Comparing Sales of One Product with Another [Excel Techniques]

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This is a guest article by Theodor on how to Compare Sales of One Product with Another

Ok, now here’s one for you.

Suppose you’d like to come up with a sales report on different products, comparing their evolution on the same period of different years (say Jan ’09 vs. Jan Jan ’10). At the same time, you’d like to keep an eye on their yearly trend (entire 2009 vs. entire 2010).

No big deal, you’ll say, but here’s the twist: the products have not been available for the entire time span taken into consideration. Let’s say you’ve only had Product 1 available for sale for Feb ’09 onwards, while it had been discontinued from October ’10. If you’re really looking for a Like-For-Like (LFL) comparison, you’d only want to compare the months where you have data for both years. It’s false to claim you’ve had a sales boost of 300% when you entered the market with Product X in October 2009, selling 1000 units over 3 months and compare that to the full results of 2010, when you’ve sold 3000 units. In the first scenario you were averaging some 333 units/month, while later you’ve dropped to a mere 250/month. Nothing to brag about there, is it?

Ah, but we also have different product classes. One is aimed for the high-profile buyer (A-Class products), the second for the middle level (B-Class) and so on. Given that different products were added to each class’s portfolio and then later discontinued, we should see the total LFL development of each product class in the same graphical representation.

Hold on another second. One country is defining its quarters as Jan-Mar, Apr-Jun etc, while other might relate a quarterly result to a specific day in the company history (such as the company launch date, or since the new CEO took over or whatever). Wouldn’t it be nice to be able to compare equivalent datasets in any user-defined time span?

So how do you compare sales of one product with another?

Now I’ve always said that the second hardest thing mankind has ever done was to send men on the Moon and safely return them home. That’s only because the MOST difficult thing in the world has become to compare apples with apples. There are so many subtle differences between one dataset and the other (even though they both relate to the same source), that if one reporting template is to have a long life, it should first and foremost come with the built-in ability to allow the end user to drill down through the data and change criteria in order to get relevant results for today’s issue. And all that will change tomorrow, as there will lay a new and unexpected issue on the table.

With that in mind, when I create my templates I follow the self-made golden rule (which later I found many others have applied for themselves long before I knew Excel ever existed) – keep the raw data in one sheet, preferably hidden; use a second sheet for calculation, ALWAYS hidden, and provide a simple and useful graphical interface for the end-user in the third sheet. This will avoid any mishaps such as “Could you please put your formulas back in, I donno which button I pressed and….!!”

Comparing Sales of One Product with Another – Demo:

First see the demo of this technique. Then, we can learn how I created it.

Comparing Sales of One product with Another - Demo

Coming to the attached example – which only works in Excel 2007 and later, by the way:

  • Your data is in sheet ‘data’, ordered by product and timeline (Jan-Dec, 2009 and 2010). I’ve created the values using the =randbetween() formula, and then copy-pasted the values only so they will not change anymore.
  • To keep things more clear, I’ve placed the calculation formulas in the same sheet as that with the graph, just so you can compare values and figure out formulas more quickly, without having to switch between sheets all the time.

Comparing Sales - Data

How the Sales Comparison Chart is made?

Now, to bring up values of a particular product, I’ve created a list in C44:C70 (values in column B are just for guidance). We can compare two products, which can be chosen from a couple of drop-down boxes linked to cells B6 and B8. Here’s where the values in column B help: basically, they tell me which item index from the drop-down corresponds to a product. I then placed the same item indexes in data!A7:A46. This is all because I am lazy and I find the sumifs() formula a blessing: all I have to do now is to add up the results that correspond to (1) the chosen Product in the drop-down, which is looked up by the index, and (2) the year, which is in data!E6:E45. [More on INDEX Formula]

How does the sales comparison chart work

An alternative in Excel 2003 would have been to concatenate the value of “Product 1″&”2009” for example, to get a unique identifier and not return the sales value of 2010 by mistake. Then vlookup() after the concatenated value. [Related: How to lookup based on multiple conditions]

These calculations are placed in ‘Yr sls’!F51:Q54. Note there’s an initial IF() there, to only display the values if the respective month is selected. There are two sliders up in the second row, which can help you ‘cut’ your desired portion of the year for comparison.

‘Yr sls’!F61:Q68, using sumifs() again, I added the sales values for each product class. Finally, in ‘Yr sls’!F45:Q48 are the final calculation, where if an item index lower than 8 (corresponding to Product 1) is selected, the values in F61:Q68 are brought up, else the values in F51:Q54.

So now we see our resulting values above the chart, in cells F6:Q9. The deviation is calculated in F5:Q5. But for the yearly totals, I only want to compare apples with apples, i.e. months in which sales have been recorded in both years. For that I used cells U6:AF9. The totals in R6:R9 are based on these isnumber() results. This allows you to have the exact deviation between similar months over an user-defined time span.

