Data types and Visualization
This document aims to provide clarity on technical elements of the Centricity platform. Below you will find detailed descriptions of both the data types and data visualization tools available to our users.
Data type | Description |
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Department | The broadest classification of products in our hierarchy. In many cases, these instances are similar to store departments from brick and mortar layouts (Dairy, Frozen, Floral, etc.) |
Category | Categories are a classification under Departments. The Category level starts to break up the Department, but does not name narrow product types. For this reason, Categories are more valuable for navigation purposes, rather than product selection. Examples of Categories within the Dairy department include Cheese and Yogurt. |
Subcategory | Subcategories are a classification under Categories. The Subcategory level gets closer to actual product names (Greek Yogurt, Fruit on the Bottom Yogurt, etc.) Users will generally see more shared characteristics across Subcategories than across Categories or Departments. |
Subset | Subsets are a classification under Subcategories, representing the narrowest classification of products in our hierarchy. These nodes have defined products that can be selected, such as Greek Yogurt - Cup. However, users may need to apply Facets to identify a more specific product (i.e. “is Organic” for Greek Yogurt - Cup). |
Facet | We assign Facets to any of the four levels of the hierarchy or to individual products. This classification by attribute allows us to offer our customers the highest level of granularity in our data insights. We offer two types of facets: Binary and Ordinal.
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Intent | Intent tracks online consumer activity through human and AI classification, measuring interest in particular categories, subcategories, and individual products. Intent assigns a rank to every product we see on the Internet, based on the likelihood a viewer of a given page is to purchase a specific product. This metric captures a pre-purchase picture of sales trends, offering insight before sales data is available. Total Intent is calculated as follows:
An easy way to think about this is by taking a hypothetical example of a recipe on abc.com. There are 3 mentions of Organic Skinless Chicken Breast that each receive +4 Intent. We group the 3 Instances into 1 Entity. Say this recipe on abc.com has been viewed 100k times in the last month. This means that abc.com would contribute +400k Intent for Organic Skinless Chicken Breast last month. |
Positive Intent | Content that indicates a likelihood of consumer purchase. Positive Intent results from web pages that demonstrate a favorability toward the indicated product. [See “Intent” for a detailed description of how a product’s Intent score is calculated on a given URL.] |
Positive Events | An Intent Event refers to a product being viewed on a URL—a Positive Event occurs when a product is represented favorably, indicating a likelihood of purchase. |
Negative Intent | Content that indicates an unlikelihood of consumer purchase. Negative Intent results from web pages that demonstrate a negativity toward the indicated product. [See “Intent” for a detailed description of how a product’s Intent score is calculated on a given URL.] |
Negative Events | An Intent Event refers to when a product is viewed on a URL—a Negative Event occurs when a product is represented unfavorably, indicating an unlikelihood of purchase. |
Total Events | The sum of all Intent Events within product criteria selected by user. This feature helps clarify the volume of Events that contribute to an Average Intent score. |
Average Intent | Average Intent refers to the average Entity scores for a given product, across all web traffic we process. For example, if we see 1,000 URLs that mention Butter, this metric reflects the sum of all those Entity scores divided by 1,000. Average Intent = (Sum of all Entity scores) / (Total Entities) [See “Intent” for a detailed description of how a product’s Intent score is calculated on a given URL.] |
-5 | Total count of URL views with this Intent score for the selected product. This score is assigned when an Instance exhibits: |
-4 | Total count of URL views with this Intent score for the selected product. This score is assigned when an Instance exhibits: |
-3 | Total count of URL views with this Intent score for the selected product. This score is assigned when an Instance exhibits: |
-2 | Total count of URL views with this Intent score for the selected product. This score is assigned when an Instance exhibits: |
-1 | Total count of URL views with this Intent score for the selected product. This score is assigned when an Instance exhibits: |
0 | Total count of URL views with this Intent score for the selected product. This score is assigned when an Instance exhibits: |
+1 | Total count of URL views with this Intent score for the selected product. This score is assigned when an Instance exhibits:
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+2 | Total count of URL views with this Intent score for the selected product. This score is assigned when an Instance exhibits: |
+3 | Total count of URL views with this Intent score for the selected product. This score is assigned when an Instance exhibits: |
