Harnessing The Power of Machine Learning in Digital Marketing – The Ultimate Toolkit

Machine learning is a fairly young technology but it’s already being applied to various fields of marketing in ways that might change the industry for good. With digital marketing, in particular, it is possible to provide better personalization and automate certain manual tasks such as moderation with the help of AI-driven solutions – which, in turn, tends to lead to higher returns on investment compared to traditional tools.

And yes, we’ve compiled an entire collection of solutions that already actively use machine learning to give you a competitive edge.

Curious to know more? Before you can use this exciting new tech to your advantage, it is worthwhile taking a moment to understand what machine learning is and how it can help.

Understanding Key Concepts

Almost. Well, not at all, quite frankly. To begin with, here are some broad definitions of key terms related to machine learning to keep in mind:

• Artificial intelligence (AI) is a sweeping definition for any computer software that mimics the role of human intelligence in decision making
• Machine Learning (ML) is a set of technologies that make it possible for computers to solve problems autonomously based on prior inferences from data
• Deep Learning is the sub-field which uses neural networks to replicate the learning functions of the human brain

In a nutshell, Machine Learning is one of the leading methods to achieve automation in knowledge-intensive fields because it can learn and improve as it consumes more information. Deep Learning is a special type of machine learning algorithms that uses neural networks with a lot of hidden layers to achieve top-notch performance that even sometimes rivals humans.

Is Somebody Already Using All of That in Marketing?

A machine learning approach to digital marketing is not a complete replacement for all your traditional marketing to date. However, it can help you in the following critical areas:

• Decrease advertising costs by taking on some of the tasks that were prior only manageable by humans
• Get better insights by finding hidden trends and correlations in datasets of previously unmanageable sizes
• Reach customers based on purchase intent by predicting their future moves based on existing behavioural data
• Improve prospecting through computer-generated recommendations and “you might also like” lists

ML can enable computers to perform tasks that even humans find challenging. It therefore finds a plethora of applications in advertising and marketing, where it can efficiently and optimally target the right customers and reveal to them the right content so they can easily find what they’re looking for. Moreover, it provides a great facility for humans to make data-driven decisions. And that can be a huge advantage in the modern arena:

Impact of Machine Learning on Marketing

According to Forbes, machine learning is already revolutionizing the marketing landscape, with 84% of marketing organizations beginning to implement or expand their use of AI in 2018.

These efforts can be quite profitable for business, as Capgemini reports that 83% of businesses in the marketing industry use Artificial Intelligence and Machine Learning in 2018, and that among those who do, 75% see a 10% boost in profits. If your organization has been asking how machine learning works for marketing, the data should be quite encouraging. Capgemini and others buttress this view with additional statistical insights, including the following:

• 3 out of every 4 organizations that make use of AI and machine learning in their operations see an increase in sales by more than 10%.
• Among business executives, 57% see customer relations and support as the biggest area for growth brought about by the use of AI and machine learning.

How Does Artificial Intelligence Work in Advertising?

One area of digital marketing that is applying the new technologies of machine learning is in digital advertising. You can work with professionals knowledgeable in the latest AI tools and trends to implement your programmatic advertising.

Programmatic advertising is the automated buying of digital ad space using computer algorithms. In the past, media buying was a mostly manual process. It required countless hours of bidding and sorting through media inventory to find the best advertising opportunities. Now, not only have software been created to automate ad buying..

Artificial Intelligence is now being employed to add value to programmatic advertising, such as by finding the optimal matching between buyers and sellers, as well as by finding the most optimal target audience for various products.

According to data from the Digital Marketing Institute, programmatic advertising has been growing very rapidly in the last five years and now amounts to $40 billion annually. This growth is projected to continue in the next couple of years.

Below we show you the specific machine learning tools that you can use today to augment your digital marketing efforts. The tools are categorized by the area of digital marketing they focus on, from personalized marketing to predictive marketing and content curation.

More Personalized Marketing

Social media marketing and content marketing are industries where digital marketers can make use of AI to improve their output by producing more effective and customer-targeted materials. For this purpose, a number of tools may be used to aid in employing AI.

The first category of tools you can use is those that have to do with personalized advertising. Instead of having a one-size-fits-all marketing campaign that attempts to appeal to as many customers as possible, personalized marketing adds value by creating customized marketing strategies for each individual target customer. Some tools for digital marketers that are worth taking a look at are the following:

• Acquisio – Enhance your digital marketing strategy by using ML to optimize cost efficiency and increase relevant customer views.
• Emarsys – Employ artificial intelligence marketing that allows machines to make decisions for you and personalizes ad campaigns for each individual customer.
• Rocco.ai – An AI-powered marketing assistant that learns the inner workings of your business and recommends the best actions to take for your marketing campaign to take flight.

