In this digitally connected age, where consumers can make purchases across diverse channels, including shopping on in-store iPads and shopping on their desktops or mobile phones, consumer buying power is at an all time high. Shoppers have choice at their fingertips, and if retailers want to stand out above the noise, then they must push harder to be memorable and distinctive.
This is why 81% of companies will be competing mostly or completely on delivering an outstanding customer shopping experience over 2019. It’s no longer enough to be the cheapest, biggest or most well-known, with 76% of all shoppers now claiming that they naturally expect companies to understand their needs and expectations in order to tempt them to shop. So how can today’s ecommerce retailers do this?
When 87% of contemporary consumers begin their shopping journey on a digital device or channel, it’s vitally important that brands understand how these tech savvy shoppers are engaging with each digital touchpoint.
Thanks to an explosion of tech gadgets and online shopping options, 73% of shoppers now use multiple online channels and devices before making a purchase, so if retailers want to ensure a standout shopping experience across all of these that grabs customer attention, then looking closely at customer data trails across devices is key.
Artificial intelligence and machine learning technologies are giving many modern brands the tools to analyse customer browsing and shopping behaviour at scale to gain ground-breaking insights that will make a difference. By giving brands deep insight into how consumers are shopping across each individual reference point, retailers can gain immense power to tailor customer shopping experiences.
This way, they can suit the specific needs and wishes of diverse customer segments across a multitude of different devices. By doing this, brands can create personalised experiences that tantalise the interests and imagination of every online consumer.
By capturing insights that determine how your diverse customers shop, and what interests them, retailers can showcase relevant and personalised product selections across each channel through strategies like automating visual merchandising processes and tailored product recommendations.
The ability to do this is an extremely appealing proposition for the modern retailer who needs to adapt their business offering quickly to serve digitally fluent customers in today’s eclectic omnichannel shopping space.
AI-driven processes empower online merchandisers to create tailored experiences that are extremely relevant to each customer’s interest by recognising different shopper needs and allowing merchandisers to adapt product displays, navigations and content features automatically to reflect these diverse needs.
However, while automation makes this process more precise and relevant, it also frees up merchandising and wider ecommerce teams to take a more strategic approach in line with commercial goals.
But a great online shopping experience isn’t just about showing products that interest consumers. It’s also about guiding customers to these products quickly and efficiently in an online browsing process that is smooth, seamless and trouble-free.
Machine learning algorithms and artificial intelligence also excel at helping brands do this by empowering shoppers to ask questions that will lead them to the most relevant onsite results.
Algorithms can learn different synonyms that customers use for different products in the onsite search process, while understanding customer typos and mistakes, and mapping all of these search terms to pages that resonate with the customers wishes and likes.
Machine-learning algorithms can also populate and reveal unique onsite navigation menus based on the types of bespoke products that a customer is searching for. This helps customers to find what they want onsite in the fewest clicks possible while giving merchandisers more power than ever to surface relevant products that their customers will love.
By adding this layer of helpful assistance to the shopping process, customers are much more likely to be satisfied and convert.
While advanced technological processes like AI and machine learning can prove to be game-changers when it comes to powering personalised and seamless onsite shopping experiences, they don’t create brands. People do that instead through their creativity, ingenuity and captivating ideas.
The world’s most memorable brands, from Apple and Coca-Cola to Chanel for example haven’t gained global iconic status through the workings of machines. They’ve become famous thanks to the creative minds that have catapulted their names into the hearts and imaginations of consumers all over the world.
This is why today’s retailers shouldn’t just rely on machine-learning robots to pull an outstanding shopper experience out of the bag. Ecommerce managers and merchandisers always make their most compelling impact by curating the shopping experience according to their own creative observations - looking to ‘in-the-moment’ trends that are relevant to now, and overriding machines and AI when it is most relevant to do so.
If you’re a luxury fashion retailer for example, you’ll know that machines can’t yet predict what best-selling creation will reveal itself on Chanel’s catwalk at Paris Fashion Week next season, or who will be the next Instagram influencer to wear this product first, let alone the importance of these influencers to the products that your company purchases and sells.
But this is why technology is so useful when creating exceptional shopping experiences – many leading merchandising teams are using automation to do the heavy lifting for a larger proportion of merchandising and personalisation, while giving them more time to work on strategic brand campaigns that matter most like responding to ‘in-the-moment’ trends and developing alluring brand propositions that will capture customer interest ahead of the competition.
By combining technology with human-driven creativity in this balanced way, brands are all set to shape exceptional shopping experiences that customers will definitely want to pay attention to.