Staying connected with customers is key, but it’s getting harder every day. As a business owner, you know how tough it is to keep up with everyone’s needs and preferences.

That’s where machine learning comes in — it’s like a secret ingredient that can turn your virtual assistant into a super-helper. Imagine a virtual assistant that not only talks to your customers but also understands them and their needs better.

In this article, we’re diving into four simple yet powerful ways you can use machine learning to make your virtual assistant smarter and your customer interactions more personal and effective.

For free AI tools and courses, visit my LinkedIn.

Data Collection and Preprocessing

There’s nothing worse than hiring a virtual assistant that doesn’t understand. Have you ever been brought a coffee mug of whiskey instead coffee first thing in the morning? 😨

AI assistants can make these kind of mistakes too if they are trained on data that is not properly processed. The first step in any AI project is to collect your data from various sources throughout the internet. These are as diverse as you can imagine.

The collected data then needs to remove the irrelevant and/or incorrect data to avoid giving the user wrong answers later. The way this data is “preprocessed” is through labelling, formatting, normalization, and imputation.

We’ll define these big words later.

Model training and evaluation

This is how big AI companies are making a profit off of your data with their virtual assistants.

After preprocessing your data proprietary AI models are trained by feeding data into neural networks to generate predictions.

In the case of ChatGPT the prediction the model output is the next letter in a sentence but for there are countless use cases for AI prediction. From soil weather prediction to your kids’ favorite show, AI is used in nearly every part of your life.

This is what makes model evaluation so important. Once the model is trained it goes through a stage of measuring performance. In the case of virtual assistants this means checking to see if the AI assistant understands and responds correctly to user requests.

Model deployment and integration

Know this before you start using AI powered virtual assistants. How are they integrating and deploying their AI models?

Before any sort of AI product can be launched and released to the world everything needs to be integrated.

In the case of artificial intelligence this means the retraining pipeline needs to be deployed to a cloud environment and a model repository created.

Depending on this process several things can happen. You get a fast, responsive, and smooth user experience or you are left waiting for the model to give you a response.

Eventually leaving to never return.

The deployment and integration result can have a monumental effect on the speed and latency of your AI VA.

Model maintenance and improvement

Am I the only one that has noticed ChatGPT has gotten better since it released?

That’s because OpenAI has one of the world’s leading methodologies of model maintenance and improvement.

On a set cadence the team at OpenAI takes all of the data that has been collected and feeds it back into the AI model that is powering their applications.

With the new data being processed by updated algorithms can evolve at a break neck pace. A majority of experts in the field have a hard time keeping up.

Consistently maintaining and improving the model not only provides a better chatbot experience but has added benefits such as improved reliability, security, and topic relevance.

User experience and engagement

The reason you are always on your phone, unable to put it down isn’t what you expect. It’s not that you’re too busy or addicted to Instagram.

It’s because smartphones have an outdated user experience. Since we use the 2 clunkiest digits, our thumbs, to type and text we spend a majority of day just inputting information.

AI VAs backed by large language models allow for a greatly improved experience and engagement. But how do they do this?

By removing the phone all together.

Modern AI can already answer all sorts of questions, commands, and conversational instructions. Now with the introduction of GPT VOICE user can speak out loud to an always on assistant to interact with their devices in real time.

For free AI tools and courses, visit my LinkedIn.