Artificial Intelligence … for those who are asking what this means, we want to explain what the hoo-ha is about. We also want to explain what’s it got to do with content marketing. Among Content Technologies & Trends now, this Artificial Intelligence is making the most noise. As the length of this article shows, there is some serious learning to be done, for sure … but if you think, “Why bother now, when it all belongs to the future …”, that would be wrong. The future is already here. Artificial Intelligence (also known fondly as AI) is already at the basis of a lot of the digital transformation taking place in online marketing and business.
Unfortunately for content marketers, though, we have not yet reached that stage where we can hand a computer a blank sheet of paper and tell it to create content on its own. So, if you’re hoping Artificial Intelligence will take content-creation off your workload, and do it all on its own, you have to live in vain hope. I doubt that day will ever come. But if you’re hoping Artificial Intelligence will make content creation easier, you are on the right track.
Solopreneurs who think artificial intelligence is about robots or wired humans need to learn more
What has happened is that businesses are now flooded by Big Data. It has become possible to gather masses of data from every single action taking place online. You click on a link somewhere; some brand can use that data to understand you. You search for something online; some brand somewhere can use that to know more about Google. You check your email; some brand somewhere could use that data to track email efficiencies. You visit a social site; it becomes bits and bytes of valuable data to millions of brand marketers worldwide to know social usage. It’s just data, data, data … whichever way you turn.
Now what do we humans do with so much data churn? Most of it is going over our heads, because the sheer volume and complexity of data is too much for human brains to work with. Besides what use is data, if we can’t put such data to some uber-valuable use? If only all this data can be “digested” and then used to predict future outcomes for businesses, or provide deeper-than-before insights into customers, think how much businesses could benefit? So, in come the AI machines …
AI is about machines telling humans: “Stay outta the way, small guys. Us, big fellas, will chomp on this Big Data, and then spit it out – not just as more data, but as pretty Predictive Analysis and User-Behavior-Analytics. Can you do that? No, you can’t. That’s why we’re here …!”
What’s machine learning and how’s that different from AI?
Well, many people use the terms “artificial intelligence” and “machine learning” interchangeably, but they’re a bit different from each other. Machine-learning is the first step towards AI maturity. It’s the early days of full-blown AI – and in a way it is the state of technology in which we all are at the moment.
We’re flirting with AI, but we’re nowhere near exploiting AI fully. Even so, this time we’re spending on getting closer to AI is key – because we’re learning how to work with machines, that are way ahead of us in their “brain-power”.
Some examples of AI already at work … did you know these were AI?
You’ve probably already comes across many examples of AI at work, without knowing it was AI. For example, smartphone assistants like Apple’s Siri and Google’s Google Assistant are all driven by AI. So are the new self-driving and autonomous cars (which many people say will soon outnumber manually driven cars).
The more recent piece of AI that I came across was IBM’s Watson. Unlike Apple’s Siri and Microsoft’s Cortana, the IBM Watson doesn’t just make suggestions based on what it learns from requests and questions. Watson can process language commands and reply to them in a near-human-like manner, verbally or as text. A great example that demonstrates the power of IBM Watson is Hilton Hotels’ Connie – a concierge robot that interacts with guests and assists them with their queries. See the video below … some talk about AI you should hear – but not swear by!
It must be said, though, that despite a lot of conversations happening now about AI, many theories are based on myths. How many of these “expert predictions” we can believe, we cannot say. Nevertheless, here is a pictorial representation of the many directions of dialog going on about AI. It makes for interesting speculation …
Image courtesy: FutureOfLife
Making machines think and take decisions like humans – it has its pros and cons
At the very heart of AI is the concept of building machines which are capable of thinking like humans. We humans, for example, have the unique capability for abstract, creative, deductive thought – and particularly the ability to learn. So, experts in technology have taken ourselves as a blueprint for creating AI machines and systems that have the kind of unique abilities we have.
People in the field call it the “application of neuroscience to IT system architecture” … if you notice closely, most AI intelligence apes the human neural network. Although all this sounds like it happened yesterday, this AI concept has taken years in the making. It’s never easy trying to make a machine have the capability of the human mind.
The two types of AI we have today – specific and general
Naturally, it is hard work imbuing every AI machine with the full range of human qualities. So, scientists have developed two distinct types of AI machines. The specific AI (or what they call weak AI) machines are those that have the limited ability to do just certain specific tasks, and no more. For example, you may have machines just aiding facial recognition, or only responding to Internet searches etc. However, the long-term goal of researchers is to create general AI (or strong AI), where AI may outperform humans at nearly every kind of cognitive task.
