Technology Trends Archives

For brands, the pandemic’s initial disruptions are easing, if not absent, while spiralling 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 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 four key technologies that will help marketers with this renewed focus of integrating customer data to drive innovation: generative AI, emotion AI, digital twin of a customer and customer data ethics.

Here’s how digital marketing leaders can incorporate these crucial technologies into their strategies.

Generative AI: Determine Initial Marketing Use Cases

Generative AI is a disruptive technology that impacts content development, CX enhancement and the generation of synthetic data. It learns from existing artifacts to generate new, realistic artifacts (e.g., video, speech) that reflect the characteristics of the training data without repetition.

In spite of third-party data depreciation, enterprises are 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 in a privacy-compliant way.

In fact by 2025, Gartner expects 30% of outbound marketing messages from large organizations will be synthetically generated.

We see generative AI take hold in digital commerce; for example, where brands can generate human images for customers 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 for deepfakes, fraud and disinformation.

What can digital marketers do? Start by investigating how generative AI techniques benefit your industry and determine initial marketing use cases where you can rely on purchased capabilities or partnerships. Document the opportunities synthetic data could bring in terms of facilitating data monetization and lowering the cost of data acquisition.

Emotion AI: Explore Vendor Capabilities

Emotion AI uses computer vision, audio/voice input and more to translate behavioural attributes into human emotions, helping marketers better personalize digital communications. This is part of a larger trend we call “influence engineering,” which seeks to automate elements of digital experience that guide user choices at scale by learning and applying techniques of behavioural science.

Emotions play a key role in all phases of customer journeys. Access to emotion data delivers insights into motivational drivers that help them 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. Yet privacy concerns remain an obstacle to rapid adoption of many use 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 in different geographies to detect nuances due to different cultural backgrounds.

Digital Twin of a Customer (DToCs): Run Pilots, Establish Trust

A DToC is a dynamic virtual representation of a customer that simulates and learns to emulate and anticipate behavior. DToCs help data-rich organizations provide a more personalized, curated CX to customers, many of whose buying habits have changed due to inflation.

DToC can both transform and disrupt: Privacy and cyber-risk concerns may lengthen the time it takes DToCs 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 digital marketers do? Begin by running a pilot and comparing results with and without a DToC and define the benefits to customers and establish trust. Explain how they can control, or cancel, data usage, and eventually integrate DToCs with 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 a company’s values. The need for such arises from the often unintended social and environmental consequences of using customer data to maximize profits.

It’s clear that AI is a growing force within marketing as techniques for marketing automation and personalization. The public — and marketers — increasingly recognize the tendency of these techniques to amplify biases in customer data used to train them. As organizations expand their focus on privacy and Environmental, Social and Governance (ESG) issues, addressing the ethical challenges of algorithmic marketing practices becomes imperative to keep company practices and values aligned.

What can digital marketers do? Go beyond mere compliance and treat customer data ethics as an ethos that your company publicly shares with all stakeholders. Operationalize the ethical 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 to economic factors (e.g., ESG ratings and brand equity measures) will ensure the most value is realized.

Conclusion: Determine Value for Emerging Marketing Technology Trends

While investment in such technologies 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 on access to customer data, yet only 14% of organizations have achieved a 360-degree view of the customer. Furthermore, consumer and regulatory concerns about their ethical implications may erode trust among customers.

Digital marketers must take a critical look at each of these technology trends to determine what value they bring to their organizations, especially within the confines of economic headwinds.

By Bernard Marr

We may not be living on Mars or traveling to work using jet packs, but there’s no doubt the coming decade will bring many exciting technological advances. In this article, I want to outline the 25 key technology trends that I believe will shape the 2020s.

1. Artificial intelligence (AI) and machine learning. The increasing ability of machines to learn and act intelligently will absolutely transform our world. It is also the driving force behind many of the other trends on this list.

2. The Internet of Things (IoT). This refers to the ever-growing number of “smart” devices and objects that are connected to the internet. Such devices are constantly gathering and transmitting data, further fueling the growth in Big Data and AI.

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3. Wearables and augmented humans. What started with fitness trackers has now exploded into a whole industry of wearable technology designed to improve human performance and help us live healthier, safer, more efficient lives. In the future, we may even see humans merge with technology to create “augmented humans” or “transhumans.”

4. Big Data and augmented analytics. Big Data refers to the exponential growth in the amount of data being created in our world. Thanks to augmented analytics (highly advanced data analytics, often fueled by AI techniques), we can now make sense of and work with enormously complex and varied streams of data.

