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What is identity resolution and how are platforms adapting to privacy changes?

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What is identity resolution and how are platforms adapting to privacy changes?

Identity resolution – the science of connecting the growing volume of consumer identifiers to one individual as he or she interacts across channels and devices – has become critical to marketing success, as well as essential for compliance with consumer privacy laws such as the California Consumer Privacy Act (CCPA) and the European Union’s General Data Protection Regulation (GDPR).

Central to that are identity resolution platforms, which is software that integrates consumer identifiers across channels and devices in a way that is accurate, scalable and privacy compliant to create a persistent and addressable individual profile. Identity resolution platforms enable marketers to “close the loop” of customer marketing, analytics and compliance with a comprehensive holistic view of activity across all of an organization’s customer touchpoints and channels. Such identifiers can and should encompass both online (device, email, cookie or mobile ad ID) and offline (name, address, phone number) data signals and attributes.



Why do marketers need identity resolution platforms?

Consumer adoption of connected speakers, home automation solutions, smart TVs and wearables continues to rise exponentially. The number of devices connected to IP networks is projected to climb to more than three times the global population by 2023, with 3.6 networked devices per capita, according to the Cisco Annual Internet Report, 2018-2023.

In this competitive environment, it is essential that brand marketers understand which online devices and offline behaviors belong to a consumer as well as who that consumer is. Every time a consumer interacts with the brand – regardless of channel – a different identifier (also called a key) can be attributed to that individual. These identifiers can include an email, IP or physical address, as well as a mobile phone number, digital tag or cookie.

However, accurately resolving consumer identities has proved challenging for a majority of brand marketers. Forrester found that a majority of C-level executives overrate their marketing organization’s customer identity accuracy and persistence.

That challenge promises to become even more difficult as tech companies make changes that essentially deprecate third-party cookies — one of the key identifiers that has been used to stitch identity data together. Google has announced plans to phase out third-party cookies in its Chrome browser in late-2023. Apple has similar plans for IDFA, its identifier for advertisers, requiring users to opt into the program. At this point, only 20% of iOS users have opted to enable it, further highlighting consumer preferences for privacy.


Identity resolution is not only critical to marketing success but is essential for compliance with consumer privacy laws such as CCPA and GDPR. Explore the platforms essential to identity resolution in the latest edition of this MarTech Intelligence Report.

Click here to download!

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What identity resolution platforms do

Identity resolution platforms support marketing processes around targeting, measurement and personalization for both known and anonymous audiences across digital and offline channels. And most enterprise identity resolution platform vendors offer the following core features and capabilities:

  • Data onboarding (including online/offline matching).
  • Proprietary identity graph.
  • Client ownership of first-party data.
  • Persistent individual and/or household ID.
  • Compliance with privacy regulations.
  • APIs for third-party system integration.

Vendors begin to differentiate their platforms by offering more advanced features, sometimes requiring additional investment, which include – but are not limited to – the following:

  • Match confidence scoring.
  • Data clean rooms.
  • Private (first-party) and/or second-party cooperative identity graphs.
  • Pre-built connections to martech/ad tech platforms.

Let’s look deeper at these platform capabilities.

Data onboarding

Data onboarding is the first step in the identity resolution process. Client data is typically onboarded via secure file transfer (SFTP), although several vendors also provide direct API transfer or pixel syncs. Data is processed with the goal of establishing a universal view of the customer and includes the following:

  • Matching individual identifiers in the identity graph (see below) to associate the customer with their interactions across touchpoints, particularly online to offline.
  • Suppressing unresolved IDs and interaction data for potential future use.
  • Hashing or tokenizing personally identifiable information (PII) with an anonymized customer ID.
  • Linking matched IDs to a universal ID representing the customer profile and all of its associated attributes.
  • Validating the accuracy of matches to a pre-established “truth set” of referential data known to be precise and accurate.

