-when-it-comes-to-online-recommendations/#comment-947217 amazingamazon Wed, 27 May 2009 16:48:30 +0000 http://gigaom.com/?p=51558#comment-947217 <p>That was incredibly informative. I finally understand what underlies these recommendation systems. And it makes perfect sense to use the best technique in each particular situation rather than always using the same approach? Why wouldn't all of the recommendation providers do this?</p> That was incredibly informative. I finally understand what underlies these recommendation systems. And it makes perfect sense to use the best technique in each particular situation rather than always using the same approach? Why wouldn’t all of the recommendation providers do this?

]]> By: Lotame Learnings » Blog Archive » Data driven targeting: Here are 4 approaches http://gigaom.com/2009/05/27/one-size-doesnt-fit-all-when-it-comes-to-online-recommendations/#comment-947134 Lotame Learnings » Blog Archive » Data driven targeting: Here are 4 approaches Wed, 27 May 2009 11:04:11 +0000 http://gigaom.com/?p=51558#comment-947134 <p>[...] his blog post over at GigaOm entitled “One Size Doesn’t Fit All When It Comes To Online Recommendations,” Darren Vengroff writes about 4 different product recommendations approaches, all deeply [...]</p> [...] his blog post over at GigaOm entitled “One Size Doesn’t Fit All When It Comes To Online Recommendations,” Darren Vengroff writes about 4 different product recommendations approaches, all deeply [...]

]]> By: eee fff http://gigaom.com/2009/05/27/one-size-doesnt-fit-all-when-it-comes-to-online-recommendations/#comment-947126 eee fff Wed, 27 May 2009 10:17:20 +0000 http://gigaom.com/?p=51558#comment-947126 <p>This seems like an advertorial with ANY DISCLOSURE!</p> This seems like an advertorial with ANY DISCLOSURE!

]]> By: Maddy http://gigaom.com/2009/05/27/one-size-doesnt-fit-all-when-it-comes-to-online-recommendations/#comment-947109 Maddy Wed, 27 May 2009 07:47:04 +0000 http://gigaom.com/?p=51558#comment-947109 <p>How to combine the techniques to create the best overall experience. After serving more than 20 billion product recommendations.</p> How to combine the techniques to create the best overall experience. After serving more than 20 billion product recommendations.

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