Creating frictionless e-Commerce buyer journeys with AI
Customers buy products and services, but what makes up this end-to-end process? Traditionally, customers become aware that they have a problem to solve. They then research and consider the options available to them, and based on these options, they decide on a product or service and commit to a purchase.
But we live in a digital world. In the UK, it’s estimated that 95% of products and services will be bought through e-commerce channels by 2040. So, it’s essential that we understand that the e-commerce buyer journeys are no longer linear. They represents a much more dynamic path, testament to the increased number of touchpoints and channels a consumer encounters whilst searching for their desired product.
From the moment a consumer starts to search for their desired product they begin on their buyer’s journey. What is unique about a consumer’s buyer journey within e-commerce is that, unlike traditional buying journeys, e-commerce journeys include a number of extra steps: Returns, cancellations, delayed delivery, online customer support, feedback forms and many others. All of these combine to create an online buying lifecycle that can define the user’s experience of the business they are buying from.
E-commerce customers are looking for tailored, convenient products and experiences meaning a good or bad customer experience throughout the buyer’s journey can make or break an e-commerce business.
75% of customers are willing to spend more to buy from companies that give them a good customer experience. 80% of consumers will switch to a competitor after one bad experience (Zendesk)
Customer touchpoints along the e-Commerce buyer’s journey
A touchpoint can be viewed as every interaction a consumer has with your business on their way to buying from you, no matter how small or large. This ranges from an advert that the customer sees about your product, to the checkout process, to a package arriving at the customer’s door.
Each stage of the buyer’s journey has its own variety of touchpoints, and the level of friction around them will ultimately determine whether customers buy your product. Although touchpoints form an experience for the customer, they are not static, one-way channels. The data collected from customer behaviour through each touchpoint informs how the customer interacts with the buyer’s journey.
So, how do we reconcile so many data points along the buyer’s journey to ensure we understand the customer and achieve end-to-end product and service delivery?
Today’s e-commerce marketplace requires not just superior technology, but also an unmatched ability to understand human behaviour. Every day, millions of consumers purchase products on the internet using complex mathematical operations and then store these products in shopper databases. E-commerce geniuses (or techies) are filling this gap by developing algorithms and learning how to use them.
AI facilitates the buyer’s journey at the product identification & decision levels
AI usage has increased by 400% since 2017 (Route 101)
AI can identify emerging trends by analysing search history and social media activity to provide better recommendations. And it can help retailers increase their profits by optimising their retail strategy by continuously assessing market performance via data mined from millions of high-quality customers and other sources. It is no secret that online shoppers are looking for better deals and more convenience when making purchases online. AI can play a major role in helping meet this need by helping to identify items that are selling well but that have long-tailed descriptions that are hard to understand.
Personalized Product recommendations increase eCommerce conversion rates by 915%
AI enhances customer support
The sheer volume and complexity of orders, queries, returns, make a personalised experience expensive on a site that should be able to run at any time in the day. Customer Support Agents cannot respond to every issue that the customer has despite the effortless experience that e-commerce customers seek in their buyer’s journey.
Using AI-driven solutions, repetitive queries and issues are automatically resolved without sacrificing the personal experience so many businesses are desperate to maintain. AI solutions are increasingly in popularity due to the high volumes of incoming tickets that can be automated, freeing up vital resources to be placed on more complex issues.
83% of IT leaders say AI and Machine learning is transforming customer engagement (Salesforce)
There’s no doubt that the amount of data available to companies has increased dramatically in recent years. But with this data comes increased responsibility: making sense of it all, ensuring that it travels outside of the walls of a single company and is efficiently utilized.
Post-sales just as important as pre-sales
Making sure the customer enjoys their product, keeps it and potentially makes further purchases in the future has become just as important as your initial sale process. Customers now expect a holistic experience and post-sales is part of that journey.
Ensuring a frictionless experience after the purchase is one of the most important parts of the buyer journey. This could include making sure the parcels are delivered to the right address or allowing for easy cancellations and returns.
It’s also important to make sure issues are resolved and not just responded to. As we all know there is nothing worse than receiving a reply after waiting, only to find it does not address the issue or question you asked, instead of waffling on about Ts&Cs. Action speaks louder than words.
Skullcandy: 60% of tickets fully resolved by DigitalGenius
Summary
Due to the higher and ever-increasing levels of complexity in the E-commerce buyer’s journey, there are many more touchpoints between the customer and the business. This means there is more opportunity for things to go wrong, as well as a higher level of attention to detail and care needed than ever before.
Not addressing this complexity risks loss of potential customers as well as reduced customer loyalty and fewer repeat sales. However, this also means more opportunities for e-commerce solutions that use AI to bolster their offering.
Bridging the gap between online and offline experiences is also important as customers want a consistent holistic approach to their purchases. This could mean showing stock of items in different shops, allowing for purchases online to be collected in-store or more flexibility in allowing returns to different shops.
All of this hammers home the point that the consumer experience should be as frictionless as possible, and the businesses that make it their priority can ensure continued success and a loyal and delighted customer base.
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