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The 2022 Guide To First-Party Data


The age of third-party data is nearly over… Don’t go down with the ship. 

The parties were fun, money was made, but owned data, i.e., zero-party data and first-party data, is the future. eCommerce brands that don’t prioritize their owned data simply won’t last the next few years. 

We’ve covered the magic of zero-party data, so let’s focus on how brands win when they know how to leverage their first-party data. First-party data opens up a world of opportunity for smarter segmentation and ultimately, more personalized customer experiences.  

What is first-party data?

First-party data (aka 1st-party data or 1P data) is information collected from your customer base, subscribers, and site visitors when they interact with your site or marketing, or when they make a purchase. 

First-party data is valuable because, like zero-party data, it comes directly from your customers. This means it is accurate, reliable, and insightful. 

Examples of first-party data

Here are some of the most prominent categories of first-party data with examples of each category:

  • Demographic info: age, education, employment, marital status 
  • Interests: individual products, product categories, preferred marketing materials, preferred content
  • Location: where individuals live or work, or where a business is
  • Purchase History: individual products purchased, bundles purchased, subscriptions, successful cross-sells or upsells, value of purchases, how long someone has been a customer
  • Loyalty program or membership status: what tier a customer is in your loyalty program, how long they have been a member 
  • Coupons: customers who have or who have not used coupons, customers who exclusively use coupons, customers who are more likely to use coupons
  • Social media: platforms a customer is most active on and where they most often interact with your marketing

How is first-party data collected?

Since 1P data collection comes directly from your customers’ interactions with your brand, you gather it from four major sources, which can help you answer many questions about your customers: 

  • Website activity: How long do customers spend on your website? What products do they purchase? What products do they abandon in their carts? What are their browsing patterns? Where do they get stuck in the browsing or buying process?
  • Mobile app activity: Do customers spend longer on your mobile app than your website? Are conversions higher on one or the other?
  • Email & SMS: How often and in what way are they interacting with your messages? What are their CTRs on each channel?
  • Point-of-sale (POS) systems: POS software often collects everything about a customer’s purchase history.

How do brands use first-party data?

Building a comprehensive first-party data strategy is vital to the future of your business. 

With third-party data collection and cookies being phased out (the Cookiepocalypse!!) over 2022 and 2023, your company’s 1st-party data (and zero-party data) will be crucial for success.

Here are some ways you can leverage it to fulfill your business goals.

Building Customer Profiles

1P data helps brands build accurate customer profiles to better predict purchasing patterns. 

For example, you might have a high-converting customer profile for a certain product category, with specific buying interests and behavior. In this case, you can predict that new visitors matching this profile will share similar buying preferences: this tailors your messaging to the profile, and will increase conversions.

Additionally, you can more directly predict future purchases based on historical individual buying behavior. By leveraging the metric time between orders, you can send replenishment emails to individual customers who might be ready to purchase again.

Sounds personalized, doesn’t it? Speaking of personalization…

Personalized website, SMS, and email content

Customer experience is a key brand differentiator, and true marketing personalization is key to delivering the best experiences, so that every customer feels special. 

But how do you “personalize” experiences? How do you determine your customers’ interests and tailor your value prop accordingly? By leveraging 1P data. (Okay, you saw this coming.)

With 1st-party data, you can personalize your campaigns across every channel. You can personalize your upselling and cross-selling recommendations and send tailored holiday buying guides to your customers’ inboxes and phones. 

Creating customer segments 

In the interest of delivering better, more personalized experiences, creating customer segments is crucial. 

1st-party data helps you build more accurate customer profiles, and it also fuels better segmentation. With 1P data-driven segmentation, you can better account for factors like your audiences’ time zones, interests, and purchasing power.

And the importance of smart segmentation extends beyond personalization—it also helps you determine your most valuable customers. 

As a business owner, knowing your most profitable customers is integral. Which of your customers have the highest customer lifetime value? And which customers are spreading the word about your brand? 

Identifying most valuable customers helps eCommerce brands drive repeat purchases through smarter upselling and cross-selling, and equally importantly, it helps you identify which customers you should prioritize retaining.

