It’s not easy sitting in a marketing meeting in 2021. You’re always at risk of being blindsided by a trendy martech buzzword you’ve never heard of. There’s always someone casually dropping some new acronym no one has ever heard of – and it’s usually Steve.

It takes a brave person to put their hand up and say “yeah, I don’t know that one”. We all should, but such is life that we don’t.

Keeping up with the buzzwords is a salaried position in itself, and no marketing leader needs to feel the unjustified imposter syndrome of not knowing today’s latest jargon.

Fortunately, marketing jargon today tends to actually mean a lot more than the “blue-sky thinking” buzzwords of the early noughties. From AI to VIs and NLU, these aren’t just throwaway phrases, but tangible additions to the marketing technology stacks of 2021 and beyond. 

We just need a refresher for the year ahead.

The state of marketing technology in 2021

Just look at this infographic, lovingly and painstakingly researched and created by Scott Brinke of the Chief Marketing Technologist Blog. There are thousands of companies offering martech solutions to help in any area of your business – from helping with advertising to content and customer experience.

And again, when choosing the area of your marketing function you need help with, you’re inundated with martech choices. There may be solutions out there perfect for your situation, but they’re hidden behind opaque acronyms that haven’t yet entered your vernacular.

So, let’s get our heads around the technologies that marketers are going to be running with – today and in the years to come.

Many of these are from Gartner’s famous hype cycle for digital marketing. Many others are from trending Google searches. And others from our own experience of technologies we see growing in the conversational AI space. 

So, hopefully, the next time Steve starts talking about using VIs to create BOF conversions through scalable CUIs, you’ll be able to tell him… “Actually, Steve, that’s a great idea. Nice job”.

Digital workforce transformation

A digital workforce is a team of virtual employees – chatbots, virtual assistants, digital humans, etc – which work alongside human employees and take the brunt of manual, repetitive or lower-value tasks.

Marketing has become about self-service. Look at SEO, for example. Brands, big and small, answer questions that their potential customers shout into the void of Google, hoping for a reply. They find their own answers, and then we expect them to convert. 

On the other side of the coin are real people, who customers can get in-person support from through two-way conversation. Unfortunately, these people don’t scale when needed to.

A digital workforce aims to bridge this digital divide by putting more human-like solutions in place. Chatbots can do the fast, low-touch work; experts can focus on specialist, higher-touch or particularly complex tasks; while digital humans and embodied AI can sit in the middle, having interactions that require value and speed of service.

Scalable and always available, this year is set to be a pivotal one for the creation of digital workforces.

Virtual influencers (VIs)

Virtual influencers are CGI “celebrities” that exist to promote the brands they’re paid to be associated with. With around three million followers at the time of writing, Lil Miquela is by far the biggest virtual influencer in the world, modelling clothing for the likes of ADIDAS and Chanel.

The benefits of a virtual influencer lie in the amount of control brands can find operating digitally instead of with a human model. VIs also gather a generally younger audience, so they are good for connecting with those younger demographics. They also won’t get a DUI, or go off on a rant right after signing a multi-million brand deal.

The cons, however? It’s yet to be seen whether VIs take off and start to hold the same influence among buyers as human ambassadors. Meanwhile, brands are tied somewhat to the actions of a virtual influencer as decided by its creators or owners – while they’re unlikely to go on a virtual rant, the creator might choose to later back something that doesn’t align with the hiring company’s values.

Digital human brand influencers

Digital human brand influencers work for one specific company. While, to date, they’re not used in the same ways as Lil Miquela, they do have the potential to offer something different.

A virtual Michael Jordan, for instance, could work for Nike and have a real chat (through conversational AI) with any number of fans at once. They could talk to kids and teach them how to take a free-throw like MJ, or how to lace up their new Nikes.

Brands are also designing digital humans from scratch to embody their brands. Aimee, below, is one example of how the largest health insurer in New Zealand, Southern Cross Health Society, has done just that. Digital human influencers allow brands to retain the entire creative control over what the VI does and says, and will do or say in the future.

Brand personification

Brand personification is projecting human-like qualities onto your brand. That can be through the tone of voice you use on your social media channels, to how much personality you put into your chatbot.

