AiThority Interview with Katrina Wong, VP of Product Marketing & Demand Generation at Segment

Hi, please tell us about your role and the team/technology you handle at Segment?

I am the VP of Marketing at Twilio Segment. In my role I’m focused on overseeing Product Marketing and Demand Generation.

How did you arrive here?

I’ve always loved data. I started my career 20 years ago when websites were first being born. At the time, brick and mortar shops were coming online and the conversation centered around how consumers will buy online.  It was all about analyzing online browsing behavior to better understand and predict buying behavior.  Back then, there was no way to collect the data well.  Fast forward to now, we are still tackling the same challenges and Segment is a leader in what we call customer data platforms (a platform designed from the ground up to track, collect, standardize and analyze customer data). Most of our customers are retailers that are looking to create the best digital customer experience while tying that to mobile, physical stores, etc.

I believe in the problem we are solving and have been passionate about using data to understand buying behavior since the beginning (when online shopping data was first available).

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Tell us more about the roles and responsibilities of a modern Product Marketing Head? How is it different from what you were doing in the pre-covid days?

Product Marketing leads should take their direction from customer feedback to help drive product strategy. The focus is on launching new products for customers that best serve their needs and to make the value proposition consumable for your target audience. Since COVID-19, we’ve seen that everyone’s focus has been on digital acceleration — for the majority of the last year our customers only had the option of engaging with their consumers digitally. We shifted our priorities to put 100% of our best practices, thought leadership and content was focused on digital engagement.

Tell us more about the marketing technology stack that you are using? How much of it has evolved in the lockdown period?

Marketing stacks are big these days and we have a ton of tools in our stack. I think we’ve really focused on instrumentation during the lockdown period. Just like our customers, we too were only engaging with customers digitally so we needed to know what was working and what was not across digital channels. Overnight, it became 100% of our spend.

Most CMOs are aware but not keeping abreast of data breaches and cyber security dangers to their marketing campaigns. How would you respond to cybersecurity challenges?

CMOs are in a unique position to protect consumer data collected through various marketing programs because they see first-hand how that data is used. At Segment, I make sure that I have an open line of communication with the chief information security officer. It’s very important that CMOs have excellent communication with the IT department and are regularly checking in. Working together across departments is an important part of maintaining strong data security in an organization.

Could you tell us more about first party data and how companies are moving away from third-party data?

Delivering accurate and relevant customer experiences is now the expectation, not the exception. 2020 brought about an acceleration of business initiatives to meet consumer demands in a multi-channel, digital world. From introducing new business lines to orchestrating omnichannel campaigns, companies across all industries are overwhelmed by the pressure to know their customer across all touch points to achieve personalization at scale.

If the expectations weren’t already high enough, companies are also up against constantly evolving data privacy initiatives, whether that is legislation like the California Consumer Privacy Act (CCPA) or the European General Data Protection Regulation (GDPR) to the impending death of third-party cookies. If companies don’t take steps to future-proof their technology in light of these public and private privacy initiatives, they’ll be left in the dust. Given the growing shift to privacy and the increasing need to personalize, companies need to adjust their marketing strategies to focus on first-party data. The phasing out of third-party cookies actually presents advertisers with a great opportunity to rebuild consumer trust using first-party data.

What kind of opportunity do first-party data management and analytics provide to marketing teams?

First-party identity resolution, or the ability to stitch all your own customer data into accurate profiles, is key to improving marketing insights, optimizing ad spend, and delivering a flawless customer experience.

Customer data platforms, like Segment, help businesses collect, clean, and control their  first-party customer data. It uses highly advanced identity resolution technology to merge customer activity into a single profile in real time. With identity resolution, you can gather data across all touch points, tie it all to one unique user, and then use that data to provide your customers with a tailored experience.

How can marketers reimagine the fundamentals of customer experience and marketing programs without relying on third-party cookies?

