DSR Are Not Anonymous: How to Find It Out for Any Item

To a seller, the importance of DSR [detailed seller rating] cannot be overstated. Indeed, your potential TRS [top rated seller] status designation, your eBay fee discount, your search ranking in "Best Match", and even your ability to sell on eBay are all tightly connected with your DSR scores.

Many buyers were misinformed by eBay and thought that DSR were totally anonymous, and a few of them would lash out unfair [especially low scores, i.e., 1 or 2, but even 3 or 4 is bad enough accumulatively] DSR rating while hiding behind positive feedback. Sellers were often baffled by this seemingly strange [though not exceedingly uncommon] behavior [the rationale of such a buyer, however, is not a subject of the current guide] and suffered serious consequence of the abuse nevertheless without any recourse except by blocking such buyers for any future purchase. On the other hand, no seller would block such buyers had eBay not placed so much weight on DSR [specific eBay policy, however, is not a subject of the current guide neither]. Many sellers were frustrated at the inability of knowing the roots of the problem. Of course, watching your average DSR closely helps somewhat [especially for low volume sellers], but there seems to be no way of pinpointing the source of the problem. The fact that fresh DSR score are recorded according to their transaction dates instead of the dates that are left further complicates the issue...

Is it really so anonymous? My answer is absolutely "No". In fact, you can find out precisely who had left you what for any specific transaction by following only two simple steps [or just one step if you had made a reference list already as outlined below] regardless of your transaction volume and history [e.g., whether you have only a few (lesser than 5) or many (1000+) transactions per month].

How? The basic idea runs like this -- eBay allows its sellers to make aggregated report on DSR with regard to [among others, e.g., time and geography] specific item # [so long as the aggregation is composed of at least ten items, hence, to keep it seemingly anonymous]. Since you already know the average DSR of an aggregate [by virtue of running the said report], if you utilized the same aggregate except that you would add an extra item # [of your interest] to run the next DSR report, then, there is nothing to prevent you from knowing the impact [or the exact DSR scores] of this added transaction and everything is in compliance with the current eBay policy.

Let's say you think the buyer of item #x [x should be a single quantity item or a multi-quantity item but with only one feedback left so far (*see footnote for an explanation)] might have left you a lesser than fair DSR and would like to know a little more about the DSR scores [let's called it X] he/she had left for you [so you might improve your future business and service]. Just follow these 2 steps below will be sufficient:

Step 1. Making a reference list -- Pick out n number of single item transactions [with their corresponding item # of course], n has to be larger than or equal to 10, click on your DSR dashboard and run a eBay DSR report for these item numbers [separating each by a comma] and record the scores for each category and let's call the results "R" which stands for Reference score.

Step 2. Computing the particular DSR -- Add item # x into your pool of n [now the total number of items become n+1], run the same report as above and record the score for each category [likewise, let's call the results "C" which stands for the Current score].

Then:

X=(n+1)C - nR [eq.1]

Thats it !

***** An Illustrative Example and Two Additional Simplified Methods*****

Method 1 [as outlined above with following real example]: I noticed [quite a while ago] that my DSR score had fallen within last five feedback of that particular period. To ascertain what DSR scores were associated with each of the five feedback left by five different buyers, I picked out 15 items [easily done by looking at your own feedback page, but make sure not to accidentally include in this reference list any items # that you are going to test next, you might pick out 10 items, I use 15 here just as an illustrative example] and run eBay DSR report with regard to item # according to Step 1 and got following results: 5.0, 5.0, 4.93, 5.0 for item as described, communication, shipping time, shipping and handling charges respectively [thus we have R=(5, 5, 4.93, 5)]. I then added the item # from one of the five recent feedback into the pool and run the report one by one. Four of them gave me the same results of: 5.0, 5.0, 4.94, 5.0 [hence these four buyers have all left me 5 stars across the board] while one item # gave me the results of: 5.0, 5.0, 4.94, 4.81. I immediately knew that this last buyer had given me a 2 stars rating for Shipping and Handling Charges while left me 5 stars for all other categories. How? Elementary: with x=(n+1)C-nR = (15+1) x 4.81 - 15 x 5=1.96 [round up to 2]. The DSR scores of other categories of this item were self-evident, take the shipping time for instance, we have (15+1) x 4.94 - 15 x 4.93 = 5.09 [hence round to 5, thus X = (5,5,5,2)].

