How To Use First-Party Data To Drive Business Growth

Aug 29, 2023 11:00:00 AM
9 min read

Illustration of cookie with a bite taken out of it. As data privacy rules continue to stiffen, relying on third-party cookies to drive your e-commerce sales is a thing of the past—and first-party data has stepped up to fill the void. More and more, online retailers are leveraging first-party data to enhance their revenue, gaining deeper insights into their customers' behaviors, preferences, and needs.

First-party data, which is collected directly from customers through interactions and transactions, is incredibly valuable for tailoring marketing strategies, improving customer experiences, and driving sales. A study by Google and Econsultancy found that 92% of leading marketers believe using first-party data to continuously build an understanding of what people want is critical to growth.

So, why is first-party data so beneficial, and how can it help you generate more growth for your e-commerce business? Read on to find out how to use first-party data to increase your revenue and delight your customers in our step-by-step guide below!

Steps to Using First-Party Data

Step 1: Collect and organize the data.

metric-columnThe first thing you’ll want to do is decide what kinds of data you want to collect. Are you interested in learning how shoppers navigate your website? Perhaps you’d like to know more about how they interact with your content. Or maybe you want to see exactly where people are falling off in your checkout process.

Once you’ve narrowed down the information that is most valuable for your e-commerce goals, you can begin gathering it. There are several ways to collect first-party data, from your e-commerce platform to social media to dedicated marketing and analytics tools (and lots more). There are also many different varieties of first-party data to accumulate, including customer profiles, website visits, purchase history, browsing behavior, and email engagement—just to name a few.

Step 2: Segment and categorize the data.  

Shopper choosing between three different blenders.The second step is an important one because it allows your brand to reach the right customers with the right products; that is, content that resonates with them or items they are interested in and most likely to buy. This creates opportunities for faster conversion. It also helps build brand loyalty since you’re letting your shoppers know that you understand their exact needs and wants.

How you divide your customer base is entirely up to you. Some common shopper segmentations include: 

  • Shared characteristics and behaviors
  • Common interests
  • Demographics
  • Region
  • Purchase or browser history
  • Frequent shoppers or buyers
  • New customers
  • Recent cart abandoners
  • Browsing or buying habits
  • Engagement levels
  • Average AOV (e.g. big spenders, sales hunters, etc.)

Step 3: Analyze your audience insights.

Curious shopper looking through magnifying glass.Now that you’ve built your shopper segments, you can take the information you’ve amassed and use it to uncover, and act upon, valuable insights about their behavior. This is the stage where you’ll be able to identify patterns and trends to help you optimize your e-commerce strategy for the greatest conversion and revenue potential. You’ll also learn what incites your shoppers to convert into customers and what might be causing them to leave.

Here are some key audience behavior metrics to keep your eye on:

  • Website pages with high bounce rates mean there’s something on them, such as product pages with poor descriptions and/or images, that is causing visitors to exit your site.
  • How long your shoppers spend on your site is integral to encouraging more leads and sales for your online store and will help you determine what content and designs are keeping them engaged.
  • A high volume of customers using mobile devices to browse or buy makes implementing a responsive website (or mobile app) design essential.
  • Your overall conversions can reveal which e-commerce marketing strategies and website pages are driving the most conversions and sales, allowing you to maximize high-performing tactics while amending any pages with a lower conversion rate.

Step 4: Optimize your e-commerce strategies.

Shopper pushing a cart. In the cart, is a shopping bag with a dress floating overtop of it.The final step in utilizing your first-party data is putting it to use through your marketing approaches. The key to driving growth for your e-commerce business is to personalize the customer experience. This can be executed on your website, social media pages, email campaigns… basically anywhere you communicate to online shoppers.

First-Party Data E-Commerce Strategies

 Here are some of our top recommendations on how to use your first-party data to your fullest advantage:

Retarget hesitant shoppers.

Mobile shopper being served a pop-up. Behind the shopper, is a graph showing an upward revenue trend, suggesting the pop-up is increasing revenue. Retargeting is a super effective way to use first-party data to reach customers who have shown interest in your products but haven't completed a purchase. Use data from website visits to create targeted ads that remind them about their viewed or wishlisted products or items left in their carts.

Not only can this subtle-yet-not-so-subtle nudge bring reluctant customers back to your site, but it also nudges them to complete their purchases.

Generate personalized product recommendations and promotions.

Shopper standing in front of a mirror while a sales associate helps them. With 91% of consumers more likely to shop with brands that provide relevant offers and recommendations, implementing this strategy into your e-commerce marketing plan is a no-brainer. Utilize purchase and browsing history to tailor offers and product recommendations that are most likely to appeal to each customer.

These can be displayed on product pages, in email campaigns, and even during the checkout process, and should include related or complementary items that encourage upsells and cross-sells to increase average order value.