Through using a customer data platform (CDP) with first-party identity resolution at the core, marketers can activate a single view of the customer to deliver relevant messaging and experiences without the need for using third-party cookies or third-party data.

If we look at how customer data has evolved over the past decade, it was first about collecting the right data. Then, as marketing tech stacks grew exponentially, it was about taking action on that data. While both of these are—and will continue to be—critical functions of a CDP, none of it matters if you can’t identify individuals across all of their systems and channels in an accurate and privacy-forward way.

If companies truly want to get that elusive single view of the customer, they instead must look inwards and get a grip on the fundamentals of their data infrastructure and first-party identity resolution. From there, brands can activate on their first-party customer data to drive better business outcomes.

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How does identity resolution enable marketers to deliver the right message, to the right person, in the right channel (without third-party cookies)?

Gartner’s Annual CMO Spend Survey Research 2020 found that the average brand spends 14% of its entire marketing budget just on personalization tactics. However, without identity resolution to stitch together accurate customer profiles in real time, companies waste time and budget managing stale, disconnected user data. As a result, low-quality, poor-performing marketing campaigns eat up valuable marketing budget and miss opportunities to maximize customer lifetime value.

The importance of an identity resolution solution grows with the need to deliver flawless omnichannel experiences, especially as companies introduce new business models and product launches in this digital-first era. With one centralized repository of customer data from all sources, only then can brands orchestrate effective omni channel campaigns based on real-time customer profiles. Whether it’s email, advertising, or even support centers, identity resolution enables lifecycle marketers to deliver the right message, to the right person, at the right place and right time.

The difference between Deterministic and Probabilistic identity resolutions – and how to make sure your marketing strategy prioritizes the correct one?

For many companies, one of the first considerations in identity resolution is leveraging deterministic and probabilistic methodologies. Deterministic identity resolution is a high-confidence approach that uses first-party data, where you know with certainty the user’s behavior and data points. It merges identifiers like phone numbers, emails, device IDs, and user IDs that you have collected from the user.

Probabilistic identity resolution uses what you predict to be true. Using predictive algorithms and/or third-party databases, it attempts to merge disparate identifiers to piece together a single view of the customer. Using a statistical model, a probabilistic approach creates a user profile within the bounds of a given confidence interval. With probabilistic identity resolution, stitching across devices is commonly accomplished implicitly through fingerprinting, IP matching, and other methods that customers have no way of knowing they’re a part of, let alone opting out of.

In fact, the EUs General Data Protection Regulation (GDPR) already prohibits companies from taking advantage of probabilistic identity resolution. While the GDPR may seem like the most strict form of privacy regulations today, countries and technology companies around the world are taking action to be more respectful of consumer privacy. For example, Apple’s latest iOS 14 release includes a new privacy feature called App Tracking Transparency (ATT). With this feature, users are given more control over which apps can track them across sites and apps for advertising. As operating systems and browsers release more privacy features, and more users choose to opt out of tracking, the value of a probabilistic strategy will continue to decrease. At Segment, our identity resolution approach is 100% deterministic. Not only does it result in more accurate, relevant customer data, but it’s also based on high-quality, first-party data that your customers actually produce and consent to.

Hear it from the Pro: Who owns the Customer Experience management success / failures?

Customer experience is a team effort — from the developers all the way to the CMO who manages strategy and implementation. Customer experience successes should be celebrated as a team, and when mistakes are made, it can serve as an opportunity for leadership to learn and improve.

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What are the biggest barriers in the adoption of CX management models for a modern data-driven company?

Before companies can adopt a CX model that will set them apart in a competitive market, they must take a step back and ensure they have the foundational data architecture needed to create cutting-edge, personalized customer experiences.

The fundamental building block of a strong data infrastructure is having a complete, clean and reliable data set that is easily accessible and ready for activation. This is the key to better understanding your customers, providing them with the information, products and services they care about, and retaining their business long term.

Thank you, Wong! That was fun and we hope to see you back on AiThority.com soon.