Perhaps more importantly, though, these tools helped created closer and stronger relationships, and not only with existing audiences, but with new audiences who were less connected to digital communication tools. As a result, the digital world looks quite different post-pandemic, and many digital communication strategies and tactics are here to stay.

Given this acceleration in digital activity, new trends and emerging behaviours signal what lies ahead. Here are five areas that will likely have a significant impact on marketers in the near future:

Automation/Personalization

Due to the computational power that is now available, artificial intelligence (AI), machine learning (ML), and deep learning (DL) are playing a pivotal role in how organizations communicate. To clarify the differences, artificial intelligence enables computers to mimic human intelligence. Machine learning uses algorithms to parse data, learn from that data, and make informed decisions based on what it has learned. Deep learning structures algorithms in layers to create an “artificial neural network” that can learn and make intelligent decisions on its own.

Many tools and systems are now using ML to identify meaningful patterns and derive insights based on user data and/or behaviours. As a result, many communications tasks and activities that used to be done manually are being automated. This potentially frees up communicators to spend more time thinking strategically and creatively about ways to engage and convert target audiences.

While some early organizational communications automation is already happening, there is still a great deal of growth that will happen in the coming years. Below are a few examples where machine learning is already helping organizations optimize their marketing activities. That said, many of these technologies are still in their infancy and are only being used by early adopters:

Programmatic Advertising

Programmatic advertising is the use of automated technology to buy advertising space. Instead of manually bidding, placing content/copy, and choosing the timing for a specific ad, programmatic advertising uses data insights and algorithms to serve ads to the right user at the right time, and at the right price. With these systems, organizations simply provide content, campaign goals, budget limits, and other campaign constraints (location, demographic targeting), and the system will optimize the campaigns to deliver the highest possible returns based on the stated goals/constraints. Since computers can monitor, analyze, and adapt faster than people, programmatic advertising can deliver higher returns, greater efficiency, wider reach, and more ad placements. However, these systems tend to be more expensive, may not always properly match the ad to the audience, and could be vulnerable to fraud. As with any automated system, professionals must review the results and to make sure these systems are best supporting the organization’s needs and goals.

Personalization/Recommendation Engines

A personalization engine (PE) (also called a recommendation engine) uses insights from a user’s behaviour combined with data from other similar users to deliver a personalized experience. The content that is delivered to the user should be contextually relevant and match the user’s needs and preferences. Since personalization engines use advanced AI and machine learning-based algorithms to make predictions of what users will need, the more data these engines access and analyze, the more accurate their predictions are. PEs are frequently used for ecommerce to make product recommendations, but they are also widely used by media organizations (e.g., news, music, or streaming companies). These are key benefits of PEs:

• Finer customer segmentation (i.e., the ability to segment your audiences into smaller segments and still support their needs)

• Tailored messages that can be optimized at the individual level

• Shorter conversion times because the customer journey is much more targeted

• Increased revenues due to promoting complementary and/or related products/services that best meet the user’s needs.

While there are many advantages, PEs can be quite expensive and require time to setup and collect enough data before benefitting the target audience. Be aware of the significant upfront investment of both time and money before reaping the benefits of these tools.

Conversational Marketing

Conversational Marketing is a way of engaging with a target audience via real-time, dialogue-driven activities such as live chat, messaging apps, or conversational AI (chatbots). The goal of conversational marketing is to create meaningful customer relationships through conversations and to make the customer experience as smooth and easy as possible. To scale conversational marketing, many organizations are turning to chatbots.

Chatbots can help automate some communications and ensure instant and timely responses to customers. By making conversational AI chatbots an integral part of communications initiatives, organizations can guide customers through the customer journey more quickly and potentially drive more conversions. Some of the key benefits of a chatbot are time and cost savings, increased customer engagement, faster response times, and increased customer data because the interactions are captured and can be analyzed and reviewed. On the other hand, chatbots do take time to setup and cannot completely replace humans. They work well for repetitive questions and basic information sharing. However, they do not work well in dealing with emotions or nuance and people can quickly become frustrated or even alienated by the experience of interacting with them. So, a chatbot may only be a suitable solution for a portion of intended interactions with audiences.

Predictive Analytics

Predictive analytics use historical data to predict future trends, events, and potential scenarios. Many analytics systems are now moving away from simply reporting what happened to offering forecasts that can help users plan and prepare for the future. The most obvious example is Google Analytics 4. This version of Google Analytics launched in October, 2020, and is using machine learning to give users more insights and predictive analytics, often related to improving conversions.

Voice Search & Commerce

Two-thirds of 25-to-49-year-olds speak to their voice-enabled devices at least once per day, according to a recent study by PwC. Whether speaking into their mobile devices or asking a voice-enabled device like Google Nest or Amazon Alexa, more and more people are searching for information using their voice. As a result, voice searches will play a more significant role in the customer discovery process. Communicators need to think beyond traditional keywords and key phrases and consider sentences and questions that might be verbally asked by prospective audiences. Voice searching has become a hot topic in mobile SEO optimization, as users are embracing voice searching when typing is either not safe (e.g., when driving) or simply not convenient.

Social Commerce

Fueled by the global pandemic and the shift to online shopping, more people are also merging their social media activity with their shopping activity. Instagram and TikTok have brought new meaning to social commerce by launching several features that allow users to buy products directly from within the social media platforms. Since many people already follow brands, these networks are creating quick, easy conversions.

Extended Reality (XR) & Immersive Experiences

Even though virtual reality (VR) has been discussed for decades, recent developments with extended reality (XR) and immersive experiences should be noted. Extended reality (XR) is an umbrella term referring to all real-and-virtual combined environments and interactions generated by computer technology. It includes augmented reality (AR) and virtual reality (VR). Augmented reality is an interactive 3D experience that combines a view of the real world with computer-generated elements, usually overlaid on top of the real-world view.

In contrast to virtual reality (VR) experiences, AR experiences can offer an immersive experience with little additional hardware required—often just a mobile device. This makes these experiences much more accessible to a wider audience. However, these immersive experiences all require significant upfront investments in time and money. In the coming years, production costs will likely drop to allow more organizations to develop these compelling and engaging experiences. Here is an example of a 360 VR marketing video:

Media Attributions

Experience Amsterdam: A Guided City Tour – 360 VR Video by VR Gorilla – Virtual Reality & 360 Videos is licensed under a Standard YouTube License.