Enhance the shopper journey.

Strengthening customer relationships is paramount for any e-commerce business’s growth. The stronger the relationship, the greater the trust. And the greater the trust, the deeper the loyalty—which just so happens to convert to higher online revenue. 

Illustration of a magnifying glass. To achieve this, analyze your first-party data to identify any pain points and areas for improvement. This will allow you to optimize the customer experience by reducing any friction throughout the conversion funnel. For example, your first-party data might highlight that many of your customers make their exit during checkout after they see limited payment options.

To resolve this, you could add more payment methods, such as Buy Now, Pay Later, which allows shoppers to pay for their purchases in installments, rather than all at once.

Strengthen your loyalty program.

A recent study found that 79% of consumers are more likely to do business with a brand because of its loyalty program, which translates to increased customer retention and revenue. Your best approach for making your loyalty program a reason that shoppers seek out your business? Begin by using your first-party data, such as shopper preferences and previous purchases, to tailor your rewards to each customer. 

ATwo hands clasping each other. nd with third-party data on its way out, loyalty programs are going to be more important than ever when it comes to customers actively sharing their information. With a well-executed, personalized loyalty program, you can increase your customers' lifetime value, drive repeat purchases, and create champions for your brand.

Target cart ditchers.

Earlier, we mentioned retargeting wavering shoppers. Here, we are referring to potential customers who have decided to leave your site and abandon their full shopping basket with no intention of ever returning to complete a purchase. While this may seem like a waste of time, it’s actually a great opportunity to build connections with online consumers you might never have heard from again.

cart - emptyFirst-party data can identify those who have recently abandoned shopping carts, and you can then send targeted email reminders or offers to encourage them to complete the purchase. This strategy is proven to work well, especially when an incentive like a limited-time offer is included. According to Moosend, abandonment emails have a 10.7% conversion rate.

Looking to catch cart abandoners before they leave your site? Machine Learning technology (like Granify) can use first party data to identify when a shopper is likely to abandon, and intercept before they’ve made their exit.

Implement dynamic pricing.

Illustration of a coin. Dynamic pricing can help you maximize revenue by charging different prices to different customers at different times, optimizing based on each consumer's willingness to pay. To determine whether this hyper-personalization strategy could benefit you, look at first-party data like customer preferences, buying behavior, and historical purchases.

You’ll also want to take a look at competitor pricing to ensure you’re not over (or under) reaching. From here, you can adjust prices based on your customer segment and offer discounts to customer groups who would benefit from them most to encourage purchases.

Create personalized campaigns.

Person with Shopping Bag and PhoneA large part of your marketing budget is likely going toward advertising. Take your wealth of first-party data, including purchase history, browsing behavior, and demographics, and use it to create highly targeted campaigns that spark interest in your segmented groups. For instance, a furniture retailer may target a group that has all purchased the same sectional with ads featuring a matching chair or ottoman, along with a limited-time discount if they buy it within a set time frame.

Manage inventory better with predictive analytics.

Person using crystal ball to predict the future. Anticipating customer needs and preferences is a surefire way to get a better handle on your store’s inventory. Fortunately, you don’t need a magic 8-ball to achieve this. Instead, use predictive analytics, a type of data analysis that employs machine learning to evaluate inventory levels and trends to predict future outcomes.

In simpler terms, by looking at the activity of your customers, suppliers, and even the market at large, you’ll be able to predict the next best action. For inventory management, you’ll want to analyze historical data to predict the demand for certain products. This will allow you to tailor your inventory strategies to prevent stockouts or overstocking.

Don’t forget to test your strategies!

Testing different strategies and messages based on first-party data is paramount to determining what resonates best with your audience.

Person pondering an idea while writing on a piece of paper. A dotted line moves from them, to a lightbulb, to the paper, as though to suggest an idea.Make sure to continuously refine your marketing and personalization strategies using A/B testing, and experimenting with different messaging, offers, and channels. You can then use first-party data to measure the impact of these changes on key metrics like conversion rates, click-through rates, bounce rates, and average order value.

Final Thoughts

There are many ways to drive your business growth, but first-party data assures you’re moving in the right direction. Just remember, using first-party data requires careful attention to data privacy and security. Always ensure you’re complying with the proper regulations and best practices, and be transparent about your data usage. Provide opt-out options to foster trust and maintain credibility. Follow these strategies and the best practices we’ve shared, and your e-commerce store will be on the path to growth and greater success.

Next Level E-Commerce Growth

Illustration of a potted plant. Want to learn more about how to leverage your first-party data to maximize e-commerce conversions, revenue, and customer satisfaction? Granify’s advanced machine learning enables the largest e-commerce brands to take their business to the next level. Reach out to find out how we can help you!

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