You may remember personification as that form of language tool you learned in school. Writers will use personification to make inanimate objects more human, therefore making us more empathetic towards them. And personification has similar functions in marketing.

In fact, personification is set to be a big trend this year, with the aim of making customer-facing marketing technologies more likeable. Our research shows that 42% of chatbot leaders are prioritizing “creating a more human experience” as part of their chatbot development plan.

Emotional connection as a metric

OK, we know you know what emotional connection means. But more and more, businesses are using it as a metric to inform how people see their brands, and the implications of that on lead generation and customer loyalty.

Emotional connection, we now know, is a more valuable way to measure how your customers feel about your brand and is the most important customer experience factor for improving acquisition, retention and lifetime value.

Considering some of the 2021 martech buzzwords and solutions we’re about to mention, it’s easy to see the desire for more emotional connection as a direct result of automated customer-facing tech adoption. In fact, PwC recently found that “64% of U.S. consumers and 59% of all consumers feel companies have lost touch with the human element of customer experience.”

Emotional connection ideally starts at the awareness stage of the customer lifecycle. So prepare for more conversations about building lasting relationships by inspiring an emotional response with your audience, and maybe some KPIs to track that.

Conversational marketing

Conversational marketing is a rejection of the old types of slow, one-way lead generation and nurture. As modern-day consumers, we want to binge-watch Netflix on demand, get a taxi to our doors in minutes and speed through marketing funnels to make purchases in real time, if we choose to.

The reason businesses couldn’t do this a few years ago was the restrictions of humans. People are the best at conversation, but we can’t be online all the time, answering every customer question as and when they come up, in perpetuity.

But conversational marketing lets people interact with your brand, ask questions, get answers and make a purchase as slowly or quickly as they damn-well want to – by using conversational AI solutions.

Conversational AI

Chatbots, virtual assistants, digital humans are all examples of conversational AI (we’ll come to each of these shortly), and conversational AI is an enabler of conversational marketing.

 Conversational AI opens up two-way dialogues that simply don’t exist throughout most of the marketing technology stack. Mailchimp, for instance, says the average email open rate is only 21%. Today, more than ever, people want real-time conversation, not one-way comms with long wait times between replies.

From a brand perspective, the chance for more human comms is a fantastic competitive advantage. To steal a quote from Maya Angelou and crowbar it into this context: “people will forget what you said, people will forget what you did, but people will never forget how you made them feel.”

Marketing automation of old didn’t make any customer feel… well, anything. By its two-way nature, conversational AI can be more personal and nurturing, when aligned with the right martech stack, that is.

AI for marketing

Another from the Gartner Hype Cycle for Digital Marketing, and the technology that’s further down the hype-to-value journey than many of these other technologies. AI for marketing is the broad definition of how artificial intelligence is used in its various forms across the marketing function.

Conversational AI will fall into this category when used in the marketing context, but so will a lot of other technologies. 

Some AI for marketing examples include tools for content generation (particularly with the advent of sophisticated AI like GPT-3), analytics and reporting, and even the delivery systems of billboards. AI is broadly impacting the digital and the physical worlds of marketing.

Conversational user interface (CUI)

A conversational user interface is a digital interface that lets users speak to software to find what they’re looking for.

If you’ve ever used a terrible search function on a website, you’ll know the value of this. You can’t find what you’re looking for, so you type it into the search bar and are confronted with 10 pages of documents, landing pages and downloadables that each *somewhere* include the keyword you’re looking for.

CUI is a means to ask the software what you want, and refine it down through two-way dialogue until you have what you’re looking for. A CUI can be a conversational AI, like a chatbot, a voice assistant or a digital human.

With our digital humans, we like to think of the CUI being the oldest, most time-tested interface that’s ever existed. More commonly called the human face.

Voice-user interface / IVR

You’ll know about interactive voice response (IVR) from the days of yore – when you’d be on the phone and could speak or press a number to lead the automation. In 2021, these tools are having a resurgence of sorts as voice-user interfaces.

Voice-user interfaces now go beyond “press 3 to do X” and make spoken human interaction with computers possible. Users now drive the conversation, with AI making the systems more conversational than scripted.

Speaking to a computer has never felt more natural, either, adding more life to voice channels. Some of the more impressive options we’ve integrated into our digital humans are Google Wavenet voices, Amazon Polly and the awesome WellSaid Labs.

