The A-Z of Personalized Marketing

A Marketer’s Glossary of Personalization at Scale

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We have entered the era of personalized marketing.

Customers expect it. Technology enables it. Brands who can deliver it are generating huge increases in ROI.

Personalization has gone way beyond simply adding a customer’s name to a communication. Customers increasingly expect highly relevant content in the right channel at the right time, whether they’re on a brand’s website, a social network or in their email inbox. For brands, delivering this one-to-one experience at scale — to thousands, or hundreds of thousands of prospects and current customers — requires leveraging sophisticated datasets, processes and platforms.

It’s no surprise that many marketers are struggling.

In a recent survey by Digiday and Neustar of 100 digital media and marketing executives, more than half (53%) reported “always” or “often” struggling to personalize their marketing at scale.

Marketers know they need to make their marketing personal, but aren’t sure how to do it at a scale that makes it cost-efficient. The challenges include data quality, difficulty of activation across online and offline channels, and a lack of understanding of the components of the process.

This A–Z deals with the latter. Personalized digital marketing has grown so quickly that it’s developed its own vernacular. Even terms which marketers have used for years can take a slightly different meaning in this new world.

This guide has been created to give you a better understanding of the components of scaled, personalized marketing, so that you can in turn give your customers the one-to-one dialogue they’re waiting for.


Activation:

Turning data into actions across your online and offline marketing channels.

These actions let you have a personalized dialogue with customers or prospects, and typically involve automation when undertaken at scale. Examples include audience segmentation, leveraging offline customer information for precise targeting, and the display of personalized banners and content for different website visitors.

Activation can be carried out across offline channels (call center, direct mail, TV) and online channels (site, search, display, social, mobile, video, email, etc.) The better the data behind it, the more effective your activation will be.


Attribution:

Assigning value to an action that contributes to a conversion.

Marketing attribution quantifies the influence each ad impression makes on a consumer’s purchase decision. This provides insight into what influences your target audience, and to what extent. Strong marketing attribution better enables you to adjust and optimize your media spend, based on the outcomes desired for each particular channel or impression.


Audience:

The demographic or target who views your ad or campaign.

Marketers can use customer and media intelligence to target specific audiences, differentiated by age, income, geography, (and other demographic information), interests, media usage and buying propensity.

Audiences can also be segmented into different categories such as “likely user,” “frequent customer,” or “top-performing.” Targeting high-performing audiences can generate huge conversion increase, especially when first-party data is combined with authoritative third-party data.


Closed Loop:

The correlation between online consumer interactions and online and offline sales.

Closed-loop insight helps you measure the success of campaigns by accurately crediting media, leads, sales, and conversions to the online content users see. A marketing platform that uses closed loop insight should be able to measure ad campaigns based on transaction lift at an individual customer level, test control groups at scale for greater accuracy, and ensure that analysis takes place in a secure and privacy-friendly manner.


Conversion:

Getting a consumer to perform a specified action.

Examples of conversion range from signing-up for an e-mail newsletter or promotion, clicking on a link, or moving from being a site visitor to a paying customer.


Cross-Channel Marketing:

Using multiple platforms and media to reach and engage your customer.

The goal of cross-channel marketing is to make conversion easier by engaging your consumer at multiple touchpoints, delivering a consistent, personalized experience.

Cross-channel includes, but is not limited to, traditional advertising, digital/web, e-mail, social media, mobile and point- of-purchase/in-store. It is also referred to as multi-channel.


Cross-Device Marketing:

Advertising and marketing campaigns that reach a consumer through multiple digital devices such as smartphones, tablets and computers.

As consumers increasingly use multiple devices to access similar (or the same) information – such as checking e-mail on a laptop or smartphone – the need to optimize messaging for these different formats is increasingly important.


Customer Experience:

The quality of the interactions a customer has with a brand.

Customer experience can refer to the sum of all interactions a customer ever has with a brand, or a one-time transaction. A strong customer experience, including personalization, is important to building repeat business, increased spending and brand loyalty.


Customer Intelligence:

Information that helps you identify and know your customers or prospects better.

Customer intelligence includes demographic data, first party (CRM data) and third-party data. It is used to segment customers into high-performing audiences you can for target across all offline and online marketing efforts. It is an essential component of personalized marketing at scale.

Not all customer intelligence is created equal. Marketers should ensure that theirs is verified, authoritative and up-to-date in order to gain a complete picture of their customers.


Data, Customer:

All of the information that can be collected on a customer or group of customers.

Data comes from many sources. It can be internal information you have about your customers or from outside sources (usually purchased). Data can include general information, such as demographics, or it can be customer-specific (purchase or usage history).

