The Evolution of Digital Marketing in the Era of AI

The Evolution of Digital Marketing in the Era of AI

The Evolution of Digital Marketing in the Era of AI Data privacy has taken the spotlight recently, reshaping the way businesses approach digital marketing. Overarching federal and state regulations combined with changing technology, like the deprecation of third-party cookies and the rise of global ad blockers, will make it increasingly important for marketers to stay ahead of the curve. As concerns over data security and consumer privacy continue to grow, marketers are confronted with a unique challenge: how to engage audiences effectively while respecting their privacy and remaining in compliance with regulatory legislation across geographies. However, amid this shifting paradigm, artificial intelligence (AI) emerges as a powerful partner, offering inventive solutions that not only save valuable time for marketers but also unlock fresh avenues for personalized, dynamic, and impactful digital marketing strategies. This new era of digital marketing marks a transformative journey, where AI paves the way for businesses to thrive in a world that values data privacy and creates meaningful and authentic connections with customers. Since the beginning of the internet, companies have been collecting, storing, analyzing, and activating user data. Third party cookies have played a large role in this process. However, popular browsers like Firefox and Safari have retired the use of these snippets of code that store user data, and Google’s Chrome is not far behind. Similarly, Apple’s App Tracking Transparency has had a large effect on publishers like Facebook and Instagram, and advertisers, big and small. The data collection process has grown in sophistication as businesses invest in marketing technology such as customer relationship management software (CRM) like Salesforce and data management platforms (DMPs) like BlueKai and customer data platforms (CDPs) like Segment. New entrants to the advertising technology industry also offer tools for creating a personal relationship with customers in an AI-driven world. Data Privacy In the past few years, data privacy concerns have become mainstream. Facebook’s Cambridge Analytica and other similar scandals, combined with high profile security breaches and hacks have led to increased attention and oversight by governing bodies and regulators. Most notable, GDPR and CCPA were rolled out by the European Union and the State of California, respectively, and have led the way for additional regulations to follow. While the United States does not currently have federal regulation over data privacy, many states are following California’s lead and have either passed legislation or are in process. Notably, 13 additional states including Virginia, Utah, Indiana, Connecticut and Colorado, have enacted comprehensive privacy laws at the state level, with many more pushing active bills through the process. Consumer rights such as the right to access, correct, delete, and opt out are at the top of the agenda. While business obligations such as required transparency notices, risk assessments, and prohibition on discrimination are also important factors. Figure 1 US State Privacy Legislation Tracker 2024 Source: IAPP Additionally, the use of third-party cookies in browsers is becoming obsolete and will essentially end in 2024, when Chrome officially retires them (although that date has been moved back several times). Apple’s sweeping changes to how they handle user privacy have also caused waves. Essentially, their App Tracking Transparency allows users to choose whether an app can track their activity across other apps and websites. Furthermore, users with child accounts or those managed by an educational or business account may not be tracked. Not surprisingly, this has affected advertisers, data brokers, and publishers in their ability to collect data. Apple has taken the position that users want transparency and control over how their personal data is handled but advertisers see things differently. For businesses reliant on digital advertising, the deprecation of third-party cookies and ATT represent the loss of certain targeting capabilities such as lookalike audience modeling and retargeting. Consequently, this can be equivalent to loss of engagement, interaction, leads and ultimately sales. Data Landscape Along with this evolving data privacy ecosystem comes challenges as well as opportunities. Brands must keep their customers at the center of everything, as they navigate changes related to data privacy, regulations, and transparency in the world of technology and marketing. Marketers must be aware of this evolution so they can continuously adjust their approach to data and privacy for their stakeholders. While companies and marketers have traditionally relied on first, second- and third-party data sources in the past, a new era is upon us where zero party – or ethically sourced – data is moving to the forefront. Third party data is that which has been purchased, typically through a broker like Acxiom, Experian, CoreLogic or Oracle. In recent years, purchasing third party data has become an outdated and ineffective practice. Similarly, second party data which has been obtained through partners or affiliates, has begun to fall by the wayside. That leaves the coveted first party data source. First party data, that which is obtained directly from users typically through marketing, can include ads, websites, mobile apps, email, SMS, point of sale, beacons, call centers, live events, and more. Although first party data has been an integral part of an overall marketing strategy, there are numerous challenges associated with it. Challenges include the ability to collect, store, and analyze the data but also the ability to resolve identity and profile information to make the data actionable. Further, many users are not aware that their data is being collected and are quick to opt out or unsubscribe as quickly as possible. Similarly, many users have become more educated and thus more untrusting leading them to give fake information or create fake profiles, thus gaming the first party data system. Fresh Approaches