Groupon And Clone Data Scraping (scrape Website)

Bidding on this project will end after 4 days.

I would like to have some sites scraped. The sites are clones of Groupon. See the attachment for the URLs (10 sites in total). I need the following info from the sites:
1. product/deal titel
2. deal picture
3. deal summary
4. deal description
5. old price
6. new price
7. discount percentage
8. number of times bought
9. time that the deal ends

You can look at groupon to see the items I am refering to. All the clone sites have the same items (the 9 I listed above) as groupon.

The script only needs to echo those 9 items. No need to save to a database. The sites must be scraped using cURL (some of the sites may set cookies which you can save in the cookiejar so cURL can visit the website).

Your quote must be for all 10 sites.

Payment will be done in escrow after I see a working demo on your own site/server.

Source: http://blancer.com/freelance-projects/173784/groupon-and-clone-data-scraping-scrape-website/

Note:

Roze Tailer is experienced web scraping consultant and writes articles on coupon code website scraping, groupon data scraping, tripadvisor data scraping, amazon data scraping, yellowpages data scraping, product information scraping and yellowpages data scraping.

Groupon is getting killed in the Middle East

The Middle East is probably the most underrated growth market on the planet right now: Over 350M people with 70% under the age of 30. Groupon recently established an operation in the region but according to data for the last month they’re being crushed by Cobone.com, the local competitor. Can Groupon execute outside of their core territories?

The graphs below are based on data scraped from the Groupon and Cobone sites (UAE, Lebanon, Jordan, Saudi Arabia and Egypt) between May 14th-June 14th.

At first glance, Cobone is really hammering Groupon just in terms of coupons sold by about two to one.

But taking a closer look at the deals themselves and you see where Cobone is really killing them. Over the same period, Cobone turned over almost three times Groupon’s revenue. Clearly Groupon are having trouble getting to the higher quality merchants in the region.

What’s particularly interesting is how the two companies are leveraging social media in the region. Although the overall user numbers for Facebook and Twitter in the Middle East are still low (but growing rapidly), clearly Cobone understands a) how to engage them and b) how to monetize them. Groupon, on the other hand, appear to be either ignoring social completely (which seems odd) or simply don’t have a handle on it in that particular market.

Source: http://dylancollins.com/?p=316

Note:

Roze Tailer is experienced web scraping consultant and writes articles on coupon code website scraping, groupon data scraping, tripadvisor data scraping, amazon data scraping, yellowpages data scraping, product information scraping and yellowpages data scraping.

Groupon Math: Data Scraping to Estimate Revenue

There’s been a lot of talk recently about the Chicago startup Groupon. Groupon brands itself as a group-buying site, but it’s really more of a localized version of what woot.com does. They post a new deal (which they call a Groupon) every day, available only on that day. If enough people want to buy it, everyone gets it for a substantial discount. Otherwise, nobody gets anything, but this rarely happens from what I can tell.

According to TechCrunch, the company is in the process of raising money at a $1.2 billion dollar valuation. There was lots of speculation about the future worth of the company, but little information about current revenue, even though there is a lot of raw data readily available in the site’s archives. I put together a scraper (in just a few lines of Python, thanks to BeautifulSoup) and gathered a total of 1065 past Groupons.

It isn’t clear how Groupon decides which Groupons to display in its archives. Presumably they are the better selling ones, so my sample is not a random sample, which would affect the numbers. Everything that follows should be taken with a grain of salt, but they should be reasonable as ballpark figures.

According to the data I collected, the average Groupon costs $30 and entitles the buyer to 57% off. On average 1155 people purchase it, resulting in $28,130 of revenue to Groupon ($28,130 is less than 1155 * $30 = $34,650 because, apparently, people are more willing to buy the cheaper Groupons.)

Averages are nice, but what I really wanted was totals. I was able to approximate what fraction of the data I had because Groupon advertises the “Total dollars saved” and “Total Groupons bought” on every page. By dividing my numbers by those, I determined that I had a little over a third of the data. Specifically, my data covered 31.2% of Groupons sold, and 37.4% of total savings.

Extrapolating the data I had (again, with the disclaimer that my sample may not be random), I calculated the total revenue since the beginning to be $80,188,176. If Groupon takes a 35% cut (to take a wild guess), $28 million of that is left after Groupon pays the company offering the deal. According to CrunchBase Groupon employs 90 people. I won’t speculate as to the operating costs of Groupon over the last year and a bit of operation, but once you subtract that number the rest is profit to date.

Looking on a monthly basis, the recent growth of the company is clear. A third of the total savings — in over a year of business — happened last month. This works out to $26,706,059 in revenue last month alone, or about $9.3 million (less the operating costs) profit if you assume they take a 35% cut. The below graph shows the growth by month.

Whether or not it’s a $1.2 billion company (BusinessInsider says that’s actually low, though without any quantitative justification), they’re clearly doing well for a company just over a year after launch.

Here are a couple more graphs constructed from the data

Source: http://paulbutler.org/archives/groupon-math-data-scraping-to-estimate-revenue/

Note:

Roze Tailer is experienced web scraping consultant and writes articles on coupon code website scraping, groupon data scraping, tripadvisor data scraping, amazon data scraping, yellowpages data scraping, product information scraping and yellowpages data scraping.