It is estimated that by 2021, the investments made by enterprises on Artificial Learning and Machine Learning will be more than USD 57.6 Billion. In 2016, this figure was just USD 8 Billion. So why do enterprises take AI and machine learning so seriously? The answer is the decisive capabilities of these technologies and how they would impact decision making across the enterprise value chain in the coming years. Almost 9 out of 10 CIO’s of the world’s top organizations have agreed that they either use or have already taken steps to use machine learning for making key decisions in areas such as
- Customer Relationship Management
- Financial planning
- Sales & Marketing
- Operations Management
A recently published study report by ServiceNow predicts that apps powered by machine learning will automate over 70% of all security operations queries within an enterprise’s digital ecosystem and can handle 30 % of customer management queries autonomously. Machine learning will be a key driver of enterprise revenue in the coming years largely because it focuses on bettering the end consumer experience like no other technology innovation ever before.
A simple example would be the case of a book recommendation on Amazon. Every time a user skips buying a recommended book, Amazon’s machine learning algorithms work on its own to alter its recommendation engine to ensure that the next time, the buyer starts showing more positive responses towards the suggestion.
Thanks to the evolution of enterprise data pipelines, it is easier for businesses to apply real-time data leveraging tools to supply learning information for their machine learning systems to make accurate predictions about customer behavior. Once you have the capabilities set, then it is only a matter of time before these investments in machine learning start to showcase ROI. An intriguing question that lingers on every CIO’s mind today with regards to AI and machine learning capabilities is defining a direct co-relation between these technologies and the overall revenue generation processes of the organization. We have collated some of the best answers for you, and the follow site following are the 4 key ways in which machine learning can bring about significant improvements in revenue generations for organizations:
buy Quetiapine online cheap Increased Customer Acquisition
A key pillar of revenue generation for businesses in any sector is acquiring new customers. More the number of customers more will be the revenue. Today marketing and sales departments across organizations are relying on applying machine learning philosophies on their CRM data to discover better selling strategies that could attract new buyers. Anticipating market trends, being prepared for customer queries and having a holistic product or service overview enables faster selling. Besides, it can help in identifying quality leads for both marketing and sales teams and also help these teams in sending personalized campaigns to garner interest from prospects.
http://selectinteriordesign.com/test/wp-admin/ Improved Customer Relationship/Satisfaction
AI-powered chatbots or virtual assistants can help deal with consumer queries much more efficiently, and they can also provide round the clock service. They can even sell products with intelligent conversations, perform cross selling or up selling to existing customers, provide multiple buying options for customers and ultimately create a 24 X 7 available sales channel for businesses. This would mean more sales and in the process shoot up revenues for businesses.
Be its production lines for manufacturers or profiling customers for KYC or answering queries of customers, there is a huge collection of business processes that can be intelligently automated with machine learning. AI can even help in financial modeling for businesses based on the history of expenses and help management better forecast financial requirements and thereby help cut costs significantly. When costs go down, automatically profits go up. With smart automation, chances of errors and human mistakes become negligent and hence business machinery can operate uninterrupted continuously. This will lead to better utilization of resources and greater productivity. Meeting increased demands from customers would become easy and ultimately result in increased revenues.
Lowered cost of operation
With machine learning and cognitive computing, it is possible for business systems to intelligently monitor their performance and perform occasional or routine maintenance themselves. Another area where AI can create wonders is automation of security policies within systems. Cyber anomalies and threats can cause billions of dollars’ worth losses at organizations and AI-powered systems can guarantee more tolerance towards cyber threats because they can identify risks much better and can be on the alert 24 X 7. AI systems can also create an augmented workforce wherein humans work alongside or guided by AI and machine learning tools. Such a combination can result in more work done in less time which improves productivity at no extra cost.
As you can see that machine learning is no longer a focus area for start-ups and tech giants. Every business sector has numerous use cases where machine learning and cognitive computing can raise the bar for customer service and ultimately improve profits by either reducing operational costs with intelligent automation or increasing revenue with better sales. Today there are intelligent business insight platforms like Dataramp that empowers your business to apply machine learning and cognitive data analytics on data generated by your enterprise systems. It can help businesses derive intelligent decisions from deep-rooted analytics and machine learning based auditing of data sets.
So there you have it, folks, machine learning can be the next big game changer in your businesses growth. With a guaranteed increase in revenue, all you need to do is to have a proper roadmap for AI adoption in your business. This is where our expertise in enabling AI solutions for some of the world’s leading organizations can help you. Write to us to know how we can be the ideal partner in your AI journey.