Marketing is something that has long been characterized by rapid change.
Strategies must quickly adapt to technological advancement, algorithm updates, new regulations, and shifting customer expectations.
This is set to continue, and marketers could well be taking advantage of brain interface technology, augmented reality, and robot advertising by 2030.
Virtual reality could be so real that people are truly able to try before they buy.
Advertising could be completely optimized for cars, and alter their channel automatically for the deaf or blind.
The landscape is constantly shifting, like sand dunes in the desert, and competition is fierce.
And, within this context, integrating the latest technologies into their marketing strategies is recognized as essential for companies to keep their edge.
Even before considering the implications of COVID-19 on global strategies, five years is a long time in marketing.
Alternative social media platforms, like TikTok, Twitch, and Clubhouse, have emerged to challenge more seasoned ones, while changing indexes have forced marketers to adapt how they approach search engine optimization (SEO).
Beyond such changes to more orthodox marketing channels, this time period has been long enough to identify a number of important trends - which will be outlined below.
These new trends represent key components of any company’s overarching strategy, and can be seen as guiding principles that will enable you to stay relevant online and drive marketing effectiveness.
User Experience (UX) refers to the process of designing products and services with a firm focus on all user interactions - from a brand, usability, and functionality perspective.
As the digital era evolves and competition inevitably increases, UX has become increasingly important in providing that edge and making customers come back.
Ultimately, if the last five years have taught companies anything, it is that the user experience needs to be front and center if your overarching marketing strategy is to be effective, with research backing this up:
The last five years have undoubtedly seen digital marketing increase in importance.
Overall, companies should now be dedicating between 10.4% and 13.7% of their revenue to marketing (CMO Survey 2021), and managing these limited resources effectively is key to success in a ferociously competitive marketplace.
But marketing budgets have tanked, sitting at 6.4% of company revenue in 2021 - the lowest level in recorded history (Gartner).
In this context, the cost effectiveness, convenience, and results-driven nature of digital marketing goes some way to explaining the continued shift in the landscape away from more traditional marketing channels.
The research backs this up. Globally, advertising spend on traditional formats - like television, newspaper, and real-world placement - is predicted to plummet by 20.7%, as digital channels receive a greater and greater share of the budget (Finances Online).
By comparison, digital advertising is expected to exceed 60% of total spending for the first time in 2022, and will pass 65% by 2024 (Zenith Media).
Thanks to the mushrooming number of smart devices and advances in data collection and management technology, the amount of data available to marketers is bigger than ever.
Personal data is now the world’s most valuable resource (Economist).
Today, it can give marketers a level of understanding about their prospects and customers that was unimaginable even a decade ago, and enables them to respond immediately to market changes and drive sales.
Consequently, analytics software - and the tech-based insights that can be drawn from related solutions - has grown in importance for marketers over the last five years. This is because they are the most effective way of using big data to create better, more personalized marketing campaigns.
Today, 97.2% of companies are investing in big data and artificial intelligence (New Vantage), with analytics software central to how marketers interpret the mind-boggling amount of data at their disposal.
In 2018, 3.9 billion people used the internet globally (Statista). This figure had already grown five times over since 2015, and yet is expected to pass the five billion mark in 2022.
And, as an ever-increasing proportion of human activity takes place online, so has the importance of internet security and privacy.
Consequently, the number of national and international data protection laws has grown exponentially over the last five years.
This was spearheaded five years ago by GDPR, but the rest of the world is following Europe’s lead, and today, over 120 countries have introduced legislation to restrict what companies can do with the data of internet users.
These changes are forcing companies to adapt data management strategies to ensure legal compliance in a privacy-centric world.
Many more laws are in the pipeline, and existing ones are being modified to fix issues that have so far restricted their effectiveness.
As the burden on marketers has only increased over the last five years, they have looked to cut costs and increase the efficiency of data mining and communication across the full customer journey by using marketing automation.
Put simply, this software takes a lot of human involvement out of marketing channels - like email, social media, and websites - and enables companies to dedicate employees to the work that would most benefit from a human touch.
One useful automation tool is Multi-Channel or Multi-Touch Attribution, which enables marketers to simultaneously track all their various channels, and to assess their effectiveness at collecting leads that convert into sales.
Another is dark social media tracking, which gets its name from the difficulty that comes from gaining insights from privately sent messages and content.
This rush to automation has been a huge trend in a time of many, and will only become more important as marketing budgets continue to shrink.
Marketing strategies have had to be completely restructured over the last five years to respond to changes in user expectations, as well as in response to martech innovations and privacy legislation in a shrinking economy.
A key business-to-customer trend is community building - a marketing strategy that brings people together around a subject in a way that is engaging but non-intrusive, and that puts them first.
There has also been a move towards localized and personalized digital marketing, which needs to be integrated seamlessly into the full customer lifecycle to ensure that they get the best service possible.
Business-to-business activity has seen a shift towards account-based marketing (ABM). This approach identifies the key decision-makers at prospect companies, who can then be contacted with personalized messages and content.
The COVID-19 pandemic was unprecedented in our lifetimes. And, while the health of the world’s population sits head and shoulders above every other concern, economic prosperity has a real bearing on people’s standard of living and cannot be ignored.
This feeds into both the success of businesses and the job security of their employees.
Consumer spending dropped considerably during COVID-19, and companies responded to this by reducing marketing budgets and adopting shorter-term strategies.
With governments easing restrictions and most businesses now open again, there’s real confidence that life is returning to normal.
However, COVID-19 has substantially changed consumer habits and catalyzed sweeping changes in every walk of life, and we’ll look at the trends that look like they are here to stay.
The COVID-19 pandemic had a seismic impact on how people lived their lives. A huge number of people barely left their homes; things got more expensive for everyone, and global consumer price indexes shot up, placing an upward pressure on wages.
People have also grown accustomed to zoom meetings, quasi-immediate deliveries, and door-step pickups. This has brought with it expectations of customer experiences that bridge the divide between the physical and digital worlds.
In effect, the pandemic has made the customer experience more important for companies than ever before, with 73% of people saying that it is a key factor in their buying decisions (PwC).
However, the customer experience includes everything from user personalization and up-to-date technology to cross-platform integration and community support.
It also means integrating the marketing department with sales, customer service, IT, and others. Even the best marketers would struggle to integrate these into outreach strategies and redesign the customer journey in time to capitalize on it.
Crucially for marketers, people are using the internet differently.
With local shops closed and people stuck inside, people started buying more things online and internet sales skyrocketed.
Global online sales rose to $4.28 trillion (Statista). In Latin America, 13 million people bought something online for the first time.
Customer preferences have also changed according to new realities. Figures show a steep decline in brand loyalty, as if they couldn’t find something online, they had no choice but to seek out an alternative.
However, the pandemic was a real cash cow for companies that had already invested in digital, with 90% of the top online sites seeing double-digit revenue growth (GlobalData).
Others have cottoned on, and this rush to digital is visible in the 11.3% growth in digital spending by marketers during this time (Deloitte).
