Unless you were living under the rocks for the last decade, you have certainly come across Artificial Intelligence, in one way or another. You would have also seen how most of the E-commerce platforms magically know what you exactly want (snooping?).

AI has been seeing more and more applications in recent years. Many E-com businesses nowadays are using AI for better understanding the needs of their customers, and provide an even better customer experience. In order to understand how they are achieving it, read on.

  1. Better product recommendation
  2. Improved visual search
  3. Improved cybersecurity
  4. Increased personalisation
  5. Better price management
  6. Reformed the sales process

Artificial Intellignce in Ecommerce Business

Better product recommendation

The importance of product recommendation is huge in the E-com domain. Having an effective product recommendation system can significantly increase, if not sky-rocket, the revenue of the organisation.

We have the opportunity of collecting a huge amount of customer data and use it to generate an individual’s purchasing preference and trend. Using consumer behavioural patterns on top of this personal consumer data your organisation can come up with a product recommendation engine.

Some of the biggest E-com giants like Amazon or E-bay does the same. By tracking the buying behaviour of a specific user from their account, they can recommend relevant products.

Product reviews, purchasing history, social media, web history – online retailers have utilised a host of different ways for collecting the consumer data. An effective recommendation engine can generate the consumer profile by taking into account all these pieces of information.

Improved visual search

Consumers usually have a very brief span of attention. Potential buyers would head to some other website if they don’t find the relevant items, sooner rather than later. Studies found that the presence of inappropriate items is one of the major reasons for a majority of the online consumers getting annoyed.

This hurts the business – both in short-term and long-term. It increases the bounce-rate, in turn decreasing the number of future customers.

Many E-com businesses are working on curating a better visual search engine. Users, for example, would be able to search an item with the help of the picture. You maybe want to have the watch that your friend has. Just take a picture, and you are presented with hundreds of watches that are similar to the product that you want.

One major advantage of this method is that, unlike a recommendation system, you do not need a prior history of the user for coming up with the recommendations. By embracing the power of AI, E-com businesses can cater to the needs of their customers better.

Improved cybersecurity

It is said that half a billion personal records were compromised alone in 2018. Data breaches alone account for the leak of over 4 billions of records in the first half of 2019. And according to Gartner, worldwide spending on cybersecurity is going to reach $130+ billion by 2022.

Various predictive algorithms are being used actively for strengthening the security of the E-com platforms. The platforms usually store a lot of useful information such as name, card and bank data etc.

Increased personalisation

Personalisation is the key factor in sealing the deal. E-com businesses strive to create an experience that is as personal as possible, preferably moulded to the needs of the specific users.

A new trend in this field is to use the multi-channel route. Some of the newer technologies take into account multiple consumer touchpoints. This helps in analysing and creating a map of how the users are interacting online.

The AI engines keep track of all the different devices that a user might be interacting with. They monitor each and every type of channels the consumer might be using, be it a website, an application, or some online campaign.

This enables the E-com businesses to generate a unified model of customer behaviour. By utilising this information, they can cater to the customers better and deliver a seamless experience.

Better price management

Dynamic pricing systems are anything but new. They have been the centre of attraction for a long time. This model implies that the price of a product is not static i.e. fixed, it is dynamic. The price is set by the retailers according to the current supply and demand, and some other factors.

You can see the dynamic pricing system getting applied in very many different domains including the stock market, ticket booking system, and transportation. But now that we have access to bulks of data including pricing information, transactional and customer data, we can utilise them to come up with an educated guess about the best time to decrease the price, start a discount, or hike the price.

The study of the dynamic pricing system is a hotly researched area. AI enthusiasts, as well as corporate researchers, are constantly trying to improve our current understanding. Most of the big names in the E-com domain employs the dynamic pricing model for the best possible outcome. This not only makes the price much more competitive compared to the other similar platforms, but it also helps attract the right kind of buyers.

Reformed the sales process

Cold-calling is no more the norm these days – at least not other than the darn credit card or insurance guys. But jokes aside, cold-calling is not only inefficient but also ineffective in most of the cases. If having the attention of the person in front of you is your goal, then kudos! You have failed right away.

A lot of parameters decide what and how much a customer should buy. Everything aside, social media and advertisements play a big role in that decision. This makes the purchase and social media history of the customer a viable tool.

Integrating AI tools with customer relationship management tools can be a good choice. This can include functionalities like natural language recognition. This feature specifically can be very helpful for voice input from the user.

The CRM can answer a customer query, or even find opportunities for additional insights (especially for the sales team). Add multitasking with this and you have got the perfect recipe for a great AI-driven CRM that can help revamp the sales process.