Breakdown: 4 Types of Analytics for Retailers
Retail analytics involves making sense of data to augment decision making processes that impact profitability.
The goal of retail analytics can be to increase sales revenues or cut cost (or both).
Many of you may have heard about the four types of analytics but might not understand how it applies to your store.
Here is a breakdown…
1. Descriptive – What just happened?
What happened to the business last quarter or last week? How did yesterday compare to the same time last year?
This level of analytics focuses on a reporting function as to the health of the business. How sales and marketing funnels were performing and what went better or worse than expected.
This level of analytics shows you the pulse of the business, how “healthy” the entire machine is and if you don’t get this right, nothing else matters.
2. Diagnostic – Why did it turn out that way?
Oh! Sales skyrocketed. Cool, but why?
Some detective work has to be done at this level to identify the triggers that caused something in the past to happen. This can be a promotion that you ran or a seasonal holiday- regardless of what it was, you have to identify it.
If you don’t know what it is, you will not be able to repeat the success and worse still, you might repeat a mistake.
Take an example of discounting a particular item for a period of 3 months, sales skyrocketed- great! So you want to try the same trick for the next 3 months- this time it doesn’t work- why? Maybe you were initially discounting a winter jacket and now its summer time- nobody wants that product anymore.
Yes, you have to get this right down to the product level.
3. Predictive – What is going to happen?
Right…forecasting again, time to talk about inventory.
Well yes and no.
There are more implications to getting your predictive analytics right than just inventory levels. If you are just starting up, getting this wrong can severely affect your cash flow. Getting this right, on the other hand, can really free up your cash to be deployed else- e.g. marketing.
Manpower could also be an issue, if you know that a huge sale is coming up, might be time to get some extra help.
4. Prescriptive – How can we make it happen?
Now, this becomes interesting but REALLY difficult to get right.
Given our current knowledge of why something occurred in the past, how can we replicate a success or avoid failure?
With so many levers to pull in the business, we try to randomly pull on ones that seemed to work in the past to “double down” on success. The biggest mistake here is overspending on marketing without fully understanding the reason for a past campaign. Doubling ad spend doesn’t always bring the lift that you want and it can really hurt the wallet.
The simplest way to do this without breaking bank? Patiently.
Make a list of 3 possible reasons and test these hypotheses in short spurts to see if the experiment yielded the expected results.
- When we run flash discounts on category Y, we see a 10% lift in monthly sales.
- During the holidays, we see shoppers switching from buying products A, B, C to products Q, W, E, R for a period of 8 weeks prior to the holiday
- Nobody is willing to buy product E if it is above $45 dollars
If you have any feedback or questions about this post, we would love to hear from you.