Data comes in several different forms:

  • First Party: Information about your customers collected by you – aka CRM data. First-party data can include information about your customers’ behaviors, actions or interests, purchase histories and other customer-relationship and/or transactional information. This data often contains personal information such as names, addresses and other identifiers, making it particularly valuable for a personalized marketing experience.
  • Second-Party: Another company’s first-party data that you have acquired directly from them. Second-party data can include customer data from a competitive or non-competitive company (acquired directly from them), or audience information acquired directly from a publisher or content creator. It contains the same valuable information as first-party data, but often doesn’t include your own customers. Second-party data can be very effective for creating personalized communications for new customer acquisitions.
  • Third-Party: Information acquired from an outside party. Third-party data can come from one outside source or be aggregated from other sources. It is then used to categorize consumers into different groups, targets and audiences. The collection of third-party data is generally out of your control. It provides a greater breadth and depth of information that you currently possess on customers and prospects. Data degrades over time. For example, about 45 million people change their phone numbers each year; another 16 million people change residences. Your third-party data provider should have strong systems in place to ensure not just accuracy, but real-time updates to data.

Data Ownership:

Having legal rights and control over a piece of data or set of data elements.

Marketers own huge amounts of first-party data that help them personalize offers to their customers. Ownership is key in learning about current customers and finding additional customers that look like them.

Today, marketers typically only share this information if they retain data ownership, data rights, and can ensure data portability. If, for example, you want to switch marketing partners or advertising agencies, data ownership means you can leave with any learnings and best practices.

Because of the numerous privacy issues involved with data (particularly first-party data), having ownership, rights and final approval about how that data may be used (and to what extent it may or may not be shared) is a doubly important issue for marketers, particularly when it comes to customer relationship management.


De-Duplication:

The elimination of overlap in your online advertising.

De-duplication increases your media spend efficiency by ensuring that you only pay for an audience once.

Users that show up in other channels are weeded out so that they only see a message once on any single inventory provider (as opposed to on multiple providers). De-duplication is often accomplished through the use of cookies.


Demographic:

Defining an audience by a quantifiable characteristic or set of characteristics.

Demographics include age, gender, geography, income, employment status or a host of other characteristics. A demographic profile helps you identify an audience that might be receptive to a given product at a specific time (college-educated women who have just had their first baby, for instance).

This information is used to inform your marketing campaigns to create targeted, personalized messaging. First-party, second-party and third- party data can all be used used to develop demographic profiles.


DMP:

Software that collects, stores and sorts information.

Short for Data Management Platform, a DMP is a system that helps you understand and analyze data to inform your marketing strategy. With billions of opportunities to create millions of impressions, the importance of managing data to create a personalized-marketing campaign is essential.

As media buying has become more complex, DMPs have begun to tie media, audience and campaign data together to optimize campaigns for greater efficiency and effectiveness.

Research: What's Holding Marketers Back from Personalization at Scale?

A survey by Neustar and Digiday indicates: it’s the data.

We recently interviewed 100 digital media and marketing executives on their struggles with personalized marketing at scale. More than half (53%) said they “always” or “often” struggle with it. (Another 29% said they “sometimes” struggle, while only 4% said they “never” do.)

Though marketers have access to more data than ever before, they have difficulty using it. In our survey, one-third (33%) of digital marketers said poor and/or incomplete customer data was the biggest obstacle to achieving personalization at scale. Another 26% said they had difficulty turning their data into action, and 15% said they struggled to identify customers across different devices.


Exclusive Reach:

The size of an audience reached exclusively by a particular channel.

When “Channel A” delivers 50,000 users that cannot be reached on Channels B, C and D (or anywhere else), Channel A has an exclusive reach of 50,000.


Frequency:

The number of times an audience member sees a campaign.

Frequency is a measure of how often an audience member sees or engages with a specific message across different media channels. As a KPI, it can be achieved by repeating an ad or message multiple times during a campaign’s run and/or repeating the message across different channels.

“Effective Frequency” is the number of times an audience member must be exposed to a specific message to generate the desired response.


Identity:

The data that lets you know a consumer is the same no matter which touchpoint or channel he/she uses.

It is now possible to derive a single view of a prospect or customer based on just one key identifier, such as name, physical address, phone number, email address or IP address. An identity doesn’t always include a name or other personally identifiable information; it can rely instead on many other attributes, such as those above.

For marketers, it is equally important to authenticate identities, which helps you acquire customers, and to respect privacy, which helps you retain and grow them.

Marketers have access to a variety of information about their intended targets – online sales, email addresses, search information, street addresses, phone numbers. These individual pieces of data need to be connected, for instance, taking an email address and matching it with offline information. Those sorts of data matches are crucial if, for example, a customer calls in for information but doesn’t complete a purchase; a follow-up contact can then be made via a postcard or email message.