+4 | Total count of URL views with this Intent score for the selected product. This score is assigned when an Instance exhibits: |
+5 | Total count of URL views with this Intent score for the selected product. This score is assigned when an Instance exhibits: |
State | Data aggregated on the State level. |
County | Data aggregated on the County level. |
Date | Expressed as YYYY-MM-DD. |
UPC | 12-digit UPC code. |
Intent Delta | Intent Delta measures the change in aggregate Intent from the previous time period to the selected time period. It can be expressed as a positive number, a negative number, or zero, depending on the scale and direction of a line item’s change:
For example, when viewing a report for the Butter Subcategory over the last month (e.g. June), its Intent Delta would be calculated by taking its Intent score over the selected month (June) and subtracting from it the Intent score from the month prior (May). If Butter’s Intent score increased from 380 in May to 400 in June, then it would have an Intent Delta of +20 for this report. Intent (selected time period) - Intent (previous time period) = Intent Delta |
Sales ($) | Your organization’s actual Sales figures, in USD, integrated into our platform. |
Unit Sales | Your organization’s actual Sales figures, expressed in units sold, rather than USD. |
Sales Delta ($) | Sales Delta ($) measures the change in total sales from the previous time period to the selected time period. Sales Delta ($) is expressed as a percentage, indicating the percentage change in Sales, rather than the change in raw Sales numbers. For example, a line item whose Sales increased from $90 in the previous period (e.g. May) to $100 in the current period (e.g. June), would have a Sales Delta of 11.11%. This number indicates an 11.11% increase in Sales from the previous period. This is calculated as the difference in Sales over the periods ($100 - $90 = $10), divided by the Sales for the previous period ($90). 10 / 90 = .1111 or 11.11% When Sales decrease, Sales Delta ($) is expressed as a negative. For example, if June’s Sales totaled only $90, compared with May’s $100 Sales figure, the Sales Delta ($) would be calculated as follows: 90 - 100 = -10 -10 / 100 = -0.1 or -10% This number indicates a 10% decrease in Sales over the selected date range. |
Sales Delta (Units) | Sales Delta (Units) measures the change in total sales from the previous time period to the selected time period, expressed as Units sold, rather than USD. It also differs from Sales Delta ($) in that it is expressed as the change in raw number of Units sold, rather than as a percentage change. For example, if an item’s Sales increased from 1,500 Units to 2,000 Units from one month to the next, its Sales Delta (Units) would be calculated as: Units sold (this time period) - Units sold (previous time period) = Sales Delta (Units) 2,000 Units - 1,500 Units = +500 |
Correlation ($) | Correlation measures the relationship between Sales and Intent for a particular line item.
OR Sales and Intent both decrease:
Correlation will always be contained in the range of -1 to 1, with 1 indicating direct (positive) Correlation and -1 indicating inverse (negative) Correlation. Line items with negative Correlation should be investigated. |
Correlation Delta ($) | Correlation Delta measures the change in aggregate Correlation from the previous time period to the selected time period. It can be expressed as a positive number, a negative number, or zero, depending on the scale and direction of a line item’s change:
For example, a line item with a Correlation of +0.87 in the selected period (e.g. June), increasing from +0.83 in the previous period (e.g. May), would have a Correlation Delta score of +0.04. Correlation (selected time period) - Correlation (previous time period) = Correlation Delta |
Correlation (Units) | Measures the relationship between Unit Sales and Intent. Positive correlation indicates that Unit Sales and Intent are moving in the same direction, either both increasing or both decreasing. Negative correlation indicates that Unit Sales and Intent are moving in opposite directions—either Unit Sales increases while Intent decreases, or vice versa. Correlation will always be contained in the range of -1 to 1, with 1 indicating direct (positive) Correlation and -1 indicating inverse (negative) Correlation. Line items with negative Correlation should be investigated. |
Correlation Delta (Units) | Measures the change in Correlation (Units) from the previous time period to the selected time period. It can be expressed as a positive number, a negative number, or zero, depending on the scale and direction of an item’s change:
Correlation (Units) (selected time period) - Correlation (Units) (previous time period) = Correlation Delta (Units) |
Visualization | Description |
Bar | Use when comparing many aggregates/sums during a set time period. |
Line | Use when comparing how several variables (<10) change over time. |
Pie | Use when comparing several categories against each other. |
Table | Use when a close analysis of several variables is needed. |
Heatmap | Use when analyzing data geographically. |
Number | Data expressed as numeral, rather than visualization. |
Text/Markdown | Text/Markdown to help your data tell its story. |
Image | Upload an image. |
More questions about Centricity? Check out our website or talk to our Support Team.