Most vendors provide persistent customer IDs during the identity resolution process, which means the ID follows the individual (or household) even as identifiers change, which they inevitably do. For example, when browser cookies expire or are deleted or customers buy and use new devices, the customer ID will remain the same. Persistence is also critical to enabling temporal time-series analytics, such as churn analytics. Matching algorithms differ among vendors, with matches established via probabilistic or deterministic methods or a combination of both. Deterministic matching relies on explicit links between identifiers, such as an email address that is used to sign in to a website or mobile app and can be associated with the resulting cookie or mobile ad ID (MAID). Probabilistic matching relies on implicit links between identifiers, such as a desktop cookie and MAID both associated with a residential IP address. The goal is to consider multiple signals like location and browsing history.

Both approaches have their pros and cons, which should be considered when choosing an identity resolution platform. Deterministic matching takes an omnichannel view that attempts to connect identifiers across digital and offline interactions. It can be difficult to scale and prone to inaccuracy. Probabilistic matching can “weed out” inaccurate data because it looks at a variety of data points versus binary matches. Its drawback is that it is limited to online touchpoints. Some vendors are using hybrid identity resolution approaches, which try to compensate for deterministic and probabilistic weaknesses while capitalizing on their advantages. It uses deterministic and probabilistic linkages, and then merges the two linkage sets together to form new, combined clusters.

Many vendors provide their overall match rates to potential clients. A few vendors go a step further, providing clients with customizable match algorithms or confidence scores (how likely the matches are accurate) based on their specific first-party customer data and data quality profiles. For example, a pure online organization may rarely use postal addresses and is likely to have lower-quality address data than an organization that relies on fulfillment to a physical shipping address. Addressability is another factor that can help marketers measure their match accuracy by assessing the number of consumers that can actually be contacted.

Identity graph

Most identity resolution vendors maintain a proprietary identity graph or database that houses all the known identifiers that correlate with individual consumers. There is no standard model for an identity graph. Each vendor differs in the types of foundational PII used, the matching methods employed and the non-PII integrated to enrich the individual profiles. Across the buyer’s journey, many identifiers can be associated with an individual, including email addresses, physical addresses, landline and mobile phone numbers, mobile ad and device IDs, account usernames and loyalty numbers. The identity graph collects these identifiers and links them to customer profiles, which are used to target and personalize marketing messages.

Identity graphs may also incorporate demographic, behavioral, financial, lifestyle, purchase and other data compiled or licensed from third-party sources, such as online news sites, purchase transactions, surveys, email service providers (ESPs), motor vehicle records, voter registration and other public records. Having all of this customer device, channel and behavioral data in one place allows brand marketers to more accurately measure the reach and frequency of their campaigns, and analyze how different ads and marketing tactics perform across channels.

In response to the dwindling availability of third-party cookie data and the increasing use of consumer privacy tools, such as advertising and location blocking apps, several identity resolution platform vendors are offering new identity graphs built on first-party or second-party datasets. First-party identity graphs are exclusively used by a brand to house and match known customer data. Second-party identity graphs use cooperative data-sharing agreements between multiple brands or publishers to create common, anonymized identity assets.

Participating organizations can build, plan, activate and measure custom audience pools to either target or suppress customers across addressable media.

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Privacy compliance and data ownership

Marketers with customers in the European Union have had to comply with GDPR since May 2018. The CCPA, impacting all brands with customers residing in California, went into effect in January 2020, and empowers consumers to make a Subject Access Request to see all the data an organization has about them, which raises the stakes of identity resolution match accuracy. CCPA defines personal information as anything that can be associated or linked with an individual or household.

Marketers in the highly regulated healthcare market must follow Health Insurance Portability and Accountability Act (HIPAA) and Health Information Technology for Economic and Clinical Health Act (HITECH) regulations. In addition, all organizations that accept, process, store or transmit credit card information must maintain a secure environment that meets Payment Card Industry Data Security Standards (PCI DSS), as well.

These regulations are driving an expanded industry focus on data transparency and consumer consent, with a view toward complying with new standards for the benefit of consumers, as well as marketers. Many identity resolution platform vendors adhere to advertising industry guidelines from the Digital Advertising Alliance (DAA) or Interactive Advertising Bureau (IAB).

Lastly, and importantly, the majority of vendors profiled generally allow enterprise brands to retain ownership of their first-party data.

