Data drives the marketing industry. From a marketer’s perspective, data is time; data is money. Marketing dollars are trustingly thrown at data to build campaign strategies and targeted advertising across all marketing channels.

Despite the time, money and sophisticated technology shifting towards data mining, many marketers still can’t determine proper attribution across channels in a way that accurately measures their brand’s lift and consumer experience. At the root of this is a persistent lack complacency when it comes to properly matching data to an actual consumer in a way that allows advertisers to reach them with relevant and appropriately timed messages.

Unfortunately, for the most part, data targeting has been focused on scale over accuracy, resulting in an upside down model that benefits everyone but the advertiser. The result – the digital data and identity matching industry gets a bad rep by marketers for high cost and low returns. For consumers, the experience is forgettable at best and, at worst, full of skepticism about the source and quality of data fueling targeted ads. The problem is the glut of low fidelity data that has flooded the marketplace over the past decade in both identity resolution across device and data insights. Yet, advertiser priorities have not changed while accuracy is being scrutinized, verified and measured in more ways than ever before.

Today, accuracy in identity resolution and data targeting is a requirement for all marketers. But all this technology has focused so heavily on proxies rather than delivering individual-level targeting, because resolving to the right individual, onboarding data correctly and serving the right consumer relevant ads is not an easy proposition.

Here’s How Throtle Does it Differently

Identify Sources and Context
One key to building robust, accurate data is to know where the data comes from, including its timeliness and its context. Keep in mind the demographic and other online/offline behaviors, not just transactional data in a single moment in time. For example, we all shop for gifts, whether or not they are personally relevant to us. A consumer may at one point have shopped for a baby gift for an expectant friend. Five months later, that consumer has ended up on a mailing list for baby formula and incessantly receives free samples in the mail, although the consumer in point is not a mother nor expecting in the near future. You can see where the discrepancy lies and why knowing the source and context makes this data all the more accurate.

A Fully Deterministic Approach
Marketers must have a deterministic understanding and approach to their data to ensure accuracy. This means ensuring that a single consumer is accurately matched, with definitive proof, to an organization’s corresponding first-party data. This approach ensures that the person is a single user and not generalized under a household or group of consumers. Measuring every interaction across devices can be challenging, but attribute something to the right person and you can identify trends and patterns across all marketing channels. Without accuracy and deterministic matching at the individual level, cross-device attribution is impossible to obtain.

The Identity Graph
Creating this deterministic approach is easily accomplished through a consumer identity graph. An identity graph ensures that all first-party and third-party identifiers for a single consumer reside and are resolved in one place. This is imperative for marketers who want to accurately read consumer behavior and interactions across multiple touchpoints. If you look at everything separately, the picture is hazy and the 360 degree view of a consumer’s core identifiers are lost.

The Results of This Complexity

CONSUMERS: They want to see relevant, harmonized experiences across content. There will be those that complain that after browsing online for new living room furniture, they see cross-device ads from multiple couch vendors for the next three weeks. However, in a world where customer experience is the majority of the battle (according to Gartner and 89% of marketers), when a consumer experience is accurate and relevant, a brand elevates itself above the competition.

ADVERTISERS: Highly accurate targeting is required to reach the same consumer on different channels and devices. Targeting, attribution and defendable measurement can’t happen using inaccurate data; campaigns will produce better ROI because a marketer is able to determine which specific activities are producing the best results

Our Commitment
In short, many of the old approaches to collecting accurate data no longer work. Ad and MarTech companies should be held to a higher standard and greater level transparency when it comes to the data that they source and provide.

Throtle is a 2nd generation data onboarding company focused on deterministic matching, identity resolution, and closed loop enablement. Our data centric onboarding approach guarantees the highest level of accuracy, scale, and responsiveness for our clients.

Identity has become a fundamental component of the digital ecosystem. The more brands understand about their customers and what channels and devices they use, the more effectively they can connect with them.

Everyday, individuals switch between multiple screens (smartphones, laptops, tablets). Trying to understand the individual behind the ever-changing screen through multiple data points is critical for marketing success and the reason why creating a single view of that individual has never been more important. It’s time to look at the consumer holistically from every angle, rather than in silos.

What is an identity graph?

An identity graph allows brands to connect and unify all the known identifiers that correlate with an individual customer.

Each customer has multiple personal identifiers — email addresses, postal addresses, mobile numbers, mobile ad identifiers (MAIDs), logins, usernames, and cookies from web browsing. The identity graph collects these personal identifiers and connects them to an individual profile, which ‘lives’ in the identity graph, along with other types of data, such as demographic, behavioral, lifestyle and purchase data.

