AI driven personalisation

eCommerce AI personalisation is the key to
improved consumer engagement and increased turnover. Find out why.

Personalised online shopping journeys are more likely to end in a sale compared with generic shopping experiences. That’s something that all eCommerce businesses know. The problem with personalisation is that it’s not easy to tailor shopping journeys for every single consumer that visits your webstore. In fact, it can be a challenge for many eCommerce SMBs to effectively segment their customers, to implement a successful product affinity strategy and to leverage targeted personalisation methods.

Only 20% of eCommerce brands and businesses use targeted personalisation, which means 80% are treating their customers in exactly the same way, serving up the same offers, campaigns and shopping experience to everyone. Individually targeted personalisation increases conversion rates, revenue and profitability. And because a majority of eCommerce brands and businesses aren’t doing targeted personalisation, those that do implement it will have an advantage over competitors in terms of CX, customer retention and brand integrity.

Why AI personalisation?

Artificial intelligence (AI) can help brands and businesses deliver personalised shopping experiences for individual consumers, based on their personal data, browsing and purchase history, location and activity in your webstore in real time. AI personalisation can show consumers product recommendations and content that will be relevant and valuable to them as individuals.

eCommerce personalisation takes a variety of forms, including bespoke product recommendations on your webstore homepage, personalised landing pages and emails, such as shopping cart recovery communications and other EDM. AI personalisation can also offer consumers more intuitive ways to interact with your webstore, offering chatbot conversations and even personal shopping assistants.

Businesses and brands that are able to provide personalised, individualised shopping experiences will attract and retain more customers:

• 3% of companies see an uplift in conversion rates from personalisation
• Having a personalised homepage can increase sales by 7%
• According to Forbes, 74% of customers feel frustrated when website content is not personalised
• 59% of consumers who experienced personalisation say that it significantly influenced what they purchased
• Personalisation technology that recognises customer intent will enable eCommerce businesses to increase profits by up to 15%

AI personalisation strategy

A successful AI personalisation strategy is 100% consumer driven. A successfully targeted personalisation strategy must enable shopping journeys that are highly relevant and help individual consumers to achieve their shopping objectives as quickly and with as little fiction as possible. A Walker report revealed that customer experience is overtaking price and product as the key brand differentiator.

To be truly effective, personalisation should look beyond what consumers want to achieve whilst shopping in your webstore; it should be able to predict what your customers will want and need in the future. For example, knowing when customers make birthday gift purchases will help to better target gift products; knowing which customers go on beach holidays and which customers prefer walking holidays in the countryside will determine what kinds of accessories and apparel they might need; and knowing which customers are vegan can help food and kitchen supplies companies better target recommendations.

Each business will have its own targeted personalisation criteria, but the principle is the same across sectors. As an idea, targeted personalisation is fairly straight forward. Implementing it on the other hand is tricky.

How does AI personalisation improve shopping experiences

Consumer expectations are evolving faster than ever and it’s becoming increasingly difficult for SMB eCommerce businesses to keep up with those expectations. Consumers expect personalisation as standard—think of Amazon and Netflix recommendations based on past browsing, purchases and preferences. 35% of Amazon’s revenue is created by its recommendation engine. And 80% of watched content on Netflix comes from algorithmic recommendations.

Your business may already be collecting and analysing customer data. But the vast number of datapoints that need to be analysed and streaming that data into targeted personalisation can be a challenge, and as your business scales it could become overwhelming.

Using an AI system to manage targeted personalisation enables you to analyse and filter vast amounts of data and to help predict customer behaviours and needs. AI personalisation is becoming crucial for offering consumers the experiences that they expect: relevant product recommendations, valuable marketing communications and more satisfying shopping journeys.

eCommerce brands and businesses that still rely on generic marketing are being outperformed by those companies that use personalisation. And in turn, those businesses that rely only of traditional personalisation methods are being outdone by those employing AI technology to better serve consumers with hyper-personalised, real time shopping experiences.

Landing page algorithms

AI, machine learning algorithms can carry out sophisticated content testing and optimisation at a rate that humans cannot. Algorithms can assess which page layouts and content drive the highest conversion with different customer segments, and then configure the online experiences to individual consumers in real time.

Product recommendations

Algorithmic product recommendations update in real time. Consumers expect ‘you may also like’ and ‘customers also bought’ features to show them relevant products. Personalised merchandising creates a product display to show customers items that will appeal to them based on their personal and behavioural data.

Semantic search

The search box is one of the most important elements of your webstore. Yet many eCommerce search functions are actually hindering as much as helping shopping journeys by using keywords alone instead of using AI to understand the meaning of the search terms in context.

Also, searches can be messy, with consumers using vague search terms and sometimes making spelling mistakes. If a customer isn’t sure precisely what they want, searching for it with keywords alone can be problematic. For example, if a consumer searches the phrase: ‘checkerboard trainers’, the search may return irrelevant results, such as items that have a checkerboard design but are not trainers, and trainers that are not checkerboard. By comparison, an AI semantic search will take a search phrase as a whole, in context, and serve up more relevant results—only trainers that have a checkerboard design.

Intelligent search offers consumers more personalised experiences because it not only works semantically, it can combine search criteria with other customer data such as browsing behaviour and purchase history, serving up more relevant and valuable search results and reducing friction on the path to purchase.

Consumer profiling

AI gives eCommerce businesses real time insights into consumer behaviour. As visitors browse your webstore, AI can analyse their actions and behaviour. In the same way that an experienced salesperson in a showroom might take subtle cues from a customer as they interact, and then use those insights to inform product recommendations. AI profiles can take behavioural cues from consumers, check inventory and match related products for informed, real time recommendations.

In addition to making super-fast personalised recommendations, AI can look at previous shopping behaviours, searches, browsing and purchase history, match customers with segments, and then combine it all with the real time behavioural data. AI can even use this data to create new customer segments.

If an outdoors retailer knows that customers will soon be looking for festival wear and accessories, especially in light of Covid, they create a landing page and add in the products they believe festival goers will be hunting for: tents, backpacks, waterproofs, cool face masks, visored hats etc. The AI then watches consumer interactions on the page to see which products are performing well, ensuring that those items are promoted and that there is enough stock to cover demand.

Personal shopping assistants

The logical conclusion of using AI for targeted personalisation is that every customer has their own virtual shopping assistant to help them quickly find the right products, make content recommendations, make personalised special offers and to guide them through their shopping journey.

The AI virtual personal assistant doesn’t have to operate only within your webstore. If you have a brick-and-mortar store too, your customers can use their mobile phone to interact with their AI personal shopping assistant, who can not only guide them through your store, but can use augmented reality to enhance the shopping experience. This blurring of the line between online shopping and physical shopping experiences is known as omnichannel and is on the rise, along with consumer personalisation expectations.

Final thought

As AI personalisation becomes increasingly sophisticated and increasingly accessible more eCommerce businesses will be able to offer consumers more relevant and valuable shopping experiences. This will in turn help improve customer acquisition as retail brands become known for their outstanding shopping experiences. Lower friction customer journeys made possible by AI hyper-personalisation will increase conversion rates and lift customer lifetime value.

How personalised is your business’s personalisation strategy? If you would like to learn more about AI personalisation, then get in touch today for a chat with one of our eCommerce specialists.