eCommerce is one of those industries where the understanding of the customer is one of the most important elements of establishing and maintaining competitiveness on the market. It is obvious – you just can’t do anything of note without understanding what your target audience is, how it is segmented and what are the needs of its every segment.
For years this was quite a feat but now things have changed.
The reason for that is simple – rapid development of artificial intelligence and machine learning algorithms. According to the experts from The APP Solutions, these technologies had brought eCommerce business operation to a completely different level and opened up numerous opportunities that seemed like science fiction even a decade ago.
These days, eCommerce marketplaces can adapt to the customer and deliver exactly what he is looking and even suggesting what he might need in addition to the product he is looking for. All thanks to a couple of algorithms and user data.
In this article, we will take a look at how Artificial Intelligence and Machine Learning technologies improve eCommerce Customer Experience.
Table of Contents
1. Personalization of the customer experience
As you know, every action that occurs on your website is monitored. Every user produces lots of information that can be used for his benefit. That’s what personalization is for.
The purpose of personalization is simple – to show the customer the products he is interested in instead of the stuff that means little to nothing. Elimination of superfluous brings more focus on the relevant product thus greatly increase the conversion ratio.
Here’s how it works. The customer is a source of information – his behavior on the website speaks volumes to the algorithms.
Through such actions as going from page to page, time spent on pages and search queries – one can understand what kinds of products to show, which brands are preferred and what is the approximate price range available for the customer. In addition, that you have browser information, geolocation data and some other identifiable information.
All this information allows to calculate the best possible matches and present the most relevant products that are more likely to result in a purchase. In addition to that, the store can change the layout language accordingly and provide relevant payment options.
2. AI Assistants
The rise of conversational commerce is one of the most fascinating developments of recent years. Just in a couple of years, chatbots became a permanent fixture of eCommerce marketplaces. It is easy to see why – they are good at helping customers to buy things.
Here’s how it works. Chatbots are built around a library of scenarios based on key situations (such as product search or explaining how to do something) plugged straight into product inventory.
When the bot gets a query (for example, little red dress, coca-cola bottle-like) – the bot goes through the database, matches the results with the available user data and presents the product that perfectly fits the query.
In addition to that, bots can handle payment proceedings, shopping cart management, and shipping options.
AI Assistants make the whole customer experience seem as if it really happened. And they can handle large amounts of customers at the same time (which is always a good thing).
Since the whole experience is more about verbally expressing what you are looking for and less about undertaking the clicking odyssey – it is far more engaging overall experience.
3. Fighting fake reviews
Reviews play a big role in the consideration process. Oftentimes they act as the decisive factor in whether the customer will proceed with the purchase.
And often this particular detail is exploited in order to fool the customer into buying some product that is not exactly as good as it was stated in the reviews.
The fact of the matter is – fake reviews are destroying the credibility of the marketplace. How to stop it? For example, you can manually moderate the reviews, but then again when the number of reviews is counted in thousands – that’s not exactly feasible. Enter AI.
Here’s how AI can handle this problem. With a little help of text-analyzing and web-crawling algorithm, AI can check the credibility of the reviewer (whether it is a bot with no previous history or not) and compare the reviews for the products from different sources. All this can help to filter out suspicious and downright fake reviews and leave only the credible ones.
4. Inventory management and sales forecasting
Knowing what is coming next is a strategic advantage for an eCommerce marketplace. Sales forecasting gives that advantage in managing the available inventory and focusing on the relevant products all while avoiding needless spending and downright losses.
Here’s how it works. There are lots of historical data stored in your system regarding past purchases and trends. All this information allows to calculate probabilities of certain turns of events and thus be prepared for them.
For example, forecasting can suggest which periods of time it is better to promote certain types of products (related to holidays, cultural or sporting events). In addition to that, forecasting shows the most and least popular types of products over certain periods of time.
5. Visual Search
Image recognition and visual search are amongst the most exciting technologies these days. Its implementation to the eCommerce can greatly expand the realm of purchase possibilities for the customers.
How? A visual search is a perfect option for mobile purchases. It streamlines the customer experience to its essentials.
Basically, the products are one snap away from the purchase and such things are finding the product and handling the checkout are done by an AI.
At the moment, such commerce giants as Pinterest, Amazon, and AliExpress are experimenting with this feature and the majority of brands are implementing it into their ad content.
In Conclusion
As you can see, the implementation of Machine Learning and Artificial Intelligence is a surefire decision.
It makes the customer experience more about the customer buying stuff and less about the customer trying to find the product he is looking for.
And as such it greatly improves the level of engagement and boosts the conversion rates simply by focusing on what matters to the customer.
