Knowing what your customers want and how they shop is essential in retail. With ecommerce sales continuing to grow significantly, reaching over $6 trillion in sales in 2024, businesses are experiencing increased online traffic––and collecting more valuable first-party data––all year long.
When collected and used effectively, first-party data can bring fresh consumer insights, sharpen marketing campaigns, and help turn one-time shoppers into loyal, repeat customers. This isn't just theory: According to a report from Deloitte, the most high-growth companies are already doing this, with nearly two-thirds using first-party customer data to create personalized experiences.
If you're not already leaning into the potential of first-party customer data, there's no better time to start than now.
What is first-party data?
First-party data is information a business collects directly from its audience. A business’s audience may include:
- Customers
- Newsletter subscribers
- Site visitors
- Social media followers
Since first-party data is collected directly from a brand’s audience, it’s considered more reliable for understanding customers’ likely purchasing habits and behavior.
Businesses may collect first-party data from:
- Product recommendation quizzes
- Email lists
- SMS marketing campaigns
- Loyalty programs
- Social media platforms
- Google Analytics
- Post-purchase surveys
- Customer feedback
Second- and third-party data is information that a business gets from another party. While second-party data often relies on an established brand partnership, third-party data is usually collected by an external provider that’s not directly connected to your audience.
Through third-party data providers, it’s usually easy to purchase large quantities of demographic data on your audience—but it’s debatable how reliable or relevant the data is.
Plus, as global privacy restrictions increase and consumers become aware of how their personal data is used, it’s more challenging for brands to rely on second- and third-party data.
A key benefit of using first-party data is that businesses can rest assured that customers know exactly who is using their data and how.
Why is it important to build a first-party data strategy?
Reduction of return on ad spend (ROAS)
With a cookieless future on the horizon, it’s becoming harder to encourage customers to opt in to data-tracking or third-party cookies. Apple's iOS 18, released in September 2024, builds upon previous privacy measures by introducing features that allow users to lock and hide specific apps, enhancing their control over personal data. Privacy regulations like GDPR, CCPA, and PIPL are also impacting brands’ advertising and marketing efforts.
Web browsers are also reevaluating their approaches to third-party cookies. In July 2024, Google reversed its decision to phase out third-party cookies in the Chrome browser, though they did introduce new privacy controls allowing users to manage their tracking preferences.
Overall, the industry continues to head toward a cookieless future. Browsers like Safari and Firefox have already implemented measures to block third-party cookies by default, and there is a growing emphasis on privacy-centric technologies. Google's Privacy Sandbox initiative, for example, seeks to develop alternatives that protect user privacy while enabling targeted advertising.
Retailers are getting smarter about how they spend their advertising money by making better use of their own customer data. Instead of relying on third-party cookies, they're using information they collect directly from their customers to create more targeted and personalized ads.
Increase in traffic
While many businesses scramble to capture customer insights during peak periods, the most successful ones have systems in place year-round to collect and analyze first-party data.
This approach is particularly valuable given how retail has evolved. With approximately 20% of retail purchases now happening online, businesses have many opportunities to collect direct customer insights. Modern consumers spend significant time researching and shopping online, creating multiple touchpoints for data collection. However, this data is only valuable if businesses have the infrastructure to capture, analyze, and act on it effectively.
A unified data model combines all browsing, purchasing, and order data across all selling channels into one cohesive view. These insights become especially powerful during high-traffic periods, when increased volume allows for faster pattern identification and trend validation. With the right infrastructure in place, businesses can capitalize on peak periods and drive personalized shopping experiences and cost-effective customer acquisition year-round.
Different purchasing behavior
Consumer behavior can be understood through two lenses: aggregate-level data, which helps identify and anticipate broader market trends, and first-party data, which enables personalization based on individual customer profiles and habits.
At the aggregate level, businesses can spot emerging patterns in how groups of consumers shop, what features or products are gaining traction, and how online shopping trends are evolving over time. This broader view helps inform strategic decisions about product development, inventory, and market positioning.
First-party data provides deep insights into individual customer preferences and behaviors. This understanding helps create tailored shopping experiences, from customized storefronts to relevant product recommendations. The key is building these personalized experiences on a unified customer data model.
Together, these two perspectives give retailers a complete picture of who their customers are today—and where they’re heading tomorrow.
How to collect first-party data
Brands should aim to gather first-party data using a variety of collection methods. Doing so gives a more complete picture of customer behavior and preferences.
