Why is personalization the future of E-commerce?

By Immo Salonen, on 14 December, 2017

What does personalization mean and why does it even matter?

Let me start with a real-life example. Couple of years ago a friend of mine decided to enter a triathlon race. That was not something I had ever dreamed of before, but since I have a relatively competitive nature, it didn’t take too long for me to jump aboard. If he could do it, so could I.

At this point, I was not concerned about the fact that to actually finish the race; I needed to improve my non-existing swimming skills significantly. Instead, I was determined to make sure that I have the best possible equipment for completing the task. The one thing I needed the most was a new bicycle.

I spent the next weeks searching for information and making comparisons online. All this only to end up going to a brick and mortar store to make the purchase. So, what exactly happened and what did the online store lack?

The problem: relying on best guesses

Online shops in general follow extremely similar buying path. First you select the products, customise them, put in your address, choose the delivery method and so on. Things like insurance and financing are only to be found at the end of this funnel. Thus, online stores treat all their customers the same way. While there are analysts trying to figure out how to make the path easier, the path still remains just someone's best guess of an optimal purchasing path.

This is problematic because, in reality, every customer is different which means that they also follow their individual paths. There is no one-path-fits-all option. We all have our individual needs and we want those needs to be met in the right manner.

One needs financing to even consider a product whereas another person is loaded with money, but there are multiple questions regarding the insurance of the Bentley he is looking to purchase. Someone might need to discuss with a product specialist to confirm the suitability of a product for one’s use.

In my case, questions related to the coverage of my insurance. That was mainly because of in my initial enthusiasm I had forgotten I did not know how to swim. I wasn’t worried about the bike. Thus, I would have needed first to explore the coverage on insurance; then the choose the product after which maybe discuss financing options and so on. In this sense, I started my buying process at the “wrong end” of the funnel.

The solution: Data, smart people and algorithms

So, how could this have been avoided and customer needs and expectations better met? By using personalization.

You already have a lot of data. You know the pages visitors have been to, how many times they have visited certain pages, how much time they have spent looking at specific items etc. The amount of data collected is not the problem. The real issue is, whether you know how to use it?

In a nutshell, machine learning helps you to recognise different behavioural patterns. In the future, the online retailer doesn’t design the purchase funnel. He innovates ways to stand out from the competition. Namely, he decides what product to sell, what services to offer, what discounts to have, what content to publish and how to inspire visitors best. Services can be produced either by the retailer himself or by 3rd parties.

After this we let machine learning algorithms to decide what, and in which order, will be displayed to each visitor. In the future, an online store will be different for every visitor. You can read more on this
blog post .

Personalization today

The next generation web store is going to be a blank canvas. The content of the site and services offered will be designed based on every visitor’s individual needs.

While we are waiting for the smart people to get us there, we can already benefit from machine learning algorithms. They can already detect the hesitant visitors and calculate which incentive or reassurance they need to push them into a purchase. That leaves the retailer the sole responsibility to brainstorm incentives and ways to reassure the hesitant buyer so that the algorithms can choose the right actions.


Read Next: How machine learning fuels conversion optimisation - Case XXL






Topics: Real-time analytics, Personalisation, eCommerce