Marketers want their brands to reach the right people across all platforms. That requires linking consumer information and online behaviors to offline sales. The best data management provides not just pieces of information but also the full picture: a 360-degree portrait of consumers that understands who they are in order to send the right offer via the right channel at the right time. In fact, according to a Forrester Research survey done for SAP in November 2013, more than 70% of senior-level marketers surveyed said this kind of personalization “can have a significant or very significant impact on customer retention rates, customer lifetime value, customer advocacy rates and promotion conversion rates.”


Impression:

The number of times an ad is seen or displayed. Impressions refer to the placement of an ad in a space where it might be seen by your customer in a given time. The ad does not have to be engaged with (clicked on or some other action) to be counted as an impression.

Because there has been more incidence of click-fraud and robotic activity to increase ad appearances, the industry has been moving from “served impression” (based on the server’s record of an ad’s display) to “viewable impression,” which is an ad that is at least 50% visible for at least one second.


Inbound Personalization:

Tailoring web content to a specific audience.

When consumers visit your website, microsite or splash page, you can lift response and sales by personalizing the content.

Multiple data sources enable you to do this. For example, offline data (third-party or first-party CRM) lets you build custom segments based on purchase histories, brand preferences, media consumption and other information – then personalize each segment’s experience with relevant offers.


Key Performance Indicator (KPI):

Measurable goals to gauge campaign performance.

Key Performance Indicators are the ways you measure how successful a campaign is. They can range from impressions to clicks to actual sales, but they must be clear, quantifiable and determined before a campaign has been launched.

KPIs are based on quantifiable data and should be presented in a context that aligns with your business objectives, but also eliminate factors outside of your control that can affect outcome.


Last Touch Attribution:

Attributing a conversion entirely to the last interaction a customer made with a brand.

Last-touch (or last-click) attribution gives credit to the ad most recently seen by your customer, regardless of how many other campaign elements the customer may have seen in other channels. For this reason, the industry is moving away from it and towards multi-touch attribution models.


Lookalikes:

Audiences that look like existing ones, preferably high performers.

Using the information you have on your highest-performing customers, you can segment a lookalike audience and engage them with proven tactics.


Media Intelligence:

Data and insight that helps you buy the right media, deliver it to the right audience, and measure performance across both.

This intelligence enables marketers to pinpoint investments as they grow reach and increase sales. Often provided by a marketing platform, the best media intelligence connects your audience across multiple channels in one view, and links online and offline data. Media intelligence is key to understanding which channels and campaigns drive sales, and which media partners and datasets work best to reach your target customers.


Multi-Touch Attribution:

Distributing credit of an ad’s effectiveness to more than one impression or channel.

In contrast to a last-touch model, a multi-touch model looks to measure the impact of each content piece a customer engages with up to the point of conversion. ‘Upper-funnel’ channels like social media score more highly in a multi-touch model, reflecting their effectiveness in generating initial awareness at the beginning of the buying process.


Omnichannel:

Using different channels to deliver your marketing campaigns.

As consumers use multiple devices to access content, marketers use multiple channels (including mobile, web, television, brick-and-mortar stores, and direct mail) to reach consumers with relevant messaging. The goal is a seamless shopping experience that touches your customer at multiple points along the path to conversion.

An effective omnichannel campaign should provide a consistent message and brand experience across channels, optimized for each channel or device.


Platform (Marketing Platform):

A software suite that enables you to deliver personalized marketing at scale.

Today’s best marketing platforms combine customer intelligence and media intelligence with tools to activate both into personalized campaigns at scale.

Your marketing platform should deliver a real-time portrait of customers, based on authoritative, verified data, to enable personalized dialogue across all marketing channels, at the scale you need. It should link your customer interactions with the right data, so you can act on insights the moment customers engage, whether during inbound or outbound activities.


Predictive Analytics:

Analyzing data to predict buyer intent.

Predictive Analytics help you better understand what your customer is thinking at different points along the path-to- purchase. Such information can be used through personalization to target the right message to your customer at the right time.

Predictive analysis can be used to target new customers, manage current customers, or keep dissatisfied customers from leaving for a competitor.


Privacy:

The boundaries that define how marketers store, repurpose or share consumers’ personal information.

Consumers give information with every click, search and purchase. Naturally, people have concerns about how this data is used. Marketers must walk a fine line: respecting privacy while displaying the relevant messaging consumers expect.

Privacy can entail either personally identifiable information (PII) or non-PII such as a visitor’s website behavior, his/her age and physical address, none of which explicitly discloses the person’s name.