Consider how you can encourage and incentivize customers to share their data with your brand. Here are eight ways to collect first-party data.
Post-purchase surveys
The key to successfully gathering relevant customer data is to strike while the iron is hot. Instead of waiting a week to ask customers for feedback, consider asking them while your brand is still on their mind–right after purchase.
Zigpoll founder Jason Zigelbaum explains how retailers can tap into customer engagement right after purchase to receive higher survey completion rates.
“The most effective way to start collecting first-party data is through a post-purchase survey embedded directly on the Thank You page of your Shopify Store,” he says.
“This is always our first recommendation, because customers are highly engaged with your brand after purchase and are therefore much more likely to provide honest and insightful feedback about their experience with your business.”
Clothing brand Everlane sends out a simple post-purchase survey to customers to get a star rating and written review of purchased products:
When customers make purchases, brands can focus on asking about their buying motivation. For example, post-purchase surveys could ask shoppers whether the item is for themselves or someone else. If it's a first-time shopper, the survey could ask how they found the store. Was it through their online research or a personal recommendation?
Responses to questions like these can help brands build a more complete picture of who is shopping with them and why. This data can then inform future holiday season marketing campaigns to attract ideal customers.
Loyalty programs
People who choose to join loyalty programs are some of your most engaged customers. McKinsey reports that integrating loyalty programs with pricing strategies can drive growth, especially in challenging economic landscapes. The study highlighted that loyalty programs offering exclusive promotions and benefits can lead to increased customer engagement and spending.
In exchange for access to your loyalty program and associated perks, you can ask customers for some of their personal data––that way you can tailor your offering and make it relevant to each individual.
For example, Rose & Rex offers 200 Play Points when customers sign up for their loyalty program. Customers can also receive points for following the brand on social media.
Peter Messana of Searchspring explains how brands can effectively use loyalty program customer data to better target return shoppers in the future.
“If you have a loyalty program, you can capture every transaction, both online and offline, and can do much more effective repeat purchase retargeting. The key is to know which exact data you are collecting as well as have a plan for how you are going to use it. Then you can effectively decide which promotions can use what you collected,” he says.
Loyalty programs are an effective year-round strategy for gathering customer data. Exclusive discounts, promotions, and early access are all perks that could be offered in exchange for filling out full customer profiles. Additional seasonal rewards and exclusive perks can also help boost datasets.
Peter explains how a DTC wine brand can use first-party data to personalize their communications beyond just retargeting campaigns.
“An effective recent example I have is Total Wine & More. Because of their loyalty program, they’re able to track all my purchases, so they have a lot of first-party data on me,” he says.
“The best use of this data was an email from a specific winery thanking me personally for buying their wine from Total Wine. This is an amazing use of first-party data to extend to more than just retargeting or repeat purchase. It was subtle and great.”
Quizzes
Quizzes can help ecommerce brands get hold of unique customer information, like their skin care routine, which you could never get through cookies, and provide personalized product recommendations.
They're based on value exchange—when a customer shares this type of information with you, they expect something in return.
Product finder quizzes are effective examples of this. When you're shopping for a new moisturizer, you may take a quiz on a brand's website to find one suited to your skin type. You're giving that brand information about your skin care routine and lifestyle with the expectation you'll get something in return—in this case, a personalized recommendation that will save you spending time browsing the site.
Beardbrand’s quiz is one of the better product recommendation quizzes out there. It takes two minutes to evaluate your beard style, and in response, you get grooming tips, product information, and special offers delivered to your inbox.
These quizzes are also great for building customer trust too. Since they're personalized, the customer can trust that they've found the right product for them. It's comparable to a scaled back, digital version of the helpful employeewoman at the beauty counter in the department store.
Tiered discounts
Brands can experiment with running discounts to incentivize customers to share their data as well as purchase from them for the first time.
During the holiday season, tiered discounts can be particularly effective for encouraging first-time customers unfamiliar with your brand to make a purchase. Instead of a first-time purchase feeling like a risky decision, customers can instead feel like they’re part of an exclusive offer that won’t last forever.
As Daniel Romano says, “Brands could offer a limited amount of discounts on a first-come-first-served basis. They could increase the incentive by, say, 15% to 20% for dual submission of email addresses and phone numbers. This is also a great tactic to improve the quality and usability of data collected.”