Beyond the squeezing of marketing departments that are being forced to do more with less, the way people work has also changed.
The number of people working from home increased massively, forcing companies to reassess how employees could communicate better remotely, and to change accordingly.
This has resulted in a substantial increase in the use of remote technology, such as video conferencing and cloud computing, and many training courses and industry events have also migrated online.
What’s more, the COVID-19 pandemic also exposed operational weaknesses that companies never knew existed and spurred many to rebuild digital practices from the ground up.
Spending on digital technology increased notably during the COVID-19 pandemic, and has clearly increased the speed of digital technological adoption in marketing by a good few years, which has gone through somewhat of a revolution.
In February 2021, 42.8% the marketers surveyed reported that their company had recently invested in marketing automation technology, for instance (Rackspace); while 42.5% reported investment in data integration technology - up 71% in a year.
The near complete lockdown suffered by people meant that, even if they were venturing outside to shop in the real world, they were sticking closer to home than before COVID-19. Consequently, Google searches containing the keywords “local” and “business” exploded by 80% (Google Search).
What’s more, the pandemic increased public knowledge about the vulnerability of supply chains, and the desire to support both local businesses and worthwhile causes grew significantly.
Marketers have been forced to adapt strategies to these new preferences.
This has required the adoption of geolocational technology and personalized outreach - so as to target specific neighborhoods. This is then sent out using community networks, which have flourished during the pandemic.
The COVID-19 pandemic has sped up change for marketing departments like never before, and all indications are that mutating customer expectations and the complexity of marketing strategies are here to stay.
As a result, the global health emergency has also ushered in more recognition for the difficulty and importance of modern digital marketing, as well as its effectiveness when done properly.
In June 2020, 62.3% of companies surveyed believed that the importance of marketing had grown over the last year, and this figure jumped to 72.3% six months later (CMO Survey).
The effects of the COVID-19 pandemic are still with us, and economic recovery will take far longer than the vaccine took to create. Unemployment is still high, as are consumer prices - a result of both rebounding demand and constrained supply.
Artificial intelligence (AI) and machine learning - key elements of the next internet generation - will fundamentally change digital marketing, and this technology has already been creeping into the back end of platforms that people are using every day.
For companies, AI is more accessible than ever, and this enables marketers to analyze data, predict future trends, and enhance the quality of their outreach.
Data volumes will only increase as we move forward, and AI’s capacity to quickly analyze data and integrate it into marketing strategies - while saving companies money - means that the marketing industry will have to adapt with it, or businesses will be left behind.
Augmented reality is another key component of Web 3.0 and, by blurring the border between online and real world shopping, it is arriving on the scene at just the right time to capitalize on post-COVID-19 consumer expectations about engaging experiences.
One of the main issues with the current 2.0 generation of the internet is the freedom it has given companies with regard to user data. However, stricter privacy laws have now placed real restrictions on what marketers can do with this information, shaking up the way digital marketers have long worked.
Technology offers no easy solution to this problem; as such, the need to acquire user consent before harvesting their data forces companies to place the customer relationship at the center of any first-party data strategy.
The marketing technology landscape has been growing at an incredible rate, with the number of marketing technology solutions growing from 150 in 2011 to 8,000 in 2020 (Chief Martech). That’s 5,233% growth in 9 years!
The industry was worth $344.8 billion in 2021 (Martech Alliance), and will continue to grow as new innovations reach the market, and marketers search for new ways to securely capitalize on big data and make their jobs easier.
Quality and engaging content will need to sit at the center of any marketing strategy, with research showing that nearly half of consumers will read three to five things before speaking with a salesperson (Hubspot).
The importance of engaging content will only grow in the future - the only question being what medium marketers should use to make it as exciting as possible for internet users.
Live video - being versatile and easy to create - is one option that is growing in popularity. Another is interactive content, which encourages user participation, and which 93% of marketers believe is effective for educating buyers (Demand Gen).
And, as with everything, all content needs to prioritize customers first, and this means using the wealth of data available to understand your audience and to calculate how best to reach them.
Search Engine Optimization (SEO) will continue to be vital, and should be used alongside content and data to maximize results - in fact, it remains the top inbound marketing priority for 61% of marketers (Hubspot).
However, SEO work will need to be adapted to new realities - particularly with regard to images and videos, which are growing in popularity as search vehicles.
Voice search is another search area that will require focus over the next few years, if not today. Alexa and Siri are now fully integrated into the lives of many, while Microsoft Cortana and Google Assistant are also increasing in popularity.
Indeed, 55% of households already own a smart speaker in 2022 and 76% of users take advantage of voice search at least once per week (BrightLocal).
As we move forward, optimizing content to be viewed on smartphones and other devices on the Internet of Things will continue to grow in importance for digital marketers.
This vitality has been spurred further by Google’s mobile-first index, which means that SEO work will not bear fruit unless content is optimized for smartphones.
Put simply, if content is compatible with mobile devices, users are much less likely to walk away from it.
Native advertising is paid media that has been designed to fit seamlessly into the content of a media source.
Research shows that consumers look at native ads 53% more frequently than traditional display ads (Sharethrough and IPG Media).
They’re much more contextual than traditional advertisements, and are a great way for companies to associate themselves with particular subjects.
The modern world is changing quickly - people today expect a wide range of choice, immediate transactions, and next-day delivery. It’s fast moving and, for marketers, standing still really does mean falling behind.
Before anything else, the reason to keep pace with technology is simply to keep up with competitors and stay relevant to customers, but there are a range of other reasons, which we’ll go through below:
Estimates are that there are over 100,000 software companies in the world; this translates into a huge amount of martech to choose from, and makes it almost impossible to keep pace with innovation.
But by choosing the right martech, companies can better meet customer expectations, improve overall operational efficiency, and give themselves a competitive edge.
Internet usage is growing. In 2021, the number of users stood at 4.9 billion, which is almost two-thirds of the total global population - this is a staggering figure, and one that will grow to 5.6 billion in 2025 (Statista).
This is a large pool of consumers and prospects for digital marketing, but its size also makes audience targeting even more important and advancements in technology mean that marketers need to use locational, contextual, and segmentation data to completely personalize every element of the consumer journey.
In this context, choosing the right martech is vital for business success in a fiercely competitive market.
The technology that the internet is built upon is constantly advancing, meaning that marketing practices can quickly become outdated.
This is crucial for survival in an environment where over 40% of businesses will disappear in the next decade, unless they can restructure their entire company around the latest technology (Cisco Systems).
By contrast, more “digitally mature companies” are generally better able to navigate the massive changes happening within the post-COVID-19 marketplace, and bring in much more revenue.
Indeed, Futurist, Jim Carroll, believes that the leading 10% of companies that were successful during the last financial crisis were characterized by their investment in world-class innovation during what was a time of real economic uncertainty.
Cybersecurity is an arms race between innovations in malware and hacking techniques, on the one hand, and defense and enforcement, on the other. Security measures that were effective five years ago are much less reliable today, and keeping up with technology is therefore vital for minimizing security risks.
