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Advertising is a big portion of an eCommerce site's budget. Advertising expenditures need to be evaluated on the basis of online sales they generate.
Does this mean that eCommerce sites have additonal requirements? If yes, is your current tracking software satisfying these requirements?
Suppose they bought an advertisement in a newsltter that was being emailed to 200,000 people. Let's say this cost $ 70 a thousnand. or $ 14,000.
Now the media buyer has to determine if that was a good expenditure or not.
Let's look at it in real world terms. The emails went out Sunday night and on Thursday afternoon a decision has to be made on whether to place the advertisement again and pay the $ 14,000 for a second wave.
Could your marketing department get the tracking data they needed to answer this question?
If you are just sending them to the main page of a site that otherwise generates traffic, you are looking at a lot more work. Most surfers are only going to 3 or 4 pages deep on any site so you could actually build a self contained "mini-site" to track them very easily.
I'm not so sure that the solution is in the tracking software or in the planning of the response and where you send them.
Sunday to Thursday? I can't imagine why you would need that much time.
That gateway page idea works for some sites. It only solves part of the problem. Once the visitor leaves the gateway page his association with the email is generally lost.
The media buyer knows the number of people that responded to the offer. 200,000 emails were sent and about 16,000 clicked to the page. How many of the 16,000 bought anything?
Now most activity on emails ends after three days. A few response trickle in later than that. If 100 visiitors bought it might be wrong to continue renting the mailing list. If 2000 bought it might be a great list to buy.
Without being able to see this information, the media buyer must make a decision without all the facts. These decisions are as often wrong as right.
The great dot.com fiasco was caused in part by people buying volume and not ensuring that it was profitable.
They lost a little on every sale and tried to make it up on volume.
The fiasco was caused by underwriters making huge fees bringing dotcoms public, blame it on the Morgan Stanleys' of the world.
The efficiency of the web is apparent when you begin to look at the alternative; a traditional bare bones 200,000 piece mailing will run you close to $80,000.00 when you calculate postage, printing and list rental. At 14 grand, you can email that same list almost 6 times.
Are you selling one product or directing the visitors to a shopping cart?
First, I had to "wrap URLs" so that what were really different requests would get processed as the same request. Specifically I took the session ID out of the URL. That way I know how many times a certain product info page was viewed, not the number of times Joe Blow happened to view it.
Then I wrote some custom processing in Perl to get down to the real e-commerce aspects. For example:
#1. The number of times people see a thumbnail vs. the number of times they ask for more info by clicking on it. I call this "interestingness factor." Things with a good interestingness get clicked on a lot, they must be interesting. (Note, low numbers are good. A number of 1.0 would be ultimate.)
#2. (number of times the info pages was seen) / (# of times the product was actually bought) = the saleability-factor. Again, low numbers are good. I find that even the hottest products have a factor over 100 here.
#3. (number of carts for a given period) / (number of orders for a period) = abandonment-rate. When this is high people are loading up their carts and fleeing the site.
Is there software out there that does this automatically? Not for my system. The way I see it, if you author an ecommerce system, you're not really done until you get into custom log analysis which has to be designed specifically for your system.