DTC home furnishing brand Hem’s tiered discount approach and designer-exclusive discounts have been a great segue to introduce the brand to customers who at first glance may prefer to shop brands at a lower price point. The brand uses a newsletter subscription popup to offer customers 10% off their first order.
Wishlists
Wishlists are anchored in value for the customer, while also offering value to merchants. When set up correctly, they benefit both the in-store and online customer experience.
Online, customers create a profile that’s usually linked to their email address, and then add items from the online shop to their personally curated wishlist. They can share the list with friends and family, or use it as a reminder of the products they’re interested in purchasing at a later date.
For the customer, wishlists carry the benefit of being a super convenient way to shop both for themselves and others. For the merchant, wishlists are excellent for remarketing––they know what the customer has the intent to buy but hasn’t yet purchased.
Right now, customers can use the Shop app to build wishlists from Shopify stores. Shopify Partner apps like Wishlist Plus also let merchants add wishlist features to Shopify stores.
When paired with appointment shopping, wishlists can fuel store visits. For example, brands like SSENSE let shoppers book a store appointment to try on the clothes on their wishlist without committing to making a purchase. It makes for a curated store experience, plus in-store staff know exactly what the shopper is interested in buying beforehand.
Early access
Hotly anticipated product launches and back-in-stock bestsellers are great ways to build excitement among your audience and gather customer data. In exchange for early access to products, ask customers to leave their email address.
Daniel Romano of Good Moose explains, “By using this approach, we generate a waiting list of interested people and manage scarcity to incentivize people to share first-party data with the brand.”
He adds that other kinds of limited-time perks can incentivize customers to share their data with brands before certain dates.
“Brands can experiment with creating prelaunch or promotional offer momentum by announcing a compelling product or offer that will have limited quantities at launch, or guaranteed delivery before a certain date, for example, gift-wrapped presents delivered before Christmas Eve” he says.
Shopify partner app Wait.li lets merchants set up waiting lists for their stores.
Stock replenishment notifications
Surge seasons create significant inventory challenges across various industries. Retail sees multiple surge points throughout the year:
- Back-to-school shopping in late summer
- Black Friday/holiday season in winter
- Post-holiday sales in January
- Major sporting events like the Super Bowl for certain categories
Frequent stockouts can represent money left on the table by retailers. But with the right approach, they’re also an opportunity to capture personal data from your most engaged shoppers.
Daniel suggests offering customers stock replenishment notifications in exchange for customer data like email addresses. Instead of losing out on sales, retailers can use out-of-stock notices as a chance to email visitors a stock replenishment notification when the product becomes available.
“During surge seasons, it is very likely that bestselling products will run out of stock, so offering notifications that collect email addresses or phone numbers to notify when a discount, offer, or product gets back in stock is a great way to grow the CRM list while getting strong signals of interest and potential demand of products that have run out,” he says.
Bedding brand Italic sends out a simple note to let shoppers know a previously out-of-stock weighted blanket is available again.
Mobile apps
App users are some of a brand's most keen customers, since they’ve made the extra effort to download the app. Marketers can collect first-party data on app usage and behavior to gain a deeper understanding of how their audience interacts with the brand on the app.
For example, using app analytics tools, marketers could see whether people use the app to browse and later purchase products—or alternatively, if they use the app for inspiration, education, or another activity.
DTC sportswear brand Gymshark has an app to connect their community with exclusive member benefits, provide seamless shopping experiences, and support their fitness journey. The app offers workout plans and training resources to help their audience achieve their strength and conditioning goals while making browsing the brand’s latest athletic wear collections easy.
By studying the app's analytics, Gymshark gains a deeper understanding of their customers' behavior. Are they coming to Gymshark to reach their sports goals? Or are they shopping with the brand to buy stylish athleisure garments? Knowing this, the retailer can tailor their marketing campaigns to each segment.
Websites
With the use of some website analytics tools, retailers can track user behavior like when website visitors hover over specific images or text. They can identify which web pages customers visit most, and what they're looking for in the site search. Tracking web behavior is also essential for optimizing retail websites.
Christina Martinez, CEO at Traject, says that tracking user behavior is key to boosting conversions.
“Use website analytics software to track user behavior on any web property you own. Tracking online behavior will give retail businesses insight into what kinds of products customers gravitate toward. Most importantly, businesses will be able to uncover ways to optimize the online checkout process to generate more revenue through online sales channels.”