The political climate is also less forgiving. Given that high profile data breaches make for daily news, it is unsurprising that people are increasingly concerned about how their personal data is used online.
What’s more, a great many believe that brands are complicit in the wider problems that plague the internet - putting more onus on companies to be seen to be prioritizing data security.
As such, managing security risk is now essential to marketing, as is keeping software secure in the face of complex threats.
The legal risk to companies that do not look after the personal data of internet users is now central to their success. Under GDPR, for instance, companies can be fined up to €20 million, or 4% of worldwide turnover for the preceding financial year (whichever is higher).
However, our research shows that 42% of marketers only know “some things” about GDPR, 29% said they knew “very little”, and a worrying 19% said that they knew nothing at all.
Thankfully, new privacy-centric marketing technology is arriving onto the market every day, with many such platforms designed to help marketers stay compliant with privacy legislation.
Keeping pace with technological developments here will become more and more vital as we move forward.
We won’t try to redefine this entire concept, so here are three of the most common definitions of AI:
Wikipedia: Artificial intelligence is intelligence demonstrated by machines, as opposed to the natural intelligence displayed by animals including humans.
Google - Oxford Languages Dictionary: the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
Britannica: the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.
There are two types of artificial intelligence:
General AI: the science fiction AI you can see in the movies. This one is based on the idea that machines can and will become self-aware in the future. This, of course, is implausible at this point in its development and is just a good movie storyline.
Functional AI: the real thing that you’re already interacting with (maybe without even knowing it); the one that can help you with your marketing, business development, or career advancement.
Currently, AI programming is done by trying to copy the way the human brain functions. But the truth is we don't actually fully understand how our own brains work, so how could we be capable of writing code based on something we don't entirely understand?
Even so, by writing code that imitates how we think our brains function has led to creating systems that are far more powerful than any other previous programming we as humans have created.
And nowadays you can easily access and make use of these systems to unveil vital information that could change your entire marketing strategy.
Natural languages processing, computer vision, and machine learning solutions are just some of the AI technologies that can help you skyrocket your KPIs.
The future is already here and we want you to be ready, so here’s a short intro to some of the most widely used AI tactics:
Do you like talking to inanimate objects? That’s fine (we are not here to judge), especially if that object is answering you back.
Natural Language Processing, or NLP for short, is the interaction or meeting point between human and computer languages, teaching and allowing systems to analyze and replicate language-related data.
Siri, Alexa, and Google Assistant are the most famous examples of AI that use natural language processing to interact with you, the user.
They’re capable of listening, responding, and even learning through each interaction.
Customer support bots also fall into this category. For example, ChatBot uses NLP to interpret human speech and deliver personalized answers, and machine learning to constantly improve its performance.
Advanced NLP systems are able to comprehend text and transcript, they perform speech recognition, and some are even capable of human sentiment analysis.
Grammarly is one of those tools. It uses artificial intelligence and natural language processing to identify the tone of voice, correct words, suggest rephrasing, and all in all help you improve your content writing.
Do you know how sometimes in life you have to prove you’re not a robot? Like when you’re meeting your future in-laws for the first time, or you’re trying to sign in to an old account and you forgot your password, or sometimes even when you are creating a new account.
There’s a great irony here.
Whenever you get a reCaptcha asking you to prove you are not a robot by selecting “all the squares with street signs/ street lights/ busses/ etc.”, you are actually teaching a robot/computer system to recognize and isolate that particular object from a complex image.
Without even knowing it, you are contributing to improving Computer Vision programs for Google Street View, Maps, and for self-driving cars.
If NLP is the technology able to recognize speech and text, Computer Vision is the one able to identify images and videos.
Computer Vision is behind those Instagram filters that allow you to catfish innocent people.
This computer programing recognizes where your eyes are, how big or small your forehead is, and based on an algorithm it places those fake lashes and puppy ears exactly where the creator (of the filter) intended them to be.
This division of AI can provide you with creative ways to increase your conversion and engage with your target audience.
For example, in eCommerce marketing, Computer Vision is widely used for recommending similar items.
If you are online shopping for clothes and you look at a pair of blue sweatpants, computer vision-based algorithms will recommend to you, on that very same page, a bunch of other blue pants or sweatpants. This has been a proven method to increase overall sales.
You can read more here on How AI is Changing the Future of Digital Marketing.
Machine learning is a subset of artificial intelligence; it is the science behind computer algorithms that can improve and develop automatically through repetition and experience.
Through machine learning, computer programs can learn and adapt their algorithms and statistical models to analyze patterns and similarities in large amounts of data.
Machine learning can be used for problem-solving, repetitive work, forecasting, and removing obstacles in your day-to-day work as a marketer.
There are three main types of machine learning, each of them used for solving different types of problems.
All these types of ML models look inside big piles of data for specific patterns and models and, based on those, build rules in order to answer specific questions or make predictions.
This type of machine learning is based on input-output rules. You give your computer labeled data and a set of rules, and based on those rules it can extract detailed answers for some of your very specific questions.
Supervised machine learning takes place when you educate your algorithm through example and correction.
And we circle back here to the reCaptcha images. It would be hard to write a code that would allow the machine to recognize street signs since there are many variations out there, but if you show the machine a million different street sign images, it will eventually learn to recognize them.
Of course, it will sometimes get them wrong, but as long as you correct it, it will eventually learn from its mistakes and avoid them.
Supervised learning is recommended for identifying patterns (competitor patterns, client patterns, etc), comparing them, and recommending outputs (like recommending ideal leads).
On the other side of supervised learning, we have unsupervised learning.
This is where you give your computer a large amount of unlabeled data, with no rules or corrections, and it tries to create rules and patterns on its own in this massive amount of data anarchy.
This machine learning method is able to discover previously undetected patterns that you might have not even thought about. And this is the beauty of it.
Besides finding patterns, it will also unveil similarities and differences in your data that might make you rethink your entire marketing strategy.
New correlations between your customers' traits might come up. For example, 40% of the people who brought item X also came back and purchased item Y. Of course, then you will push item Y to all the people who want to buy item X from now on.
This is the method where the machine learns on its own through trial and error.
With reinforcement learning, you give your machine a task and a goal, and it learns from the results of its own actions. You only need to set some clear parameters around the task and allow it to do some testing in order to find the best output.
For example, reinforcement learning AI can be used in email marketing with the goal of increasing open rates. The program will look at your previously sent subject lines, test out a few variations, and find the most effective one after sending out different batches of emails. It's like A/B testing on steroids.
Do you run online ads? Know that programmatic advertising is based on machine learning. You might have been using machine learning without even knowing it.
If in the past you would choose your ad’s target by selecting their location, gender, age, etc., nowadays programmatic advertising does the matching for you based on algorithms.
It basically takes what it has learned from previous experiences and optimizes the placement and the target’s traits in order for you to have the best outcome from your ads - be it reach, conversions, clicks, or others.
Machine learning programs will most certainly be used in the future to offer each and every user a personalized shopping experience.
Because everybody is unique and wants to be treated accordingly, personalizing communication to the very last detail was proven to increase conversions and customer loyalty. And, although this is complicated to do nowadays, this is something very likely to happen in the future.