Third-party software integration

The ultimate marketing goal for identity resolution is to support and enable data activation by pushing segmented audiences into highly personalized campaigns through a variety of martech (CRMs, DMPs, marketing automation platforms, ESPs, etc.) and ad tech (DSPs, SSPs, ad exchanges, etc.) tools and platforms. Identity resolution platforms should be able to streamline integration with the client’s martech and ad tech ecosystems by providing pre-built (or native) connections and an extensive set of APIs for custom integrations. Access to these APIs may or may not be included in base pricing.


Explore platform capabilities from vendors like Acxiom, Experian, Infutor, Merkle and more in the full MarTech Intelligence Report on identity resolution platforms.

Click here to download!


The benefits of using identity resolution platforms

Connecting consumer identifiers has become a mandate for enterprise marketers trying to meet and exceed customer expectations for a consistent and personalized brand experience.

Automating the process with an identity resolution platform can provide the following benefits:

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  • Deeper customer insights. Piecing together data signals from multiple data sources and interactions enables marketers to build more robust customer profiles. Knowing the customer at a more granular level can help drive rich customer insights that enhance campaign targeting, personalization and relevance.
  • Personalization accuracy. Better personalization is a primary marketing use case for many identity resolution platforms, which create a consistent set of identifiers to fuel personalized interactions. If you don’t know with confidence who your customer is, you can’t personalize your messages or experiences.
  • More seamless customer experiences. Automated identity resolution allows marketing organizations to create a unified view of customers, which can be communicated and deployed across brands, business units and product lines. Recognizing customers across every step of the customer journey reduces waste by eliminating duplicate contacts, and enhances their experiences by enabling interactions in the right channel at the right time.
  • Stronger privacy Governance, Risk and Compliance (GRC). Effective identity resolution supports your organization’s commitment to data governance and, ultimately, consumer trust in your brand. Using an identity resolution platform makes customer preference management (including opting out), as well as regulatory and corporate policy compliance easier and more comprehensive.
  • Enhanced cross-channel attribution and campaign tracking. Persistent IDs that identify customers (both known and anonymous) across channels enables more accurate, closed-loop measurement and multi-touch attribution.
  • Improved marketing ROI. Identity graphs reduce data overlap and duplication, resulting in more efficient spending on campaigns that work. Conversely, not knowing who your customers are leads to misidentifying them and engaging in ways they may perceive to be intrusive or irrelevant.

Identity resolution platforms: A snapshot

What it is. Identity resolution is the science of connecting the growing volume of consumer identifiers to one individual as he or she interacts across channels and devices.

What the tools do. Identity resolution technology connects those identifiers to one individual. It draws this valuable data from the various channels and devices customers interact with, such as connected speakers, home management solutions, smart TVs, and wearable devices. It’s an important tool as the number of devices connected to IP networks is expected to climb to more than three times the global population by 2023, according to the Cisco Annual Internet Report.

Why it’s hot now. More people expect relevant brand experiences across each stage of their buying journeys. One-size-fits-all marketing doesn’t work; buyers know what information sellers should have and how they should use it. Also, inaccurate targeting wastes campaign spending and fails to generate results.

This is why investment in identity resolution programs is growing among brand marketers. These technologies also ensure their activities stay in line with privacy regulations.

Why we care. The most successful digital marketing strategies rely on knowing your potential customer. Knowing what they’re interested in, what they’ve purchased before — even what demographic group they belong to — is essential.

Read next: What is identity resolution and how are platforms adapting to privacy changes?


About The Author

Pamela Parker is Research Director at Third Door Media’s Content Studio, where she produces MarTech Intelligence Reports and other in-depth content for digital marketers in conjunction with Search Engine Land and MarTech. Prior to taking on this role at TDM, she served as Content Manager, Senior Editor and Executive Features Editor. Parker is a well-respected authority on digital marketing, having reported and written on the subject since its beginning. She’s a former managing editor of ClickZ and has also worked on the business side helping independent publishers monetize their sites at Federated Media Publishing. Parker earned a master’s degree in journalism from Columbia University.