Using website analytics tools, a brand could send out personalized abandoned basket reminders to encourage visitors to convert. This personalization tactic is especially effective with the use of images that show customers the objects in their shopping cart.
SMS
Customers who let brands interact with them via SMS show a high level of interest. Following SMS marketing campaigns, retailers measure how and why customers engage with their brand.
For example, a retailer encouraging subscribers to purchase by sending them offers and perks can analyze who is converting and why. By purchasing products, subscribers give an indication of their preferences, helping tailor future communications.
To get customers' phone numbers in the first place, remember to find a way of exchanging value for the data.
Skincare brand LATHER uses SMS marketing to promote their loyalty program. The brand offers a dual incentive: subscribers receive both 25% off their purchase and double loyalty points. Rather than explicitly promoting self-gifting, LATHER framed the offer as a rewards opportunity, allowing customers to save points for future treats while getting immediate savings.
Email campaigns provide data like open rates, click rates, and bounce rates. Retailers can dig deeper into the finer data on who is opening emails, who is clicking through, or whose interest is waning.
DTC brands can segment their email lists based on customer attributes or preferences to promote relevant products. This personalization ensures subscribers receive content and offers that match their specific needs.
After running email campaigns, brands can identify their most engaged subscribers and send targeted follow-ups like purchase reminders. Companies can focus on collecting additional first-party data for subscribers showing less engagement to better understand their preferences and improve future communications.
CRM systems
Don't forget about offline data—a CRM or POS system can sometimes be a brand's best source of first-party data. They are particularly useful for targeting a brand’s best customers. By knowing a shopper's purchase history, a retailer can provide more personalized experiences and product recommendations.
This first-party data is also helpful for analyzing what's selling and where.
For this first-party data collection method to be efficient, it's vital to centralize POS data and website data in one place. Modern ecommerce platforms provide a central hub that connects all your business tools and data sources.
The best modern ecommerce platforms give you access to specialized apps for things like marketing, sales, or inventory management. This integration lets you manage your entire business, from performance analytics to automated workflows, all in one place.
Customer service interactions
Brands often invest in automation, customer service systems, and team member training. But they forget that customer service interactions are valuable sources of first-party data. Customers usually contact support to track orders, start an account, or complain about a problem.
This data is valuable for better understanding customer needs, priorities, and preferences. It can help define customer profiles and identify where to focus marketing campaigns.
POS system
Being face to face with customers in-store provides further opportunities to collect first-party data. You can create unified customer profiles that lead to up to 20% more sales per order. This gives you the chance to retarget store visitors through your website and improve marketing ROI through better customer segmentation.
The process is easy with Shopify POS because it's built on the same platform as your online store. There are several ways to collect customer data during these in-store interactions:
- During checkout
- When signing up for loyalty programs
- While processing returns or exchanges
- When placing special orders
- During product consultations
Staff can ask customers for information and explain the benefits of sharing their data with your brand. This enables features like Buy Online Pickup In-Store (BOPIS) for a true omnichannel experience.
The data gathered through POS allows associates to follow up with personalized suggestions for complementary items while incorporating relevant details from their in-person conversations. This turns the checkout process from a simple transaction into an opportunity to build lasting customer relationships.
What can you do with customer data?
Customer data from peak shopping periods offers some of the most valuable first-party data your brand will collect year-round. Site visitors during these times are often high-intent shoppers who are close to making a purchase the moment they land on your page.
Data from these customers can help you better understand purchasing habits and why certain marketing campaigns are effective.
Currently, only 47% of companies offer personalized experiences based on live consumer data––over half are missing out on a significant aspect of personalization.
Plus, the increase in traffic means brands have plenty of datasets to compare.
When harnessed correctly, holiday season first-party data isn’t just about predicting next year’s holiday season purchasing habits––it can also highlight how to convert one-time shoppers into regular customers throughout the rest of the year.
Create personalized campaigns
Customers want personalization––but not at the expense of their privacy. First-party data that consumers willingly provide before, during, or after shopping with your brand offers the ideal way to curate personalized experiences that don’t infringe on their desire for privacy.
Despite increased awareness surrounding data privacy, 49% of consumers said they would likely become repeat buyers if offered a personalized experience by a retail brand.
Segment’s 2024 State of Personalization found that Gen Z consumers in particular demand more authentic and engaging digital experiences. That’s why 85% of businesses plan to optimize their marketing strategies to cater to Gen Z’s needs and preferences.
