This article is sponsored by TransUnion
Connected consumers have an unprecedented ability to decide what content they consume and how it’s accessed. This empowerment has fueled a growing demand for personalized experiences, with 76% of consumers expecting companies to understand their needs, according to research from Salesforce.
Brands are achieving that deeper understanding in part by turning to first-party data – a critical asset with important constraints tied to privacy legislation, data scrutiny and the end of the third-party cookie.
Yet almost half of marketers lack confidence in their ability to activate against multiple data sets, according to Kantar, and 90% can’t connect multiple channels across the buyer journey.
While marketers have increased focus on their own data, a critical eye on third-party, sourced data has only uncovered how greatly advertisers still depend on it for basic marketing capabilities. That’s why seasoned marketers are taking more stock in tools and technologies that help leverage additional, complementary data holistically to make the most of their own audience insights.
Marketers have noted accuracy as one of the biggest hurdles in leveraging their own data. An infrastructure of cross-verified data sources – based on a reliable truth set – is an effective mechanism to validate internally sourced data, improve accuracy, and fill in gaps. This additional data also helps create more depth, uncovering customer insights and scaling a marketer’s overall addressable universe.
Brands need a strong understanding of customer preferences to build meaningful, one-to-one connections and experiences. Data insights are critical to personalizing the customer journey, particularly in the early stages where external, sourced data helps improve your understanding of consumers.
Most companies also require help to link data sets to customers across channels and devices, especially as audience inventory becomes more partitioned across various channels such as advanced TV and publisher domains.
Harnessing predictive power
Predictive modeling remained one of the top priorities occupying marketers’ time, attention and resources last year. That’s because modeling distills multiple, large data sets to drive meaningful decisions often based on existing customer data.
Predictive modeling extends the utility of internally sourced data by using correlative third-party data to create predictive audiences. Marketers can leverage a customer data sample to help identify people who look like high spenders, customers who purchase across multiple product lines or are likely to respond to digital offers, or power any other campaign objective.
Modeling helps companies anticipate customer preferences by revealing the data attributes commonly shared between marketers’ best customers and other users. Backed by a foundation of customer data, marketers can tap into predictive modeling and other insights to identify millions of additional prospects across marketing channels who look like existing customers.
Driving interactions across the entire journey
High quality third-party data increases the value of your first-party data. Marketers who properly cultivate their own data will find external data sources a valuable asset – if they validate it and focus on insights that best drive accuracy, personalization and decision-making.
Without the right tools, marketers may find evolving expectations and behaviors of connected consumers a challenge. But with the right data and technology to understand behaviors and preferences holistically, marketers can act in ways that build goodwill at every stage of the buyer journey.
