Success often comes down to a slim margin between your business and its competitors. From customer service to product features, brands compete against each other in every way possible. Organizations are always looking for an edge, which leads many businesses to invest in technology like machine learning.

However, machine learning does require an investment. It’s not only necessary to invest in the right infrastructure, tools, and software, but also in employees who have the technical expertise to make machine learning a reality. Some businesses balk at the cost and time of implementing machine learning, but Edward Scott, the CEO of ElectrifAi, has seen the benefits of machine learning firsthand. Scott shares the five ways machine learning benefits business growth.

1. Better Understand Your Customers

Stop guessing what your customers want. Machine learning solutions such as ElectrifAi make it possible to gather and synthesize data to better understand your customers at scale.

“Be curious, humble, adaptive, and customer-obsessed,” Scott told the website Authority Magazine. “Every business needs to constantly listen to customers who will tell you the path forward or what needs to be changed and optimized.”

With machine learning, businesses can gather data from many sources and draw better conclusions from that data. What would take a team of humans a year to uncover would take machine learning just a fraction of that time.

It allows businesses to learn what their customers like and adjust their approach. For example, if your machine learning solution detects an uptick in churn rates, it can often pinpoint which changes led customers to churn in the first place.

2. Improve Customer Experience

Shoppers will only stay if your business treats them well. But thanks to the Great Resignation, more employers struggle to meet customer demands adequately. Fortunately, ElectrifAi’s team knows that machine learning can improve the customer experience through personalization, improved customer service, and smarter marketing.

Over 90% of customers say they’re more likely to shop from brands that personalize their offers. If you want to personalize, machine learning is a must. For example, machine learning can act as an intelligent recommendation engine for e-commerce. “We help several large global telcos acquire and retain customers with machine learning-based customer segmentation and personalization solutions. In industries with high customer acquisition costs, these solutions are must-haves,” said Scott.

Improved customer service is always a worthy objective. Machine learning-powered chatbots allow brands to offer the 24/7 assistance that customers crave. There’s less of a need to hire human customer support agents when machines can answer basic customer questions, too.

Nobody wants to receive shotgun-style marketing. Companies like ElectrifAi market smarter to help brands home in on their target audience, so they only expend marketing resources on campaigns that are most likely to lead to a sale. Plus, shoppers receive a more targeted experience, so it’s a win-win.

3. Improve Efficiency

Inefficient work processes increase errors, decrease work quality, and often lead to rework. Worst of all, it’s difficult to spot these inefficiencies, especially in a large enterprise.

Machine learning can fill in these gaps. It isn’t about replacing human employees, but empowering your team to spend their time on value-laden activities instead of minutiae. According to ElectrifAi, enterprises are using machine learning for data analytics as well as workflows, project management, metrics and reporting, and task automation.

Solutions like ElectrifAi decrease the costs of data science by as much as 10 times. Many organizations see time to value in as little as six to eight weeks, so it’s clear that machine learning offers much-needed efficiencies.

4. Predict What’s Next

With machine learning, organizations can see what’s coming around the corner. It allows businesses to gather data and spot trends in global economic performance, marketing, demand, and resource utilization.

Data science can be expensive, but machine learning makes it cheaper and easier to make accurate predictions. By analyzing historical data, machine learning platforms can spot trends and help businesses adjust for the future. It’s the closest thing enterprises have to a crystal ball.

5. Increase Agility

Organizations have so much messy, unstructured data they can’t use. Instead of allowing that data to languish — or trying to make decisions based on unstructured data — you can use machine learning to give that data structure again.

For example, prebuilt solutions from ElectrifAi gather both structured and unstructured data to create practical business knowledge. This helps enterprises improve speed.

Machine learning automates finicky tasks that take humans longer to accomplish. Instead of assigning your team mindless chores, you can automate them with machine learning and boost employee productivity in the process.

It can also spot trends. Instead of relying on the market to spot trends for you, machine learning allows businesses to detect trends using their own data.

Another benefit is making faster decisions without spending hours poring over your data. Machine learning quickly spots anomalies that your team can then review and act on.

“Every business has significant amounts of data, and ElectrifAi unlocks the potential of that data with prebuilt machine learning software solutions that quickly help enterprise clients drive customer acquisition and retention, as well as cut costs and risk through spend and contract analytics,” said Scott.

Improve Efficiency With Machine Learning Solutions Like ElectrifAi

Sometimes manual processes are necessary for business, but more often than not, they slow down your team. Errors and wasted time erode a business’s competitive advantage, so it’s never been more important for organizations to go all in on machine learning. According to ElectrifAi’s CEO Edward Scott, machine learning offers these four benefits: customer insights, improved customer experience, advanced predictions, and increased agility.

But even so, many organizations struggle to implement machine learning in their business. It’s possible to start from scratch, but it costs more time and money to build internally. When in doubt, opt for machine learning solutions like ElectrifAi to see time to value in just a few weeks.

Said Scott, “To be successful with machine learning, companies have to precisely identify the problem they are looking to solve and then identify the relevant data required to solve the problem. And as important, companies need to consistently establish clean, high quality data. Get these things correct foundationally, and the rest should move smoothly.”