Glossary

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1

1-to-1 personalization

1-to-1 personalization

The practice of delivering a unique, optimal digital experience for each customer using all available data from first- and third-party sources. To take action in real time to deliver a customized experience to every visitor across channels, 1-to-1 personalization requires rapid data aggregation and analysis, cross-channel deployment, and machine learning optimization. The term 1-to-1 personalization is derived from the more general term personalization and is interchangeable with individualization.

A

AOV

AOV

See average order value.

audience

audience

A segment of a client's site traffic as defined by selected characteristics and used for testing and segmentation.

Audience Discovery

Audience Discovery

Monetate's algorithm for automatically classifying a client's customers into audiences.

automated personalization

automated personalization

A technique used in personalization strategy to automatically optimize the customer experience for each person. It uses rapid data aggregation and analysis, cross-channel deployment, and machine learning to predict customer behavior and adjust to changes faster than marketers can.

Automated Personalization experience

Automated Personalization experience

A type of Web experience that a client can configure and deploy in Monetate; formerly called Individual Fit experience.

average order value

average order value

A calculation of how much customers generally spend on each transaction. Use the following formula to calculate average order value: Sum of revenue generated ÷ Number of orders received.

B

behavioral targeting

behavioral targeting

The ability to focus a marketing message on an individual based on their past interactions with your site. Behaviors used as targets include such events as when a customer browses a specific product category, adds an item to their cart without converting, or returns to the site after a long absence.

Boost and Bury

Boost and Bury

A function in various Product Recommendations features that allows a client to manually influence if recommended products that meet filtering criteria are more likely (boost) or less likely (bury) to appear for the customer.

bounce

bounce

To leave a site without browsing or clicking any elements.

bounce rate

bounce rate

A measure of how many visitors leave a site after landing on just one page with no interaction on the page. If visitors bounce immediately, this behavior may indicate that what they saw was different from what they expected. A visitor who bounced after spending a fair amount of time on the site suggests there may be a problem with the page.

C

cart abandonment rate

cart abandonment rate

The calculation representing visitors who were initially interested in products compared to those who actually made a purchase. Use the following formula to calculate cart abandonment rate: Completed transactions ÷ Shopping carts with at least one item × 100.

conversion rate

conversion rate

The rate at which visitors to a website complete a predetermined action. Use the following formula to calculate conversion rate: Conversions ÷ Total number of visitors.

customer lifetime value

customer lifetime value

The sum of a customer's past order totals.

D

dampening

dampening

A setting in Monetate experience analytics that allows clients to scale purchases in the report that are above the selected threshold to a specific number of standard deviations (SD) above the mean.

Dynamic Content

Dynamic Content

A feature that allows clients to display text, images, and other user interface elements that change based on a customer's predetermined targeting value. It is responsive not just to differences between customers, but also to a single customer's evolving context as they log more behavioral data in the moment.

Dynamic Testing experience

Dynamic Testing experience

A type of Web experience in Monetate that determines the right content to show to the majority of the experience's audience. Experience results are monitored in real time to automatically allocate more traffic to the winner.

L

LTV

LTV

See customer lifetime value.

M

machine learning

machine learning

A subfield of computer science that involves the ability of computers to "learn" from past experiences and observations. This predictive programming combines data, code, and science to find patterns that rule-based programming cannot. With machine learning, instead of creating a program based on "if-then" rules, an algorithm is programmed to find opportunities based on mining data to produce reliable decisions. These decisions are consistently improved when more data is stored and analyzed.

Multivariate Test experience

Multivariate Test experience

A type of Web experience in Monetate that is similar to A/B and A/B/n testing yet enables testing multiple combinations on a single page at the same time.

P

product badging

product badging

A way to graphically highlight specific products, promotions, new items, etc., on product list pages and on product detail pages. Monetate's product badging actions also allow you to dynamically target visitors based on audience segmentation so that you can emphasize a key selling point of a product based on your audience.

Product Finder

Product Finder

A Monetate feature that allows a client to create a guided questionnaire for use in a Web experience to deliver filtered recommendations to customers based on a recommendation strategy.

S

seasonality

seasonality

A statistical consideration that is based on an estimated monthly traffic percentage.

segmentation

segmentation

The process of using qualitative and quantitative research to identify defining characteristics that are likely to influence a purchase decision.

Social Proof

Social Proof

A Monetate feature that allows a client to deploy messages with the aim of generating the fear of missing out on popular products amongst visitors browsing its site.

Standard Test experience

Standard Test experience

A type of Web experience in Monetate that is an A/B/n test that offers a controlled learning environment.