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MARKETING

8 major email marketing mistakes and how to avoid them

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8 major email marketing mistakes and how to avoid them

As email marketers, we know we need to personalize the messages we send to subscribers and customers. I can’t think of a single statistic, case study or survey claiming an email program of one-to-everyone campaigns outperforms personalization.

Instead, you’ll find statistics like these:

  • 72% of customers will engage only with personalized messages (Wunderkind Audiences, formerly SmarterHQ)
  • 70% of consumers say that how well a company understands their individual needs affects their loyalty (Salesforce)
  • 71% of customers are frustrated by impersonal shopping experiences (Segment)

But what marketers often don’t understand, especially if they’re new to personalization, is that personalization is not an end in itself. Your objective is not to personalize your email campaigns and lifecycle messages. 

Rather, your objective is to enhance your customer’s experience with your brand. Personalization is one method that can do that, but it’s more than just another tactic. 

It is both an art and a science. The science is having the data and automations to create personalized, one-to-one messages at scale. The art is knowing when and how to use it.

We run into trouble when we think of personalization as the goal instead of the means to achieve a goal. In my work consulting with marketers for both business and consumer brands, I find this misunderstanding leads to eight major marketing mistakes – any of which can prevent you from realizing the immense benefits of personalization.

Mistake #1. Operating without an overall personalization strategy

I see this all too often: marketers find themselves overwhelmed by all the choices they face: 

  • Which personalization technologies to use
  • What to do with all the data they have
  • How to use their data and technology effectively
  • Whether their personalization efforts are paying off

This stems from jumping headfirst into personalization without thinking about how to use it to meet customers’ needs or help them solve problems. 

To avoid being overwhelmed with the mechanics of personalization, follow this three-step process:

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  • Start small. If you aren’t using personalization now, don’t try to set up a full-fledged program right away. Instead, look for quick wins – small areas where you can use basic personalized data to begin creating one-to-one messages. That will get you into the swing of things quickly, without significant investment in time and money. Adding personal data to the body of an email is about as basic as you’ll get, but it can be a start.
  • Test each tactic. See whether that new tactic helps or hurts your work toward your goal. Does adding personal data to each message correlate with higher clicks to your landing page, more conversion or whatever success metric you have chosen?
  • Optimize and move on. Use your testing results to improve each tactic. Then, take what you learned to select and add another personalization tactic, such as adding a module of dynamic content to a broadcast (one to everyone) campaign. 

Mistake #2. Not using both overt and covert personalization

Up to now, you might have thought of in specific terms: personalized subject lines, data reflecting specific actions in the email copy, triggered messages that launch when a customer’s behavior matches your automation settings and other “overt” (or visible) personalization tactics.

“Covert” personalization also employs customer preference or behavior data but doesn’t draw attention to it. Instead of sending an abandoned-browse message that says “We noticed you were viewing this item on our website,” you could add a content module in your next campaign that features those browsed items as recommended purchases, without calling attention to their behavior. It’s a great tactic to use to avoid being seen as creepy.

Think back to my opening statement that personalization is both an art and a science. Here, the art of personalization is knowing when to use overt personalization – purchase and shipping confirmations come to mind – and when you want to take a more covert route. 

Mistake #3. Not maximizing lifecycle automations

Lifecycle automations such as onboarding/first-purchase programs, win-back and reactivation campaigns and other programs tied to the customer lifecycle are innately personalized. 

The copy will be highly personal and the timing spot-on because they are based on customer actions (opting in, purchases, downloads) or inactions (not opening emails, not buying for the first time or showing signs of lapsing after purchasing). 

Better yet, these emails launch automatically – you don’t have to create, schedule or send any of these emails because your marketing automation platform does that for you after you set it up. 

You squander these opportunities if you don’t do everything you can to understand your customer lifecycle and then create automated messaging that reaches out to your customers at these crucial points. This can cost you the customers you worked so hard to acquire, along with their revenue potential.

Mistake #4. Not testing effectively or for long-term gain

Testing helps you discover whether your personalization efforts are bearing fruit. But all too often, marketers test only individual elements of a specific campaign – subject lines, calls to action, images versus no images, personalization versus no personalization  – without looking at whether personalization enhances the customer experience in the long term.

