Somewhere between art and science, merchandising is essentially the process of selecting which products to show to customers to drive engagement and conversion.
As well as choosing which products will appeal to various customer segments, merchandisers must also carefully consider timing, placement and a whole host of other factors besides.
In today’s data-driven landscape where omnichannel personalisation is critical to customer retention, ecommerce sites can no longer use catch-all strategies that rely on merely displaying items where they are likely to be seen.
Merchandisers must understand the many and diverse customer segments that make up their buyers, as well as more abstract data points like shoppers’ intent, browsing behaviour, preferences and more.
Only by leveraging such insight is it possible to create user experiences that consistently achieve maximum conversion click-through rates, conversion rates and other KPIs.
However, joining the dots between extensive inventories, masses of user data, high volumes of traffic to achieve this and meet often challenging merchandising KPIs across many sales channels isn’t always easy.
In this guide, we’ll see how merchandising is in the midst of a revolution, as technologies like machine AI, machine learning, self-learning algorithms help teams design and deliver goals with greater accuracy and efficiency than ever before.
Ecommerce merchandising is about aligning brands’ KPIs with shoppers’ goals and making the buyers’ journey from discovery to checkout and beyond as easy, efficient, and profitable as possible.
Merchandisers must factor in several considerations when doing so: Seasonal offers, reducing overstock, margin, future mark down based on a lack of sale through, meeting demand and responding to new market trends are all part and parcel of successful merchandising strategies.
To accommodate these, merchandisers apply insight about visitors’ data, their intent, preferences, behaviour and more to design journeys that capture the shoppers’ attention and encourage purchases.
Branding, eye-catching product displays, strategically-placed offers and calls-to-action and innovative product discovery techniques are all part of the merchandisers’ toolset for achieving this.
Data is the key to unlocking insights about market segments and implementing merchandising strategies that work.
Information about how the user reached the site, their past purchases, browser behaviour and viewed items can all be used to generate user-unique merchandising strategies in real-time.
Artificial intelligence (AI) is at the forefront of putting such data to work – and it’s revolutionising the merchandising process.
Machine learning, self-learning algorithms and other AI-powered technologies allow brands to incorporate intelligent product recommendations and discovery, personalised dynamic content generation, retargeting ads, omnichannel integration and much more into their merchandising strategies.
Online retailers often find themselves with too little data to design merchandising strategies. But, conversely, they can also end up collating vast datasets that prove challenging to work with from an analytical or computational standpoint.
Where teams face the sparsity problem – the availability of little or no user data – Attraqt provides powerful out-of-the-box omnichannel merchandising strategies that don’t depend on masses of information to generate quick ROI.
For teams who struggle to make sense of extensive existing data, Attraqt provides pre-trained algorithms that make fast work of large data sets to seamlessly align merchandising touchpoints with little technical know-how or management required.
Personalised landing, category and product listing pages drive conversions by displaying products that synergise shoppers’ goals with merchandising teams’ KPIs. They are indispensable tools for merchandisers in today’s ecommerce landscape, where shoppers expect relevant omnichannel personalisation.
Attraqt’s personalisation tools understand both user behaviour and merchandising goals. They work in the background to collate and interpret users’ data to generate dynamic landing, category and listing pages to meet both. And the process continues off-site, where the same tools power personalised marketing emails, landing pages and more.
It takes advanced data science and AI expertise to implement personalised customer journeys successfully, and customers’ goals don’t always align with those of merchandising teams.
Attraqt is designed to plug directly into the most common ecommerce platforms for fast and easy integration out-of-the-box. Its self-learning algorithms can balance shoppers’ goals against those of merchandising teams. With constant A-B testing and always-on optimisation, Attraqt continually improves at finding the right approach to specific merchandising challenges.
Omnichannel merchandising is the process of creating a seamless customer experience across all sales channels, including the website, app, email, social media and brick-and-mortar stores.
When merchandisers get it right, shoppers should feel they continue where they left off when making the jump from website to app to the high street.
Attraqt’s headless, omnichannel dashboard acts as a central hub for collating and analysing data. Crucially, this takes place across all sales channels to create a seamless journey where offers, products recommendations and other merchandising strategies can flow freely between physical and digital stores and other channels.
Collating, integrating and managing data from diverse channels and devices can be challenging. Moreover, the omnichannel landscape is quick to change, with new technologies and channels falling in and out of favour all the time.
Attraqt’s headless dashboard for omnichannel merchandisers features plug and play integration that unites data from diverse sources quickly and easily. It is built using a future-proof composable architecture that lets teams quickly develop reactive solutions, keeping merchandisers ahead of the competition when responding to new market trends.
Attraqt’s product recommendation and discovery tools give merchandising teams the power to deliver on crucial KPIs like click-through and conversion rates, average order value, lifetime value and more.
The AI and machine learning technology behind Attraqt gives merchandising teams the predictive power to spot and react to emerging trends and new market segments before the competition.
Shoppers love personalised experiences, and Attraqt’s tools for merchandisers help teams create meaningful online journeys that visitors want to return to again and again.
Want to find out how Attraqt could supercharge your e-commerce merchandising strategy? Ask us about seeing a demo today.
