About the Segmentation
STI: Spending Patterns - Consumer Expenditure Estimates
STI: SpendingPatterns is a proprietary product developed by Synergos Technologies, Inc. (STI) to measure and analyze consumer spending behaviors across the United States. Built on the foundation of the U.S. Bureau of Labor Statistics (BLS) Consumer Expenditure Survey (CEX), the dataset provides detailed estimates of both per capita and per buyer expenditures, along with historical trends that reveal how consumer demand shifts over time. By extending and modeling this survey data to granular geographies, SpendingPatterns equips researchers, retailers, and real estate professionals with a consistent framework for understanding local market conditions, evaluating consumer demand, and tracking long-term shifts in spending behavior.
Call for Segmentation
To make the insights from SpendingPatterns more actionable, it is often necessary to classify product categories into meaningful groupings. While raw spending and buyer data provide valuable measures, customers want clearer ways to interpret how categories are changing over time and what those changes imply. By segmenting categories based on consistent patterns of spending, popularity, and price movement, we can create a framework that helps users see beyond individual numbers and understand broader trends. This classification supports more effective comparisons, highlights which categories are becoming more niche or more universal, and ultimately provides a clearer lens for decision-making.
Classification of Spending
Within the STI: SpendingPatterns product, and consumer expenditure analysis more broadly, spending can be viewed in two distinct ways: per capita and per buyer. Per capita represents the average spending distributed across the whole population, while per buyer reflects the average spending among only those who purchased within a given product category. For the purposes of our classification, we focus on per buyer averages and establish two thresholds to define three categories of change. These thresholds are determined using both a fixed annual benchmark and a normalization procedure that accounts for the average change in spending across the full time frame. This dual approach ensures comparability across different periods. For this segmentation, classifications are generated for both one-year and five-year intervals. Our resulting classification levels are called Shrinking, Steady, and Expanding.
Classifcation of Popularity
By measuring spending at the per buyer level, the number of buyers can be treated as a distinct concept. This measure ranges from no buyers to all buyers, and is naturally expressed as a percentage. Conceptually, the proportion of people purchasing a product aligns with the idea of its popularity. To classify changes in popularity, we again apply two thresholds to create three categories. Unlike spending, popularity does not require normalization, as it is assumed to remain proportionally consistent over time. The resulting categories of change are defined as Fading, Holding, and Trending.
Classification of Price
The final measure of change is price, which is critical because it helps answer the “why” behind spending shifts. When spending increases, is it due to consumers purchasing more, or simply because prices have risen? Incorporating this dimension provides a more complete understanding of category-level dynamics. Price data is not inherent to the STI: SpendingPatterns dataset; instead, it is sourced from the U.S. Bureau of Labor Statistics (BLS) Consumer Price Index (CPI). Because CPI categories do not align one-to-one with the Consumer Expenditure Survey (CEX) categories that underlie SpendingPatterns, we establish a cross-reference and use the closest available match. As with spending, thresholds for price change are defined using both a fixed annual benchmark and a normalization procedure that accounts for the average rate of change across the full time frame. This classification produces three categories of price movement: Falling, Stable, and Rising.
Resulting 27 Segments
The combination of the three three-level classifications results in 27 possible segments that describe the type of change a product category is experiencing within a given time frame. It is important to note that the time frame itself plays a central role in shaping the narrative. The system is designed to be time-frame neutral, meaning that the same product category may fall into very different classifications when evaluated over a one-year period versus a five-year period.
Color Scheme
In order to create a more clear visual representation, a color system was developed. This is designed to make the three signals readable at a glance while keeping every category distinct. Overall performance is carried by the base hue—shifting from red (weaker) through a neutral middle to green (stronger). Within that hue, Spend is shown by brightness (lighter tones for shrinking spend, mid tones for steady, darker tones for expanding), Popularity is shown by vividness (muted for fading interest, more saturated for trending), and Price adds a subtle temperature shift (cooler when prices are falling, neutral when stable, warmer when rising). Read hue for the overall picture, brightness for spend, saturation for popularity, and temperature for price.