Amazon has become a disruptive force in retail and e-commerce, partly because of their seamless user experience, but mostly because of their intelligent use of customer data to influence purchases.
According to BloomReach, 55% of US online shoppers start their product searches on Amazon. Smarter data and insights are a driving force behind Amazon’s success in understanding its customers’ purchase intent. The power of intent—the ability to anticipate what a customer needs when they need it—has driven the value of search, but marketers should be applying the power of intent across all channels.
As more data on consumer buying habits, interests, and social activity has become available, marketers need to take these data sets into consideration as they optimize their marketing strategies.
Marketer’s leveraging Data Sources
With more than two billion active users, Facebook has become a leading platform for marketers to share brand messages with consumers. According to eMarketer, Facebook is estimated to take in over two-thirds of social media advertising revenue worldwide in 2017. However, internet users only spend 20 percent of their time on that one platform. Marketers see Facebook as an easy solution to reach audiences, but user behavior and profiles even on Facebook are still incomplete. Imagine building a shopping mall, and only using buyer behavior from one store to get a sense of the market.
Today, marketers can gain a holistic view of their audience's interests, passions, and behaviors, by collecting data from each user action on every website they use. When customers visit websites, they leave swaths of data points on what they’ve shared and clicked on, the amount of time they spend on a page, where they’re located, and how they arrived to the site.
By analyzing all of these data points, marketers can get a better understanding of a customer's journey. They can then leverage this insight to craft the message that will most resonate with their target consumers based on who they are and which stage they are in the purchase journey.
Real Time Audience Interest
Because online behaviors and trends change rapidly, data has a limited shelf life. Marketers have to be able to refresh their audience data and augment their CRM files based on real-time insights to reach the right audience at any given moment.
Bombarded by ads at every turn, consumers start to tune out the ads that don’t appeal directly to their passions and needs. Targeting consumers based on their interests not only helps marketers, but also helps customers. According to a recent report, 71% of consumers want personalized ads.
Google, for example, regularly changes their keyword search results based on user intent in order to deliver a better user experience based on what a person is looking for.
All Data is Not Created Equal
It’s advantageous to have a vast amount of data to analyze a target audience. With the right data science and analytics hundreds of data points can provide valuable insight to improve targeting, creative and overall campaign effectiveness.
However, when it comes to data, it takes far more than scale to ensure a campaign will be successful. True ROI depends on data quality and insight into user intent.
All data is not created equal. For marketers, it is clear that first party and first party permission data deliver the strongest value—which is why we’re seeing more marketers have shifted to building their data stacks in-house. Additionally, marketers have to examine everything from refresh/expiration issues to combining disparate data sources.
Direct and clean sources of first and second party data, from publishers or your own CRM files, can provide you with better insight into interest and intent. Just visiting a website, viewing a product page, or fitting in a certain demographic group does not always indicate an intent to purchase. This is where basic retargeting fails -- when done improperly, it can lead to negative effects for marketers, especially if the retargeted ad is no longer relevant and there are no frequency caps to stop the irrelevant ads.
It takes more than just scale and quality of data to maximize marketing effectiveness. Marketers need to look for behavioral patterns in data sets to truly identify interest and intent-based signals. By applying machine learning to enrich data sets, marketers can precisely target the right audience with the right message.