Consumer Insights

Overview

10 years’ (40 quarters) of online survey data in the United States. Unaided product and outlet capture allows read of much smaller brands and retailers. Data in this file is for years 2012-2022. Primary, quantitative survey data allows collection of comprehensive KPIs not available through POS data, receipt data, or other sources.

OpenBrand's market insights and consumer survey data for durable goods provides researchers with the information needed to uncover trends, reveal patterns, and even predict consumer behavior and industry trends. These data include 10 years of historical data from market share to purchase drivers to consideration sets, demographics, online v. in-store channel and more.

Data Information	Value
Refresh Cadence	`Quarterly`
Historical Coverage	`2012`-`2022`
Topic	`Durables`

Schema

Create a Dewey Data login and navigate to the Table Structure view in the product for a description of each variable. The table structure is the same across OpenBrand datasets. Consumer Insights - Major Appliances

Key Concepts

Primary Key

The primary key of a data file is: Period, RespondentID, and ProductID.

Multi-Punch Variables

Several variables are “multi-punch” variables. In a multi-punch variable, the respondent can provide more than one answer to the question. To accommodate this, another column is added with three underscores and an index number. For instance, a respondent provides two answers to the Why_Bought_Brand question, in the table there are Why_Bought_Brand and Why_Bought_Brand___1.
- If a column has three underscores, then it is a multi-punch variable. No other variables contain three underscores.

Multi-Punch Variable	Single Punch Version
`Why_Bought_Brand` `Why_Bought_Brand\_\_\_1`	`Why_Brand_Appearance` `Why_Brand_Features` `Why_Brand_Good_Name` `Why_Brand_Guarantee` `Why_Brand_Other` `Why_Brand_Prev_Owned` `Why_Brand_Price` `Why_Brand_Quality` `Why_Brand_Recommended` `Why_Brand_Right_Size`
`Why_Bought_Store` `Why_Bought_Store\_\_\_1`	`Why_Store_Advertising` `Why_Store_Credit` `Why_Store_Display` `Why_Store_Experience` `Why_Store_Location` `Why_Store_Other` `Why_Store_Price` `Why_Store_Recommended` `Why_Store_Repairs` `Why_Store_Salespeople` `Why_Store_Saw_in_Store` `Why_Store_Selection` `Why_Store_Stands_Behind_Prod`
`BrandConsidered\_Multi` `BrandConsidered\_Multi\_\_\_1` `BrandConsidered\_Multi\_\_\_2` `BrandConsidered\_Multi\_\_\_3`	Shopped_Brand_X, where “X” is some brand name. This will have a value of `1` if the respondent bought Brand X or shopped for Brand X.
`Outlet\_Shopped\_Multi` `Outlet_Shopped_Multi\_\_\_1` `Outlet_Shopped_Multi\_\_\_2` `Outlet_Shopped_Multi\_\_\_3`	Shopped_A, where “A” is some outlet/retailer name. This will have a value of `1` if the respondent bought from Store A or shopped at Store A.