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Data, Identity Graph, Identity Resolution

Why Identity Should Be at The Forefront of Your 2020 Marketing ‘Resolutions’

It is no secret that identity has become a fundamental component of the digital ecosystem. The increasing volume of consumer data and sheer number of devices and channels in-market, coupled with privacy-first policies like GDPR and CCPA, has created increased demand for identity resolution.  Though identity resolution brings much promise, with it also comes many challenges.

As the number of touchpoints grow and become more complex, so will the challenges for marketers as they attempt to collect, analyze and build a unified customer profile. A study on the state of identity resolution strategies in marketing conducted by Forrester Consulting reveals that less than half of marketers are fully capable of identity resolution management.

If marketers plan to be grow and continue their success into the upcoming year, identity resolution needs to be at the forefront of their strategies. Below, we highlight some of the most important benefits of identity resolution for marketers:

Effective Personalization: If you don’t know with confidence who the customer is, you can’t personalize your messages or experiences to them. That, in turn, lowers the quality (and probably the duration) of your relationship with that individual. With trusted identity resolution, marketers can obtain an in-depth understanding of their customers, ensuring that the right message gets delivered to the right customer, on their preferred channel and device.

Better Customer Insights: Identity resolution helps marketers better understand who’s on the other end of a browser, mobile app, CTV, or IP address.  Accurate identity resolution allows companies to create a true single view of their customers that can be consistently communicated and deployed across brands, business units, and product lines. You should be able to continuously enrich, update, and share identity data across your entire organization in order to facilitate greater control and personalization.

Privacy Compliant Identity: Well-executed identity resolution embraces industry best practices and principles that ensure data is harnessed in ways that are ethical, compliant, and privacy safe. In the wake of GDPR, CCPA and others to soon follow, identity resolution ensures secure data transfer and encrypted storage, data processing controls and access restrictions as well as regulatory compliance.

Data and Consumer Accuracy: To properly execute 1:1 marketing, the data and methodology you use to identify customers on a truly individual basis must be accurate. If it isn’t, you’ll risk sending the wrong messages to customers at the wrong time. Identity resolution provides a constant stream of data to dynamically validate customers as they interact in offline and online channels. Accuracy data is vital to the success of personalization efforts.

Ultimately, identity resolution is a must have, not a nice-to-have for 2020 and beyond.  To remain competitive in the age of the empowered, connected consumer, marketers must be able to connect customer data into a cohesive whole. Those who leverage identity resolution will be able to provide a seamless customer experience that is consistent and personalized across channels, creating increased engagement and relevant interactions that improve loyalty, thus ensuring long-term success.


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Data, Identity Graph, Identity Resolution

Identity Resolution and Why It Matters: Q&A with Throtle CEO, Paul Chachko

Understanding who and where your customers are across all screens and channels is no easy task. Identity resolution creates a valuable asset for brands. However, the explosion of devices and touch points, combined with siloed or inaccessible data, has left most brands with only a fragmented view of their customers.

We sat down with Paul Chachko, founder and CEO of Throtle, to get his take on the importance of identity resolution and the advice he has for brands.


How do you define identity resolution?
At Throtle, we define identity resolution as the continuous mapping of disparate consumer data accurately associated with a single individual.

As the industry is starting to realize, an accurate identity resolution strategy is critical to the success of every marketing campaign executed today. It not only fuels customer experiences, but it allows brands the ability to create and build richer customer profiles overall. With the ability to view the entire picture surrounding one individual customer, their buying behaviors, demographic and geographic data, a brand can create more tailored marketing messages and campaigns that drive loyalty, engagement, and success.

In your words explain why brands need identity resolution?
Today, consumers own an estimated 3-4 different devices, and use these devices in different ways to research, browse, view and purchase products.

Without identity resolution, brands can’t associate and understand a customer from one device to another leaving them with a very fragmented view of the consumer. Identity resolution is the process by which a firm collects all of these various identifiers across all devices and touchpoints and unifies them into one holistic view of the individual behind them and makes them available for targeting.

