How Marketers can Leverage Machine Learning to Foster Revenue Growth

Altudo Artificial Intelligence (AI) is taking great strides, apart from being significantly responsible for digital transformation. The AI market is expected to exceed more than $191 billion by 2024, at a CAGR of 37%. Machine Learning (ML) forms an indispensable part of AI. ML is all about segregating data and characteristic development – transforming raw characteristics into the set of features that represent the gist of the data.

A 2018 CMO survey points out that 61.4% of companies aren’t yet using it, and around 30% companies have no near-term plans to explore the use of ML. Increasing conversion and customer engagement have always been on top of a marketer’s priorities, and for some years – they have been looking at data-driven marketing. This is where ML plays a monumental role.

An increasing number of organizations are implementing ML in their marketing strategies, and are deriving great results. Here are 3 ways how marketers can leverage Machine Learning better to foster revenue growth:

1. Less Data, More Insights

In present times, there is a lot of talk on big data and brands are swimming in it. The need of the hour for marketers is to develop insights from data, and not merely churning more data. Machine Learning and big data analytics can determine and create new segments for marketers to pau attention to.

This includes segments that marketing might otherwise overlook. Thereafter, segmentation of databases, target market, and brand messaging can be prioritized accordingly, and provide a boost to ROI. In simple words, when you have access to enough customer data – ML will try to find insights and patterns to drive lead conversions.

2. Improve 1:1 Personalized Experiences

Yes, brands are trying a lot to create omnichannel and personalized customer experiences. However, customer journey in the present day is more often than not – fragmented. Customers research for products, check out prices, make purchases, and ask for support on their preferred channel – regardless whether you are managing it or not. Moreover, in the world we live in, 1:1 personalized experiences is swiftly becoming the order of the day. ML is instrumental in connecting all devices and channels that customers use, in order to create a smooth customer journey. Chatbots are a great example of providing 1:1 personalized experiences with the help of ML. Therefore, a carefully planned and managed ML strategy will increase conversions through personalized marketing, accompanied by a process of continuous optimization.

3. Greater Adoption of ML & Automated ML

Some industries are leading the bandwagon of adopting Machine Learning and Artificial Intelligence. In retail, global spending on AI will hit $7.3 billion a year by 2022, up from $2 billion in 2018, states Juniper Research. Moreover, the AI healthcare space is predicted to top $6.6 billion, by 2021. This greater inclusion of AI and ML is largely due to the fact that brands wants to identify themselves as different and more effective, when it comes to improving customer experience.

Moving forward, automated machine learning will gain precedence, which will allow business analysts and developers to evolve machine learning models to address compound settings. Automated ML will enable the right level of personalization, without the hassles of going through intricate workflows.