1. Student: Christian van ’t Hof 11th of January 2016
Marketing Experiment Assignment
1 Introduction
This report is about a marketing experiment for Viking Beds of Sweden. This Swedish
boxspring brand has just been introduced on the Dutch market in the upper-middle and
higher segment. The marketing will be a TV advertising campaign for their boxspring
type ‘Royal Viking’. Since boxsprings are gaining more market share, these high quality
beds are being the ‘real deal’. The experiment that is going to run will be a before-after
design experiment. Since there hasn’t been any brand exposure yet, a basic experiment
won’t be working because the city with the TV ads will always be selling more.
Moreover, a full factorial experiment won’t be working either, because it’s about 1
product with the same pricing for both cities. In this case, the before-after design
experiment will be working by showing two different ads.
2 Experiment Design
The variables in this experiment will be independent as well as dependent. The
dependable variable will be the amount of units sold and the independent variable will
be the TV advertisements.
This experiment will run in the cities Laren and Naarden in the Netherlands. These cities
are both in the same geographical area, share almost the same amount of population and
have both on average about €50,000 income per household1, which is almost the highest
in the Netherlands.
Both Laren and Naarden have above 10,000 inhabitants, which is enough for statistical
significance. The entire cities will see that TV ads, so this makes this a valid experiment.
The first round of TV ads will run from March till April and the second round of TV ads
will run from May till June. In the first round, both cities will see TV Ad 1. In the second
round Laren will see TV Ad 1 and Naarden will see TV Ad 2. The lift in sales will be
calculated from the differences between the two periods.
In terms of causality three rules will at least be applicable, the other one is in this case
not applicable. The two applicable rules are the first, second and the third one: Change
in the marketing mix produces change in sales, no sales increase when there’s no change
in the marketing mix (Round 2, Laren) and the time sequence. In this high-end market,
competitors will probably respond, so that will be the external factors.
1 Centraal Bureau voor Statistiek. (2015, December 8). StatLine - Centraal Bureau voor Statistiek. Retrieved

2. Student: Christian van ’t Hof 11th of January 2016
3 Anticipated Issues
3.1 - 2 Issues to be considered
In this experiment there could be issues. In the Netherlands people get around May and
June, their holiday fee from their jobs, this could increase their budget in those months,
which could be an external factor that could affect the net lift.
Another issue could be our competitor Carpe Diem. Carpe Diem is also from Sweden and
has already entered the market. If they launch a new campaign, than this would
definitely affect the net lift as well.
3.2 - 2 Things the experiment demonstrates
This experiment could point out a difference in outcome of both TV Ads. It could indicate
which TV Ad would work better.
On the other hand, a result of this experiment could also indicate which city would be
buying more products from our company compared to the other. If the outcome of both
cities shows very different numbers, the most interesting city could be appointed.
4 Experiment Adaption
In this 2nd version Viking is going to show their TV Ads on the Internet. This campaign
will span in the same months in the second year. In this case, a full factorial experiment
will assist in providing more specific metrics, which can be controlled more precise. In
this case the video ads will be an independent variable as well as gender. According to
metrics Sweden, males tend to buy these boxsprings over females. The dependent
variable will still be the amount of units sold.
This more specific experiment will show more relevant information on the gender of our
customers, which we can use to improve the targeting of customers by more specified
videos that will be more focussed on the differences in gender. The results from this
experiment will be easier to measure and to analyse, which saves the company money
and gives the company better results.
On the other hand, just like TV ads, it only measures the people that use the Internet on
their computer or watch TV.