Using First-Party Data in Email and Beyond | Blueshift

Using First-Party Data in Email and Beyond

With the demise of the third-party cookies and IDFA, marketers will have to lean more heavily on their first-party data and the channels that are closest to their known customer base.

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Speakers:

Welcome and Introduction

Marina Ben-Zvi: Welcome, everyone! We're excited to have you here as we dive into first-party data and how to use it to improve engagement across your channels, email and beyond.

I'm Marina Ben-Zvi, Director of Product Marketing at Blueshift. We're a leading Smart Hub CDP that helps marketers deepen customer engagement by delivering more relevant, timely, and connected interactions through unified customer data, AI, and omnichannel orchestration.

Joining me today is April Mullen, Director of Brand and Content Marketing at SparkPost. Welcome, April!

April Mullen: Yeah, thanks for having me.

Marina Ben-Zvi: We have a great discussion for everyone today about how to use first-party data to gain a competitive edge. With related data restrictions, first-party data is definitely having its moment in the spotlight. It has become a priority for marketers across industries.

Today, we'll dive into:

We'll also be leaving the last five to ten minutes or so for Q&A. Please add your questions in the chat anytime throughout the webinar, and we'll answer them at the end. With that, April, let's start with understanding why first-party data has become so topical.

Why is First-Party Data So Topical?

April Mullen: Yes. First, I want to talk about the difference between first- and third-party data. Many of you probably know the difference, but sometimes people don't, so it's important to clarify.

First-Party Data vs. Third-Party Data

First-party data is still very strong. This isn't the demise of all first-party data, but it's definitely the first foray into first-party data being impacted by this new trend in privacy.

The End of the Advertising Industrial Complex

April Mullen: What I think is happening, and I'm a little dramatic in my description, but I do think that we were in this state of having an advertising industrial complex, and I believe that's definitely coming to an end. The biggest drivers are the third-party cookies going away and IDFA.

Marketing has long been addicted to the notion of targeting users with third-party cookies and spending a lot of money on advertising, assuming customers would just come. A big part of that is because CMO tenure is typically very short, and CMOs have to prove value very quickly. As a result, quick hits for proving value became prioritized.

However, that's not how marketing is going to work going forward. Marketing should have always been a long game, and now it's forcing us into that long game. The idea of the advertising team not talking to the retention team, and different people managing different channels without talking or tapping the same data pool – those days are over. We're going to have to play a much longer game.

The Changing Marketing Equation

April Mullen: The critical equation for marketing has long been that the cost to acquire customers (CAC) should be lower than the lifetime value (LTV) you're driving. But working with marketers for years, and being one myself, I've seen that LTV is often difficult to track if it's not a direct, easily trackable transaction (like in retail).

What's happened is that companies have traditionally spent a ton of money to acquire customers. Once customers convert from third-party data to first-party data, instead of investing enough in cost-effective channels that work well with first-party data (like email, SMS, app downloads, push notifications), companies continue to pay to acquire these customers all over again.

I think this equation is going to start to balance the way we need it to be, with LTV increasing as a result of all these data changes. Marketing as we know it is definitely going to change. I'm very interested to talk to CMOs and find out how they're thinking about all of this, because the marketing landscape is definitely changing. Some of the "breadcrumbs of data exhaust" we've had for years are being pulled back, and we have to figure out what to do with it.

What we know:

We're going to have to strengthen that value exchange. When someone comes to our website or is exposed to our brand, how do we show them that really great experiences await them on the other side of giving their data and permission to reach them? I think that needs to be our ultimate goal. It's also stressful because it's not an easy problem you can pay to make go away; it requires humans speaking to humans. Strengthening that value exchange upfront and then continuously reinforcing it once they've given you their data is what I think we'll have to do going forward.

Marina Ben-Zvi: You know, it's a really interesting point about the value exchange because brands are being squeezed from two sides:

So why would someone actually want to share their data with your brand or engage on your brand properties? It's because you provide value in exchange for their data. Relationships are very much give and get. You provide value. Make every interaction enjoyable, make it personally relevant. And consumers will gladly share their data in exchange for that. In fact, a recent study found that 76% of consumers will actually share data if they see that they're receiving certain benefits or enriched experiences.

Building a Strong First-Party Data Foundation

Marina Ben-Zvi: We all know that first-party data is important. Now, how do you actually build those strong first-party data foundations? First, let's pause and just reflect on why we actually want to use our first-party data. What are we ultimately trying to accomplish with it?

