The data-driven approach to converting more ecommerce customers
88% of products added to online baskets in 2022 were not purchased , resulting in £18 billion of lost sales in the UK alone. But this number barely scratches the surface, with millions of potential conversions failing to materialise every day because of inefficiencies at every stage of the customer journey.
Read on as we explore how ecommerce businesses can convert more users by embracing a data-driven approach to optimising their customers’ online experiences.
The truth about ecommerce conversion
Conversion rates on ecommerce sites are objectively low. Even if an impressive 5% of a website’s visitors go on to make a purchase, the overwhelming majority do not. Two things should be inferred from this fact. Firstly, that it is very difficult to convert online users to customers, and secondly that every ecommerce business has huge room for improvement in this area, given the right approach and the right technology stack.
Businesses can achieve a revenue leap in the short to medium term – while laying the foundations for sustainable growth over a longer period – by targeting conversion rates. There comes a point for many ecommerce brands (especially those in the mid-market), when adopting a data-driven approach to conversion rate optimisation is the only way to maximise this growth.
What does a true data-driven approach look like?
The decisions all ecommerce brands make around merchandising, recommendations, navigation etc. are likely to be influenced by some level of traffic and sales analysis. But when it comes to optimising conversion rates, the huge amount of data available to ecommerce businesses cannot be unlocked by humans alone.
Brands must leverage technology which examines the relationships between customer behaviour, personal information and stock levels, among a myriad of other factors to really understand their audience and meet their needs at every touchpoint.
Artificial intelligence (AI) and algorithms are helping brands serve customers with the items they are most likely to buy, at the optimum point of their journey. When deployed correctly, AI can deliver the ultimate personalized shopping experience, to increase the average value of orders and even benefit the development of future products.
Merchandising is an area that’s ripe for new data-driven efficiencies. By analysing customer data, browsing behaviour, and purchase history, sophisticated platforms can optimise product assortment, placement, and sequencing to ensure that the most relevant products are prominently displayed to customers. This data-driven approach to merchandising can significantly improve the visibility and appeal of products, resulting in higher conversion rates.
This isn’t to say that embracing data means ecommerce businesses must relinquish creative control over merchandising. In fact, AI-assisted merchandising enables brands to deploy their own unique strategies automatically and at scale, taking care of the real-time A/B testing that is crucial to improving conversion rates.
Advanced ecommerce platforms make segmentation of your customer and user base much more effective through the creation of detailed personas. While your company’s merchandising and personalization strategy will be what converts potential buyers into customers, the segmentation process will go a long way to determining long-term success. Interpreting the huge amounts of personal information, activity data and shopping preferences that can be collected from each customer – and using this to shape meaningful personas that are based on your commercial priorities – can be so much easier with the help of automation.
This data-driven approach also enables the deployment of a true omnichannel experience for customers. With 90% of web users switching between screens to complete tasks, creating a consistent experience between all channels has never been more important for maximising ecommerce conversion rates. Whether users are switching between your desktop site and your mobile app, engaging with your brand through personalized email, Whatsapp and SMS messages, or even making an in-store appointment, platforms like Crownpeak (formerly Attraqt) ensure a seamless experience guaranteed to maximise engagement and conversion rates.
Most ecommerce sites make use of dynamic content (website content and product recommendations which change depending on which user is viewing). But truly dynamic content requires a recommendations engine that takes thousands of data points into consideration. From search patterns, products viewed and cart data to a user’s age and location, platforms with the greatest AI and algorithmic capabilities spot the most important patterns instantly to serve the most relevant and inspirational products every time.
Dynamic recommendations can improve outcomes at all stages of the customer journey, including the all-important cart stage. According to Baymard, the average ecommerce cart abandonment rate in 2023 is an enormous 70%. The right kind of recommendations can significantly improve conversion at this final stage, by helping your customers to resolve any issues they may have around item colour or styling, for instance. The right recommendations at the cart stage is also a perfect opportunity to upsell. Personalized recommendations don’t just benefit your customer, they can also be used to serve other goals such as stock management.
Advanced image recognition software has become a staple of the best ecommerce recommendations engines, with the technology proving increasingly useful for upgrading sales outcomes. By using AI to overlay all product images with comprehensive metadata, brands can serve customers with products that match their shopping preferences, consequently boosting conversion rates significantly. Australian fashion retailer Forever New have increased their conversions by 135% and their average order value by 21% since implementing Crownpeak’s (formerly Attraqt) image recognition software – Visually Similar.
43% of website visitors go straight to the internal search bar when they first visit a site. Combine this with the fact that visitors using a site’s search features are 2-3 times more likely to convert, and the importance of maximising the potential of search on your ecommerce site becomes clear.
Most ecommerce sites still utilise extremely basic search functionality. By embracing a search platform which is able to provide smarter, more accurate results by using machine learning algorithms and real-time customer data, your brand can set itself apart from competitors and convert more of the captive market that is on-site searchers. Put simply, by intelligently prioritising products within the search function, ecommerce sites can dismantle the barriers customers often face when looking for a specific product and drastically reduce abandonment rates.
The most advanced platforms like Crownpeak (formerly Attraqt) have built-in search functions that go beyond just regular keyword recognition. As well as the searcher’s individual preferences, they also take into account the frequency of keywords on product pages, any potential synonyms for the searched keywords and spelling mistakes which more rudimentary systems would fail to account for.
A complete product discovery platform that converts
In a world where millions of potential conversions are lost daily, embracing a data-driven approach to optimise the customer experience is crucial. Crownpeak (formerly Attraqt), the most complete product discovery platform for ecommerce brands, could be the solution for your business. By harnessing the power of artificial intelligence and algorithms, Crownpeak (formerly Attraqt) enables businesses to analyse huge amounts of data, deliver personalized shopping experiences, improve merchandising strategies, and enhance search functionality. Take the first step towards maximising growth by arranging a demo today.
Alternatively, if you want more information on product discovery solutions, download our latest buyer’s guide, produced by London Research, which provides an objective set of evaluation criteria for assessing product discovery engine vendors. The guide is grouped into practical use-case models and draws from real-world experience to help you in your next phase of converting more ecommerce customers.