Right now, on the planet, humans are the most brain-evolved species. But the question is: are we using our brain-power to create a species superior to ourselves? Many people are looking forward in excitement to see what all this would look like – while other people are living in dread that we may be creating monsters we cannot control. Are the fears of these doomsday lot justified? Let’s see …
The prevailing dread about AI misuse
People who think AI may one day take humans over, and turn us to pulp, have visions in their minds that resemble sci-fi movies. In actuality AI machines may never really look as fearsome as some of the characters of sci-fi flicks, but therein lies the real fear. The AI machines we may have in the future may look benign enough, like the nearest photocopying machine – but have mental abilities that outstrip our own.
We may find it hard to keep these machines in control. It’s would be like a pilot flying a plane which is always on autopilot and does what it thinks best – and the pilot can try all he can but the manual override is beaten down by the machine every time. With AI, you may have to cope with a “thing” that thinks it knows best!
A lot of people also fear that automation may lead to profound societal change – maybe for the better, or maybe for the worse. It’s not just about how individual humans will adapt to AI machines, but how families, groups, societies, children, work communities – the whole world of humankind as we know it – will adapt.
What will our interactions with each other be like, when machines criss-cross our pathways, and intervene in our bonding areas? What will the relationship of a marketer be with his customer, for example, if there are layers of AI machines between them, intermediating the relationship?
What you should be careful of with AI
Whether you belong to the group that looks at AI with eager anticipation, or alternatively, with a sense of dread, I think all of us have to beware that there can be two types of potential pitfalls with AI – and, to the extent we can, we have to be cautious in adoption of AI, bearing these two factors in mind:
- The AI machines themselves may be maliciously programmed to do something devastating to humans.
- The AI machines may be programmed for beneficial uses, but may get bugs, viruses or malfunctions that change them into monsters.
These kinds of understandable fears have led to a number of tech giants including Google, IBM, Microsoft, Facebook and Amazon forming a group called the “Partnership in AI”. The mandate of this group is to research and advocate ethical implementations of AI, and to set up guidelines for future research and deployment of robots and AI.
3 main marketing areas where you could use AI to increase efficiency
Many solopreneurs ask how they can efficiently use AI to improve their marketing, speed up results or even boost results. In several areas of marketing – especially online marketing – AI is not yet fully developed. But there are three areas where substantial progress in AI has been made, and where even small businesses online can begin to gain.
1. AI can be used for very efficient micro-targeting of customers. What is micro-targeting? Experts define it as follows: “Micro-targeting is a marketing strategy that uses consumer data and demographics to identify the interests of specific individuals or very small groups of like-minded individuals and influence their thoughts or actions. An important goal of a micro-targeting initiative is to know the target audience so well that messages get delivered through the target’s preferred communication channel.”
Let’s take a simple example. Let’s say you are a marketing consultant specializing in helping people concerned with health and fitness.
Now, obviously, there may be smaller groups within this group – for instance, kids who need more fitness, fitness for athletes, fitness for the differently-abled, fitness for women, fitness for the elderly etc. Again, take fitness for women – you may have women from different age groups as sub-sub-segments. You could of course address marketing messages to all women interested in fitness, but would you not be far more likely to hit the hearts of your targets if you addressed them in smaller groups according to their ages and suggest the absolutely right ideas for them? And what if a machine or software could automatically adapt your main marketing message so every customer in every sub-segment gets just the right angle of the message?
Micro-targeting becomes possible through AI. Using various detecting variables, AI can help you isolate smaller and smaller target segments, and automatically customize your messages to them, to help you connect more compellingly with them. You can also use machine learning to evaluate the possible reception of your content by the intended targets, on different online channels.
2. AI can be used for very efficient agglomeration of various pieces of business research. Marketers need a wide variety of research. Some of it needs to be top-down, some of it needs to be bottom-up. Some research needs to industry-wide, while other research needs to be extremely granular. Marketers also need research on competitors, keywords, customers, behaviors, content mixes and a whole host of other specifics. Usually all such research is done as independent projects and not always at regular intervals. So, the resultant picture always tells a businessperson just part of the story of his business, from an angle he has opted to see it all from.
