Machine Learning And How It Affects Your Business

Machine Learning is essentially the science of getting computers to think without being explicitly programmed. This phenomena has rippled through various professional sectors, as companies are becoming more privy to the power behind this technique. For example, in our childhood, barbie dolls and action figures used to be a prominent source of entertainment. Even though they couldn’t communicate with us, we enjoyed using our imaginations. However, with the advent of technology, and the introduction of machine learning, curating dialogue is now possible! Hello Barbie is now able to listen and respond to a child through the use of a microphone on Barbie’s necklace that records the sound of your voice; from there, the recording is analyzed and used to determine an appropriate response from 8,000 lines of dialogue. Additionally, large credit card companies like American Express are using machine learning algorithms to detect fraud. The beauty of this phenomena resides in the fact that computers work at a speed and accuracy that far exceeds that of a human agent; this is advantageous for any company.

So what are some examples of the impacts machine learning can make on facets of your business? Here are a few!

Marketing will get smarter

Brand awareness and visibility, of course, is a crucial aspect of any business model. After all, no matter how great your product is, what does it matter if no one will ever get to see it? Machine learning and AI are already making massive leaps and bounds in this area. Matter of fact, Salesforce conducted a study on marketing leaders worldwide. More than 60% of marketers envisioned leveraging AI to create dynamic landing pages, tailored to your individualized tastes, programmatic advertising and media buying. However, the truly exciting way in which machine learning will impact marketing is through lead nurturing via social media. Using personalized, real-time content targeting, it is predicted that this will lead to 20% more sales opportunities. For example, machine learning algorithms might learn that a specific buyer who logs into LinkedIn on Tuesday will have also started looking for a new CRM tool. The software can then create targeted posts to be published on the days and times the user will see them. Pretty fancy!

Intelligent Chatbots

Chatbots are incredibly important in terms of lead generation and stellar customer service. When a customer visits a real estate site, either to find their new home or sell an old one, they’re typically expecting immediate answers. However, what if the real estate agent is unavailable? What if he or she is sleeping when the question comes at a particularly late hour? And yet, even though it is unrealistic to expect a human agent to be available around the clock to answer queries, it is a strong selling point for a business to be able to offer 24/7 service. While chatbots are certainly an answer to this question, sometimes standard bots don’t offer the assistance certain customers may need. What if he or she has a more detailed query? Like overall market trends for homes for sale in Miami? It would be frustrating to receive a general, canned response to a question that perhaps needs a little more insight.

Intelligent chatbots are a new phenomena that go one step higher than the typical, programmed bot. Rather, these bots, when given enough information, can perform advanced tasks like market research, as well as answer more specific and complex queries.

General Automation

It’s comes as no surprise that machine learning and AI are taking over tasks from human workers, and doing things they would never be able to do. In recent years, basic automation measures have become widespread, rapidly increasing the productivity and production rate of various companies. Some examples include:

  • Increased productivity: Let’s start with the most obvious benefit. There’s only 24 hours in a day, and try as you might to work around the clock, you’re a human being that needs sleep and food. Using data from the International Federation of Robotics, researchers George Graetz and Guy Michaels displayed the change in productivity in factories that had become automated. Across 17 countries and 14 industries, average labor productivity rose .36 percent! Which is a lot if you think about it.

  • Automation: As humans, we are much slower and prone to error when it comes to data entry in comparison to a machine. Innovations in bank feeds, rule-based categorization, and integrated payments have dramatically reduced the workload of clerical and bookkeeping staff, and have given business owners more timely access to accurate financial information. Research done by Xero suggests that by 2020, automation will be commonplace in accounting.
  • Data Visualization: Data visualization allows humans to make decisions based on emergent patterns. Matter of fact, for visual learners out there, and that’s most of us, we react better to seeing the bigger picture rather than read a massive amount of text. It’s also known that our brains process visual information faster and more holistically than text—which is why it’s easier to understand a picture of an apple, rather than a long-winded paragraph describing what it is. Tools like Sisense work with businesses dealing with data that is expanding exponentially, while their ability to process it is still the same.