AI Marketing
June 26th 2020

Machine Learning for eCommerce and SMB (Guest Post)

It’s never too late to learn – in fact, now is the best time. If you run a small to medium-sized company or e-commerce business, getting to know more about your customers will help you make better business decisions than ever. No need to go door to door: Machine Learning (ML) does the trick for you.

While AI is about mimicking human abilities, machine learning technology trains a machine on how to learn – it’s basically a self-taught employee processing and interpreting consumer data, which is particularly important for online retailers.

Machine Learning algorithms can be found in various Artificial Intelligence applications. We’ll tell you more about the two major benefits and the five things you can implement in your eCommerce and growth strategy.

Benefits of ML for e-Commerce Sites and SMBs

The benefits of ML go beyond improving e-commerce sales. With ML, you can create business advantages for every department of your e-commerce business. Improve efficiency, productivity, give better customer support, and make better HR decisions. Here’s how ML helps SMBs and e-Commerce websites.

It helps to identify patterns and trends

Get inside the head of your average customer, know what makes them tick, and what they need – before they do. Machine Learning algorithms identify trends and discover patterns from data, without you having to specify what you’re looking for. This ensures that you actually get accurate and true information, instead of what you were maybe hoping to find. Sorry.

Every action we undertake online leaves a digital footprint. From previous purchases to online interactions – we leave a lot of valuable information behind. This sounds very Big Brother, but rest assured: with current privacy guidelines and the systems in place, they won’t actually know who you are, just what kind of person if that is less scary.

Machine Learning collects all this data and combines it into a persona or profile that can help online businesses create a better customer experience – simply because they understand who they are interacting with. Hello, better relationships! Online, at least. And with businesses. But still!

It’s accurate and automated

As we said, ML searches for actual patterns, without you pushing it into some desired direction. It can process large volumes of data incredibly fast. This enables you to take appropriate actions at the right time. After putting a Machine Learning technology in place, you’re actually free to go do something else and let it do what it does best. 

Machine Learning is completely automated and very accurate, especially compared to manual analysis of customer data. This improves productivity and efficiency for your marketing and sales department. It saves time and (let’s hear it all together!) money! This also goes for customer support, if you implement ML into that. Find out how later on, because now we’ll highlight 5 ways to make use of ML.

Five ways to tap into the power of ML for your eCommerce site or SMB 

Artificial Intelligence and Machine Learning are not just tools for big organizations – more and more SMBs and e-commerce websites are implementing it to boost sales and lower costs. Here are five ways for you to do the same.

1. Product recommendation and personalization

You know when you’re at the supermarket and head to the checkout, where you stumble upon all that candy you’ve been craving, but it wasn’t on your list? So you grab a Snickers because it won’t matter for the total, right? Imagine if ecommerce business could do the same.

They can. The biggest part of webshops will show you what “you might also be interested in” after you add one item to your basket. 

That in itself is nothing new. But whereas traditional product recommendations show products based on their popularity amongst everyone, a recommendation engine helps create personalized shopping experiences: it shows individual recommendations. 

Using predictive analytics, this AI technology substantially increases conversion and customer engagement. 80% of shoppers are more likely to buy from a company that offers personalized experiences. That’s a whole lot of shoppers.

Amazon's list of personalized recommendations.
Amazon is the king of personalized recommendations.

Small business owners and those just starting out with ML for their e-commerce platform may feel a bit clueless as to where to get all the necessary data from. Start out small, for instance, by implementing quizzes on your website to collect information about your customers, without making it feel very intrusive. 

2. Implement dynamic pricing and retargeting

It’s not just about showing the right product – the right price also plays a big part in the decision-making process of consumers. ML detects demands and changes in consumers’ behavior. With these predictive models, you can offer real-time discounts, helping you to adjust prices to increase sales or improve margins.

Sometimes product and price aren’t the problems. It’s timing. ML helps the ecommerce retailer put in place smart retargeting campaigns to remind visitors of its products when the time is right. Besides retargeting, this tactic is also helpful for upselling and overall customer retention.

3. Improve search engines

The way we search has changed drastically over the years. Search engines have become a standard part of our life, and the way we “talk” to them shows this change in the relationship. Like in many relationships: we want them to understand everything we want without actually saying what we want. 

We use search engines to find what we need. But if these engines are able to give us even better options than we were actually thinking of ourselves, it changes the whole game. ML is able to do that using a machine learning model with short-term and long-term user preferences, history, and previous queries. 

Keep in mind that even though ML can subtract all this info from users, your website should be prepared for this. ML wants to match keywords and synonyms, the keywords you have attributed to your products, so make sure these are in place. 

4. Chat-bots 

Some people just need a nudge in the right direction. Maybe they are looking for a link to information on deliveries. If you have a customer agent spending time on that, that’s nice, but not very cost-efficient. 

An intelligent chatbot can interpret individual users’ questions and respond to them individually. Meanwhile, your service agent can focus on more pressing queries and deliver more personalized support.

Showing the interaction with a chat bot.
The chatbot from Roof Ai helps his human colleagues save time. 

Smart chatbots rely heavily on Machine Learning. The more conversations they have, the more human they will appear. But over time, and depending on your investment, they can learn to do much more, like identifying potential upselling opportunities, or finding out the customer’s long term needs. 

5. Supply & Demand Prediction

Last but not least: while ML helps you predict which products will sell best to individual consumers, it also helps you optimize your supply chain. Simply put: by predicting customer behavior, it also predicts the stock required and helps with supply chain management. 

Linking eCommerce efforts to inventory management offers benefits beyond increased sales and customer loyalty. No unnecessary stock means better cash flow – all thanks to Machine Learning. 

Alex Birch is the SEO Manager at Typeform. Lover of all things marketing & search. Originally from Manchester, UK but now enjoying life in sunny Barcelona. Connect with him on LinkedIn.

MarketMuse

Written by MarketMuse MarketMuseCo