Online consumer behavior has become more complex. Shoppers no longer just want quick answers—they expect to be understood, supported, and reassured. The era of traditional search is coming to an end. Welcome to the age of assistance.
In this fifth article, we explore the new expectations of online shoppers and the concrete levers to meet them. Artificial intelligence, deep understanding of intent, real-time personalization… To convert, it's no longer enough to inform—you have to guide.
It’s your job to accommodate your customer
Google has announced the end of the golden age of search and the start of the era of “assistance”. It’s time to provide your customers with personalised, instant and contextualised answers.
Google foresees the end of the traditional search engine and the dawn of the age of assistance. Essentially, Google is pre-empting a major change in online shoppers’ expectations, which go beyond a simple response to a question. They now expect tailor-made support from online retailers, focused on their individual needs.
To meet this challenge, Google has put forward three guidelines:
- provide a truly individualised response to every search on your website;
- introduce a standardised system for learning and anticipating requests;
- and move beyond text and allow voice interaction, which is still our most natural method of communication.
Google’s vision essentially echoes the interactions we used to have with our local shop owner.
They called us by our first name, knew what we liked and could anticipate what we wanted. It’s all about putting yourself in the customer’s shoes so that you can help address their needs.
For example, if you sell lawn mowers, you have to go beyond the power and type of motor. The real pain point for a customer is not buying an engine with a certain feature, it’s finding the lawn mower that can best cut THEIR grass!
Adding information to each mower that relates to its use, such as the area of lawn that it can cut, rather than its technical characteristics, will undoubtedly be much more useful in resolving your customer’s problem.
Consumer psychology is becoming more subtle and the decision-making process is increasingly complicated to predict. New behavioural analysis technologies provide real answers on the subject.
So how do you convert the customer? This is the question that behavioural science has been wrestling with for more than a century, well before the invention of the internet. The famous sales conversion funnel that you’re trying to optimise every day was theorised in 1924.
So, faced with the explosion of offers and new means of communication, Google recently conducted a study aimed at decoding internet users’ buying decisions. Scientists have named the resulting data as the “messy middle” which describes the customers’ state of mind when making a purchase. Essentially, before making a purchase, the customer swings between two stages:
- an explorative research stage that drives them to visit product information pages, read the content and digest the information, before forming an opinion on their future purchase;
- and a selection stage that allows them to narrow their choices, to reach a decision or move on to an exploration phase.
On a website it is extremely difficult to keep up with these interactions. The listing pages are often static and the search path is rigid. It’s here that new automated learning methods (e.g. Deep Learning) designed for e-commerce are able to help.
When a customer enters the exploration stage on your website and starts to narrow down their choices using your navigation structure, visiting product information pages or using your search engine, they leave several clues behind. AI designed for e-commerce, programmed well and properly aligned with your product catalogue, can take over instantly and broaden the spectrum of the search from the start of the journey. It can identify the tipping point, when the customer has identified the desired features or functionality of the product, and put items that perfectly match their purchasing criteria at eye level. We are close to realising the dream of right product, right time, right place!
Magic number: 100%
This magic number demonstrates the importance of offering an individualised search experience according to the buying cycles and intentions of every customer. After 12 months of using our solutions, our customers have seen an average increase of more than 100% in their internal search conversion rate.
Cheat-Code 5: Take into account the problems, needs and preferences of each customer, and offer each one a unique solution just for them.
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