when to predict the cheapest online shopping when to predict the cheapest online shopping

almost all of the electricity supplier sites are advertised their price, the lowest of the whole network, but consumers often find that the fact is not the case, was fooled when the situation occurs. U.S. start-up company for this situation, the introduction of an electricity supplier parity platform. (micro-blog), Amazon is able to grab the best buy, Newegg and a number of other electricity supplier website data, and integrated in a page, convenient for consumers to view the comparison. But it’s not the end of it. What it really wants to do is to let consumers know what to buy and when to buy".

to this end, added three main features: user evaluation, new forecasts, and price trends. As shown below:


in, Nikon D5100 scored 90 points, which means that the site believes that this product is worth buying

in the user evaluation column, Nikon D5100 won 90 points (out of 100 points), is one of the highest rated products. This is the average score given by 551 users and 7 experts. In the new forecast column, you can see in the next 6 months, the series will not release new products, so consumers do not have to worry about this SLR will soon be eliminated. In the price trend column, you can see the next 2 weeks prices will remain stable. In addition, in the upper right corner, you can see the price of home appliance manufacturers are $646.95. hopes that these data allow consumers to make rational judgments. initially provides only the contrast of digital products, has now extended to 150 product categories. This site is not only convenient for consumers, but also for the home appliance manufacturers to bring traffic and sales, commercial prospects are very clear. did not disclose user data, only that its iPad application downloads has exceeded 100 thousand, has made a recommendation to the consumer of the 7 million. The company CEO Mike · (Mike Fridgen) in particular, has saved $75 million for consumers $.

in fact, there are a lot of people in the domestic electricity supplier parity, but are not formed, it is not enough to use, only to see the trend of price changes, it is difficult to determine whether ordinary consumers should be shot. The success of is that it is not satisfied with the simple data integration, but through data mining, in a more intuitive form to tell consumers how to do. Perhaps that’s what consumers want to see

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