Projections indicate that retail media ad spending in the United States will surpass $100 billion by 2027, more than doubling its current levels. To harness this growth, retailers must strike a delicate equilibrium, crafting engaging and memorable experiences while embracing privacy-safe solutions. With the phased elimination of third-party cookies and identifiers, retail media networks need to commit to privacy-focused solutions, robust data-driven measurement models, and AI-powered innovations to seize real-time engagement opportunities for a prosperous future beyond 2024.
Step 1: Implement privacy-focused solutions to enhance customer relationships, foster trust, and provide a meaningful value exchange.
Anxiety about online privacy is a concern for 80% of consumers in surveyed countries today.2 Therefore, your primary focus should be on ensuring that any data you collect builds trust in your brand and aligns with people’s privacy expectations. This entails clearly communicating your privacy policies and providing individuals with transparency, choice, and control over the usage of their data. This becomes even more crucial for retail media networks, which heavily rely on robust first-party data.
Once retail media networks effectively convey their policies and data management practices, consumers are more willing to share their data. In fact, Boston Consulting Group discovered that over 90% of consumers are open to disclosing their personal information in exchange for the right incentives. To deliver value to shoppers in return for their first-party data, benefits such as tailored messaging and loyalty programs prove to be attractive incentives that enhance the convenience and value shoppers receive. As a retailer’s relationship with customers develops, the resulting first-party data can then be leveraged to enhance marketing campaigns, anticipating customer needs and delivering relevant and timely messages that contribute to business growth.
Step 2: Establish a data-driven measurement framework for precise evaluation of customer interactions.
As privacy-centric solutions are developed, and as first-party relationships evolve, retailers and brands require a solution capable of automatically interpreting these available signals to provide the most comprehensive reporting. Data-driven measurement is of paramount importance to offer a more comprehensive perspective on the performance of retail media – a quality that brands anticipate from retail media networks. This attribution model offers a deeper understanding of all the touchpoints that influence a customer’s purchase decision, as opposed to solely attributing conversion credit to the last click prior to purchase. The evidence lies in the outcomes: those transitioning from a non-data-driven attribution model to a data-driven one typically observe an average 6% increase in conversions.3 By employing conversion modeling, which harnesses machine learning trained on first-party data and other signals, advertisers attain the most accurate measurements. Additionally, leveraging Google Analytics 4, which prioritizes privacy, enables a more profound exploration of activities across your websites and applications.”
Step 3: Drive expansion with AI-driven solutions to engage both new and existing customers
As privacy-centric solutions are developed, and as first-party relationships evolve, retailers and brands require a solution capable of automatically interpreting these available signals to provide the most comprehensive reporting. Data-driven measurement is of paramount importance to offer a more comprehensive perspective on the performance of retail media – a quality that brands anticipate from retail media networks. This attribution model offers a deeper understanding of all the touchpoints that influence a customer’s purchase decision, as opposed to solely attributing conversion credit to the last click prior to purchase. The evidence lies in the outcomes: those transitioning from a non-data-driven attribution model to a data-driven one typically observe an average 6% increase in conversions.3 By employing conversion modeling, which harnesses machine learning trained on first-party data and other signals, advertisers attain the most accurate measurements. Additionally, leveraging Google Analytics 4, which prioritizes privacy, enables a more profound exploration of activities across your websites and applications.”
