As AI and big data-powered innovations keep disrupting the way we live and work, the meaning of the term machine learning (ML) may remain opaque to many people despite its increased prevalence and business applicability.
At one time, implementing machine learning algorithms and integrating the necessary underlying technology was out of reach for many businesses because of the prohibitive costs and advanced knowledge necessary. Now, however, this is no longer the case.
Large tech companies like Google, Amazon, and Microsoft have found that sharing their cutting-edge ML tools can be a win-win proposition for the giants and SMEs (small and medium enterprises) alike. Doing so democratizes access to these advanced capabilities and their potential benefits.
Popular solutions like Google Cloud AutoML (which includes Vertex AI), Amazon SageMaker Autopilot, and Azure AutoML, in addition to open-source Python packages, have leveled the field. Business owners can incorporate these game-changing tools into their businesses and capitalize on all the benefits that they have to offer. These benefits range from increased visibility into their sales funnels and marketing and customer acquisition strategies to optimization of their human resources practices.
If you’re not sure what these benefits are, here are six of them to get started.
6 Ways Small Businesses Can Use Machine Learning
- Optimize sales forecasts.
- Create more effective sales channels.
- Anticipate customer churn rates.
- Get unbiased opinions about customers’ feelings.
- Predict employee attrition and improve HR processes.
- Unleash the power of online sales channels.
1. Optimize Sales Forecasts
An unexpected downturn in sales can be fatal for SMEs, especially during a busy season for a heavily seasonal business. Unfortunately, with constantly growing competition, such dropoffs can happen.
Nevertheless, thanks to AutoML solutions, business owners now have a trusted ally to increase the accuracy of their sales projections and identify patterns that they might have missed on their own. Then, if they detect a potential negative trend emerging, they can take adequate steps to remedy it.
Practical examples include analyzing historical sales data together with other key factors like promotion activity and sales efforts. For example, if the manager of a craft brewery wants to know whether it was the Monday Night Football happy hour or the social media giveaway campaign that led new customers to visit and spend their evening there, applying AutoML to analyze the relevant data can help. This way, owners can be clear on what’s working and what’s not and then make the appropriate decisions to grow their businesses.
2. Create More Effective Sales Channels
In line with the previous point, having clear visibility into which sales channels are working and which ones are not is helpful. I’ve met more business owners than I can count who maintain an ineffective sales channel only because they have never taken a hard look at the data that would tell them it doesn’t work.
I understand that one of the reasons why many owners don’t do proper data analysis is because it’s time consuming. AutoML solutions make it a lot easier, however. Because these solutions go through data way faster than a human could, they provide immediate visibility about whether a sales channel is profitable or not, as well as assessing additional indicators like conversion rates, money spent per customer per channel, and much more. This way, owners and managers know how to focus their marketing efforts.
Also, for retail businesses that are considering opening up new points of sale, AutoML solutions can be the best consigliere in making these decisions. By using publicly available data, an AutoML-powered assistant can tell you what the best location would be based on factors like expected sales, foot traffic, cost per square footage, competitors with a close location, and much more. This way, business owners can save both time and money.
3. Anticipate Customer Churn Rates
Losing customers is costly for any business, but the implications are higher for SMEs, and even moreso if the company is just starting to develop a brand and build a reputation. For companies at this stage, acquiring customers can be costly. Therefore, you don’t want to lose them.
The reality is that some customers will leave, however. They’ll either unsubscribe or simply take their business elsewhere, depending on the type of product or service that you offer.
AutoML solutions can analyze previous interactions with a customer, that customer’s purchase history, and a lot more. This way, they can detect common patterns between those customers who have stopped patronizing your business, giving you more visibility into the factors that are causing the customer churn rate to grow. By learning what’s prompting your clients to leave, you can be proactive and approach those customers with either a personalized offering, an inquiry for feedback, or simply reach out to increase your rapport with them. Although there are no guarantees, this can prevent them from leaving and increase your retention rates simply by changing the nature of your customer interactions.