How you measure success is a key part of this equation. The metrics you choose must line up with your objectives. That’s one reason I’ve warned marketers for years against relying on the open rate to measure campaign success. A 50% open rate might be fantastic, but if you didn’t make your goal for sales, revenue, downloads or other conversions, you can’t consider your campaign a success.

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As the objective of personalizing is to enhance the customer journey, it makes sense then that customer lifetime value is a valid metric to measure success on.  To measure how effective your personalization use is, use customer lifetime value over a long time period – months, even years – and compare the results with those from a control group, which receives no personalization. Don’t ignore campaign-level results, but log them and view them over time.

(For more detailed information on testing mistakes and how to avoid them, see my MarTech column 7 Common Problems that Derail A/B/N Email Testing Success.)

Mistake #5. Over-segmenting your customer base

Segmentation is a valuable form of personalization, but it’s easy to go too far with it. If you send only highly segmented campaigns, you could be exclude – and end up losing because of failure to contact – many customers who don’t fit your segmentation criteria. That costs you customers, their potential revenue and the data they would have generated to help you better understand your customer base.

You can avoid this problem with a data-guided segmentation plan that you review and test frequently, a set of automated triggers to enhance the customer’s lifecycle and a well-thought-out program of default or catch-all campaigns for subscribers who don’t meet your other criteria. 

Mistake #6. Not including dynamic content in general email campaigns

We usually think of personalized email as messages in which all the content lines up with customer behavior or preference data, whether overt, as in an abandoned-cart message, or covert, where the content is subtly relevant.

That’s one highly sophisticated approach. It incorporates real-time messaging driven by artificial intelligence and complex integrations with your ecommerce or CRM platforms. But a simple dynamic content module can help you achieve a similar result. I call that “serendipity.”  

When you weave this dynamic content into your general message, it can be a pleasant surprise for your customers and make your relevant content stand out even more. 

Let’s say your company is a cruise line. Customer A opens your emails from time to time but hasn’t booked a cruise yet or browsed different tours on your website. Your next email campaign to this customer – and to everyone else on whom you have little or no data – promotes discounted trips to Hawaii, Fiji and the Mediterranean.

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Customer B hasn’t booked a cruise either, but your data tells you she has browsed your Iceland-Denmark-Greenland cruise recently. With a dynamic content module, her email could show her your Hawaii and Mediterranean cruise offers – and a great price on a trip to Iceland, Denmark and Greenland. Fancy that! 

An email like this conveys the impression that your brand offers exactly what your customers are looking for (covert personalization) without the overt approach of an abandoned-browse email.

Mistake #7. Not using a personal tone in your copy

You can personalize your email copy without a single data point, simply by writing as if you were speaking to your customer face to face. Use a warm, human tone of voice, which ideally should reflect your brand voice. Write copy that sounds like a one-to-one conversation instead of a sales pitch. 

This is where my concept of “helpful marketing” comes into play. How does your brand help your customers achieve their own goals, solve their problems or make them understand you know them as people, not just data points?  

Mistake #8. Not personalizing the entire journey

Once again, this is a scenario in which you take a short-sighted view of personalization – “How do I add personalization to this email campaign?” – instead of looking at the long-term gain: “How can I use personalization to enhance my customer’s experience?”

Personalization doesn’t stop when your customer clicks on your email. It should continue on to your landing page and even be reflected in the website content your customer views. Remember, it’s all about enhancing your customer’s experience.

What happens when your customers click on a personalized offer? Does your landing page greet your customers by name? Show the items they clicked? Present copy that reflects their interests, their loyalty program standing or any other data that’s unique to them?  

Personalization is worth the effort

Yes, personalization takes both art and science into account. You need to handle it carefully so your messages come off as helpful and relevant without veering into creepy territory through data overreaches. But this strategic effort pays off when you can use the power of personalized email to reach out, connect with and retain customers – achieving your goal of enhancing the customer experience.

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Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


About The Author

Kath Pay is CEO at Holistic Email Marketing and the author of the award-winning Amazon #1 best-seller “Holistic Email Marketing: A practical philosophy to revolutionise your business and delight your customers.”

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