Lead generation

To help our current and prospective clients better understand our approach to lead generation, we’ve created a glossary of common industry terms relevant to our agency’s services, tools and techniques.

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1st party data can be understood as audience and customer data that your company directly collects from their own source(s), and then owns, controls, manages and stores. Relating to a customer’s behaviours, actions or interests, this data could come from your company’s website, app, CRM, social media, surveys, or any other online or offline sources that your company has created and owns exclusively. .

2nd party data is data that has been collected by one party (the first party), with access then given or granted to one or more external companies that will then privately share that data for a mutual benefit. Proper handling of 2nd party data requires the sharing of mutual customer records and only the segment of customers you and your partners have in common.

3rd party data is data collected on sites and platforms that do not have a direct relationship with the user on whom the data is being collected. Typically collected from a variety of platforms before being aggregated by another party outside of your organization (referred to as ‘data management platforms’ or ‘DMPs’), 3rd party data is usually bought and sold in bulk and is best for targeting demographics with specialized contextual or behavioural characteristics.

An ad exchange is a marketplace and technology platform for buying and selling media advertising inventory from multiple ad networks. Used by both advertisers and publishers, inventory prices are determined through automated real-time bidding vs. the traditional negotiation marketplace approach used previously.

An ad server can be described as a web server technology that stores online marketing advertising content before delivering that content to publishers and prospects through digital platforms like websites, mobile apps and social media outlets. With the capability to count clicks and generate reports, advertisers may also use ad servers to better manage their ad inventory and reports.

Audience suppression is when you remove a subset of your audience from a campaign or exclude them from receiving a certain ad or piece of campaign content. Ensuring that customers only receive content that is directly relevant to them by preventing recurring ads, audience suppression can drastically improve your ROI by ensuring that your ad dollar is used in the most efficient way possible with the highest chance of conversion.

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Addressability refers to the destination or location to which your marketing efforts are directed and reach your customer, such as an email or postal address. Unlike offline addressability, online addressability is notoriously fickle given that many addresses are anonymously tied to devices and constantly changing, making it difficult to reach the same customer across multiple channels and devices with a consistent but non-redundant message.

In simple terms, analytics is the systematic discovery, interpretation and communication of particular data set patterns. In a centrally data-driven world and industry, analytics are an essential step in both understanding past user activity and making strategically-informed decisions around how to conduct activity in the future.

API stands for ‘Application Programming Interface’, which most easily understood as a software intermediary (or messenger) that allows two applications to communicate with each other. Comprised of a set of predefined commands, functions, and protocols that programmers interact with, an API makes a request to one application before delivering the response to the other

Attribution modeling is a framework for analyzing which touchpoints or marketing channels receive credit for a conversion, or contribute most to a certain customer action. While each attribution model distributes the value of a channel’s conversion differently, each aims to deliver the data needed to optimize budget allocations and strategies for future campaigns.

Big data is a broad term for extremely large sets of data that are too big to be processed using traditional, old-school technology, especially when searching for patterns relating to human behaviour and interactions. Instead, ‘big data’ must be analysed computationally to reveal patterns, trends and associations within the set.

In contrast to the previous digital campaign optimization measurement techniques like clicks and impressions, closed loop analytics (or closed loop marketing) focuses on measuring impact through sales. It’s the process of sharing information between marketing and sales teams to improve results, while “closing the loop” between the marketing data collected from sources like Google Analytics (reporting on customer behavior) and the sales data collected from a CRM (reporting on customer purchases).

Also referred to as HTTP or browser cookies, cookies are small files stored in a web user’s browser directory or data folder that allow the device to be recognized during a future visit. Often used by ecommerce websites to retain information about a user’s previous activity on a site (like login credentials, shopping cart items, etc.), they enable a customized experience and the connection of marketing platforms based on matched data sets.

Cross-device marketing is the practice of reaching the same customer or audience across different devices. desktop browsers, smartphones, tablets and other internet-connected devices. This multi-channel strategy allows marketers to reach users with consistent messaging across all their screens, be it through a Facebook display ad on a smartphone or a YouTube video ad on a laptop.

A customer ID code is a unique number or symbol combination given to a customer or prospect when interacting with a marketing system or platform.