Voice assistant / virtual assistant

At the pinnacle of voice-user interfaces are voice assistants (also known as virtual assistants – we can’t seem to collectively settle on a term just yet).

From Siri to Cortana, Alexa and dozens of other offerings, voice assistants are intelligent personal assistants that sit in the homes and on the devices of your customers and those you’re trying to sell to.

For anyone still skeptical of people’s desire to speak to their devices, take a look at the stats above. If you’re still skeptical, just imagine the budget Amazon put behind their awesome Superbowl ad for Alexa.

Chatbots (in marketing and more)

Chatbots aren’t a new term, and by now you’ll likely know exactly what a chatbot is and does as a subset of conversational user interfaces. You can read our article, what are chatbots, if not. 

But it’s important to note how they differentiate from voice assistants and digital humans; as well as how the different types of chatbots differ themselves.

Chatbots tend to operate via text interfaces. Write your question into a box and the chatbot will “write back” through automated text generation, driven by a conversational platform. That means they don’t convey tone of voice like top-of-the-range voice assistants; nor combine that with body language like digital humans.

The types of chatbots include: 

  • AI chatbots (who learn)
  • Scripted chatbot (who don’t learn)
  • Choose-your-own-adventure bot (who are simplistic)

AI chatbots are the ones you can have a realistic conversation with. They can use machine learning in some instances to get better at understanding and generating a conversation, so the more they’re used the better they become. AI chatbots are capable of holding small talk, or have an in-depth conversation on a topic.

Scripted chatbots do not learn. Their dialogue can be broad, but they cannot learn to answer questions they aren’t programmed to know. Having a conversation with a scripted chatbot is more like chatting to someone who can only read you the answers to things he or she finds on Wikipedia.

Choose-your-own-adventure chatbots go more rudimentary than this, with a set path to lead you down. They might ask you things like your clothing size, style and colour preferences, before suggesting a dress you might like to buy. Conversational skills are nil.

Brands might also choose to design an avatar to be the face of these conversations. It’s interesting to consider why that is, and what an avatar is offering to the user experience – a brand representative to build a connection with users.

NLP / NLU / NLG

Computer programmer and all-round genius Alan Turing developed the Turing Test in the 1950s. The test is simple: if people can be convinced that an AI is a real human, the AI passes the Turing Test.

Many chatbots and AI interfaces have passed the test to date, and are only getting better.

But if an AI has any hope of passing the Turing Test, it will have to process, understand and generate conversation in a natural way, like we do as humans. There are three subsets of conversational AI technology that deal with these:

Natural Language Processing (NLP) is an engine for computers to read, hear and analyze language – often by deriving meaning and intent behind a sentence. Chatbots, virtual assistants and digital humans all need an NLP. 

You might also come across the subsets of Natural Language Understanding (NLU) and Natural Language Generation (NLG) as ways specifically for AI to comprehend and respond naturally to spoken or text interactions.

Your marketing efforts may not pass the Alan Turing’s famous robotic test quite yet, but natural language processing will allow users to create a more lasting connection to your conversational AI – a connection based on functionality first (the AI is good at its job) and emotional connection second (the AI is friendly and approachable, and I like it).

Digital humans

Saving the best ‘til last – because it combines almost everything of what you’ve read so far.

Digital humans are conversational AI-powered beings that recreate the best parts of human interaction – conversation, communication and emotional connection. Like voice-user interfaces, people can speak to them and hold a genuine conversation to find their answers, all while embodying the brands of the companies they work for. 

Digital humans live to communicate using the human interface – spoken word, tone of voice and facial expressions that show empathy responses (smiling when a user says something positive, or showing concern when a user shares something negative).

Neither chatbots nor voice assistants can do this; nor can any existing virtual influencer do it in real time, not being AI-led and able to hold a conversation.

Digital humans build the basis for digital workforce transformation that has human connection at its heart. But there’s much more to say beyond that. If you’re new to the world of digital humans, we recommend starting by checking out our free eBook.

Or, if you’d like to impress Steve in your next meeting, get in touch and we’ll tell you all there is to know about the next wave of brand-aligned conversational marketing.

Digital humans eBook CT