Yes, no doubt about it. Embrace the change.
So what you need to take from all of this boring theory is that AI and machine learning algorithms are great at recognizing patterns, ranking, sorting, and prospecting lookalikes, and can basically save you a lot of time and headaches.
Why would you spend hours or days trying to correlate data yourself when a program could probably do that in seconds?
The answer here should be pretty obvious that you shouldn’t, but keep in mind that there’s also the financial aspect of deploying machine learning for your business.
Can you afford to hire data scientists and pay them to develop an artificial intelligence tool specifically tailored for your marketing needs? Congratulations, you are rich!
Or should you just use the affordable machine learning tools that are already available on the market?
You can browse through a list of such tools we’ve put together here.
Don’t know where to begin with implementing AI into your business? Try this:
Way back in 1994, Paul Milgram defined the transition between the physical world and the new digital worlds, calling it the Reality-Virtuality Continuum.
That term has now evolved into XR (eXtended Reality).
This umbrella term encompasses Virtual Reality (VR), Augmented Reality (AR), Mixed Reality (MR), and any other future realities.
Augmenting the perception of reality using digital elements in real world environments. Think games like Pokemon Go, various phone filters, or shopping apps like IKEA Place.
Could be called the opposite of AR, AV augments the perception of a virtual space using real-world objects in digital environments.
A fully digital environment using headsets to immerse the user in the virtual world.
A continuum where digital and physical realities mix in real-time. Includes both AR and AV.
For many marketers, thinking about using XR can be overwhelming; in truth, it can seem more complicated than it actually is in reality.
There are more and more tools out there, which make it much easier for marketers to benefit from XR - and there are a whole host of benefits.
By utilizing AR - a technology that is standard on most smartphones now - marketers can provide users with more ways to interact with their products or services.
VR can add even more depth to the experience by placing the user in a world that a company creates exclusively to showcase their products.
Seeing or hearing about a product in an ad is one thing; actually using it is entirely different.
AR/VR improves a user’s connection with a product or service by letting them try it on, see how it works, and imagine what it would be like to own it.
This experience provides a more concrete and emotional experience, leading to higher rates of purchase.
AR/VR takes your marketing efforts to another level. And most often, customers will notice that.
Although XR is becoming more commonplace, there are still ways to stand out. Finding those ways will get you more shares on social media, more mentions in the news and on blogs, and more opportunities to reach people who may have never heard of you.
XR is a unique experience, and with it comes unique sets of data. You can learn more about your potential customers by seeing how they interact with your product or service in AR/VR. And, as a result, you can then better refine your marketing strategy.
When you think of the metaverse, you might first think of Meta (which is pretty good marketing by Mark Zuckerberg), but the metaverse is more than just Meta and it has been around for a lot longer.
The term metaverse was first used in 1992 in the novel Snow Crash, by Neil Stephenson. In the novel, the metaverse is a dystopian virtual reality that replaces the real world since humanity has made it unliveable.
Regardless of the connections you can make to the current state of our world, most tech giants now view the metaverse more as a utopia.
In this version of the metaverse, it would be a “unification of physical and virtual realities enabling peer-to-peer, lifelike interaction in digital environments. Collaborations would imitate real-world experiences where AR/VR elements would combine to allow users to experience palpable conditions unbounded by the laws of physics.”
Metaverse technologies are expected to be valued at $800 billion by 2025 (Bloomberg Intelligence) and could possibly reach the $2.5 trillion threshold by 2030.
The metaverse stack that Microsoft is creating would replicate real-world assets, such as workspaces, warehouses, retail stores, etc. These digital twins could be used to train employees and simulate other business processes.
Using Pixar’s Universal Scene Description technology, Nvidia created an open-source omniverse. Their version of a metaverse is a 3D web browser that people can log in to using laptops. The browser is built as a place that connects everyone. End-users and content creators can connect and accelerate their 3D workflows, while developers can use the tech stack to build new tools and services.
Currently, there is no functionable version of the Meta metaverse, but they intend to dedicate approximately 30% of their resources to create AR and VR projects. Their vision of the metaverse includes AR/VR and smart glasses, which will enable people to socialize, learn, work, collaborate, and play in 3D worlds.
Unlike some other video game companies, Epic Games is investing $1 billion to create an open-source platform. The current name is the Epic Megaverse, and they have partnered with Spire Animation Studios to help create engaging metaverse experiences.
Many metaverses will accept, or even exclusively use, cryptocurrencies for all transactions. NFTs (Non-Fungible Tokens), using blockchain technology, can be used to establish ownership and authenticity.
The cornerstone of any metaverse is XR. These technologies make it possible to create digital worlds or digital objects that users can interact with. But what makes this even more important for the metaverse is the immersive, interactive world building and the social connection. A single-player VR game is not the metaverse, but a shared experience - like a meeting or other interaction - is.
In the world of gaming, AI is often seen in the form of NPCs (non-player characters). These characters will allow for more sophisticated interactions as AI advances. In other versions of the metaverse, AI could be used for image classification, facial recognition, natural language processing, location & mapping, and high-end computer imaging and refinement.
Advanced 3D modeling and graphics allow the metaverse to look as close to the real world as possible. AR/VR have been around in some form for many years, and 3D modeling has come a long way. If you think back to the early days of polygon models, that experience is interesting, but there is still a disconnect since it does not really feel like the real world. Better 3D modeling will allow people to really immerse themselves in the environment since it will feel more like the real world.
Not to get too technical about it, but edge computing is a form of distributed computing that brings data storage and computing closer to the sources of data. This will allow for faster response times and save bandwidth. With advanced VR requiring so much data, edge computing will enable faster data processing - making the metaverse experience more complex and fluid.
5G is very important in making the metaverse mobile. While edge computing is important for faster processing, it has to go hand-in-hand with more advanced mobile networks that can handle so much data at the same time.
AR/VR really are everywhere these days.
A lot of the time, we don’t even realize we are using these technologies - that’s how commonplace they have become.
These are just a few examples of how they are used in marketing, but there are many more out there.
The app, IKEA Place, lets customers place furnishings in their own space to see if it’s the right size, style, and function before they buy it.
Adidas & Gucci
If customers aren’t sure if a new pair of Gucci or Adidas sneakers are for them, their AR app lets them try on the shoes before they buy them.
Redecorating rooms can be difficult, but Home Depot has made the process a little easier by allowing customers to use an app to choose a paint color.
The AR app changes the color on the walls of any room and uses real lighting to show how the color will look in real life.
Alzheimer’s Research UK
To show the impact of dementia and to increase donations, Alzheimer’s Research UK has created a VR app called “A Walk Through Dementia” that enables people to experience the debilitating disease first hand.
Movie posters are not interactive at AMC. Customers can open an app that scans the movie poster and then watch a trailer, read reviews, and even purchase a ticket.
To enable better financial trades, CitiBank created a system that allows traders to visualize financial data and records in real time.
With every new type of technology, there are new types of data and often more of it in general. And with all this comes the question about how we protect that data.
