Why Marketers Should Explore These 4 Emerging Technology Trends – CMSWire
Marketers should explore four emerging tech trends and how they impact customer data management and consumer privacy.
For brands, the pandemic’s initial disruptions are easing, if not absent, while spiraling inflation, talent scarcity and lingering supply chain challenges continue to contest marketers’ best laid plans.
Against this conflicting backdrop, marketers seek to balance between tried-and-true, personalized campaigns with novel digital experiences that differentiate their brands.
In contrast to the new customer acquisition strategies of 2021 and early 2022, the rest of this year and next will emphasize a more comprehensive view of the customer in order to unify cross-functional data to improve customer experience (CX), drive conversions and ensure retention.
New to this year’s Gartner Hype Cycle for Digital Marketing are 4 key technologies that will help marketers with this renewed focus of integrating client data in order to drive innovation: generative AI, emotion AI, digital twin of the customer plus customer information ethics.
Here’s how digital marketing leaders can incorporate these crucial systems into their techniques.
Generative AI: Determine Initial Marketing Use Cases
Generative AI is a disruptive technology that impacts content development, CX enhancement and the generation associated with synthetic data. It learns from existing artifacts to generate new, realistic artifacts (e. g., video, speech) that will reflect the characteristics of the particular training information without repetition.
In spite of third-party data depreciation, enterprises are usually still charged with both delivering a strong CX and influencing customer decisions. Generative AI can help marketers identify the core characteristics of customers to then target them with custom content material in a privacy-compliant way.
In fact by 2025, Gartner expects 30% of outbound marketing messages from large organizations will certainly be synthetically generated.
We see generative AI take hold in digital commerce; for example, where manufacturers can generate human images for customers in order to try on clothes or makeup virtually. Avatars and virtual influencers can also engage customers on social media and in the metaverse to provide customer support.
Obstacles in digital marketers’ use of generative AI include potential government hurdles that seek to limit associated research, or the unfortunate reality of the technology being used with regard to deepfakes, fraud and disinformation.
What can electronic marketers do? Start by investigating how generative AI techniques benefit your industry plus determine preliminary marketing make use of cases where you may rely on purchased capabilities or even partnerships. Document the opportunities synthetic data could bring in terms of facilitating data monetization and lowering the cost of information acquisition.
Related Article: If You Want in order to Succeed With Artificial Intelligence in Marketing, Invest in People
Emotion AI: Explore Vendor Capabilities
Emotion AI uses computer vision, audio/voice input and more to translate behavioral attributes into human emotions, helping entrepreneurs better personalize digital communications. This is part of a larger trend we call “influence engineering, ” which seeks to automate elements associated with digital encounter that guide user choices at scale by learning and applying techniques of behavioral science.
Emotions play a key role in all phases of consumer journeys. Access to emotion data delivers insights in to motivational drivers that assist them test and refine articles, tailor digital experiences and build deeper connections between people plus brands.
By 2024, 30% of online marketers will use emotion AI, up from less than 5% today. Yet privacy concerns remain an obstacle in order to rapid adoption of many make use of cases, especially in live situations (versus lab/research environments). Hesitation around the manipulative power of emotion-aware algorithms and potential bias are prevalent, too. To avoid bias when using facial expression analysis, models must be retrained within different geographies to detect nuances due to different cultural backgrounds.
So what can digital internet marketers do? Review vendors’ feelings AI capabilities and use cases carefully in order to enhance customer analytics and behavior profiling. Appoint responsibility regarding data personal privacy in your own organization to a chief data privacy officer or equivalent and be sure they work with your chosen vendor in order to avoid user backlash because of sensitive data being collected.
Related Article: Can AI Advertising Transform Your Business?
Digital Twin of the Customer (DToCs): Run Pilots, Establish Trust
A DToC is a dynamic virtual representation of a customer that simulates and discovers to emulate and anticipate behavior. DToCs help data-rich organizations offer a more personalized, curated CX to customers, many of whose buying habits have changed due to inflation.
DToC can each transform plus disrupt: Privacy and cyber-risk concerns may lengthen the time it takes DToCs in order to mature. Plus, it’s challenging for organizations to embark on customer data ethics initiatives, which are essential to the success of DToC projects.
What can electronic marketers perform? Begin by running a pilot and comparing results along with and without a DToC and define the particular benefits in order to customers plus establish trust. Explain how they can control, or even cancel, information usage, and eventually integrate DToCs with current marketing technology systems intended for maximum utility.
Customer Data Ethics: Be Transparent
Customer data integrity aligns business practices with moral and ethical policies that reflect a company’s values. The need for such arises from the often unintended interpersonal and environmental consequences associated with using client data to maximize profits.
It’s clear that will AI is a growing force within advertising as techniques for marketing automation and personalization. The public — plus marketers — increasingly recognize the tendency of these methods to amplify biases in customer data used to train them. As businesses expand their focus on personal privacy and Environmental, Social and Governance (ESG) issues, addressing the ethical challenges of algorithmic marketing and advertising practices becomes imperative in order to keep company practices plus values aligned.
So what can digital marketing experts do? Go beyond mere compliance and treat customer information ethics as an ethos that your company publicly shares with all stakeholders. Operationalize the honest evaluation of all automated decision making and tailor global brand or corporate frameworks to specific geographies, audiences and societies. Establishing and monitoring long-term metrics that tie customer data ethics in order to economic factors (e. g., ESG ratings and brand name equity measures) will ensure the most value will be realized.
Conclusion: Determine Value for Growing Marketing Technology Trends
While investment within such technology continues apace, digital marketing leaders still grapple with the challenges associated with these powerful yet immature technologies. AI and machine learning (ML) are highly dependent upon access to consumer data, yet only 14% of companies have achieved a 360-degree view associated with the customer. Furthermore, consumer and regulatory concerns about their ethical implications might erode believe in among clients.
Digital marketers must take a critical look at each of these technology trends to determine what value they provide to their own organizations, specifically within the confines of economic headwinds.