I went to Online Market World yesterday. It was surprisingly really empty. One company that I found quite interesting was Baynote, who delivers on-demand recommendations and social search for websites. Similar to Amazon.com, product recommendations are made based on your behavior and those that have displayed similar behavior. The difference, if I understand correctly, is that product recommendations and link recommendations are made in real-time, rather than the next time you visit the site.
I recently made a recommendation to a comparison shopping site to make their online retail experience more like the in-store experience. It’s great to see Baynote moving in that direction. I think this will be really effective for e-tailers that decide to partner with them.
The algorithm acts somewhat like an in-store salesperson (if salespeople had photographic memories and impressive pattern recognition capabilities). An attentive salesperson that suggests products to you no doubt increases the purchase probability and basket size compared to one that ignores you the entire time you are browsing the store. Now, if only Baynote or another company could take it a step further. For example, what happens if the product recommendation is rejected or ignored? What would a live salesperson do? They would be suggesting additional items, gathering feedback and digging deeper to find out what the shopper is really looking for. Because of this, the end conversion rate is much higher than if every salesperson stopped at the first recommendation.
On the other hand, e-commerce sites must also be weary. What’s effective in-store could backfire online. There are many reasons why people prefer to shop online. For some, it may be that they do not want to be bothered by annoying salespeople.
My favorite part of Baynote’s technology: it ignores demographics. Yes! When are people going to figure out that this is an individualistic age? Advertisers, you are wasting your dollars on serving me with endless weight-loss and dating ads. Not all 27-year old females are the same!
Thursday, October 2, 2008
Subscribe to:
Posts (Atom)