It's about:

Think about the kinds of experiences you want from brands and the kind of experiences that you actually reward with your share of wallet. You want experiences that are:

Most importantly, you want them to be relevant to you and what you seek in that moment. Batch and blast, one-size-fits-all experiences no longer work; that can no longer be the status quo. But delivering those kinds of experiences requires a really deep, nuanced, and real-time customer understanding, which requires access to the right data. Not only that, you also need the ability to actually mobilize that data across your channels.

The good news is that first-party data is readily available. Customers are generating a growing number of data points through their online interactions with your brand, as well as their offline behaviors, which are also increasingly trackable. Most likely, your company is actually sitting on a lot of first-party data. The challenge is actually, how do you harness and act on it? And most companies actually lack that first-party data strategy to do so.

There are two key components to an effective data strategy:

  1. You need to actually centralize your data from across your channels to create that complete view of your customers.
  2. More importantly, you need to actually have the tools to translate that data into better, more connected customer experiences.

Where to Begin Data Collection

Marina Ben-Zvi: Starting with centralizing your data, where do you begin? What data should you be collecting to build your first-party data strategy?

Begin by thinking about what insight you need to improve your customers' experiences. You need to understand:

For the most part, the exact data points will vary from brand to brand, but in general, the data you need falls into the following buckets:

Really think about what's important to your business.

Finding and Unifying Your Data

Marina Ben-Zvi: Now comes the part of where do you actually find this data? If you haven't already, definitely start by putting a tracking pixel across your brand properties. Then, identify the systems across your organization that have been collecting and housing customer data.

Numerous places where your desired data will be found, and it's likely already lived throughout your organization, including:

There's a variety of systems you might want to integrate. But most importantly, make a point to gather data from across your channels, both online and offline, so you can have a richer view of the full customer journey. Because the ultimate goal is really to get a comprehensive understanding of your customers, their past and current interactions from across channels. The deeper your customer understanding, the better you can tailor your experiences.

Now you might be thinking, well, how do you actually unify all this data into a central place and then make it actionable? Well, that requires a Customer Data Platform (CDP), which unifies all your data into persistent 360-degree customer profiles. Specifically, look for a Smart Hub CDP, which can then take your data to the next level by:

Putting Unified Data to Use: Driving Engagement

Marina Ben-Zvi: Now that you have your unified customer data, it's time to actually put it to use across your channels to create those multi-touch connected experiences. This starts with developing a deep customer understanding and extracting actionable insights.

From your first-party data that you've centralized, and overlaying your product and content data on top of that, you want to start understanding things like:

Really start mapping that out and what that looks like across your ideal customer journey.

Automating Personalized Experiences

Marina Ben-Zvi: Pulling all those insights together in a central platform that, in addition to unified customer data, offers predictive intelligence and omnichannel orchestration, you can actually start creating and automating personalized experiences and have those experiences adapt to each customer.

Powered by your first-party data, you can ensure that:

You can really start to optimize various customer experiences, whether it's your onboarding flow for specific customer segments or your re-engagement/churn prevention strategies. There are limitless options depending on the types of experiences you're trying to create and what will actually add value to your customers.

Start with one objective, then test, learn, and optimize. What you'll find is that first-party data-driven marketing and engagement truly drive results.

The Impact of First-Party Data

Marina Ben-Zvi: A BCG study found that first-party data-driven marketing doubles revenue and also significantly reduces costs. Blueshift research has found that using first-party data increases email effectiveness by 500% over batch and blast approaches. And 84% of customers will spend more when they have a personalized experience.

That's why we're now seeing companies like CPG brands that have traditionally sold through retail and channel partners (and haven't actually owned first-party data) investing in capturing more and more first-party data by creating apps or experiences to engage customers and testing out direct-to-consumer models, because there's just so much value in first-party data.

Real-World Examples of First-Party Data in Action

Marina Ben-Zvi: April, curious, what have you seen with SparkPost customers?

April Mullen: Yeah, this isn't a SparkPost customer, but I would love for them to be a customer. This was an email that really stopped me in my tracks. This is a company, one of those smaller companies that has popped up within the last couple of years, focusing on skincare and different healthcare needs. There's a "hers" and then there's a "him's," which is a cool brand strategy.

I love this communication because it uses that first-party data in a really good way. It's taking essentially the transaction date, adding days to it. Here, it's showing the person is at day 14 after purchasing a specific product for acne. I love this so much because I think this is the perfect example of taking a data point, a first-party data point (email address, transaction date, product purchased, and known problems with that product), and setting a cadence to use that data to engage someone, or even to say, "Trust the process, hang in there." It's super empathetic, super human. It tells them that right now, their skin isn't going to be good, it might be flaky, but to hang in there, and it's going to get better. It even shows a slider bar, so I can anticipate that as I progress through this journey with the "hers" product, it is going to get better, that there is a plan for me. Love this example. Would love to see more of this in email and other channels.