“Consumers don’t consider the challenges to well-executed personalization; they simply expect relevant content delivered at the right time and place,” says eMarketer principal analyst Dave Frankland.
While personalizing customer interactions and marketing campaigns can seem like an additional effort and cost to brands, most businesses find it’s a worthy investment. In fact, 80% of business leaders say customers spend 34% more on average when offered personalized shopping experiences.
Peter Messana of Searchspring suggests that using customer data to personalize customer interactions and campaigns needn’t be complex to start with.
“If you have their name, use it to welcome them back to the website when they return. Later, build out a drip campaign that’s based on a very granular segment. The more you know directly about someone the more you can directly target them,” he says.
Show customers appreciation
When customers feel appreciated and valued by your brand, they’re more likely to return.
One small way of showing appreciation is by saying a simple thank you. Whether it's following a purchase, a loyalty program subscription, or even a return, taking the time to say thank you is key to building a positive relationship. Tap into your customer data to send out thank you notes at the right time.
Jason Zigelbaum of Zigpoll explains how brands can easily make customers feel valued and encourage them to shop again after the holiday season.
“Customers love to be heard! Once you read their feedback, send them back a note,” he says. “You will be surprised at how far small acts like this will go. If you're operating at a scale where this isn't possible, try connecting your responses to an email provider like Klaviyo and sending back an automated message. Zigpoll has an API to make this easy, but there are lots of ways one could build it out.”
Build segmented email and SMS funnels
Customer data can help you build out ultra-segmented email and SMS marketing campaigns that better target your audience.
Mitch Turck of Fairing explains how brands can use customer survey responses to create more targeted audience segments.
“First-party data enables hyper-targeted segmentation, which is crucial to nailing the holiday content that wins in the inbox,” he says.
“For brands with a fairly short purchase cycle, there's still time to have customers self-segmenting through survey questions like, ‘How will this product impact your lifestyle?’; ‘What makes our product better than the last brand you tried?’; ‘Would you rather be the first to find new products, or discover a great deal?’ All of these responses create personalization opportunities, and even a simple question like ‘Who is this purchase for?’ immediately splits your customers into two groups: buyers, and users. How you market to those groups alone is a lesson in Black Friday Cyber Monday best practices.”
Jason of Zigpoll emphasizes that ongoing customer feedback can help shape both immediate and future advertising campaigns to better match consumer expectations.
"In the near term, you can use the collected data to influence your current marketing strategy. For example, if you notice customers frequently commenting on a specific product's price point, you can create targeted promotional offers to drive more sales," he says.
"Looking at the bigger picture, you can use this data to optimize your site for the future. If you're running an attribution survey, analyze the average order value for each marketing channel and use those insights to inform your marketing budget allocation. When conducting user-experience surveys, apply the feedback to improve your website's design and address customer service pain points."
Develop and stock in-demand products
Customer data on browsing and purchasing patterns can help you make decisions around product development and inventory management. By analyzing first-party data like favorite items, cart additions, and purchase history, you can better understand which products resonate with your audience.
Product development teams can examine metrics like product page views, time spent browsing specific categories, and items frequently added to wishlists to identify high-interest merchandise. Retailers can combine this data with customer survey responses to reveal why certain products attract attention. Are shoppers drawn to your sustainable skincare line because of environmental concerns? Or are they looking for clinical-grade products recommended by dermatologists?
Understanding both what products generate interest and the motivations behind that interest helps development teams predict which new offerings are likely to succeed. These insights can guide the creation of complementary product lines and improvements to existing ranges.
Real-time analysis of customer behavior patterns also helps optimize inventory management. For instance, if data shows certain products consistently trigger "notify when available" requests, or sell out shortly after restocking, you can adjust inventory levels to prevent revenue lost from stockouts. This data-driven approach ensures you maintain appropriate stock levels of your most sought-after items.
How can Shopify help brands gather valuable first-party data?
Shopify’s customer data model is built to unify data from all your touchpoints, from ecommerce and in-store to your marketing channels, into a single source of truth.
Centralization allows brands to collect, store, and analyze first-party data efficiently. Leveraging Shopify’s core infrastructure, businesses get a comprehensive view of their customers, including their browsing history, purchase behavior, and order details.
- Shopify's personalized storefronts based on customer accounts encourage buyers to sign in for features like wishlists, saved carts, and customized recommendations.
