Understand the different types of data, the differences between them, and what zero-, first-party, and multimodal data can do for your business.
Third-party data is dead. But from its ashes, zero- and first-party data have risen.
Many privacy and regulation shifts started the decline of third-party data, but Apple’s iOS 14.5 was the final nail in the coffin. With this update, Apple turned off tracking by default — the first time a smartphone company had done so. Given Apple’s standing as a tech giant, this change forced the entire industry to follow its lead.
Apple’s new policy now dictates that companies need the explicit consent of users to track clicks, downloads, and purchases on mobile apps. Apple also pre-emptively said that trackers can’t use alternative identifiers to track people instead.
That’s why zero- and first-party data have replaced third-party data. These data types operate on explicit consent and personal customer relationships rather than incognito tracking. Companies that succeed in harnessing the power of zero- and first-party data will find that it produces far more accurate and reliable results than third-party data ever did.
What are the different types of data?
Different organizations acquire customer data in ways ranging from covert to consensual. This data is typically categorized based on how the data is collected:
- Third-party data
- Second-party data
- First-party data
- Zero-party data
- Multimodal data
Let’s compare the main aspects of these data types:
Multimodal data is a new and different beast. It’s data on all of the human senses, including audio, video, and click-stream data. It uses Multimodal AI to analyze that data and create a holistic understanding of your customers.
What is third-party data?
Third-party data, or 3P data, is collected by companies without permission from users and then sold to others. These companies don’t interact directly with customers. If you’re still using this, it’s time to change your marketing strategy. For one, collecting data without consent violates the EU’s General Data Protection Regulation (GDPR). And, thanks to the GDPR and iOS 14.5, users can easily opt out of data collection, limiting the amount of data available anyway.
Third-party data can be used to understand customer demographics and identify high-value customers. However, it is expensive, highly inaccurate (especially compared to other data types), and often not collected consensually. And no company is safe from the ramifications of using it without consent — Meta was fined over $1B for violating the data transfer aspects of GDPR.
What is second-party data?
Second-party data, or 2P data, is collected directly from customers with their permission from cookies or privacy policies. It’s then sold to other companies, potentially without their knowledge.
2P data can be a clever way for companies to supplement their own insights with 1P data from another data source. However, 2P data is typically the result of a partnership between two entities and, therefore, requires time and effort to find, secure, and manage a partnership, along with the technical effort to ingest the 2P data. Even when acquired from a trusted source, additional work may be necessary to fully trust the data since a partner collected it. Data collection details are often described or agreed upon in partnership details and terms and conditions.
Given the other data types a company could cultivate, this type of data is likely not worth its cost unless it is a highly unique and valuable piece of data or if the data is provided as part of a data-sharing partnership rather than on a cost basis.
Another negative? If customers aren’t aware that they’ve given consent for their data to be sold and used by others, you would be in violation of GDPR.
What is first-party data?
First-party data, or 1P data, is collected directly from customers through websites and apps. This often involves behavioral data, like items purchased and time spent browsing. Companies usually find this data from sources like website activity, support tickets, and purchase histories. All of this data is gathered through transactions between the organization and its users rather than explicitly solicited.
For example, when you’re logged into your Google account as you surf the internet, Google collects your search history data. This is how they know which products to show you in personalized ads. However, customers are not actively telling Google the search history they wish to share each time they use Google.
1P data is excellent for tracking customer behavior and identifying trends. Visibility into items that customers have purchased before, their price points, and the cadence at which they made purchases is the cheat code for what they could be convinced to buy in the future.
And it’s consensual — cookie notifications and privacy policies notify users what data you’re collecting and how you’ll use it. People expect this kind of transparency, which makes it a critical component of positive customer relationships.
Even though first-party data is directly solicited, customers may have lingering concerns about their privacy or resent this collection when they notice product suggestions and ads pop up based on browsing history. To avoid this issue, ensure that your ads aren’t spammy. Instead, use the data you’re collecting to send ads specific to the person’s place in the customer journey. When people see thoughtfully targeted ads showing items they’re genuinely considering, they’re less likely to be frustrated by the personalization.
What is zero-party data?
Zero-party data, or 0P data, is data that customers intentionally and voluntarily share with a brand. This can include their contact info, loyalty program information, and customer feedback. For example, Sephora has a “Beauty Preference Center” where customers can directly tell the brand what sort of products they’re looking for. Their answers to Sephora’s questions are 0P data.
Zero-party data is excellent for collecting customer insights because it’s the most direct data brands can acquire from customers. Plus, soliciting explicit consent from customers builds trust between parties.
For example, suppose a customer says they’re interested in waterproof mascara in Sephora’s Beauty Preference Center. In that case, Sephora can be absolutely sure of that preference – and Sephora can send marketing emails about mascara knowing the customer is interested.
When using 0P data, remember that while customers are probably honest with you, they may not be objective — this is a downside of qualitative data. Ultimately, what an individual thinks they want and what they actually want are often two different things.
With 0P data, companies know more about their customers, so they can market and sell more to them. For instance, once the Sephora customer who wants waterproof mascara receives marketing for applicable products, they’re more likely to convert. Sephora then learns more about them from that conversion and can further personalize recommendations.
This positive cycle benefits a company’s revenue stream and means customers get more of the items they want.
What is multimodal data?
