With 97 percent of businesses adopting big data and AI strategies, it's clear that data is the key to innovation and growth. Good data can diagnose problems while uncovering hidden strengths. It can help you develop short-term and long-term goals, which in turn can help you develop strategies to achieve them. Today, organizations have access to more data than ever before, and recent advances in artificial intelligence are breaking down barriers to data collection and analysis. Yet, less than a quarter of executives say they have developed a data-driven enterprise, revealing a veritable gold mine of untapped potential.
The e-commerce industry has a particularly unique opportunity when it comes to data analytics. E-commerce data represents a rapidly growing percentage of the world's data across a variety of types, sources, and associated user behaviors. Yet many e-commerce companies still don't know how to optimize this wealth of data to build better products.
The instinct is to analyze end-user behavior patterns. After all, it's the end-users that retailers rely on e-commerce vendors to serve. But the most powerful data for vendors comes from those retailers' customers themselves. By analyzing retailer data, e-commerce platforms can understand how and where their customers are getting the most out of their solutions, driving better product strategies and outcomes.
Winning numbers: How to choose the right data
You can unlock incredible new opportunities for your e-commerce technology business, including new revenue streams. Being able to identify customer needs and quickly develop effective solutions is a great way to grow your business.
There are many sources of customer data to consider, including:
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Business performance and utilization – This data will tell you how customers are behaving on the platform and identify which features are leading to the most success. To measure the value of their products, an e-commerce platform might analyze commonalities among their top-selling merchants. Key statistics to look out for include those related to sales and invoices, conversion rates, return rates, and store activity trends.
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Customer Acquisition and Retention – One of the most accessible types of data, it can reveal why people adopt your product. Did updates or new features bring in an influx of new customers? Did you experience spikes and dips in customer acquisition at certain times? Did a competing vendor introduce a long-awaited new feature? Did they introduce a feature that was bad or was discontinued? All of these factors and more can impact customer acquisition and retention.
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Traffic and engagement – Changes in website traffic and social media engagement can tell you which products are resonating with customers and which products are causing problems. Traffic peaks around product updates can be good or bad, so tracking sentiment is important.
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Content – E-commerce is a content-driven industry, using images, videos, and creative copy to communicate the details of your product to potential buyers. The better a seller's content, the more likely they are to outperform their competitors.
Data is most powerful as an enabler when it can reveal potential revenue streams. For example, if your customers are consistently integrating one product with a third-party product or plugin, it may be time to develop a similar solution. That said, not every platform needs to be all-in-one (or should be). When it comes to leveraging data, knowing what not to pursue is just as important as knowing where to invest.
Merchant data trends can also help ecommerce companies reduce costs: if the data shows that customers aren't benefiting from a particular feature, scaling back support or rolling the functionality into a complementary feature could save valuable time and resources.
Ethical considerations – How to obtain seller consent
Privacy and consent are non-negotiable considerations in any data analytics strategy. A product built on unethical data is an unethical product.
End-user data is theoretically useful to e-commerce platforms, but it is harder to obtain ethically than customer data. Shoppers on mobile apps or live stream sales don't give consent in the same way as merchants who buy e-commerce products, making use of their data potentially invasive at best and illegal at worst. Customers, on the other hand, often consent to the use of their data in user agreements. These agreements ensure that merchants retain ownership of their data while e-commerce vendors have access to it, and that consumers are protected.
After all, end-user data says more about individual merchants than the e-commerce products they employ, so vendors end up deriving more value from customer trends anyway.
Data Alchemy: Turning Analytics into Action
When your teams harness the power of customer data to drive product innovation, you can make a real difference in your customers' lives. Becoming indispensable is the goal, and to do that you need to thoroughly understand what your customers actually need. But when data becomes severely distorted by human error or improper interpretation, it becomes less valuable. Nobody wants devalued gold.
This is where artificial intelligence comes in. Recent advances in generative AI (genAI) have had a revolutionary impact on the data analytics process. genAI almost instantly discovers patterns that would take a human analyst days, weeks, or months to analyze. From these patterns, certain LLM and other frameworks can summarize conclusions in easy-to-understand language, graphs, and charts. Gartner predicts that 80% of companies will adopt generative AI models by 2026, but I believe this could happen even sooner in the e-commerce space, which manages vast amounts of data.
But analytics is only half the battle. Companies need to have a dedicated team to educate other departments on how these findings apply to their operations. If vendors develop new products based on patterns discovered in customer data, they need to ensure their teams have the right capabilities. Do they need to add staff? Do they need to upskill? Fortunately, data can answer these questions, too.
Empower your customers with their own data
Entrepreneurs are curious by nature – how many great companies started with the question “what if?” Providing retailers with insights into their own data helps turn that curiosity into action.
I recently employed this tactic when I led the development of AI ClipHero at my company, CommentSold, a video commerce platform serving primarily small and mid-sized retailers. For this generative AI product, we developed a tool that manipulated customer-generated audiovisual data (footage of livestream sales hosted on the platform) and automatically cut short videos. Customers could use the data they had already generated and agreed to have used on the platform to create new content and unlock new sales opportunities. We are now monitoring how customers are adopting the tool and making updates as needed.
E-commerce companies should view every new advancement in artificial intelligence as a way to provide sellers with new data insights so they can better serve their customers while delivering the best product experience.
Conclusion
Data is everywhere and, if harnessed correctly, can present enormous opportunities for e-commerce vendors. Understanding that the most powerful data comes from consenting customers gives vendors a necessary step towards building better products. This knowledge, combined with the right analytics strategy, allows vendors to leverage the wealth of merchant data to drive product innovation and business success.
