DataMa identifies for you the different e-commerce trends that will guide your marketing strategies in 2021.
UX data for hyper-personalisation
Products adapted to each customer, a search interface that quickly responds to their needs, in short, a personalised shopping experience… A charming asset that undoubtedly contributes to the success of your e-commerce site! Hyperpersonalisation is based on the collection of user data: UX data (search history, browsing time, average budget spent, etc.). Understanding user behaviour allows you to better optimise your page, for example by sending a message that corresponds exactly to the consumer’s expectations. The challenge is to increase the site’s conversion rate.
On an e-commerce site, hyper-personalisation takes place at several levels: the home page, the search bar or the product page. If we take the example of the search bar, it becomes a space of personalised suggestions for the user according to his previous searches. In addition, the consumer is guided by a system of suggested filters that refine the results.
How can hyperpersonalisation be used in a marketing campaign?
First, the user profile must be established according to his preferences thanks to the collection of his UX data on different channels. More precisely, this involves user attributes (name, preferred message medium), behavioural attributes (products consulted), past purchase data, etc. The data analysis is completed by predictive analyses that define the perfect timing of a message sent or a product suggestion.
Then you can identify the events that will serve as triggers to execute these campaigns with highly personalised content, for example an abandoned shopping cart in the event that the buyer does not proceed with the purchase.
Finally, it’s about testing with the analysed data to determine which version of the site is best, most optimised, according to the user profile.
OK Google, what is voice marketing ?
The proliferation of voice assistants such as Siri or Alexa has launched the voice marketing trend. And a new search method means a new way of organising your web page to increase the click rate. Indeed, there is a difference between text search and voice search. In the search bar, users tend to type in short queries in the form of word associations, whereas in speech the query is dictated, often in the form of a question.
As a result, the search engine is increasingly seen as an answer engine, which explains its design change with the appearance of snippets.
A snip what? Yes, these little inserts where information from a web page related to your query appears in a few lines, inviting you to click on the link to find out more.
The snippet is an essential element to take into account in an SEO (Search Engine Optimisation) strategy which aims to highlight your web page since it is in first position in a search engine. The SEO strategy is then modified to adapt to the voice query with the introduction of new keywords, especially interrogative adverbs (who, how, where, why, etc). To go further and not only answer the user’s question but also attract them to your page, SEO is combined with UX. As a result, your page is not only visible but able to convert the visitor into a buyer. This is what we call SXO (the marriage between UX and SEO). Voice marketing therefore requires more use of SXO.
The age of chatbots
The chatbot supported by artificial intelligence is able to recreate the immediacy of an exchange, so it becomes the interface between the brand and the user. The increased popularity of chatbots is explained by the fact that they can be integrated at different stages of the customer journey. What exactly are its advantages?
- Gain in profitability thanks to its full-time availability to advise and guide the customer through the purchasing process
- create a privileged link between the buyer and the e-merchant
- provide e-merchants with information about the behaviour of their targets, information that is essential for optimising their offer.
Social selling or e-commerce on social networks
You no longer need to type the name of your favourite website in the Google search bar, now it comes to you directly on the social networks you frequent. The advantage? Not having to change the interface! This is what we call social selling.
Social selling is based on sharing value-added content, stories that can arouse emotions. Sharing content is part of an inbound marketing strategy: creating content that makes the brand visible in order to attract potential buyers. Social selling is also changing the way marketers prospect. Social networks not only help to better identify these potential targets but also to better understand them through social listening. The implementation of social listening requires being attentive to the interactions of potential leads who express their needs and their thoughts at the time. This data collection via social networks is an effective way to better adapt your marketing strategy. Social selling includes a process of researching, selecting, listening to and interacting with potential leads via social networks.
IA & marketing, a couple that lasts
AI is the new trendy technology that is taking the marketing world by storm! Two types of artificial intelligence are on the scene: deep learning and machine learning.
Machine learning is an artificial intelligence technology that allows computers to learn without being programmed in advance. To learn, computers train on big data to be analysed. Deep learning is the derivative of machine learning that allows the machine to learn by itself. Deep learning is not based on data but on an artificial neural network inspired by the human brain.
These two technologies show how artificial intelligence can intervene at several levels in a marketing strategy: the optimisation of advertisements, the generation of content, prospecting…
Two examples of the promising association between AI and marketing to make it all more explicit: the use of visual recognition in e-commerce and pre-emptive marketing.
- Visual recognition in e-commerce
Image recognition is very developed in the retail sector and many applications are also getting involved, such as Shazam or Snapchat. The latter recently launched “Visual Search”, which allows users to identify a product and then buy it on Amazon.
Visual recognition using machine learning simplifies the purchasing process. Indeed, the image processing done by the AI makes it possible to make the immediate link between the product and the purchasing platform. Visual recognition plays an important role in the hyper-personalization of the customer relationship.
- Pre-emptive marketing
Pre-emptive marketing requires a medium-term vision to refine the effectiveness of investments in relevant marketing strategies. Using artificial intelligence, marketers can sift through large amounts of data to determine future trends.
Once trends are identified, products and programmes are preemptively promoted to relevant consumers. AI algorithms also assess the likelihood of a customer’s purchase, giving the company a short- to medium-term view of its revenue.
Now that you’re up to speed on the year’s trends, you have all the tools you need to develop your best marketing strategies!