As an identity resolution provider, how do you keep up with the industry and the ever-changing consumer?
Throtle continues to heavily invest in not only our underlying data technology, but also in sourcing the most accurate and rich data currently available in market. We are constantly looking to expand our network of like-minded data and media partners that are leaders in their spaces and are very tech forward. Accuracy is one of the most crucial data elements of identity resolution, and unfortunately, we see this lacking most in current data practices. If you don’t have a constant stream of integrated multi-sourced customer data such as email addresses, MAIDs, cookies, etc., then you will fail to have accurate identifiers to validate individual customers on a deterministic basis.

For brands looking at identity resolution providers, what advice do you have for them?
First and foremost, ask if their identity graph is deterministic or probabilistic. Deterministic matching is the gold standard. It is important to understand that what some companies call “deterministic” matching, really isn’t. Some think that if they find a single 1:1 match between two data points that it’s a confirmed deterministic pairing. Others, including Throtle, hold themselves to a much higher standard of quality and accuracy that requires multi-source corroboration of all data before declaring that a match is deterministic.

I would also suggest having identity providers explain the logic behind their match rate. A match rate depends heavily on a steady flow of multi-source data that is accurate and validated. At Throtle, we view the match rate as our ability to match to a unique individual rather than unique cookies or device IDs. If we match to John Doe and we see he has 3 devices, we count him as (1) unique match because all 3 devices belong to one unique individual. Other providers count each device or cookie match as a unique match regardless if they belong to the same (1) unique individual. As such, match rates are often inflated and do not accurately depict the match rate against unique individuals in a client’s file. We always advise to ask for apples-to-apples data from all partners you are evaluating so that you can be sure that match rate definitions and calculations are consistent across partners.

Finally, the best identity resolution vendors deploy a variety of “data hygiene” steps such as email validation, de-duplication, National Change of Address (NCOA), etc. to ensure a customer’s data is at the highest level of fidelity PRIOR to match to allow for the highest possible match rate. Lastly, we always recommended a data match test before any contracts are signed. It’s important that both sides understand the depth and wealth of the data and how it might or might not perform prior to entering into a partnership.

Do you see a threat with the upcoming California Consumer Privacy Act (CCPA) going into effect in January and identity resolution?
I don’t see a threat at all. In fact, I see this as an opportunity that continually validates identity resolution providers like Throtle, and the steps that we take in championing accurate, privacy compliant, transparent data. CCPA will showcase the ability for a provider to deliver transparency and ensure CCPA privacy compliance. This includes the ability to apply a high level of data protection and security in relation to personal data that our clients and third parties entrust to us.

Data, Data Onboarding

Ad Exchanger Article – Mo’ Match Rates Mo’ Problems

Mo’ Match Rates Mo’ Problems As Cross-Device Vendors Aim For Scale – by James Hercher // Monday, October 10th, 2016

Cross-device identity match rates have shot up in recent years, but brands and agencies remain skeptical of the results.

“We were consistently disappointed with cross-device identity matches,” said David Kohl, CEO of the digital media advisory firm Morgan Digital Ventures. “There’s a gap in understanding of what’s possible between vendors and the buy side, [which leads to] frustration (on both sides) over unclear expectations or results.”

Some point to industry consolidation as the driver behind rising match rates. But as many cross-device vendors increasingly deploy probabilistic matching to manufacture scale, aggregated data is added and verifiable identities are sacrificed.

“This approach can present challenges for advertisers who may want to run verification, as there is no reliable way to measure accuracy of the match,” said Keith Johnson, EVP of strategic data solutions at Wunderman.

An agency can use a client’s CRM data or other owned personally identifiable information (PII) to verify identities if a person is served an ad to his or her phone or desktop and then visits the client’s site and logs in, makes a purchase or provides PII in some way. It’s a messy, laborious process.

“Although many clients like the idea that they can run these tests, in reality it very rarely happens today,” Johnson said.

There is no industry norm or consensus on what is a “good” match rate because they deliberately vary by type of campaign, brand industry category or first-party data used.

