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Machine learning describes how computers learn, which effectively means how computers identify patterns in large data sets.
Machine learning is a concept that a lot of people don’t fully understand. This is not “AI” in the sense that many people think of AI, but is rather a concept in computing that is closely related to AI.
Machine learning describes how computers learn, which effectively means how computers identify patterns in large data sets. A computer can use machine learning to develop face detection algorithms for example, by looking at thousands of images of faces. Eventually, the system can see similarities in images of faces – they are oval in shape, they tend to have hair, they have contrast points where the eyes go etc.
The more data you feed the system, the more accurate it becomes at detecting faces in images.
So how does this impact on internet marketing?
The answer of course, is that big data is collected by almost all websites, as a result of tracking visitors. Every time someone visits a website, Google Analytics and other tools will make a note of when they arrived, which links they followed to get there, what pages they looked at, what time they left… etc.
All this information is often wasted. But with machine learning, it’s now possible to turn that data into something actionable.
We see this, for example, when we look at the recommendations on Amazon. These recommendations are generated as a result of looking at patterns of behavior across millions of customers. By doing this, Amazon’s algorithms can learn which purchases tend to follow one another.
That in turn means that Amazon can contact you at the precise right time, with the precise right deal that you might be interested in, in order to help you make a sale!
Likewise, you might be able to identify that a user that has come from website X, may be more likely to buy product Y.
All this becomes even more powerful and effective for websites with user accounts. These are able to track the behavior of individuals over long time periods, and thereby gather far more data about their spending and their likelihood of making particular purchases.
Machine learning is only going to develop further from this point. Eventually, it will be able to alter the way that a website is laid out, and show ads that are statistically most likely to result in a purchase.
In future, our browsing experience will always be tailored precisely to our specific interests and needs, based on information from countless other users. The result will be a web that is far more efficient, and of course much higher conversions and CTRs for marketers.
For now? Just keep collecting that data. It’s about to come in very handy indeed!
Programmatic Advertising is a term that has been around for a while now, but that is used more often among large businesses than it is by internet marketers. This is a mistake however, seeing as programmatic advertising has the power to be hugely beneficial for any marketing campaign; by leveraging the significant power of AI in order to run smarter advertising campaigns.
Programmatic advertising is a form of advertising that uses an algorithm in order to place ads on a selection of multiple different platforms.
Companies can spend a huge amount of time working with different publishers and different advertising platforms, to try and get their ads seen by as many people as possible. This is not only a time-consuming process, but it can also lead to wasted cash. That’s because you might find that you end up paying for an ad that nobody clicks, and that therefore doesn’t earn you any money!
Programmatic attempts to change all this by handling everything for you. You can create just one ad and then rely on the tool to ensure that ends up on all the best sites.
More importantly though, programmatic advertising is highly optimized. This is because it will use machine learning algorithms to identify key details about your campaign and to match those with the publishers and platforms.
In other words, programmatic advertising platforms can work out the age, gender, and interests of your average customer and then use that information to place your ads in places where that kind of person will see them. This means your ads will be highly targeted, in turn meaning that the people who see them are more likely to click on them and to buy from you.
What’s more, is that a programmatic advertising tool will be able to adapt and evolve over time. If an ad is underperforming, then it might get pulled from that spot for example.
By combining automation and machine learning, programmatic buying empowers marketers to spend less time communicating with publishers, and to optimize their campaigns.
While programmatic advertising will handle a lot of the process for you, there are some tips that you should keep in mind if you want to make the most of this powerful tool.
For one, it is important that you design an advert that is engaging, attention grabbing, and well suited to your audience. At the same time, seeing as your ads can appear in a multitude of different locations, it’s important that you design them to be versatile. Your ads should look good whether they appear as banner ads on a personal blog, or whether they are plastered all over a huge website.
Finally, don’t be afraid to spend some money to begin with. As with any data-driven strategy, programmatic is all about collecting as much information as possible. The more mistakes you make, the more honed and efficient your campaign will become.
