How to Use Machine Learning in Your Business?

How to Use Machine Learning

If we sit down to look into the advancements that technology has made, the one that would top the list is how we have made them think independently and make their own decisions. What was once thought to be straight out of a Sci-fi book, Machine Learning has today given the IT world a capability to create insights from data and use them to better the industrial efficiencies.

While presumed to be present in the autonomous vehicle sector, Machine Learning is finding a place in the everyday business world as well. Deep diving into it is what our article is focusing on.

Machine learning technology in businesses helps with enhancing scalability and bettering business operations across sectors and the world. Benefits like increasing volumes, ease in data availability, cost-effective and fast computational processing, and economical data storage has led to a huge machine learning growth spurt.

Let us look at how businesses can benefit from Machine Learning app development – giving them reasons to make the move in case they are still on the fence.

How Does Machine Learning Helps Businesses?

1. Analysis of Sales Data

The sales domain stands to benefit immensely from rise in sales-centric data generated at the back of growing digital interactions. The sales teams can gather information from a plethora of sources – website metrics, social media, client calls, conversations on chatbots, etc.

However, with a huge amount of data being presented on the internet across an expansive list of resources, it can take time for the sales team to analyze all the data. Machine Learning, in this instance, can expedite the process by uncovering valuable information. An example of this can be seen in the Growbots platform which uses machine learning for connecting sales teams with the best leads.

2. Prediction of CLV

Predicting customer lifetime value and buyer segmentation is one of the biggest challenges that marketers face in the present time. Businesses work with a huge amount of data that can be used to derive important business insight.

Machine Learning in combination with data mining techniques can aid businesses in predicting customer behavior, their purchasing patterns, and help them in sending the best offers to the customers or website or app viewers on the basis of their purchase or browsing history.

With hands-on availability of data, businesses are able to predict the customer lifetime value of their users base.

3. Real-Time Personalization

Digital personalization continues to be a sought-after process of businesses for engaging customers and prospects in a way that they become regular customers. Considering the finicky nature of modern-day customers and huge availability of options for them to invest their time and money in, real-time personalization is one of those elements which businesses have to get on top of in an urgent mode.

Marketers have started turning towards machine learning for leveraging the information which they can find about a customer and use it for building personalized mobile experiences which please customers and offer them a great return on their investment.

Flybits is one of the companies which makes use of machine learning for enabling companies to offer real-time personalization. They enable businesses to have an instant cloud access to their internal and external data for developing personalized marketing messages.

4. Elimination of Manual Data Entry

Removal of manual data entry is one of the primary issues of any organization. It doesn’t just over time increase the probability of errors but also carry a dire impact on employee’s productivity and retention rate, since lack of learnability is a key reason why millennial’s don’t stay in an organization for long.

Machine Learning algorithms and formulas can be used to carry across the manual data entry tasks entirely or can be used to check if the entered data or calculation is correct. By using these tools employees can not just ease their workload but also find time to work on their advanced skill set.

5. Product Recommendations

Until you are living in a cave, you would have come across the ‘product recommendation’ functionality across platforms. While most visible on eCommerce platforms like Amazon, media houses like Netflix and Hulu also make use of the Machine Learning-driven functionality to recommend users what to watch next on the platform.

Here’s how it works: Machine Learning algorithms make use of customers’ purchase, search, and viewing history and align them with the product and media inventory to find out patterns and then group the similar products or media together. These products or media options are then suggested to the customers.

Talking about the product recommendation functionality, John Bates the senior product manager of predictive marketing solutions at Adobe says, “By leveraging machine learning and predictive analytics, brands can look beyond what customers are searching for and start connecting the dots on what they likely want. It’s cross-selling at scale — matching customers to specific products or content that will nudge them towards more conversions and greater lifetime values.”

6. Dynamic Pricing

Sectors like retail and travel see a huge opportunity in changing pricing on the basis of demand and need. However, integrating dynamic pricing can be an impossible task when there’s a large enterprise in picture with its presence in multiple locations and among a large segment of customers.

This is where machine learning comes in handy. Companies like Airbnb and Uber make use of machine learning for creating dynamic pricing models for the users in real-time. By using the real-time data to predict demand, businesses can charge a price on the basis of what a person is comfortable paying.

Here were the different ways businesses can make use of machine learning technology for making their processes efficient while delivering immersive customer experiences. What is important to understand here is that not every use case that you find on the internet will apply in your business model. So start with identifying a scope of machine learning integration in your business and then partner with AI experts who specialize in helping businesses digitally transform through the support of machine learning capabilities.

Author Bio:

Smith is a very creative writer and active contributor who loves to share informative news or updates on various topics and brings great information to his readers. His priority is to cover up new technologies and techniques for his audience. Smith has come out with many interesting topics and information that attracts readers to unravel his write-up.

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