Determining optimal fulfillment center locations

Faster, more accurate order deliveries are key to winning over today’s consumers. But optimizing your shipping network to offer an Amazon-like level of fast shipping requires a lot of time and money. Instead of catching up to Amazon by spending billions on warehousing space, you can leverage first-party data to optimize your fulfillment center locations.

How we see brands struggle with first-party data

Although 92% of marketers believe understanding first-party data is critical to growth, we see many brands struggling with first-party data, both in collecting it and leveraging it.

Not having a single source of truth around existing customer data

Modern eCommerce brands are dizzy with data. You may be selling on Shopify, Amazon, Magento (or some combination of the three), so you have multiple sources of first-party data to begin with. 

Then, when you layer in Klaviyo, Attentive, ReCharge, Google Analytics, and other tools, you have a ton of siloed first-party data that you need to roll up your sleeves and block out a few days (or weeks) to make sense of. 

To optimize your customer profiling and segmentation, you need a deep understanding of their interests, behavior, and preferences. Unfortunately, because many brands struggle to create a single source of truth, they fail to leverage their data for growth. 

To build a single source of truth, we recommend leveraging an analytics platform that centralizes all your data. Once you do, you can make smarter decisions that drive growth for your brand.

A lack of testing, measuring, and tracking marketing campaigns

How do you know if your marketing campaigns are successful? And more importantly, how do you quantify their success? Should you increase your ad spend or cut it down? Should you experiment with different email creatives and copy, or stick with your existing material? 

Your first-party data and a great testing strategy will allow you to track the metrics to answer these questions. 

For example, If you’re spending around $1000/month to capture 100 email addresses on Google, and 20 of those subscribers convert, is your ad spend justified?

If you track your customer lifetime value by channel, and your CLV for customers acquired through Google is $150, then your ad spend is more than justified. You’re printing money! You would want to increase your ad spend. 

LTV by channel from the Daasity platform

If you weren’t collecting and analyzing your 1st-party data, you wouldn’t have been able to come to this sort of insight on your ad spend. 

Using First-Party Data in RFM Analysis

First-party data truly shines when it’s leveraged via RFM analysis, a highly effective way to measure your customers’ value and engagement over a time period (usually, 45, 90, or 180 days). 

RFM is based on three dimensions of customer behavior:

  • Recency: When your customers last purchased. Customers who have recently bought from your store are more responsive to marketing content.
  • Frequency: How often your customers purchase. Customers who buy from you more frequently have a more positive view of your brand.
  • Monetary: How much your customers spent. Some customers spend more than others, and it’s valuable to know who your biggest spenders are.

An RFM-backed marketing strategy helps tailor your efforts to retain high-value customers (HVCs, who have RFM scores of 1 or 2) and gives you the confidence to part ways with unenthusiastic customers (who have poor RFM scores).

Our two major recommendations for any eCommerce brand around RFM are:

  1. Focus most on your high RFM customers: prioritize them when you run promotions, and dedicate more of your budget to keep them happy and coming back.
  2. Nurture your mid-to-high RFM customers: These customers, who generally have RFM scores of 3 to 5 may not be there yet, but you can nurture them to the top. These are the customers who are HVCs in waiting, and if you bring them into HVC territory, your bottom line will thank you.

How Daasity makes it easy to use first-party data

If this is your first time here, hi! We’re Daasity, the eCommerce data platform of choice for consumer product brands. Some of the fastest-growing consumer product brands use Daasity to centralize their 1st-party data, analyze it, and push it to their marketing channels. 

We collect first-party data from tools across your tech stack (e.g., Shopify, Shopify Plus, Amazon, Google Analytics, Klaviyo, Attentive, ReCharge) and push that data into marketing channels using our Audiences product.

Audiences enables truly 1-to-1 marketing personalization. Want to send a certain customer segment through an email flow in Klaviyo, based on a particular survey response? You can. Want to send another segment based on an SMS offer through Attentive, based on a product preference? You can. Want to build lookalike audiences on Facebook based on your own first-party data? You can. In terms of what you can personalize and do with Audiences, there’s no limit. 

Want to learn more? We’d love to show you a demo.

Special thanks to our friends at Daasity for their insights on this topic.
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