Promotion. Love it or hate it, it is a cornerstone of the business. More often than not it promotional spending can feel like giving money away. Even worse it’s not uncommon for brands to go year-after-year of recycling and re-using their same promotional tactics without diving into what is truly driving the ever-elusive incremental sales.

 

Take heart if you are the latter group who has pulled out last years promotional calendar from your archive and uses it again when planning for the next marketing calendar, there is no doubt certain wisdom to why those particular windows were selected the first time. If you’re not yet purchasing syndicated data and want to analyze your existing retailer portal data (think Whole Foods or Kroger) or UNFI, then keep on reading this article is for you! With a little technique and some simple math, you too can learn to navigate this data. If you approach promotions with a strong foundation of a category management theory and the right attitude, designing next year’s marketing calendar can transform into a fun challenge. The first time you realize the amount of money you can save at a retailer by cutting away unnecessary spending will be thrilling!

Learning to listen to what the data is telling you can give your planning meetings new life by adding in the fundamental skills that will help you become a master trade promotions planner.

Here are five tips on how to to approach a promotional analysis with gusto and technique!

1. Identify a Promotion

 

Now before you grab whatever calendar where you’ve listed out each promotional period, stop. We are going to instead identify where we were on promotion by analyzing our own data. In this example we will be reviewing how to conduct an analysis on retailer portal data that does not have all of the fancy measures for promotions.

To get started we need to calculate (1) measure. This will then enable us to construct a simple bar chart which will allow us to conduct our analysis. The measure we are going to calculate is known as ARP or Average Retail Price. With it we can look at a glance to where that price goes down. If you’ve never calculated ARP before it might be the easiest calculated metric of all time.

SUM($ Sales) / SUM(Unit Sales) = ARP

 

Is this method for tracking promotions going to be effective in all situations? No, absolutely not, there are certainly promotional events that do not involve a temporary price reduction at all. Fortunately for us, in most cases for brands at this stage, ~90% of promos DO include a TPR, so it will be up to you to consider what is true for your mix of tactics.

Next will then PLOT our data on a dual-axis chart. Set Time Period to Weekly on your X-Axis. And Add $ Sales and ARP to your Y-Axis (dual-axis bar & line graph). After some formatting and the introduction of an average line, your diagram should look something like this.

2. Calculate a baseline

This is the part of the blog where I am going to tell you to pull out your calculator. Yes, we are going to have to do a few more calculations.

In order to calculate a baseline we need to calculate the average $ Sales for the past either 4 or 12 weeks (depending on how much data and when your last other promotional event was). It is very important that we do NOT include a prior promotional week in this calculation.

So in reviewing my sample data I need to add up the $ Sales for the 4 Weeks leading into my event and take an average.

Week 1 – $216

Week 2 – $214

Week 3 – $207

Week 4 – $198

AVG – $208.75

 

3. Calculate an average promotional volume

Now let’s look at the two weeks in question for which our promotion ran. We know its two weeks because we can see the dramatic dip in our ARP. So lets grab our $ Sales for this window as well.

Week 1 – $228

Week 2 – $214

AVG – $222

 

You should expect to see your promotional AVG $ Sales to be larger than your baseline. It is possible to see it be less than your baseline. The most common explanation for that could be an out of stock issue!

4. Calculate Lift

 

Next we’re going to calculate lift. We do this by taking the formula

(Average $ Sales of Promoted Volume / Baseline $ Sales) – 1

Example: (222/208.75)-1 = 6.3% Lift

 

5. Identify Execution Issues

If we look at our analysis we see that we did have healthy execution. It won’t always be this way. If we look at the data we see that the second week of our promotion (green circle) in fact had an even better execution than the first (yellow). Even though we had great execution, it was still a soft-week so now its time to ask some additional questions such as:

  1. Did we expect 100% of stores to be compliant with the promotion?
  2. We can conduct the same analysis now segmented by pack-size and region
  3. If we start looking at a Store-Ranking, are we seeing any stores that are out of compliance? A clear method to answer that would be to look at the ARP any stores that clearly show they did not take price could be highlighted and reviewed with your team.

 

Even if our sales were lighter in week 2 of the promotion, we had a healthy execution for the duration of our promotion.

Promotional Analysis can be easy!

If you’re just getting started in retail and you’re just beginning to look for low hanging fruit, promotional analysis is one of the best places to get started. If right now the thought of conducting this analysis across different markets makes your stomach churn, just consider your scale. We were working with a pretty small baseline ($226/week). If we find a nugget to reduce promotional windows from 4 weeks to 2 weeks with our #1 retailer, those kinds of savings could add up in the thousands that you get to keep back in your pocket.

Happy Analyzing!