to Marketing Although many businesses still rely on first, second-, and third-party data, another type of data has emerged. Zero party data (ZPD), often called ethically sourced data, represents data that users have willingly and knowingly shared with brands, usually in exchange for something they value. ZPD provides an opportunity for brands to build an authentic and valuable connection with customers. Rather than falling back on deceptive techniques that force users to share their data, with zero party data, customers know their data is being collected and agree to share it in a value exchange. Value can be created in many ways. For example, custom quizzes to create personalized product or promotional experiences are an important mechanism for increasing brand loyalty. When customers feel their voices are being heard and have influence on their involvement with a brand, they are more likely to become repeat customers and ambassadors. In fact, companies like Jebbit specialize in creating uniquely personalized experiences meant to help businesses build their zero party data. These experiences can come in the form of engaging quizzes, polls, and surveys as well as enhanced forms and content opportunities. Companies like Gillette and PepsiCo are focusing on building their zero party databased while leveraging best in class technology tools to leverage data in a more efficient and effective way. Quizzes and polls can run within ads on popular social media sites like Instagram and Facebook and offer customers with an interesting and fun interaction with a brand. Zero party data offers brand the opportunity to authentically build a dialogue with customers who truly want that connection. Generative AI In the brave new world of data transparency, generative AI technologies such as machine learning, large language models and chatbots, enable marketers to create tailored, data-driven experiences for their customers. This leads to improved brand trust, awareness, and engagement. Tools like ChatGPT, MidJourney, Grammarly, Synthesia, Cleanvoice and others can streamline marketing operations and free up cherished time for busy marketers to focus on strategic planning, creativity and building customer relationships. Alongside the convenience of AI comes the caution, as well. Of course, data privacy and compliance are at the top of the list. Businesses must ensure compliance with any and all regulations such as GDPR, CCPA and others. Companies should also clearly and transparently share their compliance and data privacy policies as well as citing their use of generative AI. Marketers must also be aware of the inherent bias and inaccuracy within AI models and regularly audit and test these tools to take steps toward mitigating bias and identifying inaccuracy. Finally, marketers must not over rely on AI. The human touch brings tone, voice, and connection into the brand. An overreliance on AI can lead to a loss of trust and erode brand confidence over time. To face the future of digital marketing, a mix of AI and human contribution is the best approach for brands. Here are seven ideas (plus tools!) to help brands stay ahead of the curve by evolving their digital marketing strategy. Content Personalization: Using AI combined with human oversight, brands can analyze user behavior and internal data to generate personalized content recommendations in real-time. Providing users with relevant and meaningful content can increase the desire for users to share data and information back to a brand. Criteo, Optimizely, and Adobe Target can enable marketers to create and deliver personalization at scale. Chatbots: AI-powered chatbots can help engage customers and gather additional information on behalf of a brand. Chatbots can offer assistance, product recommendations, scheduling, task tracking or applicable content based on data collected during the conversation. Tools like Slack, Trello, Zendesk, and Drift offer different ways to integrate chatbots into the strategy. Surveys, Quizzes, Feedback Forms: AI can assist with the creation of dynamic ways for users to submit their preferences, while providing immediate feedback and personalized recommendations. Qualtrics, Survey Monkey, Feedbackly, and Typeform are examples of AI powered tools for surveys. Exclusivity: Creating exclusive membership or loyalty programs can deliver customers significant and unique value with offers, promotions, and perks. Customers are often willing to share more of their information in exchange for this type of exclusivity. Personalization engines like Dynamic Yield and Evergage or AI powered loyalty providers like and Yotpo can be useful tools. Predictive Analytics: Using machine learning or AI to analyze historical data, brands can predict user preferences and behaviors. These predictions can be leveraged to proactively create dynamic content, campaigns, offers, and promotions that align with user preferences. Companies are using IBM Watson and Google Cloud’s AI/AL solutions for predicative analytics capabilities. Testing and Optimization: New tools can provide marketers with fast and effective ways to test and experiment in their digital marketing efforts by optimizing website layouts, dynamic ad versioning, email subject lines and more. Tools like OfferFit and Unbounce make rapid experimentation more accessible for busy marketers. Translation: Language translation has never been easier, thanks to AI tools like, Google Translate and DeepL. Many AI tools offer translation of text, images, videos and audio using state of the art natural language processing algorithms in a user-friendly interface. In conclusion, digital marketing is evolving to meet the growing challenges it faces. Marketers must embrace this new era of data privacy and changing technology. A thoughtful balance of AI and human touch will expand brand trust while saving time and enhancing productivity. Kelly Cutler is program director at Northwestern University Medill School. The views and opinions expressed in Industry Insights are solely those of the contributor and do not necessarily reflect the official position of the ANA or imply endorsement from the ANA.

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