Converting First-Party Data into Personalized Shopping Experiences

When it comes to creating personalized commerce experiences and loyalty ecosystems that make your brand stand out, first-party data is pivotal.

You visit a restaurant after years. The server recognizes you, greets you using your name, and recommends the dish you enjoyed the most on your last visit. Wouldn’t that make your visit personal and special? The server organically collected your information directly from you on your last visit and used it to provide you with a personalized dining experience — that’s first-party data in action.

First-party data is information you collect directly from your audience — customers, visitors, and social media followers. But today, ‘the little black book’ used by the server has gone digital.

And research shows that 76% of digital customers are now happy to entrust this data to businesses in exchange for superior experiences, offers, and products. With this data, you can personalize every interaction on your site. Not only can you send messages targeted by customer segments and create personalized campaigns, but you can also view customer interactions and chat history, or even automate your chatbots by training them to recognize frequently asked questions.

Capturing first-party data

Unlike third-party data, which is collected from sources other than your direct customers, first-party data involves listening closely to your customers. That way information doesn’t get degraded as it goes through a third-party ‘broken telephone’.

Traditionally, we gather this data from customers through online and offline touchpoints such as mobile apps, websites, social media, questionnaires, and in-store experiences. Some commonly captured information includes web activity, demographic data, purchase history, email address, sales interactions, call center calls, customer feedback, and behavioral data.

Nowadays, an increasingly popular way of collecting first-party data is through digital fingerprinting, a tracking technique capable of identifying individual customers based on their browser and device settings. In order for websites to display correctly, your browser makes certain information available about your device, including your screen resolution, operating system, location, installed fonts, and language settings — the combination of such information helps create a customer’s unique digital identity.

Collected first-party data then helps you understand customer behaviors and discover omnichannel loyalty opportunities to pleasantly surprise your customers.

Maximizing opportunities through first-party digital footprints

All customer scrolls and clicks precisely tell us about what products the customer might be interested in. For example, the customer may scroll through shoes but click only on high heels. And finding a pattern in the customer’s browsing hours helps us reach out to them with personalized offers at a time when the possibility of purchase is high.

When the customer adds items to their cart but isn’t quickly going ahead with the purchase, it would be wise to ask for their email address in exchange for a promotional signup discount. The email address, also a first-party data, opens doors to new personalization campaigns.

As we accumulate more data, we’re empowered to interpret more information about the customer. For example, a customer who frequently shops for fitness supplements might have an active lifestyle. We can not only recommend other fitness supplements but also promote gym equipment and clothing, slowly giving them an opportunity to become a repeat customer.

If the customer has highly diverse shopping needs and interpretation is not an option, we can come up with other ways to gather more information. Offering a promo discount if a customer’s friend creates an account or giving them a chance to join loyalty programs using their phone number, etc., are a few ways of doing so.

Now we augment this data and fill in the blanks in customer profiles. Then we put these customer profiles into segments based on common characteristics – such as demographics or behaviors. So, you can market to those customers more effectively by developing personalization strategies.

Building personalization strategies for improved conversion rates

Today, every business is investing in personalization, but only the successful ones have carved experiences relevant to their customers’ expectations. So once we’ve identified loyalty opportunities using first-party data, the next step is to turn these opportunities into personalization strategies that resonate with your customers.

We use the concepts of rewards and recognition as the foundation behind these strategies.

While rewards work as a catalyst for transactions — a free item or a discount increases the chances of a successful purchase, recognition is a way to celebrate loyal customers by providing them with exclusive personalized offers.

Here are three personalization strategies that you could use on your commerce platform to gain a competitive advantage through happy customers.

Promotions: Promoting trending products outside of customers’ preferences would create new sales opportunities and help us expand our knowledge of their purchasing habits. Even though the customer only buys dresses from your website, promoting rain boots during winter might just do the trick — trendy and relevant.
Loyalty Programs: To increase the number of repeat customers and to appreciate loyal ones, we offer personalized coupons and early access to new or limited products. These are again based on deep learning of customer preferences using first-party data.
Recommendations: As first-party data makes the customer’s picture less blurry, we try testing relevant hypotheses to offer product recommendations. Recommend bags for customers who buy high heels and cheese for ones who buy pasta.

A/B testing helps you test multiple versions of your campaigns so you can learn which ones perform the best with your audience. Finally, effective personalization directly impacts conversion rate optimization (CRO). If you put what customers want in front of them, it speeds up the sales cycle, creating a relationship of trust between you and them. And here’s the proof.

While working with the multinational business consortium SMU to digitally transform their Chilean supermarket chain, we created customer profiles using national identification numbers (first-party data, in this case). This ground-breaking loyalty campaign began with a web-based initiative called "El Gran Cuponazo" (The Big Couponing) that led to the development of B2B and B2C apps. It allowed SMU to deliver personalized coupons and promotions for 2.5 million customers on the B2C and 300,000 customers on the B2B front based on their purchase history.

Putting it all together

Businesses have been trying to master personalization in commerce for more than 20 years now. Access to first-party data has definitely kickstarted this exploration in a deeper, more focused way. And the shift from traditional methods of data collection to modern techniques like digital fingerprinting is allowing businesses to keep up with ever-changing customer expectations and behaviors. But still, not every server in every restaurant around the world can remember millions of customers and their favorite meals.

In order to increase the predictability of the success of large personalization initiatives and to paint a more thorough picture of your highest-value customers, businesses need to leverage technological advancement and third-party data in addition to first-party data. Leveraging a combination of the above improves the automation, composability, and scalability of loyalty campaigns. It allows businesses to process data frictionlessly into online and in-store digital experiences.

Stay tuned to learn about the impact of modern technologies on personalized commerce capabilities in our future articles. And if you’d like to implement best-in-class personalization experiences for your customers, we’d love to hear from you.

Co-written by Rashika Srivastava

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