Artificial Intelligence to Implement on Your eCommerce this 2019

We are in privileged generation to live in this era full of technological advancements. Gone are the days when almost everything was done manually, and now we live in the time where a lot of work is taken over by machines, software, and various automatic processes. In this regard, artificial intelligence benefits to society has a special place in all the advancement made today. Ai or artificial intelligence is nothing but the science of computers and machines developing intelligence like humans.

In this technology, the machines are able to do some of the simple to complex stuff that humans need to do on a regular basis. As the AI systems are used on a day to day basis in our daily life, it is not wrong to say that our lives have also become advanced with the use of this technology.

Those who operate ecommerce website, having best artificial intelligence programs on you site might be a good move, especially as we are in the era of technological advancement. For this reason we compile a great list of AI to implement on your ecommerce website that will help you to successes.

Chatbots

Think back on the questions you’re asked most often, and utilize that information to develop a chatbot capable of answering support questions. It does not necessarily have to be a customer service bot; you might devise a chatbot that responds to questions from new employees regarding HR benefits or details on how to reach the help desk.

Microsoft QnA Maker is a service that works exceedingly well in this regard. Simply input the URL of your FAQ or feed documents and spreadsheets containing the questions and answers.

The service will divide the questions and answers into pairs, which you can review and convert into API. However, if you’re seeking an interface that provides more than text replies, consider the  Microsoft Bot Framework. This will allow you to display rich content and media.

Try to create bots that are compatible with social networking websites and evolve over time. So, instead of answering individual inquiries, facilitate a goal-centric conversation that resolves the customer’s issue.

For example, Microsoft recently introduced customer-care features in Dynamics 365, where a virtual agent offers multiple solutions and directs the customer to human support, together with details about the conversations and the recommendations given.

Even if it cannot resolve a problem, it learns how to handle the situation the next time. Some organizations like Microsoft and Macy’s have already set up this service in-house to serve as online support.

Fraud Analysis

Fraud analysis or fraud detection machine learning project is one of the most effective AI projects you can implement is one that identifies anomalous and fraudulent transactions, especially on a larger scale, that cannot be handled by traditional data analytics.

Artificial intelligence is excellent when it comes to detecting scammers who are paying multiple times within a specified trigger limit, legitimate clients who are being scammed, and newly added merchants displaying unusual actions or behaviors.

Some companies rely on Amazon Machine Learning to train numerous systems how to detect fraudulent actions instead of attempting to create one model capable of scoring fraud of all types. After all, a merchant might be at risk from multiple fraud techniques, each with its own set of variations.

Artificial intelligence also works wonders by preventing bad transactions from going through. The credit division at Ford Motors is using ZestFinance-supported artificial intelligence to estimate the possibilities of certain borrowers paying back a financial loan despite their low credit scores.

So, AI has the power to distinguish between bad risks and reliable customers properly and quickly.

Impact of Artificial Intelligence on Security

The security industry is vast and complex, and artificial intelligence is the solution to only a small part of the problem. However, it is still powerful enough to identify attacks under the cover of all the alerts and logs.

Take, for instance, the Windows Defender Advanced Threat Protection. Despite its name, it is not an antivirus software; instead, it’s a machine learning system that compares the behavior of your PC to others running Windows 10 Enterprise on your network, notifying you and your security team of malicious attacks, a document exploit, or social engineering.

While you still have to comb through logs to remedy the damage, artificial intelligence security tools allow you to cut through the noise and get to the crux of the matter.

Predictive Maintenance for IoT

Do you wait until the last moment for your system to break before fixing it? This leads to poor user satisfaction and downtime. Plus, you have to take systems offline more frequently to conduct maintenance which decreases production yields. It is better to be able to predict an issue and correct it before it becomes an issue that impedes progress and/or hurts results.

Utilize the Azure IoT Suite from Microsoft to monitor your equipment remotely, assess the chances of failure, and service equipment before a total breakdown. Not only does it improve the overall customer experience but the total costs go down as well since most product problems now get fixed on the first visit. The number of spare parts in inventory could also be knocked down considerably.

As per the 2018 report on industrial IoT from Accenture, predictive maintenance is capable of minimizing scheduled repairs by 12 percent, reducing maintenance rates by 30 percent, and decreasing breakdowns by a maximum of 70 percent.