Ok, time to close. But not before your boss knows the exact portfolio of each product class! Look shortly in data!B6:B45. This is where, using countif(), we have the number of occurrences for each product class. Knowing that product class “A” will be repeated say 3 times, we’ll use this knowledge to look up the third occurrence of “A” and bring up the product next to it. Now take a peak in sheet “Legend”. Knowing we have to lookup for A 1, that’s how I wrote the formula. But also knowing that “A” will be repeated twice for each product (once for 2009, another for 2010) and not wanting to see duplicates in my product list, there’s a very simple solution: just use odd numbers!! This will only bring up every 2nd occurrence of a product. As I said, I like it simple 🙂 I just left the numbers in C5:C15 visible so you don’t have to fish around for them, the rest are simply I the same color as the background. A bit of conditional formatting does the rest.

Of course, before presenting this to any decision maker, you’d hide the rows and columns they’re not supposed to touch and present them with a clean looking table.

Download the Excel Workbook:

Click here to download the workbook with this example. Examine the formulas and chart in “Yr Sls” worksheet to understand how this is weaved together.

[Added by Chandoo]

Thank you Theodor

Thank you so much Theodor for teaching us some valuable techniques on how to compare apples with apples. I am sure our readers will find these ideas very useful.

If you like this post, say thanks to Theodor.

Do you compare & analyze sales data?

I do this all the time. As part of running my small business, every couple of months, I would take up sales data and see if something odd is going on. I make line charts comparing sales of this year with previous year, understanding the overall trend and compare one product with another.

What about you? Do you analyze sales data? What techniques do you use use? Please share using comments.

Learn more from these pages:

If you work a lot with data & do similar work as above, go thru these articles to learn more.

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13 Responses to “Using pivot tables to find out non performing customers”

  1. David Onder says:

    To avoid the helper column and the macro, I would transpose the data into the format shown above (Name, Year, Sales).  Now I can show more than one year, I can summarize - I can do many more things with it.  ASAP Utilities (http://www.asap-utilities.com) has a new experimental feature that can easily transpose the table into the correct format.  Much easier in my opinion.

    David 

    • Chandoo says:

      Of course with alternative data structure, we can easily setup a slicer based solution so that everything works like clockwork with even less work.

  2. Martin says:

    David, I was just about to post the same!
    In Contextures site, I remember there's a post on how to do that. Clearly, the way data is layed out on the very beginning is critical to get the best results, and even you may thinkg the original layout is the best way, it is clearly not. And that kind of mistakes are the ones I love ! because it teaches and trains you to avoid them, and how to think on the data structure the next time.
     
    Eventually, you get to that place when you "see" the structure on the moment the client tells you the request, and then, you realized you had an ephiphany, that glorious moment when data is no longer a mistery to you!!!
     
    Rgds,

  3. JMarc says:

    Chandoo,
    If the goal is to see the list of customers who have not business from yearX, I would change the helper column formula to :  =IF(selYear="all",sum(C4:M4),sum(offset(C4:M4,,selyear-2002,1,columns(C4:M4)-selyear+2002)))
     This formula will sum the sales from Selected Year to 2012.

    JMarc

  4. Elias says:

    If you are already using a helper column and the combox box runs a macro after it changes, why not just adjust the macro and filter the source data?
     
    Regards

  5. RichW says:

    I gotta say, it seems like you are giving 10 answers to 10 questions when your client REALLY wants to know is: "What is the last year "this" customer row had a non-zero Sales QTY?... You're missing the forest for the trees...
    Change the helper column to:
    =IFERROR(INDEX(tblSales[[#Headers],[Customer name]:[Sales 2012]],0,MATCH(9.99999999999999E+307,tblSales[[#This Row],[Customer name]:[Sales 2012]],1)),"NO SALES")
    And yes, since I'm matching off of them for value, I would change the headers to straight "2002" instead of "Sales 2002" but you sort the table on the helper column and then and there you can answer all of your questions.

  6. Kevin says:

    Hi thanks for this. Just can't figure out how you get the combo box to control the pivot table. Can you please advise?
     
    Cheers

  7. Kevin says:

    Thanks Chandoo. But I know how to insert a combobox, I was more referring to how does in control the year in the pivot table? Or is this obvious?  I note that if I select the Selected Year from the PivotTable Field List it says "the field has no itens" whereas this would normally allow you to change the year??
     
    Thanks again

  8. Kevin says:

     
    worked it out thanks...
    when =data!Q2 changes it changes the value in column N:N and then when you do a refreshall the pivottable vlaues get updated 
     
    Still not sure why PivotTable Field List says “the field has no itens"?? I created my own pivot table and could not repeat that.

  9. Bermir says:

    Hi, I put the sales data in range(F5:P19) and added a column D with the title 'Last sales in year'. After that, in column D for each customer, the simple formula

    =2000+MATCH(1000000,E5:P5)

    will provide the last year in which that particular customer had any sales, which can than easily be managed by autofilter.

    • Bermir says:

      Somewhat longer but perhaps a bit more solid (with the column titles in row 4):

      =RIGHT(INDEX($F$4:$P$19,1,MATCH(1000000,F5:P5)),4)

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