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At the end of 2023, we teamed up with one of our clients to set up a research experiment to further optimise future pricing and branding insights.
The study aimed to refine our brand strength metric, also called a brand's pricing power, to enhance its predictive power for key pricing metrics. It also aimed to provide consumers with the most realistic simulation of a shopping process, possibly improving the way we measure price elasticity.
Methodology
We interviewed a large group of FMCG shoppers via an online survey but divided them into 8 different "experiment cells". We explored three aspects related to measuring price elasticity via a conjoint method.
- The impact of the conjoint shopping shelf: an advanced shopping shelf vs. a 2D, more flat looking shopping shelf
- The impact of promotions on measuring price elasticity: a conjoint where none of the shelves shows promo vs. a conjoint where several shelves have brands on promo
- The impact of the device: filling in on a laptop/tablet versus on a mobile phone
On top of that, we measured brand strength using a variety of metrics.
Key Questions:
- Can we optimise the way we measure brand strength?
The study aimed to determine whether our current definition of brand strength could be improved, i.e., which short list of brand characteristics best measures a brand's pricing power. By knowing how well a brand scores on these aspects, we have a good view of how price elastic the brand is, or in other words, how easy or difficult it will be to raise prices.
- Does an advanced shelf design better reflect how consumers choose real-life products versus a simpler 2D flat design?
A standard 2D graphic conjoint design is often criticised as not sufficiently representative of a shelf simulation. Hence, we compared choice behaviour between two designs to explore the following: if a more realistic 3D shelf design is presented, do shoppers behave differently, i.e. select fewer or more products, spend less or more time on the choice process, choose more realistically...
In addition, we compared the response behaviour related to the device on which the survey was taken (laptop/tablet vs. mobile phone) - see below a fictitious illustration:
- Does showing promos in the conjoint affect the non-promo price elasticity of a product?
The study aimed to understand if the price elasticity of a product is the result of its non-promo price in combination with its promo elasticity or if offering competitive promos had no impact on price elasticities. This question is often raised in promo-driven markets, where there is a need to clearly understand the effects of price changes outside of promo actions (see below a fictitious illustration):
What did we learn?
Based on the research goals and questions, here are the key takeaways:
1. Brand strength/Pricing Power is ideally measured through 4 brand characteristics
While we previously used two brand attributes, which were already predictive of price metrics, we could have enhanced the predictability by extending the definition with 2 more short questions.
We discovered that adding a specific combination of brand associations linked to the exclusivity & premium-ness of a brand had a subtle but significant impact on the definition. The effect this has on its predictiveness for pricing metrics was substantial.
2. No need to build an advanced shopper shelf
While it is essential that a conjoint exercise reflects a realistic shopping experience, creating an even better, possibly even more realistic look doesn't lead to better results, and one should accept this. Despite the more realistic shelf design and purchase simulation, key conjoint metrics did not substantially impact it. Moreover, it would only create additional, often unnecessary, technical complexity. So, "never change a winning horse" really does apply here.
Furthermore, the research also showed that the conjoint behaviour on a laptop/tablet versus a smartphone was very similar, confirming that smartphones can be used to measure price elasticity via a conjoint exercise.
3. Showing promotions when necessary is key to representing a realistic shopping experience, as it does not hamper measuring the non-promo price elasticity.
The findings revealed that showing competitive promos in a conjoint exercise had minimal impact on non-promo price elasticity. This clearly indicates that promos should always be integrated when relevant when conducting a conjoint study.
A promo landscape is a commercial reality and must be included when aiming for a more realistic simulation. Omitting promos only marginally increases non-promo price elasticities, so there is no reason to set these aside in a conjoint.
In conclusion, this research-on-research study provided crisp insights into how to and not to optimise branding and pricing research methodologies.
By refining the brand strength with a well-thought-out extra dimension, conducting conjoint testing in its purest and most effective way and understanding the relative role of promos in price elasticities, our client can now make even more informed decisions when conducting future pricing studies.
Ready to optimise your pricing and branding strategies? Contact us today to learn how our data-driven pricing and branding consultancy can help you make informed business decisions.
