It's important to know how much value you're receiving from your marketing and business intelligence activities using data analytics. Artificial intelligence (AI) can be a great help in this situation.
When it comes to collecting patterns and insights from a large amount of data, AI is a group of technologies that have stood out recently. Google Analytics, automation platforms, and content management systems are just a few of the areas where you'll find your analytics data. AI is available today to help you extract far more value from the data you already have; unify that data; create predictions about client behavior using that data.
But how do you start using this? We've spent years at MGlobal Analytics developing and implementing artificial intelligence for data analytics. This article will help you figure it out! It will also provide you with some tools and ideas for incorporating AI into analytics.
What Is Artificial Intelligence?
The definition of artificial intelligence varies widely among specialists. Demis Hassabis, CEO of Google-acquired artificial intelligence firm DeepMind, provides an excellent description. "Artificial Intelligence" is a term coined by Hassabis, As technology has progressed, we have been able to educate robots to behave like humans.
Familiar Examples of AI
There are a lot of AI-powered features in modern day smartphones. It is possible to give them the capacity to see, hear, talk, write, and move. Facial recognition technology, for example, allows you to open your phone just by looking at it (AI that sees).
Additionally, they feature voice-activated devices (AI that hears and speaks in natural language). Predictive text is another consideration (AI that writes in natural language).
Self-driving vehicles are another example of modern day AI. This used computer vision (AI that sees and analyzes the environment) to autonomously move machinery.
Other popular companies like Amazon and Netflix utilize AI to suggest products or videos to you. Artificial intelligence is even used by email programs like Gmail to compose sections of your emails for you. Regardless of where you work or what you do, you are likely to be using multiple forms of AI on a daily basis.
AI, Machine Learning, and Deep Learning
"Machine learning" is the engine that drives the most amazing AI capabilities. Based on massive quantities of organized and unstructured data, machine learning can identify patterns. Predictions are made by the machine based on these patterns. Then, predictions become better as more evidence is gathered throughout time.
The results? Machine learning models are used to improve results over time, frequently without the intervention of humans.
Comparison
Accounting software may depend on human inputs to function. Humans write rules into the system. Once programmed, the software adheres to those rules to make tax preparation easier. This can also be seen when formulas are written into a Microsoft Excel spreadsheet. When data is input to a cell, the formula knows exactly what to do with it. In this case, a human programmer is the only one who can make the system better.
In contrast, machine learning-powered models may be initially programmed by a human, but they learn and grow on their own. These models autonomously analyze their own performance and use the data to power their own development. Going a step further, "Deep learning," is the most sophisticated kind of machine learning, in which neural networks are organized to resemble the human brain.
Example - Autonomous Emails
Circling back to the mention of Gmail above, Natural Language Generation (NLG) and Natural Language Processing (NLP) are other examples of AI tools that train themselves to perform better.
To train these AI models, the tool relies on samples of text from previous messages, which help it generate email subject and body text lines. This happens through a series of split-testing sessions. After each session, the tool takes what it has learned and carries the new knowledge to the next session. Over time, the tool learns to suggest more accurate text.
This opens the door to a potentially limitless amount of performance where entire emails could be read and replied to without human interaction.
This type of AI can also be applied to any field of work that relies on data analytics to make informed decisions. Everything, from advertising to analytics to content, may benefit from AI's ability to make it more intelligent.
How Market Leaders Use AI in Data Analytics?
AI Data Analytics may be used in a variety of ways. These are just a few examples you may want to know:
#1 Analyze your data for fresh, useful insights.
Humans can't perceive the patterns and insights in large datasets quickly. AI can do it on a large scale and quickly.
You may now get answers to inquiries regarding your website's data analytics using AI technology. Conversion rate is a measure of how well a marketing campaign performs.
In addition to making recommendations based on possibilities from your data, an AI analytics platform may also suggest actions to take. For example:
#2 Predict outcomes using analytics
Predictive models based on AI data are now available to help you make better decisions. With the help of artificial intelligence (AI), computers can examine data from a wide range of sources to determine what works and what does not.
It may also provide insights into your consumers' tastes, product development, and marketing channels via data analytics. For example
#3 Combining your analytics and customer data
Artificial intelligence may also be used to combine data from different platforms. The speed and scalability of artificial intelligence (AI) can gather all of your customers' data into one unified perspective.
Even call data, which is difficult to trace, may be unified, analyzed, and classified by artificial intelligence. For example:
Over to You!
When it comes to marketing and analytics, AI may assist you in improving revenue and minimizing expenses. Your company should begin using AI capabilities today, regardless of your competence or familiarity with the technology.
There are a few methods to speed up the adoption of artificial intelligence in your profession and organization. You should either learn about the subject or book a consultation with one of our data analytics experts with AI.
Our years of experience are now at your fingertips in a fraction of the time!
We work with you every step of the way to level up your analytics game for the future. This way, you are armed with more valuable insights that keep you ahead of your competitors.