Disclosure: WHSR is reader-supported. When you buy through our links, we may earn a commission.
How to Use AI and Machine Learning for your Business
Updated: 2020-11-02 / Article by: Timothy Shim
In the age of digital it has become increasingly vital for business to adapt in order to remain competitive. Today, even the smallest business can digitize and access a much larger potential customer base it traditionally could.
The larger a potential customer base is, the more data a business would have to deal with. While some have treated this as an obstacle to overcome, that data is actually a massive goldmine if handled correctly.
Artificial Intelligence, or AI, can be combined with Machine Learning (ML) to produce very interesting results. Even better, subscription-based services have made many things available for businesses of all levels as well.
Let’s take a look at some ways this can be done;
5 AI and ML-driven Business Ideas
1. AI-driven Personalised Experiences
It has been said that today’s business needs to customize production for a customer size of one. As customers become increasingly product-savvy, they are demanding more unique products than ever before.
While this can be taken in the context of needing a highly agile product line, it can also apply to customer experience as well. However, in order to do this accurately, two elements need to come into play: a massive amount of data, as well as a service which is able to produce actionable insights based on it.
Take for example the case of Vidora Cortex. Looking past the original big data model, Cortex was designed to streamline raw data into ML pipelines. The more data which is fed into Cortex, the smarter and more accurate insights generated by it become.
In turn, businesses which take advantage of it can build personalized experiences for a variety of benefits. This includes:
Driving new subscriptions
Increasing customer loyalty
More accurate customer segmentation
Marketing delivery analysis
2. Audio Content Generation with AI
Time is money but that is often taken from a business perspective. Because of technology, user habits and behavior have changed significantly as well. Users were happy to dwell on web pages to consume content in the past. Today, you need a better delivery method to capture attention.
One way of doing this is by making use of audio. It’s less resource intensive then video, but delivers similar benefits in some ways. Don’t worry though – gone are the days of paying voice actors, studios, and even developers to build effective audio content.
All you need is a single tool like LOVO. The concept behind LOVO is stunningly simple and yet impressively effective. Simply provide text-based content and the LOVO generator is able to convert that to speed.
Not the typical robotic speech of the past, but realistic speech with a variety of characteristics. You can have the speech done as if it were by a male or female, adjust tone, and even language and accent. Amazingly, LOVO can read the content written in various supported languages.
Here's a sample of a clip done with LOVO:
Best of all, you don’t have to wait for days or weeks to get what you need. Since LOVO is fully AI-based, your audio content can be ready in a matter of minutes.
3. Sentiment Analysis from Natural Language Processing
Google, as we all know, is one of the largest companies on earth. That places it in a strong position to do what it does best – collect data. It gets information from so many sources that it can easily lead the pack when it comes to making use of that data.
Thus came into being the Google Cloud Natural Language engine. What Google has done is to build something that is capable of reading text and analyzing it based on ML. Google says this enables users to “reveal the structure and meaning of text”.
On a more realistic level though, there are many interesting ways that business might leverage on this engine. Let’s take for example myself as a content producer. What I do makes it very important that I pass along the right ‘tone’ to an appropriate audience.
By running content that I produce through the Natural Language tool, it can analyze and translate it into various forms. For me the Sentiment analysis is what I tend to look at most closely to make adjustments.
This can be especially useful in various scenarios, such as for building marketing content, that which is of commercial intent, or whatever else the user wants to focus on. This isn’t just for documents though – there is an API you can use to even extract insights from audio content.
4. Automated Service with Chatbots and AI-scripts
A major challenge that faces business is providing sufficient levels of support while maintaining healthy profit margins. This has grown increasingly difficult with increasingly widespread customer bases and the demand for faster service.
Enter the Chatbot – a tool which used to be so basic and archaic that budding young programmers used it as a joke. The Chatbots of today don’t just work on simple scripts though, they’ve grown much more advanced.
Driven by AI and ML, the modern Chatbot can not only serve as first-line support, but are able to learn and adapt so well they can effectively resolve customer problems on their own. Imagine this implemented at scale and supporting your customers across the globe.
Still though, using a Chatbot for support services merely scratches the surface. Thanks to learning capability, they can now be used in so many ways – even to help companies drive sales on digital platforms.
I’ve taken a look at a number of Chatbots and seen what they can do. The list of possibilities is as impressive as the Chatbot models and providers that exist in the market today. You can even take some of them for a test drive for free.
Let’s be honest – as a writer, there’s nothing I’d like more than for this to go away. Automated content generation just might eventually kill my livelihood. Thankfully though, it does see to be in its infancy for now.
Being ML-based, I find that initially, engines like this are able to come fairly close to producing something realistic. However, as the initial text provided dilutes, the intent tends to go haywire and run off on unimaginable tangents.
The situation is a little different from a business context though. Imagine you’re a smaller business and need some inspiration for web or marketing content. By using a tool like Inferkit, you could easily come up with some very useful ideas.
Or how about dry, boilerplate stuff like a terms of service document? You won’t have to pay to get it done and won’t be restricted to using templates either. Run the idea through Inferkit by giving it some basic content, and just tweak the results that come out.
To give you a better idea of how this might work out,I ran a sample of some support documentation text through the engine. It did produce something that was workable and could be edited for use (see image above).
What Exactly is AI and ML?
Although they may seem similar, ML is actually a subset of AI that refers to the adaptation. While all of this may sound a little daunting for those not in the tech industry, we should focus on their application from a business perspective instead.
Technology has always helped by serving as a catalyst. AI and ML are the same way and can help businesses to scale much more easily. Imagine having a support staff of one human manager overseeing chatbots supporting 100 customers at a time.
Or being able to use business tools that can tell you what customers are experiencing when they look at or talk about your products. The scope of applications where AI and ML can be exploited is vast.
It may be true that in many forms, AI and ML are still in their infancy. At the same time, it is easy to see the potential in this field of study. Already, many capable solutions exist and can be taken advantage of, such as the very capable Chatbots of today.
If you’re still uncertain about the likelihood of this, think about the Facebook business pages you’ve been visiting, or the chats you’ve been having with support personnel on some company pages. Are you certain you’ve been talking to a human?
Timothy Shim is a writer, editor, and tech geek. Starting his career in the field of Information Technology, he rapidly found his way into print and has since worked with International, regional and domestic media titles including ComputerWorld, PC.com, Business Today, and The Asian Banker. His expertise lies in the field of technology from both consumer as well as enterprise points of view.