Data integration is the process of combining data from different sources into a single place, so you have a unified view of your customer. Integration begins with the ingestion or intake process, and includes steps like data cleansing, ETL (extraction, transformation & loading) mapping and transformation. It requires a privacy-secure approach to anonymization, recognition and connectivity that enable analytics tools to produce convertible business leads and strategies. 

The first step in facilitating data migration and integration, data matching is the process of matching fields from one database to another to ensure they align with their corresponding ID codes. Correct data matching is crucial to the success of many data processes, and determines the quality of the data to be analyzed for insights.

Data onboarding is the process of transferring or matching offline data to an online data platform or system. It occurs when offline customer data (like customer records, in-store purchase data, call center data or demographic tendencies) is matched to online devices and digital IDs to retrieve the same customers in an online audience, allowing for more strategic cross-channel and omni-channel campaigns.

Data quality refers to the validity and ‘richness’ of information within a particular piece of data. High-quality data is ‘cleansed’ to ensure validity, verification and regulatory compliance and the highest possible conversion rates, whereas low-quality data may contain outdated or incorrect information, glitches, irrelevant leads and missing fields that hinder a company’s ability to make the sale. 

A data management platform (or DMP) is a software platform used for the central collection, management and presentation of data. DMPs allow businesses to identify and build audience segments which then can be used to target specific users through online advertising campaigns, ultimately optimizing budgets around media buying and creative content.

A ‘demand-side platform’ is a software system that automates the buying of display, video, mobile and search ads, allowing digital advertising buyers to manage multiple ad and data exchanges through a single interface. DSPs are a great tool for optimizing audience targeting, content creation, real-time impression buying and publisher identification.

Dynamic content is any type of online or digital content (text, audio or video format) that changes based on user data, behaviour and preferences. It breaks down all elements of a piece of media (copy, imagery, colour, size, call-to-action messaging, etc.) to produce the most optimal, real-time combination for each viewer based on their data profile or information.

An email service provider (ESP) allows users to store email addresses and send marketing emails to a list of subscribers, typically through an easy-to-use interface at scale with a variety of customizable and segmentation opportunities.

ETL (meaning ‘extract, transform & load’) is the process of copying data from a source to a destination system which will represent or communicate the data in a different way. The most common approach to linking or moving data between systems, ETL involves extracting the data from your source and transforming it into a standardized format before loading it into a destination system.

Lookalike modeling is the process of identifying new, additional customers or prospects that look and behave like a pre-existing audience. It involves analyzing current customer data to define a ‘seed audience’, and defining key characteristics of this audience to identify a segment of people with similar behavior, demographic qualities or preferences.

1:1 marketing (also known as ‘individual’ or ‘personalized’ marketing) is about delivering individual-specific experiences through custom messages and product offerings. By leveraging data analysis and digital technology, companies can tailor their content to the custom preferences of current or prospective customers, rather than broad audience segments encapsulating varying characteristics and behaviours. 

Expressed as a percentage, a match rate can be understood as the number of individuals from one data set that could be matched with individuals from another. It’s the number of users from a file that could be identified and anonymously data-tagged during the data onboarding process, where offline data is transferred or matched to an online data platform or system.

A marketing stack is the collection of technology-based tools (or ‘martech’) used to manage or execute marketing activities. The stack can be broken down into three layers: the ‘data layer’ that includes the technology used to store, manage, and analyze your data; the ‘application layer’ that contains applications which execute, optimize and manage campaigns; and the ‘connectivity layer’ that connects your data to your applications and media platforms. A well-constructed ‘stack’ allows marketers to better map and monitor efficiency, overlap and gaps to inform more optimal campaign implementation and results.

Mix optimization is the process of analyzing one’s various channels and campaigns to determine the best mix across various channels (offline and online) and media (traditional, digital and social). It allows marketers to optimize the distribution of media spend for maximum impact (ROI), and focus more time and budget on the channels and campaigns that best convert leads into sales.

Also known as cross-channel marketing, multi-channel marketing is the strategy of reaching the same customer on different marketing channels with a single campaign, with the channels still behaving independently of each other. For example, a customer may see a Facebook display ad about a new security system one day, followed by a free shipping YouTube video ad the next day and an email discount offer the next.

Native advertising is a type of advertising that matches the form and function of the platform on which it appears, often resembling editorial content despite being paid for by an advertiser with the intention to promote their product. Made to look and feel more ‘organic’ than other ads, native advertisements could appear as a newspaper article or social media post, but  with a ‘sponsored’ or ‘advertorial’ clarifier tag clearly visible to the user. 

