How to Use Machine Learning and Intelligent Automation to Scale Tech Business And Increase Success

One of the challenges facing many businesses – and subsequently their marketing departments – is how to best to deal with digital transformation and growth. Any thriving business, especially those in the tech sector, must quickly and rapidly scale their business to keep up with new trends in digital marketing because that is where the real success lies. In a marketplace increasingly saturated with digital marketing efforts, tech businesses have had to seriously increase their digital resources in order to stand out and really drive success for their business.

In a marketplace increasingly saturated with digital marketing efforts, tech businesses have had to seriously increase their digital resources in order to stand out and really drive success for their business. One of the newest ways to accomplish this is by leveraging new technology within the marketing world and adapting it to the unique needs of the business.

Machine learning and intelligent automation are the two most critical components of digital marketing that businesses must master in order to get ahead – and stay there. The new wave of marketing technologies bring about an element of personalization that has never been seen before, but that definitely gets results. Using machine learning and intelligent automation is one of the fastest ways to see success in digital marketing and get a real return on investment.

But what exactly does that entail? Take this case study, for example, done by 451 Research on a company called Backflipt on how they used machine learning and intelligent automation to increase their sales engagement. Essentially, the company’s main differentiating factor is the algorithms they use. These algorithms are machine-learning and are in a constant state of performing data analysis. Using data gleaned from customers, these algorithms use data and context of customer preferences and their email engagement to gain valuable insights.

But rather than using this data for direct marketing purposes, this is mainly used for contextual recommendations in terms of content, as well as detections of new events that could potentially provide an avenue for customer engagement, according to 451Research. The key is to use data to understand customers and provide them with real, substantial engagement – not just promotional efforts.

In order to stand out from the noise, businesses can use machine learning and intelligent automation to provide real value for customers instead of inundating them with advertisements. It allows for pinpointed, laser-focused understanding of customer preferences and what makes them tick, and gives businesses the power to retarget their efforts in how best to market their products.

As a recent Huffington Post article notes, today’s marketing is driven by time management. Machine learning and intelligent automation seek to be a remedy for this issue and give departments more time to focus on other projects while still providing a consistent level of effort. As the author notes, “It boils down to who gets the first mover’s advantage, who engages with customers more often and who converts leads faster.”

Between juggling leads, platforms, contents and of a host of other projects, marketing departments are often bogged down and underutilize their time. Scaling businesses to allow for machine learning and intelligent automation will reduce that problem while driving further success.

Engaging customers becomes an easier effort when you can pinpoint exactly what their interests are, what their purchasing behavior is like and other valuable data – and then automate some of those steps. Whether it is email follow up, or through other digital platforms, intelligent automation and machine learning will make that process far less cumbersome.

Ultimately, machine learning and intelligent automation will become an increasingly top priority for businesses looking to scale for technology, and will prove to be one of the best investments in technology a business could make.

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