Machine learning (ML) can be defined as the technology that develops algorithms to perform certain tasks and are capable of autonomously learning and improving from errors. It is a model which learns patterns through big data and analyzes a host of similar patterns in new data After algorithms have been developed.
Examples of ML Applications:
ML applications tech is deployed for various use cases some include advertisement placement, spam filters, fraud detection, recommender systems, credit scoring, some of the common examples are:
- Event organization via online calendars is enabled by ML – integrating event invitations to your online calendar from an email is an example of ML activity.
- Rental cars or taxis, such as Uber, use ML technology to locate a free cab, amongst those that are currently en route with a passenger.
- News curation – the news that we read on our smartphones is organized as per our interest which is derived from ML algorithms.
- ML and AI tech have also transformed day-to-day activities such as controlling air conditioning temperature of which can now be controlled within an app.
These are some of the common everyday applications of ML and AI. But, have you ever wondered how it may be helping sales and marketing experts?
You would be surprised to know that marketers around the globe have started relying on ML and AI for marketing strategies. In fact, most of their current strategies are centered on AI and ML-based applications. In a 2017 report, three in four companies saw a 10% jump in the sales of new products and services from effective use of ML and AI. In this article, we will explore the connection between ML, AI
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Why do we need ML or AI in marketing?
Marketing is one of the most important functions behind the success of any company. In saying this, marketing teams across the globe need the latest technology and resources to make sure that they surpass competitors. And, we all know that the present buzzwords of the world are ML, AI, deep learning and big data. Marketers have access to a vast array of customer and audience data information through online activity such as social media posts, browsing activities, content history. As a result, marketers need to ensure that they are equipped with the right tools, powered by these new age technologies, in order to prepare better strategies and implement enhanced marketing plans.
What is the connection between ML and marketing?
In saying that marketing experts have access to a voluminous amount of data, the amount of data can become confusing. Therefore, they need to first learn how to master the huge quantity of data which is there at their disposal to ensure the success of their marketing strategy such as communication strategies, segmenting audiences and developing attractive marketing campaigns.
ML and AI can aid in understanding the data – through the aforementioned new age technologies, marketing professionals can easily access, use and implement the audience related information. ML enables marketing experts to make quicker and smarter decisions. They can use the data effectively to make better plans or to also build connections with the target audience.
How is ML helping marketers fetch better ROI?
Efficient customer segmentation is important to curate and implement best marketing plans. ML algorithms can be effective when it comes to extracting identical groups of customers who have the same preferences as well has behavioral patterns.
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ML can be used in forecasting and when used correctly, can predict how many of your current customer base have the highest chances of churning business revenue. ML helps to identify patterns in the data to better understand customer value. Additionally, with this information, marketing professionals can develop plans to engage with customers.
ML applications in marketing
ML and AI can be used to enrich the customer experience and for various use cases within marketing plans of a company as discussed. One of the most powerful examples of a use case is the ability to refine the upsell strategy of a company. Furthermore, with effective use of ML, marketing experts can make sure that customers can receive data-based product recommendations.
As an example, the Hyatt uses ML technology to study guest’s travel history as well as the accommodation inclinations. Based on such insights about their guests, booking agents can automatically receive alerts when a guest is checking in, and whether that guest would want a room with a great view or a suite, or whether he or she would be interested in additional services such as a room with a spa.
ML-based solutions are capable of learning and informing marketers about effective strategies for every prospect of their marketing strategy. ML is transforming marketing tasks – activities like lead scoring, customization of customer engagement, predicting sales, cross-platform marketing campaigns are being managed efficiently.