LSI is a buzz word in SEO that a lot of people simply don’t understand. This stands for Latent Semantic Indexing, and it refers to a particular way of using keywords that in theory should be better suited to the newer, smarter, AI-driven Google.
Google has lately made a change to a more “natural language” driven process. Rather than simply looking for search terms embedded in text (called keywords), it instead attempts to understand what the user is looking for and then look for that.
At the same time, Google is attempting to get smarter when it comes to understanding context and synonyms. If a word has two meanings, Google hopes to be able to provide the correct search results by extrapolating context and meaning from the surrounding words in the search string. All this should in theory result in a better experience for the user and more accurate results in the SERPs (Search Engine Results Pages). All this is possible thanks to a (somewhat) new algorithm baked into Google called RankBrain.
What this all means as well, is that marketers need to rethink how they go about trying to optimize their content for Google. In particular, they need to create content that doesn’t just use a single keyword, but that also uses related terms and phrases in order to help communicate to Google the actual meaning and topic that is being conveyed.
And this is what we call LSI.
The idea behind LSI is that Google can look at not only the keyword, but the surrounding language in that article, and thereby get a much better idea of what the article is actually about. Let’s imagine for example that you’re writing about “weak bark.” Are you talking about a dog with a whimpy woof? Or are you talking about a tree that is a little worse for wares?
Google can now look at the rest of the text in your article to try and work out which it is. And it can look for other words in the search string to better guess what the user is looking for.
What you need to do in this case then, is use lots of related terminology: phrases like “sap” and “leaves” will tell Google you’re talking about trees. These are words with “co-occurrence” meaning that they often occur together.
Likewise, it can be useful to target search terms that include some context in them. “Weak bark” might be a vague term to target, but “weak tree bark” can work better.
Really though, LSI is something that should occur naturally. Whenever you write, you should be using lots of natural language surrounding the topic. As long as you have a good vocabulary, and especially if the article is long enough, it should include lots of additional information that Google can use.
In many ways then, the best LSI is the LSI that you don’t worry about! But with that said, it is useful to have it in the back of your mind while writing.
AI and machine learning stand to have a huge impact on the world of digital marketing. This is true partly because Google is becoming increasingly more AI-driven, attempting to answer search terms as questions rather than simply trying to match them to keywords used in a post.
It’s true as more and more businesses start employing the use of chatbots. And it’s true as machine learning algorithms are applied to big data to better make use of the huge amounts of information that an average website will collect about its users.
But in the not-too distant future, we might see an even bigger paradigm shift thanks to AI. We might see a time where websites themselves are built by AI!
When you build a website, you are often tempted to fall back on the things that you like personally: the designs that you find most appealing and the navigation that seems intuitive to you.
Of course, this is not the correct way to go about web design from a business standpoint. Ultimately, it shouldn’t matter what you find appealing. It should only matter what your users will interact well with – after all, they’re the ones you’re targeting!
More to the point – if profit is your main goal – it should be designed in such a way that it drives sales.
The smarter business owner then will fall back on the advice of their web designer. They will use market research. And they might even use split tests. A split test means creating two or more slightly different versions of the same website, to see which one performs the best. You then adopt the style of the most successful version.
But what if those split tests could occur all around the world and you could collect data from millions of samples?
And what if your web design to adapt and evolve in order to become more and more efficient at guiding the users to that buy button? This is what a machine-learning driven web design promises. It could look at patterns of behavior on your site, across multiple websites, or even for a particular user. From there, it could then adapt your web design to become better at encouraging people to click where you want them to click and read what you want them to read.
The ultimate expression of this would be a web design that would adapt in real time to the user reading it, based on their demographics or their personal history. It would thereby become instantly appealing to that potential customer, and would then employ strategies proven across millions of tests to help encourage them to buy.
This could help site owners to increase their conversion rates to a huge extent, while removing all of the guess work out of web design. Of course, it would somewhat hurt the artistic integrity of your site… but if your main concern is business, then this would be web design’s final and ultimate form.
