Is it possible to create customized recommendations for e-store customers without personal contact? Yes, it is, thanks to artificial intelligence. Find out what machine learning is and how you can use it in your e-business. See that the latest technologies are at your fingertips.
When shopping online, customers consult other users and compare the offers of different stores, and their communication requirements are very high. Retaining a customer takes more than mass communication in the form of traditional newsletters; we should communicate with each recipient personally.
Knowing the user’s profile and behavior well, we are able to tailor the right marketing communications to them. This is extremely important because such action may increase its effectiveness. The added benefit of content personalization is that we do not spam users with messages they are not interested in. Moreover, this communication allows gaining more customer confidence and more associating them with our brand more strongly. Thanks to personalization, the user feels that they are treated individually. There is a key question, how to do this through an online store visited by a large group of customers with whom you do not have personal contact?
Here the latest technology comes to aid. If your online store is integrated with eCRM, it will automatically collect data about every visitor to your website. This will include such information as historical and current online in-store activity, products viewed and also those added to the cart. You can learn how to do that in this article. If you consider how many people visit your store during the day, you will find that really large amounts of data are collected. However, collecting this information will do you no good unless you know how to use it.
What can artificial intelligence do for you?
The best solution would be to analyze this data to find out what each of your customers’ needs. However, dealing with so much user information is not really possible. Not to mention writing and sending separate e-mails, e.g. with product suggestions that the user might be interested in buying.
Image 1: Basing on the products that a customer already bought, we can tell what other items he might be interested in.
Identify the needs of your customer precisely through Segment of one.
In the case of marketing communications, it is very helpful to divide customers into segments whose members have similar needs and product preferences. This allows you to specify your offer so that it is interesting to everyone within the group. With the help of the latest technology, we are able to precisely determine customer preferences, so that each of them creates their own segment, called the segment of one. This allows you to precisely match the offer to each customer individually.
How does a machine learn?
The main issue that arises when you want to harness a machine to do some of your marketing work is that computers are still far from being as smart as people. A trader handling a customer at the store is able to advise and suggest products that may interest them. So if they buy a printer, then the seller knows that they could use with a couple of toners. For a computer to be able to do the same thing as the seller mentioned above, you must first teach it. This you can achieve with machine learning.
Machine learning is about getting the machine to acquire the knowledge that will allow it to do certain tasks. This is done by providing the computer with data that it then analyzes to find a common rule that describes it. Then, knowing this rule, it can use it to describe more data. In an online store, this can be used to determine the preferences of your customers. The computer determines them by analyzing the data on what products the users have purchased so far.
Image 2: edrone creates recommendations on the basis of what other customers bought within one transaction.
The advantage of using artificial intelligence to analyze data is that computers are much less prone to make mistakes than people. However, machine learning is not just a way to get you through this tedious work. Nowadays, technology has come to the point that allows you to perform tasks that a person would simply not handle.
How does machine learning work in edrone?
The edrone system creates recommendations by analyzing the contents of shopping carts – what products were purchased in a single transaction. So if many users purchase products A and B in a single transaction, the system knows that a customer who had only purchased product A would most likely also be interested in buying product B and will recommend it to them.
For instance, if customers at your online store often buy matching teacups together with a kettle, the algorithm will recognize that dependency and the next customer who buys a kettle will be offered to buy a cup. It is then very likely that the customer will buy a complementary product for their first purchase.
Artificial Intelligence is available to everyone
The recommendation algorithm is undoubtedly one of the major advantages of eCRM systems, including edrone. Since the machine itself learns which products to recommend, it can be used in any store, regardless of the range, industry and quantity of products. edrone allows using the latest technology in all stores, small and large alike.