In recent years, AI and Machine Learning have become top trending buzzwords for businesses around the world. By adopting solutions empowered by machine learning, organizations have enhanced the productivity and performance of their businesses.
Unsurprisingly, machine learning solutions have penetrated every major industry, ranging from healthcare, e-commerce, and retail to manufacturing, retail, and logistics. And if this trend continues, these solutions can contribute $15.7 trillion to the global economy by the year 2030.
Investing in AI and machine learning can reap countless benefits for businesses over the long run. In fact, according to almost 85% of business executives in 2017’s Artificial Intelligence Global Executive Study, AI and machine learning are essential for gaining or sustaining competitive advantage.
The best way to gauge the usefulness of emerging technologies is to determine its practical applications. For this reason, I have compiled a list of the key areas where AI and machine learning can accelerate business growth; continue reading to learn more.
Enhancing Online Shopping
According to a study conducted by The Stack, as much as 57% of major executives believe that machine learning could be most beneficial for enhancing customer experience. However, this isn’t just the opinion of a handful of executives; there are plenty of practical ways machine learning can improve the online customer shopping experience.
For instance, we can leverage machine learning to personalize the buying journey of a consumer and helping them find the products they want. Techniques such as Market Basket Analysis can play a crucial in enabling this.
Similarly, we can utilize various other machine learning techniques to ensure that the inventory of our online store never runs out. In other words, customers will not have to deal with out-stock products. Even if a product is unavailable for a reason, we can utilize machine learning to suggest alternatives for that product.
Salesforce reports that 52% of consumers can switch brands if they feel their company isn’t making an effort to personalize their marketing. At the same time, some studies claim that 44% of consumers believe that personalizing shopping experience makes them more likely to return to a brand in the future.
Therefore, both these applications streamline consumer marketing funnel for businesses of all sizes. By personalizing the shopping experience of online consumers, it will be easier for businesses to sell related products and keep their revenues flowing.
Leveraging Analytics for Data-Driven Decision-Making
Due to the revolution in network and storage technology, it is much easier to leverage technologies such as Big Data. Businesses across the world can now collect and store heaps of data related to their major business processes.
Nevertheless, even heaps of data is useless unless you can process and analyze it. Data science and machine learning enable us to process and analyze huge amounts of data, which wasn’t possible before.
As a result, it is easier to determine the underlying relationships between various Key Performance Indicators (KPIs). Similarly, with the help of data analysis, we can gain insight into countless other factors and their impact on business.
One popular example of this is the data-driven optimization carried out by SAP HANA. Coupled with SAP’s largeERP platform, the in-memory data platform leverages machine learning to identify underlying patterns in data.
Famously, the solution has enabled Walmart to implement data-driven decision-making. As a result, Walmart has been able to utilize the data of more than 245 million customers and accelerate business growth worldwide.
Optimizing Supply Chain Management
Machine learning and artificial intelligence can also play a key role in optimizing retail and inventory management in the supply chain. We can use these algorithms to streamline supply chains and automate refilling requests. In other words, you no longer need manual procedures to handle supply chain and inventory management decisions; instead, you can trust AI-based solutions to make data-driven solutions.
Technology giants such as IBM Watson are investing extensively in supply chain management. Already, IBM has launched various supply chain products to assist global businesses in automating order management and fulfillment. With the advent of the Internet of Things (IoT) and 5G, we can expect this trend to grow.
Create New Revenue Streams
Nowadays, digital marketing is centered on the flow of traffic and data. Since there is a large amount of data available from websites, the majority of companies see it as an opportunity to improvise their marketing and increase their revenue, at the same time.
By analyzing traffic streams, companies can identify the demographics of their target market. Similarly, it’s also possible to gain additional insights into the consumer market through various machine learning techniques.
In other words, machine learning and AI can help businesses gain useful insights about their products and services and tailor them according to their target market.
Improving Web Design
It’s also possible to leverage machine learning in optimizing web design for users across the world. Nowadays, consumers view different forms of web content based on the device they use.
Since consumer devices are distributed across a diverse spectrum, ranging from traditional laptops and PCs to wearable devices, maintaining a dynamic design continues to be a challenge. By analyzing real-time data and processing it through a machine learning model, web developers can implement responsive web design more efficiently.
Consequently, responsive web design will help businesses to increase page views and conversions and reduce bounce rates, at the same time. All these things will improve website performance and contribute to business growth.
Revolutionizing Manufacturing
Like any other major industry, manufacturing relies on efficient business processes for reducing production costs and maximizing profits. AI and machine learning play a key role in reducing production costs and maximizing profits, in the manufacturing industry.
Machine learning coupled with the IoT and edge computing, can help make industrial machines smarter and streamline the business processes in a way, that wasn’t possible before.
Manufacturing companies can utilize onsite resources to process data in real-time and make smart decisions during production. As a result, companies can make production cycles faster, with fewer costs and greater margins of profit.
Fraud and Cyber Threat Detection
Although machine learning and AI are often used interchangeably, there is still a clear distinction between them. Unlike AI, the purpose of machine learning is not to mimic human intelligence. Instead, it uses a series of steps to analyze available data and processes, then finds ways to classify segments by identifying underlying patterns.
This is why machine learning has significant scope in the field of fraud detection. Several businesses spend a fortune in preventing fraudulent transactions. Since fraud detection relies a lot on recognizing the behavior and pattern of fraudulent users, machine learning can play a crucial role in identifying such people.
Classification techniques such as logistic regression, gradient boosted trees, multi-layer perceptrons, etc., can help organizations catch fraudulent users and prevent fraudulent transactions.
Likewise, we can use unsupervised learning techniques to resolve pattern anomalies and identify behaviors of fraudulent users. The same method can be used against cyber-security threats to maximize security against viruses.
Antivirus solutions such as Kaspersky are using machine learning techniques to create predictive models for detecting viruses in enterprises. Similarly, companies such as deepsense.ai have various products for detecting and preventing online fraud. Being able to detect fraud and security threats helps organizations to cut losses from scams and cyber attacks, which indirectly help them in maximizing their revenue stream.
Conclusion
AI and machine learning have the potential to revolutionize businesses in all corners of the world. Therefore, making these innovative technologies a part of your business is not only beneficial but also essential for business growth in the future.
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