Not only do marketers need a lot of research – and that too, ongoing real-time research, preferably – they need all their pieces of research to present a coherent composite picture of their businesses, at any time – and not just remain as silos of information. For example, if you research your competitors, you also need to match that with your research comparing your target audiences with theirs.
If you research your content on one device platform, you need to know comparative research of complementary content that supports it from other platforms and devices. More and more marketers are realizing that if pieces of research are taken out of the total context, they can be interpreted very differently … whereas research into various aspects of the business, done continuously and seen together, may completely alter one’s business perspective.
Holistic research is very tough without AI. This is, in fact, one of the beauties of AI, that you can know your business and its nuances from a 360-degree perspective all the time, if all the pieces of research you do can be continuously collected and agglomerated – and also interpreted on the fly.
3. AI can be used for tracking the outcomes of different business decisions to establish best practices. As with research collection, business decision-making also tends to be in silos rather than viewed as a whole for its impact on business efficiencies. When even large businesses often find it very difficult to track and monitor the effects of their many business decisions, smaller businesses barely get into this area of self-assessment at all. The truth is, the better you understand the impact of the smallest decisions you take, the better will be your organizational profitability.
You can, for instance, combine advanced machine learning with Big Data to accurately analyze the top-line and bottom-line effect of your different content marketing activities. You can obtain direct evidence concerning the impact of different content lengths, headlines, topics, and brand voices. You can use your learnt insights to train your content creators to produce the content that’s just right for your market.
Also, with every new technology that hits the market you may have to study its potential impact, and also plan on the ideal ways to gradually incorporate the technology into your marketing mix.
Instead of making hit-or-miss decisions based on just gut-feel, you can now validate your hunches and preferences with real-time AI analytics. You can see which decisions would be wise to make, and how they may affect the potential productivity and cost-efficiency impacts will be for your business.
3 content marketing areas where you can give AI a try to see how to work with it
Most solopreneurs don’t know where to begin with AI, although they admit they would like to start getting familiar with it. Here are three areas where you can begin experimenting with AI … but as the wise say, however, hasten slowly!
1. Try AI for content curation. Since you need to keep producing vast quantities of exceptional content for your target audiences, it will help if you use AI driven tools or plugins (like Curata or the MyCurator Plugin) which can be understand your preferences in content resources. These tools will find fresh bang-on content for you every day, to add to your articles. This saves you loads of time and effort in looking for good resources to pad up your articles with.
Most of these tools don’t even need conscious programming. They have the “intelligence” to study your preferences from the way you pick curated resources over a period of a few weeks, and they thus “learn” your requirements. Thereafter they serve you the kind of content you have shown you like to include in your articles.
2. Try AI to improve the customer experience on your site. You can use tools like the ORBITR Marketing Automation Plugin to set up simple process flows on your website to improve customer experience. The tool can be set up to show your customers the next ideal blog post to read or landing page to visit, depending on what they last read. If your site is planned well, you can lead customers from information to purchase decisions by showing them a sequence of pages that bring them closer and closer to purchase.
AI drives tools like ORBITR to “learn” what customers are reading and how deep is their topic interest, to show them the right subsequent pages to help you achieve your marketing goals.
3. Try AI by setting up chatbots with playbooks on your site. What is a chatbot? On many sites, you may find a little messenger-like chatbox pop up on the right-hand bottom corner of your screen (or appear full-screen on mobiles). The bots start saying “How can I help you today?” Beyond just asking for email addresses, and putting people on mailing lists for later contact, these chatbots actually help real-time conversations happen between you and your customers. If you are not available, the chatbot takes a message. If you are available the chatbot gives you an alert that a visitor is on your site.
Further, some chatbots have a bit more advanced AI in the form of “playbooks” you can set up. You decide how the conversation should be nudged step by step towards obtaining a customer order and the chatbot play by the book. Look at the example of a chatbot below moving the customer towards a pizza order like a real human back-office phone operator would …
Image courtesy: LoyaltyApps
So what are your thoughts on this topic? Do share!
This post is incomplete without your input. The community of content-marketer solopreneurs would feel galvanized to hear from you … so do share your thoughts on this topic with us, in the comments field below this post.
Other articles in our series “Content Technologies & Trends”:
- How To Craft Your Campaign For Multi-Screen Content Marketing!
- Clear Your Throat And Get Ready For The Voice-Search Revolution!