Glossary (Customer Insights)
This glossary summarizes various terms used in Customer Insights Accelerator.
Term | Description |
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Customer Health Score | Calculated based on the fields Revenue Trend Last 12 months and Margin Trend Last 12 months. The Revenue Health Score and Margin Health Score are set according to the Revenue and Margin monthly or quarterly change (trend) in the last 12 months ( the maximum value is 100, the minimum value is 0) and to this classification: Example: Revenue Trend Last 12M = -19.23% => Revenue score = 25 Health Score = Revenue Score * Revenue Weight + Margin Score * Margin Weight The weight value can be set (in the configuration in Price Parameters) between 0 and 1 for each (the default value is 0.5 for each); the summary of these two has to be equal to 1 (e.g. Revenue Weight = 0,5, Margin Weight = 0,5 => 0,5 + 0,5 = 1). |
Customer Classification by Revenue | This category should be calculated based on last 12 months. Calculation:
A ≤ 20% Example: |
Product Classification by Volume | This category should be calculated based on last 12 months. Calculation:
Very High Volume ≤ 10% The thresholds are configurable. |
Product Type | Classification whether the product belongs to Commodity or Specialty, is based on Margin % = Margin Value / Invoice Price value (Margin field depends on your mapping field.) Commodity ≤ 40% The thresholds are configurable in the PP table. Make sure the value = ∑ Value of a product per all customers in the last 12 months (not per one customer). => We will have only one record to for Commodity, Specialty products based on the data for the last 12M. When select YTD, MTD etc., the chart will sort out products that have transactions in that period; if a product does not exist in that period of a customer, it will not count. E.g.: We have 30 products Commodity, 70 products Specialty in the last 12M. For customer X in YTD, only 50 products have transactions, 20 of them is Commodity, the rest is Specialty, so the chart will show this accordingly. |
Pricing Opportunity | Meaning selling at a higher price identified from customers within the same segment Average Invoice Price = Average Unit Invoice Price for the particular Product ID and particular Customer Segment Below Average Price = the particular Unit Invoice Price - Average Unit Invoice Price Pricing Opportunity = Revenue Below Target = if Below Average Price < 0 then Below Average Price * Quantity * (-1) else 0 |
Cross Sell Opportunity | Meaning selling products that are not sold yet to that customer but to customers within the same segment Formula = Average (Invoice) Price per Customer Segment and per period and for Products not bought by Customer Example: Segment buys Product A, Product C and Product E, Customer A bought only Product A and Product E = > cross-sell would be an average Invoice Price of Product C per Customer Segment. Customer Segment is defined in the configuration (Price Parameters) – a list of fields the segment consists of. |
Revenue Increase | Meaning selling more of a product based on customers within the same segment If Quantity per Product and Customer < average Quantity per Product and per Customer Segment, then: Formula = (average Quantity per Product and per Customer Segment - Quantity per Product and Customer) * average Price per Product and Customer If Quantity per Product and Customer > average Quantity per Product and per Customer Segment, then: Formula: Revenue Increase = 0 Example: Customer Segment buys Product A in Average 500 quantity and Customer bought 350 quantity, then Revenue Increase = (500 – 350) * average Price per Customer. If Customer bought more than 500 quantity, then Revenue Increase = 0. Customer Segment is defined in the configuration (Price Parameters) – a list of fields the segment consists of. |
Selling Opportunity | = Cross Sell Opportunity + Revenue Increase |
% Products buying | Formula = Number of Products buying in this period of a customer / Total of Products traded in this period * 100 Example: With YTD, total 200 products are traded. Among of them, customer A buys 50 products. % Products buying of customer A in YTD = 50/200 * 100 = 25 % |
Revenue, Margin and Volume Trend Last 12 Months
| First, the respective metric (revenue, margin or volume) is calculated for every single time unit. The least-square approach is used to compute the trend. See the Fitting a trend: Least-squares section in the Linear trend estimation Wikipedia article. Formula:
To convert the trend value â back to a percentage, the following formula is used: â / average(metric) Periods with no transactions are considered to have zero revenue, margin, and volume, and are included in the trend computation. Find the example in the the following attachment: This calculation is used in the following portlets: Portlets affected by this trend calculation change:
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Revenue, Margin and Volume Trend YTD | Formula: The least-square approach is used (see the Last 12 Months computation above). This calculation is used in the following portlets: Portlets affected by this trend calculation change:
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Number of Transactions | Total Transactions in a given period / Total days in a given period |
% of Revenue below Target | Formula = Revenue Below Target / ∑ Revenue of Product ID of the customer (calculated for Products with Revenue Below Target above zero) |
Customer Segment | To group customers by common characteristics, the Customer Segment is defined in configuration (Company Parameters) – a list of fields the segment consists of, e.g. customer size, region, country etc. According to values aggregated on the Customer Segment level, certain KPIs for particular customers are calculated, e.g. cross sell. |
Average Invoice Price per Customer Revenue Class Last 12M |
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Core Customers | Core: Customers having cumulative revenue contribution in the last 12M <= 80% (or by a PP) . |
Core Products | Core: Products having cumulative revenue contribution in the last 12M <= 80% (or by a PP).
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Projected Nr. of Transactions, Margin and Revenue (for the next 3 months) | Projected measure for the next 3 months (calculated as adjusted linear trend based on the first 3 months of the period). Calculation:
measure = Number of Transactions, Margin or Revenue Example of Revenue projection calculation:
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Always make sure your data is complete. If, for example, the revenue data are missing, the following happens:
revenue value = 0
=>
Margin % = Margin/Revenue
=>
Margin % = null
Null values may then appear in the dashboards because the application cannot resolve missing data on its own.