Method 2. [with the 10 perfect item list]: You can simplify above calculation if you could come up [just run several DSR item trial reports and you will come up with the perfect list with ease] with 10 items with perfect 5 DSR across the board [thus, R =(5,5,5,5)]. You might save those 10 items [with their corresponding eBay item #] as your future reference [so you might skip Step 1 and proceed to Step 2 directly [via run similar in detailed DSR report], but it is a good practice to run Step1 for the perfect Reference to confirm R = (5,5,5,5)if enough time had lapsed]. Adding the item # x in question into the reference pool of the perfect 10 [now that the total number of items becomes 11] and run the same report, and then calculate the x according to the following equation [i.e., the same eq.1 above with n=10, and nR=50]:

X=11C - 50.

With my particular example [as outline in Method 1], after adding item # x into my perfect 10 items list, I have gotten [5.0, 5.0, 5.0, 4.73] from one buyer and [5.0, 5.0, 5.0, 5.0] for all other four buyers in my DSR report, so the shipping and handing DSR left by this particular buyer = 11 x 4.73 50 =2.03 [thus confirmed that he had left me a 2 stars on shipping and handling charge as mentioned in Method 1.].

You can even do away with any calculation [with the perfect 10 list] by reading out the result directly according to this one line table: If any of your DSR category score [after adding the x as the 11th] became [or very close to the values given for the DSR report are round up to the 2nd decimal point] 4.63 or 4.72 or 4.81 or 4.91 or 5 then he had left you a 1 or 2 or 3 or 4 or 5 respectively.

Method 3. [with the 10 perfect item list but run the DSR report with replacement]: You might also run a variant of Method 2 by replacing one of the perfect ten with item # x and run the report according to Step 2 as an added verification. In my particular example above, my shipping and handling DSR became 4.7 [all else were 5, i.e., C=(5,5,5,4.7)], so x=10x4.7 9x5 = 47 - 45 = 2 [using the same equation (eq.1), but n now became 9 in this method of running report with replacement, hence, confirmed again that he had left me a 2 for shipping and handling charge].

The advantage of this approach [Method 3] is that not only calculations are unnecessary as with Method 2, but also the numbers are cleaner and you don't have to round them [up or down]. This is because your test results [i.e., every member of C] can only be [unless was left blank and the report will generate "no results"] one of the five values -- they can only be 4.6 or 4.7 or 4.8 or 4.9 or 5 indicating the specific DSR score left at 1 or 2 or 3 or 4 or 5 respectively. Let's put them into the following table form:

c: 4.6 4.7 4.8 4.9 5 x(DSR): 1 2 3 4 5

Note: Though all three approaches detailed above are straightforward, Method 1 is particularly useful for those sellers who have only a few transactions per month and hence who might not be able to find a reference list of 10 items with perfect DSR, it will also be able to generate extra information when other two methods are limited (e.g., when deliberately choosing a reference list of 10 with imperfect DSR score in all categories, you will be able to know the exact DSR score even if some categories were left as blank). For simplicity, however, running either Method 2 or Method 3 is suggested.

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Had more buyers known that DSR were not really anonymous, some might have been a little more impartial at giving out such [potentially unfair] rating and been prepared to stand firm if challenged [after all, eBay explicitly does not allow its members (especially if the buyer was also a fellow seller or a potential competitor) to abuse the DSR system]. Sellers in turn, when equipped with the current information, should be able to make a better or informed judgment on the nature of the problem at hand and improve their future service accordingly.

Footnote: *Multi-quantity item [i.e., item with the same eBay item # but sold several times to different buyers] with numerous feedback left within a short period of time from different buyers in general should be treated separately and the exact procedure of determining the DSR scores for each individual buyer of the same multi-quantity item is a little more complex and might not be cost-effective in terms of time spent for an average eBay seller to dig into. But it can be done precisely [via additional slicing of time of purchase and geography for instance]. I would, however, leave that for private communication should you really want to know how.

-- Edited by budnonymous on Monday 26th of August 2013 03:14:27 PM