Chart of the Day: Use Machine Learning AI to understand the propensity of your site visitors to convert
I'm reviewing a different type of Chart today since while reviewing Google's Demo Account while working on some new learning materials for our members I noticed the intriguing new Conversion Probability feature Beta.
Here's what it shows for the one hundred thousand odd sessions in the Demo account:
You can see that it breaks down these sessions into likelihood to convert, so if we can learn more about what turns the high-converting visitors onto our products, we have more chance of finding and converting more visits in future.
As we explain in our AI and machine learning guide, for us, the most exciting marketing application of artificial intelligence is using machine learning to learn from historic interactions with our audiences see what influences their propensity to convert.…
The challenges marketers face overcoming the hyperbole and mysticism that surrounds machine learning and AI
The marketing industry is abuzz with talk of how marketing applications of machine learning and AI will make us more effective and change the way we do our marketing. The problem is that while we’re all keen to embrace innovation and get a competitive edge (which machine learning most definitely provides), for many of us it sounds inaccessible and beyond our typical marketing capability.
However, within the next five years, we believe machine learning will become an everyday skill that marketers will be expected to possess, built into our software and processes as standard. The challenge for marketers today is in overcoming the hyperbole and mysticism that surrounds machine learning and AI, to understand what it might mean to them.
It helps to first look at one of the main issues we marketers face - data. Too…
Chart of the Day: How does use of Artificial Intelligence vary in different sectors
As with any new disruptive technology that is moving it's way up the hype cycle, Artificial Intelligence won't be uniformly adopted. It will be a better fit in certain sectors and for businesses of a particular type. As futurist William Gibson put it:
“The future has arrived — it’s just not evenly distributed yet.”
This new research from the McKinsey Global Institute is useful since it looks specifically about how AI and Machine Learning will generate value in the future. One finding, which mirrors our advice for marketers is that businesses should focus on using machine learning applications to support the marketing and sales process and acquire skills where needed in this area.
One example of the value that machine learning can generate in the report is about how Netflix has used a machine learning algorithm to personalize recommendations to its 100 million…
How can machine learning enhance your digital marketing strategy?
The launch of Google’s new machine learning tool, RankBrain which contributes to search engine results, left many people wondering what impact machine learning would have in the realm of Search Engine Optimization (SEO).
With the tech industry going crazy for all things Artificial Intelligence (AI), Natural Language Processing (NLP), machine learning, and chatbots, it’s important to know what the technology is, where it’s going, and what impact it will have on digital marketing as a whole.
This article will explain these concepts as well as share some tips on how to adapt to machine learning.
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The Growth and Popularity of Machine Learning and AI
Machine learning is, in fact, not new to the tech world. It first appeared as a concept back…
Chart of the Day: McKinsey Analysis rates machine learning marketing applications highly
I thought this was an interesting chart and article from McKinsey on 'What’s now and next in analytics, AI, and automation'.
McKinsey outline the range of opportunities for applying artificial intelligence in their article. They say:
'For companies, successful adoption of these evolving technologies will significantly enhance performance. Some of the gains will come from labor substitution, but automation also has the potential to enhance productivity, raise throughput, improve predictions, outcomes, accuracy, and optimization, as well expand the discovery of new solutions in massively complex areas such as synthetic biology and material science'.
At Smart Insights, we've been looking beyond the hype to look at specific practical applications for applying AI in marketing. Our recommendation is that the best marketing applications are in machine learning where predictive analytics is applied to learn from historic data to deliver more relevant personalization, both on site, using email…
Using machine learning and predictive intelligence in the B2B Buyer journey
AI (Artificial Intelligence) has become a business buzzword this past year, even featuring in the mainstream media. AI includes any kind of computer program which actively seeks to mimic a human capability, such as understanding speech, recognizing images or responding to questions. When it comes to using AI in the sales cycle, there are two technologies which are particularly useful, and it’s worth drilling down and understanding them rather than focusing on the nebulous term ‘AI’. These are Machine Learning and Predictive Intelligence.
These two technologies can work in tandem to provide your sales team with a way to target the hottest and most qualified leads, and thus save time and bring in more revenue.
The graphic below shows the range of different artificial intelligence, machine learning, and propensity modeling techniques which can be applied and different stages of the customer lifecycle.
Mapping the most effective AI technologies for marketing across the customer lifecycle
AI technology is a hot topic in marketing at the moment, but AI is a broad term covering a wide range of different technologies. Artificial intelligence means any technology that seeks to mimic human intelligence, which covers a huge range of capabilities such as voice and image recognition, machine learning techniques and semantic search. Marketers like to wax lyrical about the latest exciting technologies and bang on about AI for image recognition, speech recognition, preventing data leaks, or even targeting drones at remote communities. All well and good. But how the bloody hell are marketers supposed to do anything with that information? It's just hype, you can't implement it.
That's why we've identified fifteen artificial intelligence techniques that businesses of all sizes can implement, rather than techniques which only major tech giants can devote resources to. We've also…
How to use Artificial Intelligence to boost ROI from advertising
For marketers, the tide of artificial intelligence has finally crashed ashore.
It has begun making waves at industry events like WSDM: The 9th ACM International Conference on Web Search and Data Mining Web Search and Data Mining conference in San Francisco. In his keynote address, Google research fellow Jeff Dean told attendees it’s time to embrace techniques like deep learning. Once a land of buzzwords, rapid improvements in machine learning have made AI a pivotal member of marketer’s toolkits. As best practice guidelines on Machine Learning at Google shared by Martin Zinkevich (technical) show, Google are actively using Machine Learning in many projects.
Dean and others are excited about AI because it will finally allow marketers to take full advantage of the hordes of data they’ve begun collecting. While we’ve been able to generate mind-boggling mounds of data for a while —…