You’ve already experienced it. You were online, searching for something, possibly on an ecommerce store, and then suddenly you noticed related ads popping up.
As you navigated around the web, the products you were looking at begin to show up everywhere you go. When you go to search for something else in Google, the autocomplete bars offers you options related to your previous queries.
Have you been hacked?
No, but you are being tracked. Robots analyzed your behavior, and then they got personal.
The robots we’re talking about are the tools and processes for customer engagement that have become integral to ecommerce in the digital age. While this may seem a little intrusive to some people, this is now the reality of online marketing.
Ecommerce personalization is fast becoming a core strategy for marketers as machine learning sets about shaking up the world of online business.
While the rise of the robots may sound like an end to the personal touch for many businesses, the reality is quite the opposite.
How Does Ecommerce Personalization Work?
Ecommerce personalization is now a crucial part of enhancing the customer’s online shopping experience.
Marketers are handing more control to artificial intelligence, using recommendation engines and automation software to collect data on customer engagement and behaviors while visitors are on their site, and then using those data insights to deliver a personalized experience.
Through these techniques, ecommerce stores can utilize machine learning to refine their marketing strategies, ultimately learning from the analytics to drive higher conversions and earn a greater ROI on their marketing spend. Highlighting this potential is the research from Kibo, which ascertains that 92% of shoppers are influenced by personalized recommendations before they make a purchase.
All of this is great for those in digital marketing and ecommerce, but what about the customer? What does the prevalence of machine learning mean for the personal connection between the seller and buyer?
Machines Make Things More Human
No doubt you’ve had a frustrating experience with an answering machine. Contacting a company to discuss a problem can be an infuriating ordeal if you find it impossible to simply get speaking to a human.
With that in mind, the natural assumption may be to think people will be reluctant to embrace a more automated experience while shopping.
Surprisingly, when it comes to ecommerce, customers actually do want personalization, with 81% wanting brands to get to know them better.
So, how does this work? How does machine learning achieve such success?
While it may seem converse, the fact is that machines can make the online shopping experience more human. It does this by thinking about what people really want and then giving it to them in the most efficient and effective way. This has multiple benefits:
It is Streamlined to Eliminate Frustration
The internet is a crowded sphere, with very few industries not already over-saturated. Even in the most niche topics, customers are mesmerized by a plethora of options and alternatives.
As a result, many get annoyed by the flood of irrelevant content that doesn’t serve their needs or interests, with an astounding 97% of people leaving a site if the first product they see doesn’t engage them.
Others are just overwhelmed, too bewildered by the paradox of choice to buy anything at all. Studies indicate that less is more, with 75% fewer options proving ten times more likely to result in a sale.
It Saves People Time
People are busy and as already mentioned, they have a lot of options. They search for answers to questions, solutions to problems and products and services that will make their life easier or more enjoyable. Nobody likes to have their time wasted.
87% of visitors will abandon a site after a delay of just two seconds. When you’re trying to sell to people online, speed is of the essence. People want instant gratification.
Faster results will lead to happier customers. Marketers can use data analytics to track customer behaviors, seeing what pages they view and items they search for. By learning how to relate to a customer’s needs, ecommerce personalization makes it easier to satisfy their desires sooner.
It Makes Customers Feel More Important
Ecommerce personalization is particularly effective when the data insights are used to segment customers into different groups with similar demographics. Marketers can then tailor the messaging and content that each group sees, offering personalized product recommendations and offers that is most likely to engage those customers.
This makes customers feel more welcome as their shopping experience caters directly to their interests, making it seem like they are the only one in the ecommerce store.
The result of all this personalization is that it will foster brand loyalty. As people feel like they are being listened to and their needs are being fulfilled, they will grow to trust a brand. 44% of customers are likely to return and buy again after having a personalized shopping experience.
With Ecommerce Personalization – Everyone Wins
Artificial intelligence gives ecommerce companies untold power in reaching and helping their customers. By collecting data and using the insights to continually optimize strategies, marketers can craft their ecommerce personalization to no end, enhancing customer engagement for smaller and smaller segments of their audience.
As a result, ecommerce stores can encourage more impulsive sales by offering personalized product recommendations at different points in the buying funnel. Personalization in this way has a huge impact on average order value.
The evidence of this could not be clearer than on Amazon. The online retailing behemoth attributes 35% of its massive revenues to ecommerce personalization.
Digital transformation is changing our world in a myriad of ways, from the disruption of industries by companies like Uber and Airbnb, to the rising popularity of chatbots and the use of augmented reality.
Marketers who can use AI and machine learning to create a more personalized experience for people will boost their customer engagement levels, ultimately forging stronger relationships with them. In the end, this will benefit stores and customers.