Machine Learning Can Help the Tech Businesses – The Three Prominent Ways

Simply put, machine learning can be defined as a subcategory of AI (artificial intelligence), and it has proved to be a very effective tool for tech business owners and customers. Today, you can access the AI-enabled software that assists the marketing teams and the leaders to have a clear understanding of their target audience. It also helps to secure data and streamline multiple procedures. Hence, the existing and new customers usually have a great experience that repeatedly brings them back to a brand’s website.

Brands making fruitful use of machine learning

Today, many brands make effective use of machine learning. Let’s the example of Trendyol, which is a leading eCommerce organization in Turkey that witnessed threats from the leading market players like ASOS and Adidas, especially in sportswear. Hence, in an attempt to improve its email system and attain consumer loyalty, it joined hands with Liveclicker, an expert in real-time personalization.

Trendyol used AI and machine learning to come up with multiple customized marketing campaigns. It enabled them to distinguish the messages that will be crucial for consumers. It further developed an offer for the football jersey thereby projecting the receiver’s name at the back to take the customization a level up.

Hence, the brand’s click-through rates, open rates, sales, and conversions went up by creatively making use of customization. It resulted in a 30% hike in the click-through rates and a growth of 62% in the response rates and an increase of 130% in the conversion rates. Today, it also implemented robust market functions such as mobile app, social media utilization, celebrity endorsements, and SEO blogs for reaching the customer base.

The ways in which machine learning helps

In this article, we want to delve into three crucial ways in which machine learning can benefit a tech business. The objective is to enable organizations to execute this technology on their website and all that they can expect from it.

  1. Arrive at the split-second decisions

The tech environment is forever changing! Hence, it’s crucial to know how to arrive at split-second decisions. It’s not always a simple task to take the correct call when you don’t have precise data. Machine learning enables addressing of and resolving the pain points by enabling the organizations to collect and assess data fast. Hence, your team can make fast changes for enhancing the CX or resolving harmful situations.

For instance, let’s there’s been a data breach at the back end of the website. It will concern you and you wish that your security team gets to the root of the issue. The team assesses the traffic sources all through the website and can’t arrive at the vulnerabilities. So, what can you do now? When you resort to machine learning software, it enables you to recognize the weaknesses within seconds. And these programs search for anomalies and send the data back to your tech team to resolve the problem. And if you take more time to resolve this you will lose out on the crucial customer data. The capacity to manage the security and get to split-second decisions will enable you to save more. To know more about this, you can check out

  • Enhances effectiveness and boosts the focus on the repetitive tasks

The other advantage of machine learning is a productive tech team. It could be that your team has a reasonable workload, which can lead to stress. With AI, you can save the energy and time of your team and allow them to concentrate on the efficiency of repetitive tasks. Customer support is one such domain. Here the support teams can work through several tickets weekly. And it would always be great if there was a process to bring down the tickets as you increase the scores and cater to your customers.

This goal can be accomplished by adding chatbots to the support team to help. This technology makes use of machine learning for managing consumer requests. And if there is anyone who wants to change the password or arrive at a price check, the chatbot can manage all such inquiries. And when a person contacts the website with a tough problem, the bot can shift the call or query to a live agent and provide the required assistance. It will help to bring down the team’s overall work pressure and allow them to engage with the consumers who are in need of help.

  • Enhanced customer and product personalization

Personalization is an effective business strategy for most brands. Today, competition is too much, and hence customers search for organizations that can zero in on the goals and pain points. And that completely makes sense. Why will a person invest money and time in an organization that has no understanding of his/her particular needs?

If you look at Amazon, personalization has played a huge role in its expansion and growth. This brand’s storefront resorts to AI for categorizing items depending on the same buys from various consumers and then set up customized product lists and provides for the users depending on their shopping history. And all these customized lists get developed with AI software which assesses the consumer behavior and arrives at quick decisions about what they intend to buy.

There is no need for a brand to get as big as Amazon to leverage machine learning. Several tech business brands use AI-enabled smart advertising to show the customers useful blog content depending on their past experiences on the website. Hence, you should collate the data and use everything you have learned in the email marketing campaign to provide the best-customized experience for your subscribers.

Today, we all know that AI will benefit tech organizations and add to their growth. It’s best to execute machine learning gradually. You can simply start by recognizing the space where you want to gather and assess a huge quantity of data. After that, you can install the correct software and then can monitor the outcome. You will start viewing the data and trends, enabling you to make design, support, and marketing decisions better.

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