XR technologies collect a lot of data about users - a lot more than social media, browsers, or other forms of technology.
Not only is there a lot of data, but it is also much more personal than, for example, clicks, IP addresses, or web behavior.
AR/VR technology uses much more biometric data: iris/retina scans, fingerprints/handprints, face geometry, voiceprints, finger tracking, and eye tracking. As of right now, this data is almost impossible to anonymize, as people have a unique set of movements and behaviors that can be replicated with a high degree of accuracy.
This raises a lot of questions:
There are four main types of data associated with XR: observable, observed, computed, and associated.
|Data Type||Examples in AR/VR||Utility in AR/VR||Privacy Considerations||Mitigation Approaches|
|Observable||Virtual personas or likenesses (i.e., avatars); digital communications or messages real time in-app in world interactions; identifying in-app/in-world assets (e.g. screenshots, recordings virtual objects)||Generates virtual presence unique to the user and allows them to interact with virtual spaces and objects||User anonymity and autonomy||Disclosure and user consent; user privacy settings; encrypted communication; limits on a enforcement; laws against personal autonomy privacy violations|
|Observed||Location and spatial data (eg. geolocation, lidar); motion/hand/eye tracking; raw inputs from BCI data; user-provided biographical and demographic information (e.g. name, age, interests); linked social media profiles; user-generated behavioral data and activity logs||Creates and enhances immersive experience; positions user in virtual space; enables advanced functions (e.g. interacting with virtual objects, gesture controls, and more realistic avatars)||User anonymity and autonomy; security of sensitive provided information; potential for discriminatory use of provided information by third parties||Disclosure and user consent; access controls; encryption or local storage for certain data; limits on enforcement use; laws prohibiting discrimination based on certain information|
|Computed||User profiles (e.g., for recommendations or advertising); biometric identification; biometrically derived information||Improves services and enables advanced functions||Security of sensitive inferred information; potential for discriminatory use of inferred information by third parties||Disclosure and user consent; users able to contest or correct information; encryption or local storage for certain data; laws prohibiting discrimination based on certain information|
|Associated||Login credentials; contact information; payment information; friend lists; non-identifying virtual assets, device IP address||Associating content and preferences with specific users or devices; identifying devices and allowing for Internet-enabled functions; enhancing services with additional information||Fraud or malicious misuse; harms from combining with other forms of user data||User authentication; disclosure and user consent when combining with other data; laws establishing standards for information security|
As we have seen recently, laws are often unable to keep up with technology. This puts people and institutions at risk. So, what can be done?
Web 3.0 is the next stage in the development of the internet.
Described by some as the “decentralized web” and by others as “the semantic web”, Web 3.0 is the umbrella term for a broad range of new technologies that are revolutionizing our online world.
This new internet generation started to emerge between 2005 and 2010, and is based around the central guiding principles of security, identity, trust, and user control.
And, once it becomes fully realized in the coming decade, websites and apps will be capable of processing information with human-like accuracy.
Even casual internet users will be able to run their own servers, completely control what happens to their personal data, and use a secure digital currency to buy things online from anywhere in the world.
This is possible thanks to breakthroughs in both hardware and software, including artificial intelligence, machine learning and, in particular, blockchain - which is laying the foundation for what lies ahead.
And, like flicking a switch to light your home or using a smartphone, users do not have to understand how this advanced technology works to benefit from it.
What Came Before Web 3.0?
Web 1.0 existed during the 1990s and was basically “read-only”.
This first internet era simply allowed users to find information, and they did not have much opportunity to create their own content or interact with other people.
A good example of this internet era is GeoCities - a personal webpage with information about the site owner, but which remains static.
Web 2.0 existed during roughly the first decade of the new millennium, and is still how most people use the internet today.
It is known as the “social web”, with YouTube, Facebook, Twitter, and Amazon being its most famous components.
Web 2.0 was built around the internet users themselves, and made it easier for them to interact with others and buy what they wanted.
However, as Web 2.0 developed, it became clear that the internet had not ushered in a new dawn of democracy and freedom. Fake news, user privacy concerns, data hacks, and identity theft have instead become the fundamental online issues of today and show that web development still has a long way to go.
What’s more, Web 2.0’s business model was built on the sale of user data to third parties for marketing campaigns without meaningful consent.
Consequently, a small number of Silicon Valley companies have exploited user data to grow enormously rich and powerful. They quickly became the gatekeepers of Web 2.0, with most internet traffic flowing through them.
In this context, and by changing the very structure of the internet (or how we use it), Web 3.0 is seen as a way for users to take back power and control.
Web 3.0 empowers internet users through its defining characteristic - decentralization.
Decentralization is made possible by blockchain, which represents a giant leap forwards in database technology.
In practice, this means that user data is spread between the computing resources - including smartphones, appliances, sensors and vehicles - that belong to the users of the network, and does not need to travel via companies like Google, Apple, or other social networking sites.
This enables strangers to share personal information in complete safety and without the risks that come with third parties gaining access to their data.
Today, the better known applications of blockchain include:
Crucially, internet users also become shareholders of Web 3.0 networks, since they can actively participate in how these blockchains develop.
This is because every time someone posts comments or content, they also earn shares in the network - in the form of tokens or cryptocurrency.
Once they earn enough of these, they then have the power to make decisions about how the network will take shape. This democratization of online spaces explains the excitement that Web 3.0 inspires in so many of its proponents.
Ultimately, Web 3.0 enables marketers to seamlessly tailor campaigns to the preferences and locations of each individual user, meaning that they can better engage with customers, improve business intelligence, and sell more products.
Let’s look at the advantages for marketers in more detail:
Web 3.0 enables marketers and advertisers to re-establish trust and reconnect with their consumers, by giving them control and ownership over their data - and providing actual value.
Since personal data is stored on the user’s own blockchain, rather than in servers run by large third-party companies, it is much better protected from data breaches and identity theft.
Smart contracts are also great for building relationships with customers; they are self-executing, with the terms of the agreement written directly into the lines of code - removing human error from the arrangement.
Ultimately, smart contracts build trust; they save time, reduce conflict, and are cheaper, faster, and more secure than traditional payment systems.
While the elimination of third-party ID verification means companies have less hard data about their customer base, Web 3.0 actually improves business intelligence.
Web 3.0 supports user-generated digital content and user interaction in a data-secure environment, and this will undoubtedly encourage consumers to be more open.
Companies will therefore be able to tap into this and adapt their marketing strategies accordingly.
Companies that take advantage of Web 3.0 technology are able to provide a more user-friendly process, since the preferences of prospects and customers will be provided automatically through the blockchain.
Not only will content automatically integrate user preferences like content language and consent sentences, but it will also do away with the form filling and broad transfer of personal information that often puts people off from signing up with companies.
The amount of data available to companies is growing every day.
Crucially, the number of devices plugged into the internet is also growing exponentially - creating what is known as the “Internet of Things” (IoT).
Examples of IoT include wearable health monitors, connected home appliances, and so forth - connectivity that increases the digital immersion of people in their everyday lives.
