Monday 26 January 2015

Re. Reporting

SFK Frou-Frou Super Deluxe Camera Strap $95, Cos Melange Knit Hit £13 (down from £25), & Other Stories Short Leather Gloves £23 (down from £45), Surface to Air Le Baron Boots £105 (down from £350) at Avenue 32.com, Christopher Raeburn Arctic Print Rucksac £250 (down from £499) at Coggles.com

I have been looking with fresh eyes at some of our reporting since the start of the year.

Before Christmas, I began adding some formulas to a spreadsheet we use each week - reducing the number of vlookups and original entries we have to insert. Since week one, I've been testing it and last week showed it to some colleagues. Luckily, they were enthusiastic and we will atttempt to integrate it into our weekly routine. All going well, it'll save a lot of trouble identifying products that are missing from our pages.

Another thing I really want to look at, is how I determine whether a product/category has done as well as it should have in any given week.

Just asking if product/category sales are better than in the previous week is too simplistic, so I started comparing to average sales over the past few weeks.
But sales are always going to go up and down. If stylish underwear sells well in the weeks before Valentine's day and the less well again toward the end of February, I need to be aware when I'm looking at my figures. I don't want to be attributing the trend erroneously, and I don't want to be thinking it will last longer than it will.
So some historic data should be taken into account, but then a direct comparison may not be valid either - everything might be selling better/worse than last year.

My instincst say that looking at percentage share of sales would be good (the product's percentage share of its category, the category's percentage share of total sales).
I could compare percentage share this year to percentage share last year - but then I'm not taking into account range changes. We might have invested more in, say, sports underwear this year, and so share of sales might naturally be higher.

Ideally, I think I would be comparing the difference between this week and last week's share to the difference between this week last year and last week last year's share.
This should tell me if a product/category is improving or not, and help me decide where to work next. I think the only thing that would skew these figures would be very recent launches of new products/ranges. 

I'm mulling all this over, because - on a SKU by SKU level at least - it's a lot of work. Fun project though!

On a different note, I am - excitingly and excitedly - about to go to Berlin. So above you have some chilly city site-seeing gear.

Have a great week.

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