Privacy polices govern collection, use and storage of data both offline and online. Privacy by design is an approach that ensures privacy is embedded into the design specifications of technologies, business practices, and physical infrastructures. More marketers than ever, in fact, have a Chief Privacy Officer. Likewise, your marketing platform or first-party data onboarding should come with privacy by design built in.

Marketers must think carefully about privacy at every step. In the Age of Big Data, it is crucial to marketing strategies and your brand itself.


Quality User:

A prospect or customer who logs into an online channel consistently.

Channels which deliver quality users – social media sites, for example – are particularly valuable to advertisers because they allow for consistent targeting of the same user. A ‘user quality index’ can be used to rate different channels on this key metric.


Raw Data:

Unprocessed information, usually from a first-party source.

Also called “primary data,” raw data has not been subject to any processing or other analytics. Making raw data effective is a significant challenge for marketers. An example is cash register sales data, which needs to be extracted and organized – e.g. matched with loyalty card information – to derive real insights that marketers can act upon.


Reach:

A measurement of ad viewing.

Reach is the total number of people (or other designation) that have viewed your ad at least once during a campaign. Reach may be expressed either as an absolute number or a fraction of a given population.

While “Reach” in general refers to a total audience that may view an ad, “Effective Reach” refers to a more targeted audience, referring to the quality of that exposure.


Real-Time:

Marketing or data that reflect and react to events as they happen.

Real-Time marketing determines the optimal approach to engage your customer at a particular time and place, whether on inbound or outbound channels. Through it, you can give your customer the most appropriate offer for a given opportunity.

In online media buying, “Real-Time Buying” or “Real-Time Bidding” lets buyers compete for impressions as they become available. When buyers win a bid, the ad is instantly displayed on the publisher’s site. This process lets advertisers manage and optimize buys from multiple ad networks.


Relevance:

Delivering the right content at the right time for a customer.

Relevance is key to creating a personalized dialogue with your customer. Your campaigns might have reach and frequency, but without relevance, they won’t resonate (and may irritate).

To deliver relevance at scale, fresh data is paramount. A travel customer who has just booked a flight, for example, will consider further ads for flights irrelevant – unlike an ad for discount car rentals, which would be more relevant. The marketer who can leverage CRM data to deliver this experience is at a distinct advantage.


Retargeting:

Serving advertisements to customers based on prior Internet use.

Retargeting keeps track of your website visitors. When they move on to other sites, they see ads for the products they showed interest in while navigating your pages.

Different products often require different retargeting windows. (A person looking for a shirt may be retargeted more quickly than one shopping for a car, for instance.)


Sales Funnel:

The process through which your customer makes a decision.

Using the metaphor of an object wide at the top and narrow at the bottom, consumers at the top are considered to be in early stages of the buying process (i.e. “unqualified prospects”), who have not yet selected a vendor or specific product but may be considering making a purchase. Through various stages, consumers either drop away or become more inclined toward purchase (represented by the narrow point of the funnel).

You should be aware of consumers’ journey through the funnel and which marketing tactics and messages best work at each stage.


Segmentation:

Dividing a target market into subsets of customers.

Segmentation entails dividing a target audience into groups with common attributes, in order to market to each group differently.

Segmentation can be based on a wide variety of demographics or other information, and enables you to tailor your message based on a segment’s common needs, priorities and characteristics. It is a crucial element of creating a relevant, more personal dialogue with a large audience.


Single View:

Gaining a clear, singular picture of a customer or prospect in real time.

Marketing platforms are evolving to analyze data from multiple channels, giving you a more complete picture of an individual buyer. Neustar’s PlatformOne, for example, offers a single view of a customer from just one of six key identifiers: name, physical address, phone number, mobile number, email address or IP address.

With so much of this data delivered in real time, you can compile more accurate pictures of your customers – even as they change brand loyalties, purchasing habits and lifestyles – to enable better targeting and content personalization at scale.


Targeting:

Placing ads to reach consumers based on various traits.

Targeting makes use of data to define audiences and determine the most effective ways to reach them. It usually works hand-in- hand with segmentation to deliver tailored content at scale.

Online targeting often relies solely on consumer demographic information to define an audience. However, marketers can use additional data, including CRM data, to identify and target an audience more precisely.


Verification:

Connecting names with contact information to ensure accuracy.

Verification uses data identifiers to help marketers understand the identity and contact information of customers and prospects. Particularly valuable on inbound marketing channels such as websites and call centers, its benefits include a better customer experience and increased conversion rates through more targeted offers.


ZIP+4:

A more-targeted identifier for marketing campaigns.

ZIP+4 codes are four extra digits added on to a traditional five- digit ZIP code to identify a geographic subset within a ZIP code area. Though rarely used by the general public, ZIP+4 codes are used by marketers to better target and reach smaller areas within a larger geography.

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