Web 3.0 is also known as the “Semantic Web”. What this means is that existing online data can be structured and tagged in such a way that it can be interpreted by artificial intelligence, allowing for patterns of user behavior to be easily pulled out and integrated into marketing campaigns.
This is great news for marketers, since it enables them to collect previously unobtainable data about how people interact with devices and products, as well as analyze their buying habits across platforms and behavior.
A Web 3.0 environment enhances user experience by providing rich and interactive advertising opportunities, enabling marketers to deliver more personalized ads to consumers.
Augmented reality is another channel that digital marketers will be able to leverage to their advantage.
NFTs undoubtedly offer another opportunity for marketing campaigns and will reshape the marketing experience. They can simplify transactions and, by associating them with a product and creating buzz, can further boost sales and pull the digital and physical worlds closer together.
The integration of artificial intelligence will automate many company processes and procedures here, meaning that they can allocate resources to the parts of the journey that would most benefit from real human involvement.
Companies will also no longer have to worry about protecting user data, removing their data privacy responsibilities - which can be challenging under strict modern privacy laws.
For smaller businesses particularly, the decentralized nature of Web 3.0 will undoubtedly mean that they’re better protected from the threat posed by larger players.
It will reduce costs for various business elements, such as intermediary services, referrals, and advertising, and give them more bargaining power.
Web 3.0 hasn’t fully arrived yet; critics argue that it is utopian, and that many ideas won’t be completely realized because today’s major tech companies won’t be supplanted easily. Nor would it be simple to regulate a completely decentralized online space.
As such, predictions about how far Web 3.0 will develop - or the practical implications for marketing - are difficult to make.
But Web 3.0 is, at least in part, already here.
Google’s integration of social media signalers into its ranking algorithm is in itself undeniable evidence that Web 3.0 strategies should be added to digital marketing practices today.
But geotargeting, semantic coding, and user reviews are also commonplace, as are artificial intelligence and machine learning.
One thing that is already clear is that the Web 3.0 elements that have been introduced are making data collection more challenging for companies. With traditional marketing methods going out of the window, companies will need to adapt to new ideas or lose their competitive edge.
Put simply, digital marketing in Web 3.0 is moving away from traditional channels, like websites, email, and social media.
Instead, the decentralization of Web 3.0 means that marketing will become more about interacting directly with customers and prospects.
And, by blurring the space between online space and the real world, Web 3.0 provides new opportunities for companies to reach out to people.
Web 3.0 offers a far more interactive and immersive experience with regards how content is created and consumed.
And, without the involvement of intermediary platforms, internet uses will have considerably more control over what marketing they will and won’t accept.
In practice, this will result in an increase in both the quality and quantity of marketing content.
Marketing will also need to align with the hyper-personalized experience afforded by Web 3.0 technology. This extends to voice searches that deliver a seamless online journey, as well as to websites that will have to move away from their current static form and adapt what is shown to the historical behavior, preferences, time of day, and location of each visitor.
The collective ownership of decentralized blockchains, and the shares that users earn from participation, means that digital marketing could well need to become incentive-based to be effective.
The result of this would be an increased reliance on internet users as marketers themselves, within a mutually beneficial environment for companies and consumers alike.
And, while this may sound like pie in the sky, you only have to watch Bill Gates’ Letterman appearance to understand how baffling the initial concept for Web 1.0 was to people back in 1995.
The internet has undoubtedly brought great benefits to society, but the issues of online privacy and security are impossible to ignore.
In this context, the optimism around Web 3.0 rests on its capacity to address these fundamental problems, enabling internet users, companies, and machines to share data with far greater security, and we’ll run through the main advantages below:
The key privacy characteristic of Web 3.0 is its removal of third parties from internet use.
Since Web 3.0 is built on blockchain, this technology is decentralized and means that no single person, group, or organization has full control over the network.
Instead, the data belongs to the users themselves, who also benefit from decentralized identity technologies with no “middleman”.
This means that users will no longer need to rely on third party platforms, or will at the very least be able to better use them on their own terms.
Removing the involvement of Big Tech platforms also takes away the risks they pose to breaches and data exploitation.
Decentralization also means that huge amounts of data will not be stored in a single place, with a single point of access.
As such, data breaching is minimized and any that do occur will not affect large numbers of users.
Additionally, governments will not have access to our online data.
For hackers, blockchain technology represents a significant hurdle to stealing any worthwhile quantity of data.
Since information is spread across a vast network of personal devices - smartphones, computers, appliances, sensors, vehicles, and so forth, hacks have to break into over half of them to infiltrate the network. Given the work involved, such attacks are rare.
Blockchains enable internet users to verify their identity themselves, reducing the number of people that have access to their sensitive information.
User data is opaque, and advanced encryption methods mean that their identity is separated from the data itself. This enables users to interact with networks without giving too much personal data away.
People can use cryptographically-secure digital identities to trustlessly complete transactions, without sharing sensitive personal information - so, personal data no longer makes internet users the product when it comes to the internet.
This means that Web 3.0 is much more secure than the internet generations that came before, giving internet users better data security and identity protection.
Web 3.0 technology enables new forms of decentralized identity, including self-sovereign identity (SSI) that enables user control over their credentials without the involvement of third parties - giving them far greater control over what information they share and protecting their privacy.
Crucially for data sharing, while blockchains are impossible for anyone but the internet users to change, they are visible to virtually anyone. So, when built on this technology, users can see who has access to their data, and will be the ones to decide when, how, and for how long to share their personal data with others.
This is helped by the fact that user data is encrypted to the point that it is completely unbreakable, preventing companies from exploiting data without explicit user consent.
In the future, instead of providing personal data for each platform you use, users can simply decide in a single place what data they authorize platforms to use.
No technology is free from risk and Web 3.0 is no different.
Decentralization brings with it its own issues, since it means that data sits outside of secured centralized servers that have only one point of entry.
As such, the number of ransomware attacks, cryptocurrency breaches and data leaks looks set to continue as Web 3.0 technology becomes more widespread, particularly because of the nature of decentralization that makes it very difficult for authorities to identify responsibility for data control or catch hackers.
Confidentiality of Data
Since personal data will flow through artificial intelligence and will be scanned by machines, there is a likelihood that data confidentiality can be compromised. Personal data could also be accidentally released or moved to an unsecure location.
Manipulation of Data
One concern with Web 3.0 is the potential that artificial intelligence could be programmed with the objective of intentionally manipulating data, or to manufacture whatever results they want.
A good example here is when Microsoft set up its chatbot “Tay” to learn human behavior from Twitter, but people intentionally sent malicious tweets and trained it to be racist.
Smart contracts bring with them the risk of logic hacks and the lack of legal protection when things go wrong.
Decentralization also might make it difficult to identify liability and, even if you file a lawsuit, the anonymization of legal contracts adds further complications.
There is also the risk of “rug pulls”, in which investors lose their funds when cryptocurrency developers run away from the project.
The biggest example of this to date is Thodex, where over $2 billion in cryptocurrency disappeared.