Omni-channel marketing is the process of creating one seamless, integrated sales experience across all marketing and sales channels. Using both digital and/or traditional channels, the approach aims to deliver a consistent message to a customer regardless of the individual device or context, from a desktop or mobile device to a bricks-and-mortar physical location. 

Offline attribution refers to the act of connecting digital and traditional marketing efforts to ‘real-life’, offline outcomes. It enables marketers to see how their audience is reacting to a campaign in the physical world, and quantify an ROI for marketing campaigns that extend beyond the much more easily-trackable online world. 

Offline data is data that’s collected, stored and retrieved from ‘offline’ systems. This could include data from applications like CRM platforms or email marketing platforms, datasets purchased from third parties or in-store collected customer information, that materializes as contact information, purchase history and demographic data, to name a few. Offline data typically contains personally identifiable information (PII), such as a customer ID, name, email or postal address.

Online data is data collected from and stored in digital marketing platforms like social channels, DMPs, DSPs and ad servers, plus any relevant data collected from website clickstreams. It is typically available through the internet, and tied to anonymous devices through  mobile device IDs or cookies.

Personally identifiable information (also known as PII or ‘personal data’) is any data that can be used to identify a specific individual. Social Security numbers, addresses and phone numbers have most commonly been considered PII, but technology has expanded the scope considerably to include things like IP addresses, social media posts, geolocations and behavioral data. Anonymization is essential to PII policies (ie. GDPR) and enables marketers to deliver highly focused, more personalized experiences to audience segments while protecting consumer privacy.

Also known as ‘programmatic media’ or ‘programmatic marketing’, programmatic advertising is the process of using automated software to buy digital advertising space. Unlike the traditional method involving human negotiations and manual RFPs, machines with pre-set rules or algorithms automate the buying and optimization of media inventory to make real-time decisions about the sale.

Although a highly subjective term, a premium publisher is widely defined as one that readers or viewers actively look for, trust and feel an affinity towards, usually due to their high-quality nature or perceived value of content. As a general identification criteria, self-described ‘premium publishers’ typically pose higher prices, can demonstrate high levels of engagement and rarely work with Demand Side Platforms (DSPs).

Real-time bidding (RTB) is the fully-automated approach to buying and selling media between publishers and advertisers. With advertising inventory bought and sold on a per-impression basis via programmatic instantaneous auction, advertising buyers bid on an impression. If the bid is won, the buyer’s ad is instantly displayed on the publisher’s site.

Retargeting is a form of online targeted advertising that re-engages customers based on their previous activities or actions through custom content changes. This is most commonly done through showing users a recently viewed product or service within a new webpage or email, encouraging them to revisit the purchase. CRM retargeting (or offline retargeting) instead focuses on targeting customers using CRM data with media buys and customer insights to extend your campaign’s reach.

Marketing segmentation is the process of dividing a target market or audience into smaller and more approachable subsets based on shared characteristics like demographics, geographics, behaviours and preferences. The primary aim of segmentation is to identify the segments with the highest conversion or growth potential, allowing marketers to focus their content, efforts and budgets accordingly.

Social data is information that users publicly share via social media. This can include explicitly shared metadata such as geographical location, language spoken and external links, or implicitly shared information derived from their activity or behaviour. Social data is increasingly valuable for marketers looking for sales-driving customer insights, or for those looking to capitalize on and persuade attitudes in a direction of their favour. 

A tag is a piece of code that many vendors require users to integrate into their web and mobile sites that collect unique behaviour information to support digital marketing efforts. Tag management software has been designed to manage and extend the life cycle of these e-marketing tags, making it easier to update site content and provide a more seamless user experience.

Targeting is the process of breaking a large audience down into smaller segments before concentrating and tailoring marketing efforts to one or more specific groups. Instead of trying to reach an entire market, targeting defines a smaller segment of customers based on their unique characteristics and focuses solely on connecting with that group through an audience-bespoke channel and content strategy.

Yield optimization (or yield management) is a digital advertising strategy where a publisher sells its inventory at the highest possible price by providing the right ad to the right user at the right time and place. Through intensive data analysis, yield optimization requires understanding precise success determinants and exploiting them to maximize digital advertising revenue and efficiency.