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Why A Customer-Centric Approach Is Key To E-Commerce At Scale


Cofounder and CEO of Mirakl, a global leader in enterprise marketplace solutions. Tech entrepreneur, marketplace expert.

When online businesses commit to operating an online marketplace, they’re suddenly faced with the challenge of abundance. Partnering with third-party sellers, marketplace operators can introduce thousands of new products to the platform, with some operators overseeing new assortments exceeding 70 million products. This dramatic growth provides a range of new opportunities, allowing marketplace operators to explore new categories and product lines without taking on the risks of storing and distributing those products.

But while the benefits of an expanded product assortment are clear, this overwhelming growth comes with its own set of challenges. How can a marketplace operator possibly evaluate tens of millions of products for quality and suitability? Is it really possible to maintain a unified identity when your product assortment has multiplied by 10 or even 100 times overnight? Most importantly, how can brands give their customers an intuitive, personalized experience if they’re left to sift through millions of product listings?

The answer to these questions can be found in data, AI, and marketplace technology, enabling operators to provide curated experiences and product selections even as their total assortments balloon into the hundreds of thousands or even millions.

Assortment And Discoverability

What makes an online marketplace successful? Whether it’s a global, multi-industry behemoth like Amazon or a curated marketplace for a single industry, marketplaces succeed when they’re able to consistently serve the right product to the right customer at the right time. By partnering with third-party sellers, marketplace operators significantly increase the likelihood that they’ll have the best product for any customer who visits their online storefront. But identifying and serving that product at the right time at scale is a different matter entirely.

The key challenge here is discoverability: Will a customer be able to find what they’re looking for, or will they get lost in an overwhelming sea of products? Solving the discoverability problem requires marketplace operators to fully understand the customers themselves, as well as the newly expanded inventory. You can’t give customers the best product for them if you don’t know their likes and dislikes, nor can you give them the best product if you don’t have a firm grasp on product availability.

Global And Local Challenges

Think about the structure of most governments. Most countries are led by a national body, which is responsible for those laws and decisions that affect everyone within the country. But the challenges facing a farmer in the rural north are likely wildly different from those facing a banker in the center of the capital city. Local governments are tasked with identifying and solving the problems facing their constituents. In an ideal world, those local governments can deliver precise, targeted services and support to those around them.

On a global, marketplace-wide level, marketplace operators must use AI and product data to map their catalogs as effectively as possible. Product data mapping ensures that when a customer goes looking for a specific product or category, they can find what they’re looking for. AI makes it possible to achieve effective catalog mapping even when a marketplace has integrated millions of products: Instead of having to manually comb through these product descriptions and categorize each item, AI can detect similarities in the syntax and descriptions and automatically map each product to its specific category and subcategory. This makes it possible to quickly onboard new sellers and then connect the products with the right customers at scale.

A more “local” approach to the marketplace customer experience involves personalization—offering each individual shopper a curated selection of products based on their buying history and stated preferences. Here again, marketplace operators must use customer data and AI in order to make curated product recommendations. By understanding the purchasing behavior of anonymous users and other shoppers that share their traits, marketplace operators can offer each visitor unique recommendations specifically tailored to their preferences—even when dealing with the dramatically expanded scale of a marketplace assortment. This approach allows operators to derive more value from each individual customer, creating a rising tide that benefits the marketplace owner and third-party partners alike.

The Extra Mile

When a brand launches an online marketplace, it quickly takes a major step forward in terms of product authority—using its new third-party partners and expanded assortment to increase its share of voice and drive new buyers to its site. But this product authority doesn’t guarantee an increase in revenues and share of wallet. Marketplace operators must go the extra mile, ensuring the marketplace presents each customer with the most compelling selection of products and guiding the customer to a successful conversion. Data insights and AI make it possible for marketplace operators overseeing a massive product assortment to know themselves, know their customers and know how to best bring the two together.


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