Multimodal data is data collected about all of the human senses. It can include audio, video, and click-stream data. This sort of data aims to overcome the blindspots that occur when companies only use one type of data to draw predictive conclusions or classify customers.
Through Multimodal AI, you can analyze every aspect of customer data, from photos included in product reviews to videos they post or search queries they enter. This allows you to create a holistic understanding of your customers derived from many digital and physical customer interactions.
Traditionally, leveraging this sort of cutting-edge technology was exceptionally expensive and not widely available. Since it's still early days, multimodal data has also been complex to interpret and understand. Recent advancements like Google Gemini and technology from OpenAI have made multimodal data collection and interpretation possible for companies beyond the most prominent tech giants.
Panorama makes this cutting-edge AI, multimodal data collection, and advanced data understanding available to small-to-medium enterprise retail brands. Merging multimodal, zero-, and first-party data helps our clients understand their customers holistically and implement advanced personalization that competes with that of Amazon or Google.
Combining 0P, 1P, and multimodal data begins a progressive journey to superior personalization
While 3P data used to be a useful source, 3P and 2P data have expiration dates. Laws have changed, so companies must stay aware of the data privacy space to remain on the right side of regulations.
But that’s not the only reason organizations should focus on 0P, 1P, and multimodal data. The data you collect from your customers as they interact with you is far more valuable than 2P or 3P data. Why? It gives you the insights you need for hyper-specific, superior, progressive personalization.
1P data centers customer privacy and launches personalization
First-party data is the place to start your personalization journey since it comes in such large volumes. It’s useful as long as you ensure that no data errors are confounding findings. It provides the backdrop and context for a user’s online behavior that makes 0P findings usable. Hyper-specific 0P demographic and user interest information is not as helpful if you don’t know how those users move online.
To build positive, long-term customer relationships, there’s nothing more critical than respecting customers and their privacy. So, for successful 1P data usage, only rely on information that customers have consented to. The Panorama JavaScript Tag helps retailers easily and securely gather first-party data without any compliance risks.
0P data gives you the most accurate insights for superior personalization
Zero-party data is the new oil: lucrative, untapped, and information-rich. It’s a strong next step in personalization because soliciting explicit consent from customers to collect it makes it trustworthy. Customers don’t feel the need to falsify information because they know how the data is being used and by whom.
0P data also gains an edge over other types because it doesn’t rely on inference, and it’s not aggregated or reproduced – so it’s inherently more accurate.
All of these benefits enable better personalization. Companies can use it to tailor experiences and ads to each customer while learning about the customer base as a whole. Then, they can create content that resonates with a larger audience. When done properly, zero-party data makes customers feel seen and heard by brands in the best way.
Multimodal data creates hyper-personalization + holistic customer understanding
Multimodal data is used to power advanced personalization previously reserved for big tech companies like Amazon. Collecting, interpreting, and using this data paints a detailed, never-before-seen picture of your customers. This gives you a competitive advantage in a market where multimodal data isn’t yet widely used. The insights it provides can significantly improve predictive models used for personalization — and help brands go toe to toe with big tech companies.
Adding multimodal data to your stack is the final step to creating a personalization flywheel that iteratively improves over time.
Combining first-party and zero-party data creates a complete data landscape
The combination of 0P, 1P, and multimodal data is a potent tool. While 0P data provides critical, direct information about your customers, 1P data contextualizes it against their online behavior. Multimodal data takes those findings and supercharges them.
Comparing 0P data to 1P data can further illuminate shopping trends and help brands build their customer journeys. 0P data provides the demographic information that tells you how to segment your customers accurately. As you continue collecting data, you can see if the buyer personas and customer touchpoints you’ve created reflect what you see.
Panorama AI empowers eCommerce personalization with a single click
Panorama AI is the only privacy-first personalization platform that helps retailers holistically understand their customers, enhance their revenue, and gain a competitive advantage through AI-powered solutions. This boosts average order volume, increases customer lifetime value, and reduces acquisition costs.
- One-click implementation – Our JS Tag implementation is a copy-and-paste integration that immediately begins 1P data collection. We sift through hundreds of data points on your behalf, so you gain the insights to power predictive models and personalize the customer experience.
- Advanced data collection & personalization – We work with brands to arrive at a data collection strategy and help implement 0P-data collectors such as quizzes, surveys, and preference centers. They gather the most informative and trustworthy data from touchpoints across the customer lifecycle. This additional data allows our AI to produce even more powerful personalization and segmentation, leading to higher marketing ROI.
- Holistic customer understanding & hyper-personalization – This is for enterprise retailers looking to compete with the level of personalization that companies like Amazon offer. We help identify and develop multimodal and cross-lifecycle data collection opportunities that lead to the greatest possible customer understanding. For example, collecting video through AR experiences or photos submitted with product reviews. Collecting and interpreting photo, video, audio, text, and geospatial data creates comprehensive customer profiles that power cutting-edge personalization.
- Privacy-first, to the core: Panorama AI can help collect and understand this rich information securely by leveraging proprietary, privacy-first solutions that allow us to extract the maximum value from your customer's photo, video, and other multimedia data under full consent and without ever having to store this intimate information. Imagine gaining a deep understanding of your customer's lifestyle, home, environment, and more without ever sacrificing their privacy!
