||Do Factors for Success apply globally? What about differences by category and geography…shouldn’t the breaks be different?
Alternate Client Question: What are the Factors thresholds for my category/country?
|How many countries and categories were the Factors for Success analysis cases based on? What is the breakdown by continent?
Note to analyst: Don’t get hung up on details. These lose sight of the big picture, we have the ability to provide accurate advice regardless of the situation (country, category, etc).
|New Factors for Success: In overstatement countries how can we feel certain of results when the response scale is condensed at the top end of the scale?
Note to the Analyst: The answer is essentially how we accurately forecast in overstatement markets.
|How predictive is the Factors model for snacks? Of course no one "needs" potato chips, why do you ask that for indulgent categories?
Success breaks (Outstanding/ Ready/ Risky/ Failure) are the same for every concept we test regardless of category, country, and other classifications. Example: if a concept in the US needs to meet the 45 %ile to be ready on Need/Desire, so does a concept in GB.
Universal success breaks are possible because the foundation of success models are database ranks, ranking on a relative basis, equivalizes category or country differences and provides a universal prediction of success. What it takes to be successful (in terms of absolute scores) may differ between countries/categories however, what’s important is performance vs competition ( database ranks)
More: Although, our R&D indicated the most predictive success models use database rank.
- Actual scores: absolute performance
- Scores indexed to category medians
- Database ranks: rank vs. competitors in BASES Key Measures Database (relative performance)
- A rank + score hybrid
Submodel details: Sub-models were compared for each success model we built: continent, category, developing vs. developed, etc. Sub-models didn’t show any significant differences from the main model. Market factors were also included in the regression inputs, but did not emerge significant in any model.
In addition to the 600 launch cases, BASES conducted additional R&D on our full testing experience of 20,000 concepts with introSCAPE data. We feel good about the dataset. The profile is consistent with BASES overall global testing mix, which allows us to accurately advice regardless of the situation (country, category, etc). The dataset is well represented across:
- Geography. All geographies represented, more than 30 countries spanning all continents
- Categories. Proportion of cases in each category consistent with BASES overall global testing mix
- Clients. Over 60 clients included
- Study types. Line extension versus New Brand mix is consistent with our testing history
Our country/methodology-specific survey data conversions remain one of our key assets. We have the ability to account for overstatement, both large and small. Database ranks are predictive in all markets including high overstatement markets. We generate an accurate db rank resulting in a reliable success prediction.
- We’ve been able to mitigate overstatement with to identify measures that render a greater data differentiation; this was imperative in determining which (of the 78 potential) measures are used in the Factors for Success model.
- Factors R&D investigated regional & category specific success models (as well as many other types of models) and none of them varied from the larger model in any significant way. This is the basis for the conclusion that the Factors apply to all geographies and categories.
More: For Factors for Success: Most of the measures are not as susceptible to overstatement, as measures like Purchase Intent, because they are behavioral in nature.
|The Factors model "hit rate" is ~75% for all categories/countries. There is no meaningful difference in the overall predictability of the Factors model by country, region or category.
We ask the Factors questions in the same order and same way on every study for two reasons. First, in order to database the results, the question must be asked in the same way every time. Secondly, the databased results are an input into our Factors model. We evaluated hundreds of questions in the Factors R&D and this series of questions (need/want) question asked exactly this way added to the predictability of the model. Remember, we use the maximum of the need & want questions in the Need/Desire calculation. This question was purposefully designed to account for category specific variations. So, for indulgent categories, the maximum responses may mostly fall to the "want" question and the model/predictability will not be impacted.