The Rise of ML for SMBs

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The Rise of ML for SMBs

Today, machine learning is all around us. From fraud detection, to facial recognition technology, to even the handy recommendations made by Netflix, machine learning is something that we encounter every day and is powering the artificial intelligence revolution.

Aside from these everyday applications, the opportunity to leverage machine learning (ML) to your business’s competitive advantage is also on the rise with reporting a 97.7% increase in AI adoption at work from 2017. Think machine learning is only exclusive to larger companies that deal with and have access to vast quantities of data? Think again.

AI is an investment in which both large and small companies can benefit. It has the ability to not only help to provide a better service, but also to reach new markets. AI models can process large volumes of data, spot patterns and make predictions so that you can act on new opportunities, fast – something that many businesses may not have had the chance to do previously.

Studies show that AI is now breaking into the mainstream workplace, with a huge 70.6% of respondents indicating that they use some form of AI within their business. With predictive analytics built on AI and machine learning infiltrating the workplace at such velocity, giving businesses insight into market analysis, sales forecasting, churn prevention, customer segmentation and more, could you be at risk of losing the competitive edge by choosing to ignore implementation?

Machine Learning-Led Predictive Analytics: The Benefits

Customer expectations are now at an all-time high, and competition is increasing. Businesses are under constant pressure to increase efficiency and improve results. Advanced predictive analytics tools enable deeper insight and offer significant potential to give competitive advantage. This information can help companies to save thousands of pounds, develop their marketing strategies, and critically, support business growth and increase ROI.  

Gain a Competitive Advantage

While 70.6% of businesses are using AI models, that means that a large proportion of businesses are still yet to implement a solution that effectively draws insights on future behaviour. Implementing such solutions means that you will have a significant advantage over your competitors, and the ability to create a better customer experience and more wins within your market.

Evaluating Clients and Potential Clients

Every customer may deserve excellent service, but when it comes to maximising profit it makes sense to focus on the clients that are likely to bring you the most value. Using predictive analytics makes it easy to determine which clients are worth the most before you make the sales call, in turn helping you to allocate your resources effectively – from marketing budgets to sales time.

Understand What Customers Want

How well do you know your customers? You may have a general understanding, but predictive analytics can take this knowledge to a whole new level. Machine learning algorithms can help you to form a detailed picture of who your customers are, and determine the best product to recommend to each customer based on a multitude of points, including past purchase behaviour. By leveraging this information, you can greatly increase profits and customer retention.

Reduce Business Risk

By knowing who your most profitable customers are, which channels they’re coming from and which products they’re most likely to be interested in, you can leverage predictive analytics to minimize business risk and begin to allocate your resources into the channels that yield the most profit.  

Isn’t Machine Learning Only Viable for Large Businesses?

Long gone are the days when ML was only accessible to larger businesses that had the resources to employ expensive engineers. Since tech companies such as ArtuData and Apache Mahout have done the heavy lifting to build and perfect machine learning solutions, businesses no longer have to spend-out to develop their own ML processes and tools to reap the benefits.

Vast data-sets are also no longer necessary, with many ML companies using an innovative multi-layered approach that merges and enriches your business’s own small data-set with data obtained from Google and other third-party sources.

The future of ML is built for scalability and flexibility, with providers now offering solutions on a pay-per-use basis (no more large and unnecessary fees for features you don’t need) with no setup costs.

As with any technology, only a few companies had the resources to become early adopters. With ML now becoming more and more accessible to mainstream businesses, and with many providers even offering a free proof of concept to give the assurance that the solution provides value before purchase, every company should now investigate the wealth of big data tools and solutions. What have you got to lose?