We are living in exciting and innovative times with futuristic technology literally at our fingertips to impact business. But for the longest time, small to medium sized businesses were not serviced by the latest tech trends enterprises have been able to benefit from. That is, until now.
In this article, we’ll explore these technology trends and how they will impact business in the future.
So, what kind of things can this ‘smart’ tech do? Just 4 months ago, an AI machine managed to complete a University level math exam 12 times faster than it normally takes the average human. How? Through the art of machine learning; where computers learn and adapt through experience without explicitly being programmed. That will impact business.
Furthermore, Facebook made headlines earlier this year when their chatbots created their own language. Some Fake News stories say that the engineer’s pulled the plug in a panic after they were getting too smart. However, the truth is that for Facebook’s purposes the chatbots needed to stick to English rather than developing their own short hand. However, their machine learning chatbots did create their own language outside their explicit programming.
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This evolving area of computer science is the future for service businesses, and it’s already affecting the way we live and work today. In fact, research firm Markets and Markets estimates that the machine learning market will grow from $1.41 billion in 2017 to $8.81 billion by 2022!
So buckle up because these technology trends will impact business, from marketing, to operations all the way through to payroll. Here’s how:
Marketing Gets Smarter with AI and Machine Learning
AI and Social Media Marketing
In April 2017, Salesforce conducted a study of marketing leaders worldwide, and the results were mind blowing. Respondents said they expect to see improvements in efficiency and advancements in personalization over the next five years. More than 60 percent of marketers also envision leveraging AI to create dynamic landing pages, websites, programmatic advertising and media buying.
However, what people were most excited about is AI’s potential impact on social media listening and lead nurturing. In the not so distant future, AI will become increasingly sophisticated and a powerful tool for social media marketing.
The main way AI will affect marketing is through nurturing leads through social media. But how? Through personalized, real-time content targeting that produces 20 percent more sales opportunities. With behavioral targeting methods, AI will be able to locate and start the nurture process, for example, a marketing stack that employs AI algorithms might learn that a specific buyer who checks into LinkedIn on Monday mornings has recently started looking for a new CRM tool. The software can then suggest (or even create) targeted posts to be published on the days and times that they’ll see them: one that asks their requirements of the software and another follow up piece with a comparison of the CRM ecosystem.
Currently, savvy marketers that are using social listening as as way to nurture leads don’t have the necessary enhancement of AI, so it is time consuming, manual and not in real-time. So how do you start to get ready for this type of future content marketing distribution?
Firstly, you will need to have your buyer personas well defined. Taking a solid look at your CRM will give you tons of hints for content that will get qualified leads to respond. By taking a step back and analyzing your channel’s content (like emails, phone calls and social media messages) you will start to get the right kind of insights that will prompt a lead to take the next step into the second phase of your sales funnel. For instance, a C-Suite executive might respond best to data-driven whitepapers and infographics to peak their interests, whereas a fellow marketer might be more suited for an interactive case-study or video.
The only way to get these kinds of insights is to do a deep dive into your CRM platform and conduct a thorough review of customer details – using semantic analysis to understand the level of buying intent behind the words your qualified prospects use.
Hot tip: Starting to run your analysis now and developing strong personas will be key to implementing AI algorithms to your social media in 2018 and beyond.
Marketing and Machine Learning
Put simply, machine learning is about understanding data and statistics. It’s a technical process where computer algorithms find patterns in data, then predict probable outcomes – like when your email determines whether a particular message is spam or not depending on words in the subject line, links included in the message, or patterns identified in a list of recipients. This is a perfect example of how machine learning can be applied in marketing to optimize for successful campaigns.
Businesses can also use machine learning to up-sell the right product, to the right customer, at the right time. In 2018, marketers will continue to rely on machine learning to understand open rates when it comes to email – so you know exactly when to send your next campaign to increase click through rates and ROI. The next big thing? It might sound small but ticket tagging and re-routing can be a massive expense for small businesses – costs that can be saved with machine learning. Having a sales inquiry automatically end up with the sales team, or a complaint end up instantly in the customer service department’s queue, is going to save companies a lot of time and money, and this is all being made possible with modern technology.
And while solving issues in record time and delivering successful email campaigns is great, this is just the beginning. Here’s what else to expect:
Machine Learning Can Improve Retail Results
Machine Learning (ML), a subcategory of Artificial Intelligence (AI), may be confusing at first to many retail business owners and managers. But once they learn what it is, how it can benefit the bottom line, and how to use it, it becomes another device in the arsenal of increasing sales and profits.
The attached infographic, Machine Learning in the Retail Sector, presents an all-encompassing overview of the topic. It starts with simple explanations of artificial intelligence and machine learning. Essentially, artificial intelligence is the development of computer systems that can perform tasks that we typically think of as requiring human traits. For example, AI applications use visual perception, speech recognition, language translation and decision-making tools to analyze and solve problems, speed up processes and even learn.
How does machine learning work in the retail world? ML uses what is known as predictive analytics technology, which is the use of data, algorithms and machine learning techniques to make predictions based on historical data. In the retail sector, predictive analytics can be used to figure out how customers will respond to various marketing and advertising campaigns and what they will purchase in the future, to target the relevant ads to customers, and to personalize offers of related products that complement what they previously bought. This helps retail businesses to retain current customers and grow sales.