5. Intelligent spaces and smart places. Closely linked to the IoT, this trend is seeing physical spaces – like homes, offices, and even whole cities – becoming increasingly connected and smart.

6. Blockchains and distributed ledgers. This super-secure method of storing, authenticating, and protecting data could revolutionize many aspects of business – particularly when it comes to facilitating trusted transactions.

7. Cloud and edge computing. Cloud computing – where data is stored on other computers and accessed via the internet – has helped to open up data and analytics to the masses. Edge computing – where data is processed on smart devices (like phones) – will take this to the next level.

8. Digitally extended realities. Encompassing virtual reality, augmented reality, and mixed reality, this trend highlights the move towards creating more immersive digital experiences.

9. Digital twins. A digital twin is a digital copy of an actual physical object, product, process, or ecosystem. This innovative technology allows us to try out alterations and adjustments that would be too expensive or risky to try out on the real physical object.

10. Natural language processing. This technology, which allows machines to understand human language, has dramatically changed how humans interact with machines, in particular giving rise to…

11. Voice interfaces and chatbots. Alexa, Siri, chatbots – many of us are now quite used to communicate with machines by simply speaking or typing our request. In the future, more and more businesses will choose to interact with their customers via voice interfaces and chatbots.

12. Computer vision and facial recognition. Machines can talk, so why shouldn’t they “see” as well? This technology allows machines to visually interpret the world around them, with facial recognition being a prime example. Although we will no doubt see greater regulatory control over the use of facial recognition, this technology isn’t going anywhere.

13. Robots and cobots. Today’s robots are more intelligent than ever, learning to respond to their environment and perform tasks without human intervention. In certain industries, the future of work is likely to involve humans working seamlessly with robot colleagues – hence the term “cobot,” or “collaborative robot.”

14. Autonomous vehicles. The 2020s will be the decade in which autonomous vehicles of all kinds – cars, taxis, trucks, and even ships – become truly autonomous and commercially viable.

15. 5G. The fifth generation of cellular network technology will give us faster, smarter, more stable wireless networking, thereby driving advances in many other trends (e.g., more connected devices and richer streams of data).

16. Genomics and gene editing. Advances in computing and analytics have driven incredible leaps in our understanding of the human genome. Now, we’re progressing to altering the genetic structure of living organisms (for example, “correcting” DNA mutations that can lead to cancer).

17. Machine co-creativity and augmented design. Thanks to AI, machines can do many things – including creating artwork and designs. As a result, we can expect creative and design processes to shift towards greater collaboration with machines.

18. Digital platforms. Facebook, Uber, and Airbnb are all household-name examples of digital platforms – networks that facilitate connections and exchanges between people. This trend is turning established business models on their head, leading many traditional businesses to transition to or incorporate a platform-based model.

19. Drones and unmanned aerial vehicles. These aircraft, which are piloted either remotely or autonomously, have changed the face of military operations. But the impact doesn’t stop there – search and rescue missions, firefighting, law enforcement, and transportation will all be transformed by drone technology. Get ready for passenger drones (drone taxis), too!

20. Cybersecurity and resilience. As businesses face unprecedented new threats, the ability to avoid and mitigate cybersecurity threats will be critical to success over the next decade.

21. Quantum computing. Quantum computers – unimaginably fast computers capable of solving seemingly unsolvable problems – will make our current state-of-the-art technology look like something out of the Stone Age. As yet, work in quantum computing is largely restricted to labs, but we could see the first commercially available quantum computer this decade.

22. Robotic process automation. This technology is used to automate structured and repetitive business processes, freeing up human workers to concentrate on more complex, value-adding work. This is part of a wider shift towards automation that will impact every industry.

23. Mass personalization and micro-moments. Mass-personalization is, as you might expect, the ability to offer highly personalized products or services on a mass scale. Meanwhile, the term “micro-moments” essentially means responding to customer needs at the exact right moment. Both are made possible by technologies like AI, Big Data, and analytics.

24. 3D and 4D printing and additive manufacturing. Although this may seem low-tech compared to some of the other trends, 3D and 4D printing will have very wide applications – and will be particularly transformative when combined with trends like mass-personalization.

25. Nanotechnology and materials science. Our increasing ability to understand materials and control matter on a tiny scale is giving rise to exciting new materials and products, such as bendable displays.

Read more about these 25 key technology trends – including practical examples from a wide range of industries – in my new book, Tech Trends in Practice: The 25 Technologies That Are Driving The 4th Industrial Revolution.

Feature Image Credit: Adobe Stock