AI is something that we tend to associate with science fiction. In fact though, it is a big part of our reality right now and drives many of the mundane services we take for granted. That depth-effect on your camera? That’s achieved by a form of AI called machine learning!
If you’re an internet marketer, then you should know that your specialty is not safe from the march of this new technology. AI is already affecting internet marketing in a number of powerful ways, and its effects are only likely to be felt more greatly as we move forward.
In this post, we’ll look at some of the biggest ways AI is affecting internet marketing, and the biggest ways it will!
Google has already adopted an AI-heavy approach to search. In fact, it has described itself lately as an “AI first company.” What this means, is that Google no longer simply tries to match keywords with text in an article, and instead aims to properly understand what the user is asking, in order to provide a more relevant answer from a piece of text.
Google is doing this to improve Google Assistant, another piece of AI technology that it hopes more and more of us will use to get information from the web and even to make bookings!
Marketers have had to adapt to this new algorithm called RankBrain, and that’s only likely to become a more prominent going forward.
Oh and we can also expect computer vision to enhance Google’s ability to search through images, too.
Apparently 80% of businesses hope to have a chatbot by 2020. We can very well expect this to be something that is prominent going forward, and especially as weak AIs like these become closer to passing the Turing Test.
What benefit is there for marketers? A chatbot can provide instant guidance and assistance as soon as someone lands on a webpage, significantly improving conversion rates and convincing more people to buy. Some fast food stores now allow you to make orders by simply messaging their chatbots. Moreover, they can even initiate conversations with people in order to encourage them to buy!
We are tracked all the time by cookies stored on our browsers, by our user accounts, and more. This information is then used to serve us up ads that advertisers think will be relevant to us. While this is an effective strategy, it could stand to be far more effective once you start using machine learning and big data.
In other words, as we collect more and more data about the behavior of users, smart learning algorithms can then assess that behavior and look for patterns. This will then allow them to predict items and links that the user might be interested in – even before they demonstrate an interest in it.
In other words, you don’t show them something they’ve looked at before, but rather introduce them to entirely new products that countless other interactions suggest they might be interested in.
Using keywords in digital marketing seems very simple. You just take a phrase that people search for, and then incorporate that into your content – right? If a keyword has a lot of people searching for it, and there isn’t too much competition surrounding it, then that suggests it’s a good one to target. Couldn’t be easier!
Except smart keyword use is much more nuanced than that. Using keywords well, means understanding the type of person who searches for those specific terms, the reasons that they search for them, and what that can tell you about how you should be marketing to them.
One of the biggest ideas to understand here is “intent.” And in a more AI-focussed era for Google, this is now more important than ever before.
Intent essentially refers to the reason that someone is searching for something, and the action they intend to take next off the back of those results.
If someone searched for “how to build muscle,” then that suggests they are doing some research of their own and want to learn about muscle building. But if someone searches for “buy muscle book online,” then that suggests that they actually want to buy the book.
These two people will respond to different types of sales strategy. The first group won’t take kindly to a site that teases useful content and then requires them to buy a book. The second will be perfect for a sales page. The conversion rate is likely to be much higher for the latter group.
In many ways, the intent of a search can be more important than the search volume.
Note that sometimes intent can be a very subtle and nuanced matter. For instance, when you search for “fitness apps” you are likely doing research. When you search for “fitness app” you are probably looking for something to download!
The other reason that this has become increasingly important, is that Google is now more interested in understanding what users are looking for, rather than simply looking for search terms that match. In other words, Google wants users to talk to it rather than typing static search terms.
And at the same time, Google wants to be able to answer questions by trawling the web. Once again, this means understanding not only the words and their literal meanings, but the intent that the user has when searching for those phrases.
If you think more about intent with your articles, rather than just search terms, then not only can you potentially improve your conversion rates, but you’ll also be aligning your goals with Google’s – which can only be a good thing for your SEO.
Another point to consider? The type of person and your buyer persona. That is to say that when intent isn’t the primary concern, you should think about the type of person who searches for a particular keyphrase. Is this the type of person who fits your target demographic?
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