Terms Explained: What do These Martech Terms Mean?

Marketing tech is certainly one of those - with the widest array of poorly understood terms.  Why? We think it’ because marketers cannot help themselves trying to distinguish their product or service from everyone else’s.  Everyone wants to their platform or service to be the next big thing.

This blog post aims to help you understand some of these terms to allow you to navigate themselves around the MarTech world. These are not ‘legal’ terms per se, but important terms which help understand the overall MarTech ecosystem.  

Audience Profile

Attributes of the target audience that is known to the company such as age, location, interests, etc.  

Artificial intelligence (AI) marketing

A form of marketing which applies AI concepts models such as machine learning, deep learning, and natural language processing to perform marketing tasks and achieve marketing goals. 

Chatbots

AI-powered software with which customers can engage in conversation simulating a human conversation between the company and the customer.

Close-looped marketing

Marketing which relies on the reporting back of information and data gathered from tracking the customers journey in engaging with the company to understand the impact of the marketing approach on the company’s success. 

Cross-channel marketing

Providing the target audience/customer with a consistent experience by creating interactions between the audience and the brand through various channels. 

CRM (Customer Relationship Management)

CRM means customer relationship management.

Technology used for managing and analyzing a company’s interactions with its past, present and potential customers in order to sustain and improve business relationships with customers.

Data-driven marketing

The process of optimising marketing communication by using data gathered from customers as it allows the company to understand the present and future needs and desires.

MarTech Stack

Stack is the collection of marketing technologies used by a company to manage, optimise, and improve marketing activities. 

eMarketing Code of Practice

Provide rules/ guidelines for sending commercial electronic messages.

Privacy regulation 

Sets out rules around what can and can’t be done in relation to personal information that set out what must be done by entities at each stage of the ‘information lifecycle’, including collection, use, disclosure, storage, destruction or de-identification. This will vary depending on jurisdiction (generally, this is where your data subjects are located).

Personal Information

Personal Information includes information or an opinion about an identified individual, or an individual who is reasonably identifiable, whether the information or opinion is true or not and whether the information or opinion is recorded in a material form or not. 

First party data

Data that a company collects about customers, using its own cookies, scripts, online forms, product purchases, logged-in sessions, or any other method, such as:

• Subscriptions and registrations - Digital subscription records, Newsletter subscribers, Print subscribers, Registered customers (non-paying), audience demographics
• Performance/ Marketing - Advertising performance/ behavioural data, Digital content analytics (e.g.  how customers are engaging onsite), Marketing campaigns
• Other - Transactional data, Print circulation records, Financial reports, Social analytics.

Advertisers may also use their own first party data in order to target ads on a company’s sites, or the company may use their own first party data to target on third party sites.

Such data may be ‘onboarded’ into a Data Management Platform (DMP) or ‘streamed’ into a ‘data lake’.

Second party data

Another company’s first party data made available for purchase via a second party data market. I.e.  Company A’s records about their own site visitors - made available for use to Company B directly by Company A.

Second party data is only shared on the segment of customers that Company A has in common with Company B - to learn how mutual customers interact with partner brands, giving insight into needs, preferences and behaviors.

Third party data

Data owned and sold by data companies, about individuals with whom that company does not have a prior relationship, which is licensed or purchased to support targeted advertising.

Typically, information is demographic (‘Men aged 25-54’), intent (‘auto-intender’), psychographics (‘sports enthusiast’).  Ordinarily this data is ‘modelled’ and is only broadly accurate. However, abundance of data gives the largest possible scale.

Outside sources are typically not the original collectors of that data either - they aggregate data from multiple sources and repackage this.

In the US, industry players are moving towards a more ‘standardised’ measures of third party data – and have released the ‘Data Transparency Label’ which is designed to be a new industry standard for displaying information about audience data sets, resulting from a collaboration between ANA’s Council for Data Integrity and the IAB Tech Lab’s Data Transparency Standards Working Group.

Known (Personalised aka Deterministic) / Unknown (Non-personalised aka Probabilistic) data

• Known - means data linked to an individual, through methods such as a login or authenticated service (e.g. Gmail login);
• Unknown - means data which is inferred in relation to an identity based on their activities and behaviours online, but not actually linked to an individual

Personalization

Marketing that is targeted to a known individual or customer profile.

Google Customer Match and Facebook Custom Audiences allows businesses to target ads at specific individuals using lists of (hashed) emails uploaded to those platforms (or hashed within those platforms) against the email address stored by that publisher

Hashing / Encryption

• Hashing - A (mathematical) method of converting data ‘one way’ from a [readable format to a non-readable format] / [one format to another format]
  • Commonly used to turn an email address (personal info) into a string of characters (non-personally identifiable)
• Encryption - a two-way transformation of data which with a key can be reverted (decrypted) to its original format

Anonymization/pseudonymization

Pseudonymised data can no longer be linked (or “attributed”) to a single data subject (user) without the use of additional data.

Pseudonymous data can still go through re-identification to link (attribute) it to an individual again.

Personal Information / Personal Data / Personally Identifiable Information (PII)

This describes data about an individual - terms used in AU, Europe and USA respectively, including email name and credit card data. Data which isn’t anonymous is typically considered PII, but definitions are highly nuanced with different outcomes across markets (at the fringes).

Data Lake/ Data Mart/ Data Warehouse/ Data Stream

Lake, Mart and Warehouse are data storage repositories.

• A ‘Data Lake’ is a company-owned storage base that allows for the analysis and processing of large volumes of raw data, which may or may not be unstructured, at a low cost.
  • It distinguishes itself from a DMP in: the longevity and comprehensiveness of its data record, the wide range of thorough analyses it allows for, and the possibility to store PII.
  • ‘Lake’ denotes unstructured ‘raw’ or ‘native’ data, the purpose for which is not yet defined.  May also be semi-structured.
• A Data ‘Mart’ a portion of a data warehouse that only contains information from a single department.
• A Data ‘Warehouse’ denotes structured, filtered data that has already been processed for a specific purpose.  Can be within a ‘Lake’.
• A Data ‘Stream’ is an emerging concept describing both an ‘architecture’ and ‘use’ of data as a real time ‘stream’ of ‘events’; where the occurrence of an ‘event’ (e.g.  a signup) leads on to follow-on ‘events.

DMP (Data Management Platform)

DMP means data management platform.

These platforms allow companies to unify/ centralise all of their data related to customers and campaigns and can include all sorts of data - first party, third party, online, offline, media, CRM etc.

DMPs allow for the audience segmentation and the redistribution of such data to other advertising platforms, to which DMPs are typically connected.

Machine Learning 

This is a method of using mathematical models (e.g. regression) to predict customer behaviour. E.g. determining a propensity to subscribe value for an individual visitor based on a customer’s similarity to people who previously subscribed.

Registered/ Authenticated User

A customer that has registered with/ signed-in to a website. This typically means that customers will have accepted the terms and conditions and privacy policy of the company.

Fingerprinting

A catch-all term for various techniques that try to examine what makes a given customer’s browser unique, and in doing so fully or partially identify individual customers or devices (even when cookies are turned off).  This could include using tiny bits of information that vary between customers (such as what device they have or what fonts they have installed) to generate a unique identifier which can then be used to match customers across websites.  

First-Party Cookies / Third-Party Cookies

• First-party cookies are created and placed by the domain/website a customer is visiting directly.  They are used to collect analytics data, remember customer settings, and perform other functions to support customer experience.
• Third-party cookies are created by domains that the customer is not visiting directly, hence the name third-party.  They are used for cross-site tracking, re-targeting and ad-serving.

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