ML goes beyond marketing, however. ML helps retailers automate processes, determine pricing, optimize stocking and inventory, deliver a more personal shopping experience and manage resources. It can also be used to analyze future customers’ credit history to determine the likelihood they will default on payment. ML can be used to detect fraud and increase logistics efficiency.
It is likely that even more benefits will be found in the future. Isn’t it time to take advantage of all the data that’s out there now by jumping on the ML bandwagon?
E-Commerce Reaches New Heights
You’ve been shopping for a new pair sunglasses on Amazon, then before you know it, your Facebook feed is filled with multiple eyewear ads and related trends for Summer: this is machine learning. In-fact, this example of analyzing data based on a user’s purchase history or online shopping behavior is the future for e-commerce.
Retail companies are also tracking what ads or images you’re most likely to stop scrolling on, in order to target you with specific content. For example, if you always click on ads that contain happy women and some text, then a machine will log this as preferred content so that you are only targeted with ads that fit this description. Machines can also track what time of day you are most active on Facebook, Instagram, Twitter and/or Pinterest, in order to present these ads to you at an optimal buying time.
Then when it’s time to purchase, machine learning is applied to reduce the risk of credit fraud in small businesses. How? Machines learn from historical datasets that contain fraudulent transactions and can identify patterns that represent a typical fraudulent transaction – similar to the way spam emails are detected and deterred. Machine learning will start to affect other parts of your business funnel as well, just take a look at the rise of Chatbots.
There was a time in which chatbots were only thought of as manmade pests on the internet, but through machine learning, they are getting smarter and businesses are embracing them en mass.
In 2018 and beyond, chatbots will play a key role in the future of customer service. Why? Chatbots can help achieve a faster customer service resolution, as well as provide quick histories of each customer for impeccable customer service. There are some key benefits that chatbots have over solely human interactions:
- Giving 24/7 customer service: The great things about machines? They don’t sleep! Coupled with the fact that chatbots are getting sophisticated enough to recognize human emotions such as anger, confusion, fear and joy. So should a chatbot encounter negative sentiments from the customer, they can seamlessly transfer to a human to take over and finish assisting the customer.
- The era of being ‘on hold’ is gone: A huge barrier to providing excellence in customer service is long wait times. How many times have you tried to get customer service from Comcast (or any TV/Internet provider) and you are getting progressively more frustrated with the wait times? This can all be eliminated with chatbots!
- Quick access to customer data makes service more personal: One thing that humans will never be better at than chatbots is quickly digesting customer data and history to provide context to customer questions. Chatbots excel at collecting customer data from support interactions. They can serve as virtual assistants that can feed customer data to your customer service officers so they have a full history of each account quickly. Even though we are right at the start of chatbot adoption, there’s no doubt that this technology is going to be a key contributor to business success in 2018.
This emerging tool for businesses already has significant buy-in from thought leaders around the globe. In fact, Larry Kim, Founder of Wordstream, is all in on chatbots as he has started his own company https://mobilemonkey.com/where his bots are currently in beta. With this move, it will be interesting to see how businesses will leverage robots throughout other aspects of their business. The final trend we’ll explore is Automation and how it affects businesses today.
Though Machine Learning and AI are hot topics in the tech world, it is not to a point that small to medium size businesses can leverage it in the immediate future. But there is still hope for them to impact business with automation. Powered by the Cloud, this type of technology has already revolutionized Marketing and Sales workflows and interactions but it is also starting to touch the various other parts of a business. For example:
Once you win an important sale, you’ve got to deliver the product or service you’ve promised to the client. What does that process look like for most businesses now? You all will have a kick off meeting and hope to cover all the promises that marketing and sales has given to your client. However, with the use of operations automation and a powerful CRM you will be able to read the interactions and see all the various touch points a client had with your company before that kick off call even happens. This will give all service businesses a head start in providing great client relations and managing expectations. This category of SaaS products is called Service Operations Automation, or ServOps for short.
If there is one data-entry heavy department it would be Accounting. The problem is that as humans, we are fallible and much slower at data entry than a machine. Innovations with bank feeds, rules based categorization and integrated payments have dramatically reduced the workload of clerical and bookkeeping staff and given business owners more timely access to accurate financial information for their businesses. Research, done by Xero, suggests that by 2020, automation will be impact business and be commonplace in accounting, and a significant number of finance professionals will be using the next level of analytical tools to help them add value to business models across the globe.
Finally, the Cloud and Automation has come to the Payroll and Human Resources sector. These important areas of a business too often suffer because small businesses aren’t big enough to afford a full time HR department. What’s the alternative? Having only part-time efforts of founders and principals which can often lead to serious risk to the business. For instance, factoHR and Zenefits will automatically submit forms to the federal Internal Revenue Service on the behalf of companies. With new automation technology, compliance is automated by platforms and the effort of keeping time-off approvals in sync with PTO balances and payslips becomes a thing of the past.
In the near future, we will see the rise of great technology, powered by the Cloud, Automation, AI and Machine Learning. This truly is the start of the Golden Age of Information Technology and it is time for businesses to take a hard look at their organizations and find ways to start integrating these tech trends as they impact business.