4. Get Unbiased Opinions About Customers’ Feelings
Let’s be honest because I’ve been a business owner too: None of us likes reading negative reviews about our businesses. Recently, I was watching a Netflix show called Restaurants on the Edge, in which consultants read out loud some of the most recent reviews to restaurant owners. Most of them get defensive, even if they’re fighting to keep their business alive at that point.
In general, humans can’t be trusted to effectively handle negative feedback. The reality is that, unless we spend a lot of time growing and developing ourselves to the point where we don’t take things personally, looking at negative feedback is painful. Therefore, if we’re conducting an online audit about what customers are saying about our businesses on social media, we might have a tendency to skip the negative ones — or else find a justification for them — and focus on the positive ones. Or, if you’re a glass-half-empty person, you might do the opposite.
With AutoML, we can eliminate these biases and get an objective, realistic analysis of what customers are saying about our product or service. This way, we can focus on making tangible improvements. Also, AutoML solutions can collect a lot more information than we can on our own and do so much faster. That way, we’re not only gaining a bias-free opinion, but one that gathers all the data available, which would take an enormous amount of our individual time. Furthermore, Google has a pretrained model called Google Cloud Natural Language API that can perform this type of analysis, as well as a special feature on the Google Cloud Natural Language Processing website that allows you to upload text.
Last but not least, services like Google Cloud AutoML and Amazon SageMaker have pretrained models and an interface using NLP sentiment analysis, which can determine whether the selected data is positive, negative, or neutral, and helps business owners draw more accurate conclusions.
5. Predict Employee Attrition and Improve HR Processes
AutoML can predict customer churn and detect factors that are causing unhappiness in our client base, and the same tools can predict employee attrition or poor performance when applied internally.
By analyzing employee interactions and taking into account both quantitative (KPIs like sales targets, productivity metrics, etc.) and qualitative data (including employee engagement and peer-driven evaluations), AutoML solutions are able to determine factors that are causing employees to leave or predict a drop in their productivity. This way, we can also take the relevant actions to engage and connect with those employees. Sometimes, helping an employee feel seen and acknowledged is all they need to recover their regular output levels. If we don’t know how they’re feeling, how are we supposed to know that they are struggling and therefore can’t perform as we expect them to? With the right data, at least, we can make an initial approach backed by facts.
6. Unleash the Power of Online Sales Channels
In today’s world, and especially after the accelerated digital transition driven by the 2020 pandemic, a business that doesn’t have a digital presence is a business that does not exist.
Therefore, you must keep track of how your online presence is faring, even if your main sales channel is retail. Think about it: By selling online, you have lower customer acquisition costs, customer support costs, and much more. It’s like getting another shop that’s open 24/7 without the financial burden of hiring full-time staff.
If you find the task of opening up an online shop daunting, AutoML can help you there too. By integrating this tool, you can analyze website traffic data, user behavior, conversion rates and much more. For example, if you have several calls to action on your site, you can see which one is actually bringing in the customers. You can also find out which parts of your website visitors are engaging with the most so you know what type of content you need to create.
I would dare to say that AutoML, in some ways, can be the perfect personal digitalization assistant for SMEs.
Use AutoML and Open Up Your World
The benefits that integrating automated machine learning technologies can bring to SMEs are clear, providing them with unparalleled data analytics to make better decisions. The best part is that it is a process that has been heavily democratized by companies that are offering tools that are accessible, affordable, and easy to use.
Basically, platforms like Google Cloud AutoML and Microsoft’s Azure ML have done the heavy lifting and made cost-effective and efficient solutions available. There are even more free open source solutions. Regardless of their choice, business owners can now optimize their sales and human resources practices, as well as increase customer satisfaction by leveraging the capacity of AutoML as a very powerful assistant. By effectively using data, SME owners can transform their businesses for the better and thrive in an increasingly competitive market.