Your market conditions are constantly changing so it’s important to understand how these changes impact your marketing effectiveness. What do we mean by “changing market conditions?” A simple example is tire sales. As gas prices (market condition) increase, people drive less, and therefore buy tires less frequently. If this important market condition is not considered, advertising during a period of high gasoline prices would appear less effective than it might actually be.
How do you know which market conditions are impacting your business? The easiest way to explain this is with a case study. At the end of the case study we’ll give you access to an online simulator where you can run your own tests.
Access to the full case study and online simulator is found in our Return on Marketing Investment whitepaper.
Our client, a national brand whose product is typically used during colder weather, had just come off one of their best sales seasons to date. It also happened to coincide with one of the coldest winters in recent history. Our client wanted to better understand the external factors that impact sales, such as weather and macro-economic conditions.
We looked at their data from common sales and media metrics (e.g. $-sales, TV, radio, print, etc.) and also a wide range of external factors (e.g. temperature, sector employment, DJIA, etc.) that were potentially impacting their market.
After consolidating all of this data into a single relational database we ran it through select data mining tools. After fine-tuning the model with the client we identified a handful of variables (both internal and external) that were impacting their marketing effectiveness.
We took this model and turned it into a user-friendly online simulator where our client could play around with the data and do their own “What If” analysis.
To show you what this looks like, let’s run a few test scenarios together.
Background about model simulator
The independent variables included in the model are:
- Average monthly temperature (°F)
- Sector Employment (relative to our client)
- Media type A $
- Media type B $
The dependent variable in the model is $-Sales. The model is broken down monthly – meaning that each month has its own set of baseline market conditions. For example, the average temperature in January is much different than July.
In January, if our client doesn’t spend anything in the two media categories listed, sales ($) will be $2,947,998. This is the baseline scenario with NO AD SPENDING in January.
Let’s see what would happen if market conditions change.
If the average temperature drops from 32.5 (°F) to 30 (°F) and sector employment increases by 3%, then sales ($) would increase by 112.25% to $6,257,042 (simply from demand generated from market conditions).
This is important to understand because if market conditions are changing in your favor, it might make sense to spend less on advertising.
Let’s start with the baseline market conditions in January and assume they don’t change. This time we’ll increase our advertising spending.
- $100,000 on Media Type A.
- $50,000 on Media Type B.
By increasing ad spending in favorable market conditions, the client’s sales ($) increased by 98.88% to $5,862,926. In these first two scenarios it seems like the client can’t do anything wrong. The reality is market conditions are ripe in January for this client, so if market conditions improve they will see a natural increase in sales ($). Additionally, increasing their advertising spending in “ripe” market conditions is where they’re getting the most “bang for their buck.”
Do your own simulations
Want to do your own simulations? Grab a copy of our Return on Marking Investment (ROMI) whitepaper.
Doing a ROMI analysis helps take the guess-work out of your marketing spending. We just looked at a national brand that excels in the winter. You might be thinking, “Of course, spending more on advertising in the colder months makes sense!” What most businesses fail to understand is that maximizing marketing ROI is in the details. For example, if next winter is the coldest winter in history, it might make sense for our client to spend less on advertising. In addition, after better understanding their marketing effectiveness in other market conditions throughout the year, it might also make sense to ONLY spend advertising dollars during a specific time of the year.
A good way of understanding this is through the analogy of fishing.
- Fish when the fish are biting.
- If they’re really biting, save the good bait and use as little as you can.
- If the fish aren’t biting at all, save your bait.