Looking at Web 3.0 from the perspective of policymakers, decentralization makes it difficult to identify the controller and processor of personal data.
It is also unclear how internet users will be able to delete or change personal information on and off the blockchain, and how data access requests will work - and who exactly will be responsible for this.
Distributed content hosting also makes it difficult to work out the national jurisdiction that a particular website falls under.
This lack of centralization and data access also makes policing cybercrime, including online harassment and extortion, more difficult. How can the police enforce hate speech laws when they can’t identify internet users?
Web 3.0 may well dash the hopes of enthusiasts who see it as a way to completely take power back from large organizations, as it's likely that it will operate alongside Web 2.0.
But with Web 2.0 companies already integrating this new technology into their platforms, its final form will become more clear as we move forward.
Web 3.0 is built around the principle of data security, but it is still vital that security measures are built into it from the outside. New risks will no doubt arrive, and only time will tell whether users and businesses will benefit from the many potential privacy benefits.
Now that you've had a quick introduction to the basics, take a look at our quick explainer video about How Web3 will Help Digital Marketing to make sure that you understand what this might mean for you as a marketer.
The best martech stacks are considered future-proof, in that they fully integrate cutting edge technology into company systems and processes. This enables marketers to optimize communication across channels in a way that will work effectively now and in the future.
But it is an ever-shifting landscape, with two-thirds of marketers having altered their stacks in the last year (Martech Replacement Survey 2021).
Trends come and go, and once popular options - like Adobe and Sitecore - have lost their market share as marketers have become more selective.
This is a clear illustration of both the speed of innovation in the sector, and how complicated it can be for marketers to rely on choices made in the long term.
One issue here is the real agony of choice available to marketers, with over 8,000 different platforms now available - a 5,233% increase in options over the last decade.
Given this, building a future-ready martech stack requires marketers to understand which features are fundamental to wider company goals and which will be most beneficial to their own ambitions - especially given resource constraints.
And, while it’s a little too early to predict what the stack will look like once Web 3.0 has been fully realized, this new internet technology will undoubtedly bring many revolutionary backend changes.
This chapter will run through what this technology is, before giving advice on how marketers can build their stack from scratch in a way that enables them to work together logically and efficiently - a priority for any marketer today.
Marketing Technology - or Martech for short - is the term for a range of tools that enable marketers to communicate with internet users across the full customer lifecycle, garner more information about their customers and campaigns, automate certain processes, and make their work easier as a whole.
Think of each platform as a different app on your smartphone; taken together, they enable marketers to measure and improve the effectiveness of marketing campaigns, automate repetitive tasks, and improve the back-end functionality of other tools.
Martech is different from other IT systems, in that each tool often exists only to address a single specific task - though this is changing. And, while they can be effective when used independently, each platform becomes exponentially more useful when integrated with other technology.
This is called your stack, in which your various platforms share data and functionality to improve marketing outreach, and which is made up of 120 different tools for the average marketer (Chief Martech).
An effective martech stack integrates all your cross-platform marketing work into a single system. It supports every stage of the customer journey, centralizing all data, resources and analysis, and brings the following benefits to companies:
The last decade has seen real advancements in the martech landscape, and there are now tools available that can optimize marketing at any type of business.
However, the makeup of any stack will be different from company to company, reflecting different sizes, objectives, and preferences.
Since no two companies work in the same way, no two companies should have the same martech stack - or use it in the same way.
And, while the sheer magnitude of tools available makes it difficult to generalize about all of them, martech generally falls into the following categories:
Most companies simply search online for the “best martech stack” and opt for whatever advice they see first. But choices made like this will not reflect the real needs of your business or include the features that could most benefit your work.
Nor are any companies really building their stacks completely from scratch; they already use key components, but have simply not considered integrating them together.
For instance, a website is often the hub component that marketers build their stack around, though others choose a customer relationship management platform or automation tool.
The best advice for anyone that is considering building their stack is to start by establishing the foundations before laying anything else on top of it. As such you should begin with the basics:
Once this is in place, you can start building your stack, which will look something like this:
Drawing a map like the one above is crucial, since it will help you understand how the various elements in your stack integrate together to deliver overall marketing success.
You’ll also want to create a roadmap for establishing your martech stack, which can be done by following the steps below:
As a rule, you should only adopt the martech you actually need; start by evaluating what platforms your company requires to stay competitive in the industry. Identify your marketing priorities and goals, any challenges faced by your team, and establish your martech budget - this will enable you to make better, more informed decisions.
Draw up a map of all the different marketing technologies you already use - this will allow you to identify gaps in your existing ecosystem, and to decide on which ones to discard, upgrade, or replace.
Research the various alternatives under consideration - assess how useful their features are against your wider objectives, and identify the factors that will ultimately dictate your final decision.
Once you have chosen the best ingredients for your stack, you’ll want to set each platform up according to your preferences. This work will also require building tasks and workflows depending on what martech you’ve chosen, so as to integrate these tools into your company’s wider systems and processes.
It’s also important to remember that, to reach its full potential, your martech stack will cut through company departments - particularly IT, sales, and marketing. As such, cross-departmental collaboration is essential if your stack is to work effectively.
To get the most out of your martech, it’s important that all employees are invested in it, and are training accordingly. It’s often considered highly beneficial to install a “champion” to help promote and evangelize each new platform.
Once implemented, you’ll want to regularly assess the effectiveness of your marketing stack, identify issues, and decide how best to rectify them - switching platforms if necessary.
Ultimately, this analysis will be based on the return on investment of your tech stack, which reflects how effectively it has been designed.
In practice, a well designed martech stack will take time to develop, particularly since these tools will need to be fused with wider company systems and processes, and across departments.
It will also need to be adapted regularly in response to things like changing marketing objectives or the introduction of new martech innovations - as such, you need to ensure that your stack remains dynamic.
Businesses are investing significant resources into martech, putting marketers under pressure to optimize the tools they’ve been given and provide a sound return on investment in a challenging environment.
However, the task of building and integrating an effective and future-proof martech stack can be overwhelming - since it requires expertise to manage and coordinate all the various tools so that they work together effectively.
Unfortunately, the right people with the knowledge and expertise to help build a stack are few and far between, and marketers remain undertrained. They also often don’t fully understand what martech they already have, making the requisite investment redundant, and find it difficult to build a stack with all the tools they need.
Data security and privacy features also remain at a premium, and marketers find it hard to ensure that data is shared seamlessly across a stack, and to manage this data effectively.
Furthermore, for a martech stack to work effectively and create a seamless customer journey, it’s essential that all company departments adopt these tools and use them consistently. But this can be difficult in practice - and experience has shown that buy-in from sales is an issue for many companies.
The ever-growing number of options available is also making the stack more complex than necessary, and it is difficult to keep up with new technological trends and innovations.
And as marketing becomes more tech heavy - and with effective data security measures more important than ever - it makes sense for companies of any size to employ an expert who can ensure that it all runs smoothly, and can train other staff.
Given the importance of online work to modern marketing practices, martech is marketing today - a well designed stack helps you work smarter, not harder, and streamlines communication throughout your company.