What is the Throtle Identity Graph and why do I need it?
The Throtle Identity Graph utilizes a deterministic data matching methodology to absorb cross-channel and cross-device customer information (such as anonymized log-in data or hashed email addresses) to pinpoint an individual identity. Throtle uses this data to locate individuals on whatever device they may be using.

Throtle’s Identity Graph then creates the opportunity for marketers to produce relevant messaging for customers as they switch between various devices. For example, an individual interested in booking a vacation might browse a hotel’s website using their laptop and then again on their mobile device. The hotel’s marketing team can use the data from Throtle’s Identity Graph and onboarding process to ensure a personalized and targeted ad appears as that customer switches devices. This results in a higher conversion rate and more optimized budgets.

When we look at how the advertising industry has changed over the last five years, it’s astounding to see how digital snuck up and rewrote the rules of engagement. Instead of making assumptions, digital forced advertisers to have a more accurate and deterministic understanding of a consumer’s identity to ensure true personalization.

In her annual Internet Trends Report, Mary Meeker painted an eye opening picture of what advertisers are dealing with when it comes to digital. Meeker noted that the amount of time adults spent with digital media in 2016 grew significantly over the past year, with average time increasing to 5.6 hours a day.

As the number of devices and time spent on digital platforms grows, the advertising industry is recognizing that the identity behind those devices is more important than ever. Knowing specific details about the physical being that sits behind something as abstract as pixel or cookie is essential to targeted, meaningful and genuine delivery of ads. Now, everyone is running as fast as they can to get to the point of understanding who those people are before grouping them into segments, showing them advertisements that aren’t relevant and sending consumers running for the adblock button.

Identifying Devices Over People
Amidst all the scrambling, most advertisers are still using probabilistic methods to determine who they think that customer is behind the screen. To do so, they start by looking at, from a device perspective — where that device is resting over time, where that device going, what traffic is coming from that device, what apps are being used, etc. Herein lies the problem.

However, more often than not, those device attributes don’t have a valid email associated with that particular assumed individual. There could be an email tied to that device, but who is validating it?

Artificial Identity Management
In an attempt to validate, digital advertisers have also turned to artificial intelligence. According to Juniper Research, “machine-learning algorithms used to enable more efficient ad bids over real-time bidding networks will generate $42 billion in annual ad spend by 2021, up from an estimated $3.5 billion in 2016.”

While AI has its benefits — it has certainly improved accuracy in analyzing consumer behavior and enabling real-time campaign optimization — the true extent of AI’s capabilities is identifying and learning about an individual on a persistent basis. When analyzing data, outside of other response information obtained, it’s hard to determine the true identity of the person associated with that response. AI can show that an ID is aligned with a particular device and activities on that device over a given period of time, but AI alone can’t determine the WHO. Yes, the data says there is a person there, but who are they really? And with so much data from so many different devices flying around, how are brands supposed to take that data and use it efficiently to gain a deterministic understanding of their customers?

Personalization Lies In Accuracy
We already know that when US internet users receive personally relevant content from brands, it increases their purchase intent. But there must first be an association between various touch points on an individual on a deterministic basis to help advertisers create the level of personalization that consumers so deeply desire. Because in the end, it all comes down to creating meaningful connections with customers by meeting the needs and wants of each unique individual.

Since this level of personalization all circles back to the accuracy of a consumer’s identity, it’s imperative to start by connecting the dots between siloed data points and understanding who that person is. Furthermore, advertisers should look beyond the device level. This is where most advertisers end up getting stuck. Without drilling down past the device or the pixel, advertisers are missing core demographics, psychographics and lifestyle attributes that give us deep insights into these individuals — that personalization is completely lost.

So how can brands fix this? Simple — by bringing into a consumer ID graph authenticated email addresses that are associated down to an individual and matching them to existing data to create a connecting point. This same sequence can then be applied to mobile numbers, IP addresses, social handles, physical addresses — wherever a connector can be found. Now an advertiser has a single individual at the center of each record that is tied to multiple connectors or types of attributes, which provides a more robust picture of who that person truly is. Once you know all of this, you can associate it with a persistent ID at the individual and household level. This allows advertisers to track consumer behavior across any website or location when an ad is presented to that customer. Talk about accuracy and personalization! A win-win for both the advertiser and the consumer.

In the end, we believe that all advertisers should be digging down to the core level of understanding deeply who a person is and then CONFIRMING through multiple instances that that person does indeed belong to a specific record. There aren’t many, if any, that are using a truth set to do that. But we’re here to help initiate that change in the industry and reinstate accuracy and personalization in the world that digital ever so slyly created.