Personalization in Ads | How To Use First-Party Data on Ecommerce Platforms for Great RoAs
Marketers today are firm believers that when it comes to ads, personalization is key to driving conversions and generating high ROAs. As many as 37% of brands today use first-party data to personalize customer experiences. This is a staggering increase of 6 percentage points from 2021 alone.
However, when it comes to eCommerce platforms, personalization can be difficult to achieve.
There are a few reasons for this:
- Most eCommerce platforms aren’t built with personalization in mind.
- Even if they were, the data necessary to truly personalize an ad campaign at scale simply doesn’t exist within most eCommerce platforms.
This is where first-party data comes in.
Understanding First-party Data
First-party data is data that you collect yourself, either through your website or through other means such as surveys or customer loyalty programs. By collecting and utilizing first-party data, you can gain a much deeper understanding of your customers than you ever could with second or third-party data.
This deeper understanding of your customers allows you to personalize your ads in a way that would simply be impossible with generic data. This is important today as Google is phasing out third-party data, which is typically collected, aggregated, and pledged to other parties.
5 Ways Retail Media Networks Contribute To Retail Profitability :
1. Enhance shopper experience.
The best shopper marketing tactics improve the experience for shoppers. Shoppers benefit from a well-placed end-cap introducing a new product or a stylishly merchandised outfit on a mannequin. However, it’s not a helpful shopping experience to flood shoppers with irrelevant search results that the highest bidding advertiser has purchased. Retail media networks need to balance organic visibility with paid media and ensure that the paid media is highly relevant to the shopper’s current mission.
Impact Of First-Party Data On Ad Personalization
Now that we understand what first-party data is and why it’s important, let’s look at how utilizing first-party data can impact your ad personalization efforts.
- Lookalike Audiences: When you have first-party data, you can create what is known as “lookalike audiences.” Lookalike audiences are groups of people who share similar characteristics to your current customer base. This is important because it allows you to target people likely to be interested in your product or service. This, in turn, leads to higher conversion rates and ROAS.
- Dynamic Ad Personalization: First-party data also allows you to create dynamic, personalized ads. Dynamic, personalized ads change based on who is viewing them. As an example, if someone has visited your website and added items to their cart but never completed the purchase, you could show them an ad for the items they left in their cart. Or you could target them on the basis of user behavior defined from anonymized data on individual user journeys/searches for products. This ad personalization is highly effective as it speaks directly to the customer’s needs and interests.
- Tracking Conversions: Finally, first-party data allows you to track conversions and attribute them back to specific ads, keywords, and even individual customers. This level of attribution is significant because it will enable you to see the ads performing well and the ones that need to be tweaked. It also lets you track the customer journey and see where people drop off. This can help you optimize your ads and website to improve the customer experience and drive more conversions.
How To Acquire First-Party Data For Ecommerce Platforms
Interactive content is a great way to acquire first-party data, as it allows you to collect data about your customers without interrupting their experience.
There are a few different types of interactive content that work well for eCommerce platforms, such as:
- Quizzes: Quizzes can be super valuable sources of data. Not only do they allow you to collect data about your customers, but they also help you segment your audience. This is important because it allows you to target your ads more effectively. For example, if you have a quiz about skincare products, you could use the data from the quiz to segment your audience and show the ads only to those who, for instance, have dry skin.
- Chatbots: You can use chatbots to ask customers questions about their needs and interests while also collecting essential information such as email IDs and contact numbers. This first-party data aggregation effectively converts it into a lead-generation engine. For example, you could use a chatbot on your website to ask visitors about their skin type. Then you can follow up with them via email or SMS to offer personalized recommendations.
- Feedback Forms: Feedback forms can help you gather information about customer satisfaction, pain points, and areas for improvement. This is valuable as it allows you to alter your products, website, and even ads. For example, if the feedback reveals that users cannot find what they’re looking for on your website, you could make changes to your website navigation or create more targeted ads.
- Product Recommendations: Typically, these are similar to short quizzes where users answer a few questions about their preferences and then receive relevant product recommendations. This is valuable as it allows you to upsell and cross-sell products. So, for example, if someone buys a skincare product from you, you could use a product recommendation to suggest they buy a matching moisturizer.
- Assessments: Assessments are similar to quizzes but tend to be more in-depth. They can be used to collect data about student needs, interests, and even demographics in case you have an e-commerce platform to sell online courses. For example, an online assessment could be used to determine your student’s level of expertise. Based on the results, you can then recommend different courses or products.
- User Search Queries: Search queries are powerful references to understand users’ shopping intent and behavior. Even if retail platforms rule out the historical journeys, they can figure out a user’s immediate needs and the products they are most likely to buy in a given time frame. Coupled with user behavior, these queries can help predict the potential purchases in the future. For certain ad formats like Flipkart Commerce Cloud, PLA & PCA, these make very useful data for product placement in catalogs and listings that help you retain a native feel and air ads for real impact on brand sales, ROIs, and GMVs.
How To Use First-Party Data On Ecommerce Platforms
Now that we’ve seen how first-party data can impact your ad personalization efforts and overall profits, let’s look at how you can use first-party data on eCommerce platforms.
- Creating a Strategy: Even before you start gathering first-party data, you must set clear objectives. What do you want to achieve? Do you want to increase brand awareness, drive traffic to your website, or increase sales? Your objectives will determine the type of data you collect and how you use it. For example, if your goal is to increase sales, you’ll need to focus on data that helps you personalize the user experience and recommend products.
- Identifying Collaborative Touchpoints: Customers usually engage with a brand through various channels. This makes it challenging to create holistic customer profiles. Thus, you need to pinpoint relevant touchpoints where activities across channels can be merged. For example, you could use data from social media platforms like Facebook and Instagram to create targeted ads on your eCommerce website.
- Implement Proactive Data Churning: Data alone is not enough. You need to be proactive about churning it and making sense of it. This means setting up the right systems to reduce the lead time between incoming data and outgoing insights, reports, or actions. For example, you could use a data management platform (DMP) to unify all your customer data in one place.
- Incorporating First-Party Data into Personalization: Personalization is all about creating relevant and targeted content for your users. For e-commerce platforms, this means using first-party data to recommend products, offer discounts, and even create targeted ads. For example, you could use data about a user’s purchase history to recommend similar or complementary products. Or you could use data about a user on platform product search history to show them targeted ads.
- Re-engage consumers: Abandoned carts remain one of the biggest pain points for eCommerce businesses. The average cart abandonment rate is about 70%.
First-party data can help you re-engage consumers and recover lost sales. For example, you could use data about what items were left in a user’s cart to send them targeted emails or ads. Discount codes can also be used to motivate users to complete their purchases.
Well managed first party data helps cut down integration time with the latest AI/ML solutions such as FCC’s Pricing Manager & Ads Manager. Any retail -tech vendor you partner with will place this prerequisite, since long integrations, data leaks and faulty attribution models can all be prevented by building a strong data foundation. We advise partnering with mature retail tech vendors who have a deep understanding of handling user data and maintaining compliance while maximizing output. Your first part data is your most valuable asset. With the right checks and tools in place, you can leverage it to build a profitable ads business online. You can also employ the latest retail innovations with minimum downtime.
Conclusion
Now that you know how to use first-party data on eCommerce platforms, it’s time to put that knowledge into action. Start by creating a strategy and identifying collaborative touchpoints. Then, use proactive data churning to make sense of all that data. Finally, incorporate first-party data into personalization efforts to create relevant and targeted content for your users.