Marina Ben-Zvi: You're going to see more of this. It really shows that they know their readers. So it's not just about "come and read our paper, buy the subscription," but they're actually showing you that they know this information about you. They're telling you that because of the number of articles you've read, this is where you rank in terms of other LA Times readers. At the end of the day, your customers love themselves, so seeing data like this, exposing data like this, is just super entertaining and interesting. Why not? So use that data and explicitly show them what you have on them, not just to sell things, but also to entertain them. I think these are the kind of experiences people want.

Here's another example from the B2B world: Zapier. They created a milestone email celebrating that somebody created their first app. They have a video that's personalized to the apps integrated, showing other apps you can integrate and exploring templates. It also explicitly tells you actions of what you can do next. I kind of like these communications that follow the customer and cheer them on along the way, like a coach on the sidelines. Data can be used to absolutely drive those experiences.

Here's another example. This is a SparkPost customer, LinkedIn, talking about goals. You can put in a goal of what you want to do with LinkedIn Learning, and they'll actually track it for you. They'll reach out to you on a weekly basis and tell you where you're at with your goal, congratulate you, and tell you how many minutes you've spent and what courses you've completed. I think this is a brilliant way to keep people motivated and engaged with your brand.

And last but not least, CareerBuilder, a great customer of SparkPost. They have a super complex ecosystem. Sites promoting jobs have done a really good job of taking all those data points of different activities, actions, preferences, and behaviors to send communications that drive the next steps.

This is an example of when someone has submitted an application for a job. Instead of being like, "Okay, they've applied for a job, there's activity there, we've done our job," they go, "No, there are actually more jobs that are similar to the job you just applied for in the city in which you are looking for work." They send this job recommendations email. And it's like, "Apply now." When you tap these buttons, it actually, in real-time, will do an easy apply for some of these jobs. If you're somebody searching for a job, you're either already in a job and unhappy (so you don't have time to do the job search as your second job), or you're out of a job and urgently trying to get another one. I love what they've put into this and how they've made it super easy. It's really harnessing the power of all that data they have to get to the end goal for the customer, which in this case, is a job candidate looking to be hired.

Marina Ben-Zvi: I love all these examples. At Blueshift, we've definitely seen customers across industries and company sizes produce outsized results by using their first-party data in really interesting ways.

For example:

There are limitless ways that marketers can use first-party data to improve customer experiences and engagement strategies. One thing is clear: if you're like most brands, you're probably not harnessing your first-party data to its fullest potential, but it's definitely time that you start before your customers buy from your competitor and not you.

Q&A Session

Marina Ben-Zvi: With that, I'd love to see if there are any webinar attendee questions. The first question is: "Collecting and using first-party data is important. Where do I start?" This is a great question that many people have.

Where to Start with First-Party Data

Marina Ben-Zvi: To start, think of it in two ways. First, marketing is only as effective as the tech that powers it. So you very much need a unified system like a Smart Hub CDP that can both unify your data and has those omnichannel orchestration and real-time decision capabilities to actually put that data into use.

Beyond that, from a strategy standpoint, really start small with a single objective or experience that you're trying to optimize. For example, is it an onboarding flow or a welcome series? Test a few approaches based on the insights you discovered in your customer data and what you think will really add value to your customers. Then, test, learn, and iterate. Once you're in a good place there, maybe expand that program, and then you can move on to the next objective. Definitely don't try to boil the ocean immediately.

Marina Ben-Zvi: I received a question that says, "Will Apple mess with clickable tracking that identifies the user with a guide type query string?" From a deliverability standpoint, I'm not really sure. But let me actually drop into the chat a blog post I wrote yesterday on this open tracking impact that was announced by Apple. I will get this question answered and I will actually add it to the FAQs in that blog post by end of day today.

Marina Ben-Zvi: Next question is: "How do you use first-party data for things like paid media with cookies going away?" I love this question as well.

First-Party Data for Paid Media

Marina Ben-Zvi: The use of first-party data for digital targeting and paid media advertising use cases has actually been growing for a number of years now. Not only to produce that seed list for look-alike targeting, but other use cases as well:

Paid media is also a really great way to re-engage inactive users, and also do cross-sell and upsell campaigns. All of that obviously requires a lot of first-party data and being able to sync the data from your platform (where you centralize those profiles) to the right media properties.

April Mullen: I have nothing to add on that. That was a fantastic answer.

Closing Remarks

Marina Ben-Zvi: Okay. Well, I think that we are actually at time or post time. This has been really great. April, thank you so much for sharing your insights and the examples you provided were amazing. I want to thank the audience for joining us today. And have a great day, everyone.