Ultimately, businesses will sink or swim depending on how effectively they capitalize on the marketing tools that are available to them.
As such, without a roadmap for creating a fully integrated martech stack, marketers stand at a real competitive disadvantage.
The landscape continues to evolve quickly as technology becomes more advanced and data-centric than ever, and only those that continuously educate themselves can hope to keep up.
What’s more, research shows that marketers think that they are only using 58% of their martech’s potential (Gartner CMO Spend Survey), and only one in five marketers have a strategy in place for optimizing their stacks (Ascend2).
As such, this information can help you to find the right martech, and to use it effectively. It can also help you to understand why staff martech training is so important, particularly given that external experts are becoming more and more expensive.
GDPR was enacted only four years ago, ushering in a new era that limits what companies can do with the personal data of internet users.
Since then, many martech platforms have come onto the market that have been designed to ensure that data handling meets strict rules on compliance and privacy.
However, marketers still find it difficult to find options with strong data security and privacy features. But this will certainly change in the coming years, as more innovation comes onto the market.
The threat posed by cybersecurity is bigger than ever, with the proliferation of martech tools creating new data access points that hackers can exploit.
This is a real concern, with 58% of marketers considering it their top priority when choosing martech (Treasure Data).
Given the prospect of sanctions for companies that poorly protect user data, martech platforms are increasing security features, and future innovation will see the arrival of platforms that offer cross-platform cyber protection.
This refers to the next generation of digital technology that is reshaping how users and marketers alike are approaching the internet, and includes innovations like blockchain, cryptocurrency, smart contracts, and Non-Fungible Tokens (NFTs).
Martech will adapt to integrate into this new decentralized environment, further enhancing the personalization of communication, and cutting out Web 2.0 middle men, like Twitter and Facebook.
Marketers are well aware of the potential offered by artificial intelligence, with this technology already integrated into tools like chatbots and website analytics.
However, it will become more and more prevalent in the years to come, as marketers look for ways to work more efficiently and increase personalization while keeping data secure - a priority in the years ahead.
The Metaverse is a fully realized digital world; it includes elements such as virtual reality and augmented reality. It will take time to develop and its final shape remains unclear, but it represents a real opportunity for marketers looking for fresh ways to engage with their customers.
Modern innovation now means that marketers can use a range of mediums to deliver content to users in new and exciting ways - including live videos and podcasts.
Innovation in digital marketing continues to skyrocket, introducing new technologies that make it easier for companies to build, integrate and manage platforms.
Spending on martech will continue to increase, and it will also become a bigger and bigger part of marketing budgets. Indeed, experts predict that in five years, marketing will spend more money on technology than IT departments (Gartner).
Conversely, new options are arriving onto the market every day that offer tools that would previously have cost huge amounts of money.
Looking further into the future, artificial intelligence, machine learning, and advanced analytics platforms will be used to further optimize the full consumer journey and the various channels that form part of it.
Platforms that require no coding whatsoever are now also on the rise, enabling anyone to build and scale their own solutions.
The best way that marketers can stay ahead of the curve is to use the best martech - enabling them to work more efficiently and effectively.
As a minimum, you’ll need to ensure that these tools are kept up-to-date, to enable you to take advantage of new features and stay competitive.
When done well, marketing requires an ability to see what the market will look like in the future, and to know how customer preferences will change before they do.
However, intuition is far from foolproof. As a marketer, you’ll need to monitor the market, know who your competitors are, and understand how they differentiate themselves from alternatives on the market. You’ll also want to regularly digest trade publications and industry news, go to industry events, and take training courses.
Ongoing employee training is also vital, so as to pull everyone up to the same level of knowledge about the industry, as well as the martech they use.
To this end, promote a company culture of learning, make it an employee objective to learn about technology, and drop out-of-date practices in favor of more effective, innovative methods.
From a technology standpoint, it’s a good idea to try any free martech trials, demos, and apps regularly, and to do martech training and gain official certification.
You can also keep yourself ahead of the curve by integrating artificial intelligence and machine learning into your stack, since this software can identify future trends and provide a roadmap for surviving difficult situations.
The future of marketing will be won with data.
That’s why it’s essential for your business to know its customers.
We have been looking toward the future ever since we started in 2016 - creating an all-in-one solution that is privacy-first and always evolving with the times.
We believe in the power of all-in-one solutions.
Digital marketing is getting more complicated, especially when it comes to data. Oftentimes this requires the use of multiple apps. One might have a good way of providing detailed traffic stats, but not offer heat maps. Another might be specialized for surveys and user feedback, but not offer any conversion tracking tools.
One of our goals is to make the job of marketers and business owners easier, more cost-effective, and safer. That’s why we offer an all-in-one solution for web analytics and digital marketing.
You save money by not needing to work with so many apps, and you have more control of your data since it is centralized in one place.
They work by displaying warm colors, such as red, orange and yellow, on areas with high activity, cool colors, such as blue or green for some activity, while no color represents no significant activity.
Cookieless has been a bit of a buzzword lately and it seems that everyone is talking about the cookieless future. We have been staying ahead of this trend for the last few years and know the importance of going cookieless.
We offer cookieless by default for all website owners.
With our innovative approach to cookieless tracking at TWIPLA, cookies are never used. Instead, we use a type of fingerprinting, or - for even more privacy - unique IDs.
When a user visits a website for the first time, it leaves a digital fingerprint that can be later recognized on a subsequent page visit. With unique IDs, data is unique for every visit, so personal data is even more secure.
Cookieless has 3 main implications:
Fingerprints and unique IDs are not stored on a device and, therefore, cannot provide data about what the visitor does outside of the sessions related to the particular site. This makes cross-tracking impossible.
Some anonymized data is stored, but only within the analytics environment, and it is impossible to associate it with the habits and history of a particular individual.
Each new year brings with it new data privacy laws or changes to existing laws.
The data privacy center in our app is configurable to fit any needs: CCPA, GDPR, TTDSG, ePrivacy, and more.
As data privacy laws change, our first priority will be to stay up to date - so, your data is always safe with us.
The privacy center offers a choice of four different privacy modes:
You can complete control of the privacy of your data.
You can choose from no anonymization with default privacy all the way to complete anonymization and approximate user data using Complete Protection.
Starting with Cookieless Tracking mode, you can start accessing more data, legally and ethically, without losing any to cookie consent banner rejections.
Using Complete Protection, no tracking data or cookies are generated or stored, and the details of a user’s device are never accessed.
There is no digital fingerprint at all. No personal data is stored. No cookies are used. So, there is no need for consent - one less thing to worry about when managing a website.
This also means that 100% of ethical statistical and analytical data is available for users to rely on when making website improvement decisions.
To find out more about our privacy center, check out our GDPR & Data Privacy Hub.
Working in martech, we have our eye on the future.
To stay ahead of the trends, we are already in discussions with experts in the field about how web3, the metaverse, AR/VR, blockchain, and other future tech will impact digital marketing and web analytics, and looking to accommodate such shifts in our roadmap.
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