Say a brand wants its attribution provider to connect people who were exposed to TV and digital ads with retail foot traffic via a location analytics vendor. Stringent attribution requirements would call for a highly deterministic data set and a match rate greater than 90%, said Auren Hoffman, the former CEO of LiveRamp who now helms a startup called SafeGraph.

An automotive marketer more concerned with long-term exposure frequency and greater reach, however, may be happy with a more probabilistic set matching 30% to 40%.

This is why straightforward questions like “What are your match rates?” can be counterproductive.

Marketers are frustrated, but it’s a frustration born of optimism, said Kate Clough, a media-planning VP at MRM//McCann.

“It used to be that (cross-device) plans were breaking down in the execution. Now we see the opportunity to provide those connected experiences, but it can be pretty daunting because buyers and sellers speak very different languages,” she said.

Morgan Digital Ventures and MRM//McCann are pilot partners in an initiative launched recently by the DMA to standardize cross-device RFP templates and establish the basics with a glossary of industry jargon. Terminology can have different meaning for marketers and cross-device vendors, and it leads to confusion over results.

For example, marketers may use the words “accuracy” and “precision” interchangeably, but those are discrete terms in the cross-device space. “Accuracy” is the percentage of correctly identified matches plus correctly identified non-matches – so a campaign with a low match rate could actually have high accuracy. “Precision” is the percentage of all possible matches correctly identified by the vendor.

“Recall” is a media-buying metric to judge an ad’s impact on consumers, but a cross-device vendor considers recall to be the percentage of overall identified matches divided by all known true matches.

“Agencies typically have a clear idea of how they’d like match rates to be calculated, but if there’s any ambiguity in their guidance to the supplier the results can be inflated,” Clough said. “Are you talking about matched devices or unique individuals? In some cases it seemed accidental, but it left people vulnerable to potential manipulation.”

Michael Schoen, VP of marketing services at Neustar, was less charitable about some linkage claims: “As with everything in ad tech, where there’s a financial incentive, there’s fraud.”

It’s now common for a third-party measurement firm like comScore to verify cross-device graph results when they’re applied in advertising, said Yael Avidan, VP of product at the mobile DSP Adelphic.

Even with verification, some marketers still aren’t convinced the results are accurate.

“If I see match results I don’t like – they seem too high maybe or I’m just not confident what I’m seeing is correct – comScore verification isn’t going to change that,” said one major toy brand marketer who said she couldn’t comment publicly due to NDAs with multiple data-matching vendors.

Much of the overall confusion over match rates is due to a lack of vendor transparency, said LiveRamp Chief Product Officer Anneka Gupta.

“There are lots of people out there saying they do deterministic matching, but you have to be careful about what’s being layered into the data,” Gupta said.

Many cross-device vendors and data aggregators regularly pay publishers to help them connect a customer’s data to web traffic or email sign-ups. The inconsistencies plaguing publisher data monetization – bot farms juicing numbers with fake emails or actual people using throwaway addresses on non-billing accounts – can be passed on to device graphs.

To shake buy-side concerns about finding quality data at scale, some firms are “moving toward a shared, authoritative match set,” said Jay Stocki, SVP of data and product at Experian.

Stocki alluded to Experian’s partnership with Neustar. The two longstanding titans in cross-channel identification began selling a shared profile-matching product earlier this year.

Acxiom, another legacy giant, pursued a similar goal when it purchased LiveRamp in 2014. The European telco Telenor and Oracle each bought a cross-device ID firm this year (Tapad and Crosswise, respectively).

Executives from Acxiom/LiveRamp, Oracle and Experian/Neustar each attributed a steep growth in match rates over the past two years to industry consolidation and cooperation.

Clough anticipates more consolidation as the wider ecosystem seeks enough shared scale to mollify marketers and offset the advantages enjoyed by Google, Facebook and Amazon, all of which have their own proprietary cross-device data.

“[Cross-device vendors] are willing to work with a variety of partners,” Clough said, “because that’s actually the only way for them to differentiate.”

Article page here.

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