Social Media Automation

It used to be the case that social media marketing took a lot of time, leaving digital marketers with far less time to devote to other channels. A slew of tools using machine learning to varying degrees has now made social media automation viable for most uses.

For example, tools like MeetEdgar can perform most of the activities of a human social media manager, such as following accounts and sharing content and employs machine learning to automatically create share-worthy posts that showcase your products and/or services on social media. The stand-out tools to consider in this area include:

• Buffer – Automate postings to Twitter, Facebook, Pinterest, and other social media platforms. The app uses AI to optimize accessibility and more.
• Hootsuite – Social media management tool that eliminates some of the grunt work. The app uses machine learning for smart moderation of social media profiles.
• MeetEdgar – Grow your social media following with automated posts. The app uses AI to write posts automatically.

Content Curation..

Machine intelligence tools can help your curation efforts by showing you automatically the best pieces to curate and share to your social channels. Here are some of the best content curation tools to use:

• Curata – Uses an intelligent learning engine to create lists of suggested content for you to curate based on your interests. The app makes use of machine learning in its source code.
• Stackla – Utilizes machine learning to personalize curated content and offer effective recommendations.
• Vestorly – Uses an AI-guided engine for content curation that improves consumer engagement and increases marketing efficiency.

..And Content Creation

With ML tools, you can easily come up with content ideas that will reflect well on your brand. Here are the tools to explore:

• Frase.io – Uses natural language processing to help with content creation by learning the style of a writer and giving a brief summary of various articles
• Quill – A product of Narrative Science, this tool analyzes your data and communicates the analyzed information to your intended audience
• Phrasee applies AI to help you generate optimized emails to market to your list. The app uses AI in its features that produce human-sounding copy.

Predictive Analysis

Predictive analytics and propensity modeling tools are now enabling marketers to predict customers’ next moves. This is happening across the entire marketing stack, with tools for each marketing channel you use today.

Artificial intelligence tools can better predict when a buyer is ready to order a replacement product for an old item, for example. They can also predict which messaging will get that buyer to make a purchase, and which is likely to flop. These tools use a variety of data sources, from search data to demographic and previous purchase data. Some of the predictive marketing tools to utilize for your own campaigns include:

• Persado – A tool that performs a similar function to Phrasee, helping marketers find the most effective marketing language for their needs. The enterprise edition of the tool uses machine learning to produce the optimal brand copy.
• IBM Predictive Analytics – An extensive platform with cutting edge machine learning algorithms and toolsets for predicting your customers’ actions. The platform uses machine learning to analyze marketing and other data streams.
• Adobe Analytics – A machine learning tool that extracts insights from data to provide you with the best marketing opportunities based on what your customers need the most.

How Do I Know If ML Pays Off?

After deciding to implement AI solutions into your business operations or even making a targeted hire, you should also be able to measure whether AI or machine learning are improving your digital marketing ROI. Measuring ROI (return on investment) is a core concern for many marketers, especially when it comes to new technology.

1. The best way for digital marketing companies or teams to get ROI from machine learning or AI is to first identify a particular channel where you can deploy the technology – for example, you could look at email marketing or display advertising as a channel where you can improve your current execution by applying AI.
2. The next step is to then look for an IT professional who is experienced in using AI tools to help you apply AI to your marketing. If you are a small company, you can buy an off-the-shelf package that has everything you need.
3. You should then be able to measure the improvement in output of that specific channel in which you have chosen to implement AI, and the corresponding cost efficiency it has introduced. For example, you may notice that an improved AI-powered email marketing campaign has led to an increase in relevant clicks to your products and services, and a corresponding improvement in your sales.
4. By comparing this increase in revenue to the investment you have made on your AI implementation, you can measure your ROI. Note, however, that while the ROI might not be very significant during the first couple of months, it’s bound to become more substantial as its usage matures, so you should measure your ROI over the next couple of years.

There’s a vast collection of tools that you can use for each of these different areas of your business operations, and it is expected that using machine learning and its derivatives will help you remain competitive in an industry which moves so fast that keeping up with the latest technology is not just an advantage – it is the prime imperative for survival.