Marketers should investigate four emerging technology trends and how they affect customer data management and consumer privacy.
For brands, the early turmoil of the pandemic is easing if not gone, but soaring inflation, talent shortages and lingering supply chain challenges continue to upend marketers’ best plans.
Against this backdrop, marketers are trying to balance proven, personalized campaigns with the fresh digital experiences that differentiate their brands.
In contrast to our new customer acquisition strategy in 2021 and early 2022, for the remainder of this year and next year we will focus on cross-functional data to improve the customer experience (CX), drive conversions and ensure retention. Emphasize a more holistic view of the customer to consolidate.
New to this year’s Gartner Hype Cycle for Digital Marketing are four key technologies that help marketers refocus on unifying customer data to drive innovation. Generative AI, Emotional AI, Customer Digital Twins, and Customer Data Ethics.
Here’s how digital marketing leaders incorporate these key technologies into their strategies.
Generative AI: Determining Early Marketing Use Cases
Generative AI is a disruptive technology impacting content development, CX enhancement, and synthetic data generation. Learn from existing artifacts to generate new realistic artifacts (video, audio, etc.) that reflect the characteristics of the training data without repetition.
Despite the depreciation of third-party data, companies still have the responsibility of delivering strong CX and influencing customer decisions. Generative AI helps marketers identify key characteristics of their customers and target them using custom her content in a privacy-compliant manner.
In fact, Gartner predicts that by 2025, 30% of outbound marketing messages from large organizations will be synthetically generated.
We are seeing generative AI take hold in digital commerce. For example, a brand can generate an image of a person to allow customers to virtually try on clothes and makeup. Avatars and virtual influencers can also engage with customers and provide customer support on social media and the metaverse.
Obstacles to digital marketers’ use of generative AI include potential government hurdles to limit relevant research and the unfortunate reality of the technology being used for deepfakes, fraud and disinformation. increase.
What Digital Marketers Can Do Start by researching how generative AI technology can help your industry and determine the initial marketing use cases where you can rely on purchased features and partnerships. Document the opportunities that synthetic data can present in terms of driving data monetization and reducing the cost of data acquisition.
Related article: Invest in people if you want to succeed with artificial intelligence in marketing
Emotion AI: Exploring Vendor Capabilities
Emotion AI uses computer vision, audio/voice input, and more to translate behavioral attributes into human emotions, enabling marketers to better personalize digital communications. It’s part of a larger trend we’re calling “influence engineering.” It seeks to learn and apply behavioral science methods to automate the elements of the digital experience that guide user choices at scale.
Emotions play an important role at every stage of the customer journey. Access to sentiment data provides insight into motivational drivers that can help you test and refine content, tailor digital experiences, and build deeper connections between people and brands.
By 2024, 30% of marketers will use emotion AI, up from less than 5% today. However, privacy concerns remain Many use cases, especially in live situations (versus lab/research environments). Hesitations and potential biases in the manipulative power of algorithms that recognize emotions are also prevalent. To avoid bias when using facial expression analysis, the model should be retrained in different regions to detect nuances due to different cultural backgrounds.
What Digital Marketers Can Do Carefully review vendor sentiment AI capabilities and use cases to enhance customer analytics and behavioral profiling. Appoint a data privacy officer within your organization to be the Chief Data Privacy Officer or equivalent and work with your chosen vendor to avoid user backlash for collecting sensitive data.
Related article: Can AI Marketing Transform Your Business?
Customer Digital Twin (DToC): Run a Pilot and Establish Trust
DToC is a dynamic virtual representation of a customer that simulates and learns to emulate and predict their behavior. DToC helps data-rich organizations deliver more personalized and curated CX to their customers. Inflation has changed many of our customers’ buying habits.
DToC can be both transformative and disruptive. Concerns about privacy and cyber risk may lengthen the time it takes for DToC to mature. Additionally, it is difficult for the organization to undertake customer data ethics initiatives that are critical to the success of his DToC project.
What Digital Marketers Can Do Start by running a pilot and comparing results with and without DToC Define customer benefits and establish trust. Describe how you can control or cancel data use and ultimately integrate DToC with your existing marketing technology systems for maximum utility.
Customer Data Ethics: Be Transparent
Customer data ethics aligns business practices with moral and ethical policies that reflect the company’s values. Such a need arises from the often unintended social and environmental consequences of using customer data to maximize profits.
It is clear that AI is becoming an increasing force in marketing as a method of marketing automation and personalization. The public, and marketers, are increasingly aware that these techniques tend to amplify biases in the customer data used for training. As organizations grow more concerned with privacy and environmental, social and governance (ESG) issues, it becomes imperative to address the ethical challenges of algorithmic marketing practices to align corporate practices and values. .
What Digital Marketers Can Do Beyond mere compliance, treat customer data ethics as a spirit that companies publicly share with all stakeholders. Operate an ethical assessment of all automated decision-making and tailor the framework of a global brand or company to specific geographies, audiences and societies. Establishing and monitoring long-term metrics that link customer data ethics to economic factors (such as ESG ratings and brand equity measures) ensures maximum value is realized.
Conclusion: Determining the Value of Emerging Marketing Technology Trends
Investments in these technologies are making good progress, but digital marketing leaders grapple with the challenges associated with these powerful yet immature technologies. AI and machine learning (ML) rely heavily on access to customer data, yet only 14% of his organizations achieve a 360-degree view of their customers. Additionally, consumer and regulatory concerns about ethical implications can undermine trust among customers.
Digital marketers must look critically at each of these technology trends to determine what value they bring to their organizations, especially within economic headwinds.