- With Shopify Audiences, you can pool anonymized data with other participating brands to cut customer acquisition costs by up to 50% and improve targeting while maintaining ownership of their own first-party data.
- Shopify’s Web Pixels API offers compliance-friendly data tracking. Brands can securely collect behavior data, integrate it with their existing marketing stacks, and gain actionable insights from every customer interaction.
- Shopify’s segmentation tools let you group customers based on specific behaviors, demographics, or purchasing patterns. You can target these segments with tailored campaigns that resonate with each group.
- Use the Shopify Forms app to create popup and inline forms that collect customer data and allow customers to sign up for email marketing.
- If you use lead capture forms created with the Shopify Forms, customers can sign up for marketing updates and receive a discount code for your store through the Shop app. When they complete a lead capture form using their Shop email address, they are prompted to authenticate with Shop, and their discount code is saved to their account.
With Shopify’s unified customer data model and first-party tools, you can thrive in the new privacy landscape.
Five Shopify partner apps to help collect customer data
Shopify partners with a wide range of marketing and ecommerce apps to help you interact with your customers and get to know them better.
To save you time, we’ve vetted all our partner apps so you can more easily choose the ones right for enhancing your campaigns.
Yotpo
Yotpo helps online stores collect customer data and incentivize shoppers to share their information. With Yotpo, merchants can create tiered loyalty programs that include discounts, access to exclusive products, special members' gifts, and early access to sales.
The app also collects data surrounding customer loyalty preferences and habits––do they prefer to use smaller quantities of points for more frequent rewards, or do they prefer to save up larger amounts of points for bigger, higher-value rewards?
Within Yotpo, merchants can also build thoughtful and personalized SMS campaigns. Using already collected customer data, they can address messages to customers by name, offer relevant discounts, and solve problems.
Key features:
- SMS automation
- Abandoned cart messages
- Loyalty programs
- Referral marketing program
- Product, photo, and site review collection
Searchspring
Searchspring lets merchants target shoppers with hyper-relevant product offerings while providing deep insight into customer behavior. The app also automatically creates product recommendations based on shopper history, real-time behavior, and preferences.
Searchspring also features powerful reporting and analytics to help merchants identify search trends, top-performing search terms, and high-converting products. All of these features help brands turn visitors into long-term customers.
Key features:
- Use enhanced site search to deliver relevant results
- Target shoppers with products and offers
- Control how products are arranged onsite
- Analytics for insights into customer behavior and habits
Zigpoll
Zigpoll lets merchants automatically trigger post-purchase survey campaigns via web or email to gather accurate customer feedback. Using 12 different question types, Zigpoll lets merchants build on-brand customer surveys to generate a steady flow of unique customer insights.
A central dashboard lets merchants get a bird's-eye view of customer data at a glance. In-depth insights let merchants learn from customers at different parts of the survey.
Key features:
- Post-purchase email or web surveys
- Feed customer data into Mailchimp, Klaviyo, or other integrations
- Choose from 12 question types like multiple choice or blank answer forms
- Review customer data on a granular level or from a high-level perspective
- Incentivize customer participation with discounts or giveaways
Shop Quiz: Product Recommender
Shop Quiz Product Recommender lets merchants build shoppable quizzes that guide customers through purchasing decisions. Create targeted questions that let you segment and target shoppers based on their responses.
Help shoppers make confident purchasing decisions before sending leads to your email list or CRM. Later, use this customer data to build more personalized marketing campaigns.
Key features:
- Define targeted questions that follow conditional logic
- Personalize product recommendations
- Collect customer contact details
- Integrate with email software and CRMs
Fairing
Fairing lets merchants set up post-purchase surveys to gain unique insights from customers. Use Fairing’s surveys to identify how customers found your brand, why they bought your product, and what they’d like to see your brand create next.
Key features:
- Segment customers according to their answers and customize marketing automation
- Improve attribution modeling
- Perform customer research
- Ask open-ended, multiple choice, and follow-up questions
- Get API access to export data to a data warehouse or third-party partner
Use your first-party data more effectively with Shopify
Want to know exactly what your future customers want before they do? Every customer interaction is an opportunity to gather rich first-party data that reveals their shopping patterns and preferences.
While other brands scramble to adapt to the decline of third-party cookies, you can stay ahead by building deep, personalized connections with your audience.
