Applied Machine Learning in E-commerce for SMBs
STORY INLINE POST
Making sense of customer data is the cornerstone of any successful business and in e-commerce, there’s an endless sea of data to be gathered and analyzed. The rift between customer and brand is both larger and smaller in e-commerce.
It is larger because there are so many sources of complex data that must be considered to develop a comprehensive view of your individual customers and their behaviors. If you can’t organize and utilize all of this data to understand your customers, you aren’t able to deliver the personalized experience that they crave.
It is smaller because vast amounts of user and customer data are so readily available and have the potential to inform you about your customers in a way that was not possible before the days of applied machine learning.
This article will give insight into the reality of applied machine learning in e-commerce for small to medium-sized businesses (SMBs), discuss why implementing AI is so essential as the greater e-commerce industry moves into the future, and present some of the main benefits of using applied machine learning to better understand your customers and perfect your business strategy.
The Need for Applied Machine Learning in SMB E-Commerce
There is more customer data coming from more sources than ever before. Traditional analytics strategies are not cutting it anymore. What pieces of data are most important? How do you format and combine data points from different sources to make them actionable? Applied AI is the only solution that can keep up with the exponentially growing data pool available to you.
Without the use of algorithmic intelligence, there will be blind spots, and those blind spots prevent you from creating the products, features, shopping experience and personalized advertising campaigns that keep existing customers loyal and get new customers interested. This means lower revenue and, often, higher operating costs.
To directly quote Karan Sachdeva from a survey published by the IBM Institute for Business Value (IBV), “organizations in the AI piloting and implementing phase report a 4–7 percent revenue boost from specific AI initiatives, on average, while those in the operating and optimizing phases report an impressive 10–12 percent gain.”
Outlined below are five of the primary benefits that come with leveraging AI as a small to medium-sized business.
Understanding Your Customer and Personalizing Experiences
Every customer has their own distinctive needs and motivations that drive them to make a specific purchase or visit a particular page. Implementing machine learning to help you fully utilize your first-party data allows you to look behind the curtain and get a more comprehensive understanding of your customers. This enables you to make specialized profiles for them that are centered around more than just the traditional demographics, such as location, gender, age and profession.
AI can provide insight into shoppers’ interests, motivations, likes and dislikes, shopping behaviors and much more on an individual scale, and then help you automatically personalize their experience touchpoints with your brand. From the customer’s perspective, this might look like receiving a personalized offer when you visit a webpage or coming across an ad for a very specific article of clothing while scrolling on Instagram. These ultra-personalized experiences make customers feel understood and catered to.
In fact, according to Accenture, 91 percent of consumers are more likely to shop with brands that recognize them and give them a personalized and relevant experience. This means that if you’re a brand in the SMB sector, implementing applied machine learning into your strategy can give you a significant competitive advantage.
Anticipating Customer Behavior
In addition to learning more about your customers’ relevant defining characteristics, applying your e-commerce strategy helps you make informed decisions based on predictions about customer behavior. You can track and map customers’ patterns in shopping behavior, website browsing behavior and progressions through the customer journey to anticipate behavior on both small and large scales.
What is the good in anticipating customer behavior, and what does that really mean? Algorithmic intelligence can make predictions about customer behavior patterns, allowing you to optimize your strategy for user experience, advertising, product and inventory planning, etc., based on current customer trends/cycles.
An example of when anticipating shopper needs and future decisions might come in handy is around the holidays. As an SMB in e-commerce, it’s essential to take advantage of the high-purchase volume times of year — but how do you know to whom you should promote different products, which products will be the most popular, and how much inventory you will need? By tracking patterns in behavior, AI can make predictions that help you frame your large-scale business decisions on the future instead of the past.
Product and Feature Research and Optimization
Part of anticipating customer behavior involves predicting the ebb and flow of demand for different products and features. Leveraging applied machine learning can result in unparalleled insight into your current product catalog and the popularity or disfavor of different product features. This can help you make “small” decisions regarding tweaks to features as well as “large” decisions about entire product lines or seizing gaps in the market.
Understanding which shopper personas are drawn to or repelled by certain products or features also enables you to push optimal product promotions based on the customer, tying back into the “personalized experience” aspect that is so vital to the customer journey and making conversions.
Customer Acquisition and Conversion
The higher acquisition and conversion rates that come with utilizing applied machine learning is one of the factors tied to organizations’ boosted revenue in IBV’s previously referenced study. AI improves acquisition and conversion rates by improving the customer experience and increasing their level of engagement with ads, campaigns, products, and deals that are relevant to them.
In practice, this can be done by using enriched data to make your products and brand more visible on the web so potential customers are more likely to enter the sales funnel and convert. With insight into customer behaviors and preferences as well as product and feature data, you can understand customer intent throughout the sales funnel and customer journey, allowing you to promote appropriate content (blogs, videos, products), increasing the likelihood of movement down the funnel.
Improving Internal Operations and Productivity
Many of the above benefits are customer-centric but organizations that implement AI see positive effects on internal operations as well. Turning to applied machine learning can empower internal teams to do their jobs better with access to higher-quality actionable data. Automating data-related tasks also allows teams to prioritize the “creative” and “human” aspects of their positions.
In other words, AI handles data collection and analysis better than a human could, which results in more valuable data that the people in your organization can use to do their jobs more productively and effectively. The automation of tasks related to product promotion and personalization of experiences gives team members a chance to embrace the parts of their position that require more nuance.
Both of these factors contribute to more effective operations. In fact, the previously referenced IBV study also reported that “more than 85 percent of advanced adopters are reducing operating costs with AI.”
There are numerous benefits to leveraging applied machine learning in your overall business strategy as a small to medium-sized business in e-commerce. Using your first-party data to your advantage helps you create a more engaging personalized experience for customers, make better decisions about inventory and product and feature development, and boost revenue thanks to increased conversion rates and lower operating costs.
Take a moment to think about what your data is doing for you, and about what it isn’t. Implementing AI gives your brand a competitive advantage in the SMB sector and ensures that you’re ahead of the curve as the e-commerce industry continues to change.