Glossary

Accelerator: A customer whose rate of purchasing is increasing
Active customer: A customer whose most recent purchase falls within a specified period, typically the last 12 or 24 months; that is, a customer whose recency is less than the inactivity period
At risk: Customers whose buying behavior is deteriorating; they may be purchasing from a competitor
Attrition: Gradual, negative erosion of a customer's score; such a customer is sometimes called an ‘attritor’ or ‘defector’ (if they are no longer active)
Back test: A way to validate predictive analytics results by predicting purchasing behavior for a period in the recent past for which actual transactions are known and then comparing the predictions with the known behavior
Cross-sell: Offering customers products or services they have not previously purchased
Control group: In a marketing campaign, a set of customers who do not receive the campaign offer; used to determine the efficacy of the offer
Deceleration: The rate at which a customer's velocity is slowing down
Deceleration percentile: Where a customer's deceleration ranks among all customers; a deceleration percentile of 97% means that only 3% of all customers are decreasing their purchasing at a higher rate
Decelerator: A customer whose rate of purchase is slowing down
Defector: A customer who is no longer active, whose recency is longer than the inactivity period; see also attrition
Download: Transferring data from a remote computer to your computer; see also upload
ERP: Enterprise Resource Planning, a set of programs to manage all aspects of a business including Accounts Payable, Accounts Receivable, General Ledger, Manufacturing, Inventory, etc.
Factor: A variable of interest in an experiment; for example price, discount level, expiration date, etc.
Factorial design: A type of experiment design with two or more factors, each with discrete values or “levels”, where all possible combinations of levels across all factors are tested simultaneously
Finite State Machine: A mathematical model of an entity that describes its behavior as a result of its past history and current inputs. If an example entity is a customer, inputs might be direct mail promotions and responses could be a purchase or changed loyalty score.
Fractional factorial design: A variation of a factorial design experiment in which only a subset of all possible combinations of factor levels is tested; less runs are needed to conduct the test, but at the cost of a loss of information
Frequency: The number of purchases made in a defined time period, ignoring differing interorder wait times; for example, five times per year
FTP: File Transfer Protocol, a standard way of exchanging files over a network that supports the TCP/IP protocol, such as the Internet
Inactivity period: A company-determined time interval without a purchase beyond which the customer is no longer considered to be active; typically set to one or two years
Interorder wait time: Time between a customer's consecutive purchases; also called Time Between Sales
Lifetime value: The future revenue expected from a customer; usually the revenue expected in the next one or two years, since that is what can be predicted with reasonable accuracy
Likely buyers: Those customers who are expected to buy something in the next period (month or quarter)
Likely Buyer Score: The percent probability, from 0 to 100, that a customer will buy something in the next period (month or quarter)
List select: The process of selecting a subset of the entire customer population for a marketing campaign
Loyalty: In the context of ‘customer loyalty’, a measure of the likelihood of a purchase in the near future
Loyalty decile: One-tenth of the customer population; after customers are segmented by their loyalty score, those in the highest 10% (i.e. the best customers) are said to be in the tenth decile, those in the lowest 10% are in the first decile
LRank: The relative percentile rank of a customer compared to the rest of the customer population based on the customer's loyalty score, scaled from 0 to 100
LScore: The absolute loyalty score assigned to a customer based on the Loyalty Builders analytical model, scaled from 0 to 1000
Mean: The average value of a group of numbers, most meaningful (and near the median number) when the numbers have a bell-shaped distribution but often skewed (and made less meaningful) by a few extremely large values near the end of a distribution of values
Median: The middle value in a set of numbers; if 13 numbers are arranged in order of size, the 7th number is the median
Merge/Purge: The process of cleaning a customer data file by combining records that represent the same customer (merge) and deleting records that are duplicates, inaccurate or no longer needed (purge)
Monetary value: The revenue received from a customer so far, usually in the most recent period; also the ‘M’ in RFM, an older segmentation scheme
Nonlinear: A relationship between numerical quantities is called nonlinear if there is not a constant proportion relating changes in one quantity to changes in the other. Exponential growth, as occurs when compounding interest over time, is an example of a nonlinear relationship.
OFAT: (An acronym for One Factor at A Time, also known as a Split Run); a type of experimental design in which only one factor is changed at a time while the other factors are held constant
Pay-as-you-go pricing: Pricing is based on size of downloaded file and payment is due upon download, rather than a fixed fee paid at regular intervals
Predictive analytics: The science of predicting what customers will do based on analysis of their past behavior
Probability horizon: The time between the date of a purchase probability analysis and some point in the future within which a purchase might be made; typically one or two fiscal quarters
Purchase delay: How many times a customer was expected to purchase between the date of their last purchase and the latest analysis date, used to detect changes in customer purchase frequency
Probability threshold: The percentage purchase probability below which values are ignored (and customers discarded) when building a list of targeted customers likely to purchase a specific product within the probability horizon; identical to probability cut-off
Purchase probability: The percentage likelihood of a customer making a purchase within the defined horizon; sometimes called purchase propensity
Quintiles: The 20, 40, 60, and 80th percentiles are called quintiles
Recency: Length of time since a customer's last purchase
Recipe: A distinct combination of factor levels used in an experiment; for example, if there are 3 variables, each at 2 levels, there are 2x2x2 = 8 distinct recipes
Response rate: Percent of total recipients in a campaign who purchase or otherwise answer the promotion
Retention: Length of time between a customer's first purchase and today
Revenue rank: How the total amount of money a customer has spent compares with that of other customers; a revenue rank of 71% means that 29% of the customers have spent more money during their history with the company
RFM: An older, linear modeling technique that looks only at Recency, Frequency and Monetary value when scoring and segmenting customers; see RFM vs. Loyalty Builders Modeling for more details
Risk probability: The probability, between zero and 100%, that a customer will not make a purchase in the time between the most recent analysis date and the date when their recency equals the length of the inactivity period (in other words, when they become inactive)
Satisfaction: A measure of a customer's past experiences, most likely related to their most recent transaction
Segmentation: The process of dividing a customer population into groups based on their loyalty score
SKU: Shop Keeping Unit, the alpha-numeric code used to designate a specific product
Split run: see OFAT
Standard deviation: A statistical measure of the spread of a set of numbers about their mean value
Suppression: The process of removing certain names from a list of customers to be targeted in an upcoming marketing campaign because of pre-established rules, for example they were recently contacted or do not qualify for the offer
Upload: Transferring data to a remote computer from your computer; see also download
Up-sell: Offering customers more of the products or services they have previously purchased
Velocity: The rate at which a customer is making purchases

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