Customer retention is one of the significant causes of concern for ECommerce companies. Most ECommerce companies would invest a considerable amount of money in acquiring new customers only to see them never purchase again. The customer churn is like a hole in the bucket of business. The ECommerce business owners are trying their best to fill the bucket with more and more new customers each day. But the hole at the bottom of the bucket keeps leaking out the customers. Learning customer behavior is vital to understand how to reduce churn. Artificial intelligence technologies can help ECommerce companies learn customer behavior and thereby, ways to reduce customer churn.
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To understand the concepts of ECommerce, it is always good to know how a particular situation applies in the physical world. So let's begin with an example. You are visiting a community store to buy, say shirts and trousers. You make your choices and start bargaining a deal. The store owner knows you from the past since you are quite a frequent visitor. Generally, the store owner would give away a discount of 10% on your total bill. However, today, you've come along with a friend who is visiting this store for the first time. The store owner gives an additional 5% off on seeing a new prospect with you. On further insisting to do the best price, the store owner gives you an offer, 20% flat discount, only if your total bill crosses $200. That makes the deal irresistible for you, and suddenly the friend also jumps in to buy with you.
Superficially, the title of the blog looks like an oxymoron. We immediately map the terms Research & Development with the Innovation. It is so much prevalent in our perception that innovation comes straight out of R & D, ready made, ready to be consumed and everlasting. But when you carefully look at the process of R & D, it is just an iterative process where you form a hypothesis, conduct experiment and test the theory with the obtained result. If the results are conclusive, then you get your innovation. But it's most often that you can be wrong. When you fail at the intermediate steps of the experimentations, you go back, re-formulate the hypothesis and test again. It’s called as rinse and repeat. This process demands the sheer amount of energy of the people involved and requires time to do that.
As software architects we secretly desired, the software system should not be built by, line by line of code, but rather architected more like how we play with Lego blocks. Just grab the blocks from available blocks and connect them. There you have it the system you have imagined! More at the natural form of how you have envisioned the system.
Tags: Dation Platform