AI And Its Role In Internet Commerce

Competition online is fierce and dominated by behemoths like Amazon. The economy and consumer spending habits are both volatile, and meeting customers’ expectations in an omni-channel marketing environment is complex. For your ecommerce retail channel to thrive, you need to understand, anticipate and adapt to changing conditions, trends, and customer preferences. Embracing technology is how retail is evolving to meet this challenge. In particular, the application of artificial intelligence or AI technologies has enormous potential to improve the profitability of online stores. 

AI powered ecommerce is of great help as it enables customer-centric online searches, identifies prospective customers, answers customers’ queries, simplifies sales techniques, establishes actual conversations with customers through chatbots and a lot more. In a fast-changing business environment, online retailers are being forced to invent new ways to attract and retain customers extensively. Versatile and varied AI applications such as Niki.ai, Mihup, Bewgle, Worxogo, Doselect in ecommerce are hugely unavoidable as retailers need to keep up with the fast-paced competition.

Dominating Global Trends And Future Applications

• Voice Search and AI Assistants

If you’ve ever chatted with Siri, you know she has a way to go to improve her understanding of your requests. AI assistants on the market, like Google Home and Amazon’s Echo, have gotten better at understanding and delivering on our requests, but there is still plenty of room for improvement there, too. 

To surface results that match searcher intent, algorithms must be trained to recognize and interpret numerous patterns in our natural language. Voice recognition has been a tough problem to solve because of the countless variations in the way people speak. Unlike typed searches that map to relevant keywords, voice searches are more complex. They tend to be longer and less direct. 

That’s where artificial intelligence comes into play.

A specific type of artificial intelligence, called a neural network, attempts to emulate how the human brain learns and makes decisions. It is the primary type of algorithm used in automated speech and facial recognition. This is the same tech that powers Facebook’s facial recognition when you upload photos of people.

For voice search and AI assistants to really take off, experts agree the experience needs to feel more like interacting with a human, and not a computer. Google Home is certainly making strides there. When users ask the device to add items to their cart, Google leverages all the data it has on its users to predict brand and retailer preference and price sensitivity when returning results.

When the technology can interpret nuances of our speech, tone, and intent, we’ll see massive strides in voice search. And our interaction with AI assistants could move beyond the transactional.

• Machine Learning and Hyper-Targeting

Finding the right consumers is becoming easier for marketers who can extract insight from the data available to them.

Marketers can go well beyond high-level demographics to target shoppers. Machine learning algorithms — another sub-category of artificial intelligence — find patterns in both online and offline data to understand what consumers would likely be interested in purchasing. Search history, purchase history, social profiles and interactions, and geolocation thanks to the smart phones are veritable goldmines of consumer data.

Targeting with the help of machine learning is precise, and it can be contextual. Machine learning makes it possible to piece together customer journeys and predict future purchases. When applying machine learning to social network data, like Facebook’s, retailers can target based on pages liked and even what friends have purchased. All of this data can fuel purchase recommendations retailers can serve on their websites, in emails or in social channels.

• Personalized & Targeted Customer Experience

Artificial intelligence is making the search for customer insight faster and less subjective. In B2C retail, big market research surveys aren’t necessary to understand customer preferences anymore. Customer data is everywhere, and machine learning can help retailers determine the kinds of experiences consumers want.

Product recommendation engines run on continuously learning algorithms, which use every new action a shopper takes to personalize suggestions. The better you get at suggesting products consumers are interested in, the stickier your site becomes and the more loyalty you foster.

Artificial intelligence can help personalize your website experience for individual customer preferences. Large retailers employ data science teams to pull in data about purchase trends, customer loyalty, demographics, and browsing patterns that enable retailers to anticipate demand, identify high-value customers, and deliver relevant and personalized offers at the right time.

Even if a data scientist or a team of engineers to sift through customer data is out of reach, machine learning technologies on the market can surface gems of customer insight that can inform your marketing strategy. Remember, retailers of all sizes have access to their own data — it can be purchase behavior available through a CRM, or views of website click journeys through a free Google Analytics account.

• Customer Service Via Chatbots

Chatbots will generate over $8 billion in global savings by 2022 with the global chatbot market being valued at $1.3 billion in 2024 which was at $703 million in 2016. USA, India, Germany, the UK, and Brazil are the top 5 chatbot using countries.

While that might be surprising to some, a data scientist wouldn’t flinch at this prediction. Improvements in artificial intelligence will enable chatbots to interpret what a customer is asking for in a wider variety of scenarios.

As it stands now, chatbots need a good deal of human oversight and are best employed in well-defined scenarios where mostly routine responses are expected. But just like most things that rely on artificial intelligence — bots can be trained. Part of what makes the evolution of chatbots possible is the plentiful training data available from online chat support.

And because bots don’t need sleep or days off, chatbots will help retailers provide more reliable — and in the long run, cheaper — customer support. For retailers that need it, 24-hour customer support would be in reach.

Artificial intelligence has come a long way. The long and short of what artificial intelligence can offer e-commerce marketers and consumers is E-commerce that is more convenient, more responsive to consumer needs, and ultimately even predictive.

Conclusion

AI has a deeper and stronger grip on future of doing business. Global businesses are rapidly adopting AI to streamline and fortify their processes. Chasing this trend allows them to save millions of dollars, and thousands of hours of precious time of their agents. 40% of visitors on an eCommerce site use AI chatbots to find offers and deals. The same report also mentions that 1 in 5 customers is willing to buy from a chatbot. 

The amazing makeover that eCommerce shops made through AI and its allies are as vivifying as it is. Also, it is evolving day by day. In the near feature, we can witness momentous advancement across the eCommerce shopping experiences such as immersive shopping and autonomous last-mile delivery services.