There has never been a more exciting time to be involved in eCommerce. Every day entrepreneurs, developers, and marketers around the world are using artificial intelligence. Creating new ways for people to conduct commerce, transforming the retail landscape of tomorrow.

The eCommerce industry has been able to grow so quickly due to a rapid rate of iteration. Through the collection and analysis of data, every step of a consumer’s buying journey can be analyzed. Every single marketing campaign can easily be tracked to sales. We are collecting more data, and using the insights to optimize and improve.

This data is fuel for the artificial intelligence fire. The fields of artificial intelligence and machine learning are directly impacting how businesses operate and customers’ expectations.

If you need further validation of the growing importance of artificial intelligence in eCommerce, just look at the number one investor. Who also happens to be the world’s largest eCommerce company – Amazon.

In a letter to the Amazon shareholders, Jeff Bezos describes how companies need to embrace, not resist, great external trends to gain tailwind towards future progress. artificial intelligence and machine learning are currently at the forefront of these external trends.

So how is artificial intelligence to change eCommerce?

Improving algorithms rather than making more rules

We take for granted the automation and scale that modern software has gotten us used to:

• displaying websites to thousands of people simultaneously,
• processing payments from anywhere in the world, and
• allowing instant feedback and communication with our customers.

These tasks are all achievable through well-defined, rules of code written by some very bright people. But, as defining the solution to these tasks becomes more and more complicated, it becomes impractical to dedicate human resources to create even more complex and inevitably fragile rules.

If Amazon were to recommend the same products to everyone, the feature would be useless. So, rather than creating rules for everything and every type of customer, Amazon uses the information it has available to create ever-improving algorithms that recommend products from previous purchases.

Making resource-intensive applications available to everyday developers

Computational power and domain expertise have been two limiting factors in making artificial intelligence driven applications available to everyone. But there are already several large-scale programs being used in the wild that give developers access to vast amounts of computational power & data in an easy to use format.

Google’s Vision API

Tasks such as computer vision and analysis also require access to a vast amount of training data and computational power. But at Pixc, we are already seeing how tools like Google’s cloud-based Vision API can give developers the capability to make powerful AI-driven applications today.

IBM’s Watson

For decision-makers, IBM’s Watson continues to be a service that is both exemplary of what is possible, and accessible to a non-technical audience. Their website goes into detail on how their artificial intelligence brings improvements across many industries by offering: greater confidence in business decisions, increases in forecasting accuracy, more tailored recommendations for customers across omnichannel environments.

Apple’s CoreML library

To see widespread adoption, these new technologies need to become more accessible. As our mobile hardware and software become more powerful, cloud-based technologies may become available in new ways and even run on our devices in real time. 

MailChimp

MailChimp is also doing great work in data science fields, largely driven by their eCommerce customers.

Sending 10 billion emails a month means the company has a lot of data. With it, their data science team has been able to create tools like Omnivore, an AI-product that scans emails and has gradually learned to recognize the signs of bad URLs and spammy behavior. Other machine learning-derived applications that have benefited thousands of eCommerce entrepreneurs include the ability to optimize the best time to send your emails.

For future founders, these processes will continue to be developed in the background, silently improving their business. While their day-to-day decisions will increasingly utilize services like Kit, using these tools to provide your customers with a better experience and optimize your business will soon become second nature.

Kit

Consider Kit, Shopify’s virtual employee, that allows you to manage and market your Shopify store. While the technical inner-workings may be considerable, Kit’s simple chat interface means 400,000 Shopify merchants have access to a digital assistant that can make recommendations to improve their store and interact with other services (including Pixc).

This ability to interact with third-party applications will provide greater opportunities across eCommerce for businesses to scale and automate.

Overall Kit will assist you with your Facebook ads, Instagram Ads, Thank you emails and email marketing. Kit saves time and eliminates human error that can take place when doing these marketing tasks yourself.

How can you use artificial intelligence to augment your human resources?

The drastic rate and scope at which artificial intelligence can disrupt businesses can conjure visions of a fully autonomous workforce. Replacing human workers with software. But, as Michael Schrage explains, the opportunity for artificial intelligence to empower our human capital is currently more valuable than its opportunity to replace it.

Humans and artificial intelligence both have polarising strengths and weaknesses. By using the tools we have available, we can improve the capabilities that make our abilities so valuable. And also take advantage of the speed that technology provides us.

A company implementing this augmenting approach in their products today is Zendesk. Their assist integration augments your customer service team by scanning through existing content to provide them with relevant documents.

The Assist augmentation provides more timely and comprehensive help to the customer. Meaning your support team spends less time searching through data, and more time communicating. Knowing the strengths of your human and technical resources and how to integrate them is key.

This approach is an interesting example of how SaaS managers can get a jump start on implementing machine learning and artificial intelligence into their products today. Find bottlenecks in your processes that can be augmented by existing technology. This will improve your business today and make you more nimble for the future.

Consumers will expect a more responsive shopping experience

Customers are coming to expect a higher level of quality and service in eCommerce. As AI-tools become more sophisticated, the businesses who come out ahead will be those with higher-functioning AI-systems. 

The adoption of high-functioning artificial intelligence is going to drastically change the way consumers shop online in two ways:

Shopping is going to become more responsive to the needs of the consumer.

Having the data to predict shopper personas at every stage of the buying cycle, is a business owners dream. We can show products that shoppers are interested in, and understand what stage of the funnel they are at.

Does their shopping behaviour indicate they have already read reviews and are ready to purchase? Or can we show them more information to instil confidence and help them make the right decision? Which photo best conveys what this customer is looking for?

The aim of eCommerce will be to create a shopping experience that:

• puts the products the consumer wants where they expect them to be 
• tailor the whole experience to encourage completing a purchase
• avoid buyer fatigue due to clunky user experience

Artificial intelligence systems will react to even the most erratic changes in consumer behavior. 

IBM discuss an example that illustrates how artificial intelligence systems can react with greater precision, insight, and speed than possible with human intervention. The system implements a new marketing approach, analyses the results and automatically scales back to just the right level, reacting to these changes within the hour. This creates more effective and tailored marketing.

Presently, human capital and domain knowledge still remain a critical element in eCommerce. As MailChimp chief data scientist John Foreman states:  “A data science team should align itself with the business and serve that business”.
Having the right team and domain knowledge only puts you in a better position to take advantage of new ways for artificial intelligence to improve your business. 

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