BigCommerce: AI-Powered Tools Can Filter Merchant Data and Drive Conversions

Artificial intelligence (AI) has risen as a powerful tool, offering boundless possibilities. But even with good intentions, there exists a potential for unintended negative outcomes. 

Last week, BigCommerce unveiled its partnership with Google Cloud to add AI-powered features to its open software-as-a-service (SaaS) eCommerce platform. Through the partnership, BigCommerce is looking to empower merchants to unleash the potential of their operations. 

Read more: BigCommerce and Google Team on AI-Powered Features for eCommerce 

So, how could a positive concept carry a negative potential? Speaking to PYMNTS, Meghan Stabler, senior vice president marketing at BigCommerce, delves into the advantages of the collaboration with Google Cloud, the benefits for merchants and consumers, and the ethical framework maintained throughout this partnership. 

BigCommerce is driven to let merchants tap into their data treasure trove. The insights range from merchant analytics to shopper behavior to inventory processes to customer interactions.  

BigCommerce is also equipping merchants with the means to capitalize on these insights by extending them to other marketplaces like Amazon, eBay, Walmart, Facebook and Instagram, as well as their individual websites. 

“We want to do it in an ethical way. It’s merchant data. Expose it to them and let them decide how to use it. Give them the tools, the interfaces through APIs and AI, to decide what they want to do to improve their product listings and other areas,” Stabler said.  

Why Ethics Matters 

The ethical considerations surrounding AI and big data touch upon privacy, fairness, accountability and transparency. The potential for AI systems to influence decision-making, automate tasks, and process vast amounts of data has immense societal implications, both positive and negative. 

One of the central concerns in the tech industry is the potential misuse of AI and data, which could lead to discriminatory outcomes, invasion of privacy, and reinforcement of biases. The call for AI system auditing and data sharing addresses these concerns by urging companies to be accountable for the algorithms they develop and the data they use. By signing onto such agreements, big tech companies commit to engage in ethical AI development, mitigating the risk of unintentional harm. 

BigCommerce is looking to ensure the ethical and transparent application of AI, placing an emphasis on putting merchants in control over their own data. This includes offering user-friendly tools and interfaces and APIs that enable merchants to make informed choices about their product listings and business operations. 

Recently a gathering of executives from leading tech companies like Google, Amazon, Microsoft, Meta, OpenAI, Anthropic and Inflection met with the Biden administration to sign an agreement laying out guidelines for auditing AI systems and facilitating data sharing with governmental bodies and academic institutions. 

As part of this agreement, tech companies will conduct audits on their AI systems before making them accessible to the public. The objective is to guarantee the ethical development of these systems and eliminate potential risks or biases. Through these audits, the government seeks to enhance transparency and accountability in the deployment of AI technologies. 

BigCommerce acknowledges the importance of the data it holds, which includes information from both merchants and shoppers. BigCommerce also seeks to balance merchant access to this data with the threat of potential data breaches or unauthorized entry. 

Data Insights  

One of the upcoming features that sparks Stabler’s conversation around ethical approaches is the inclusion of a tool for creating product descriptions. These descriptions aim to evoke a feeling of authenticity and individualization, similar to the interaction a customer might have with an in-store representative. Stabler said the technology matches product characteristics with a range of customer preferences like softness, comfort and occasion. 

Stabler said the aim is to understand customer needs and tailor product recommendations accordingly. BigCommerce plans to leverage AI capabilities, particularly Google’s vertex API, to enhance and simplify the task of product descriptions. The company envisions using AI to adjust content based on real-time factors like inventory levels, thereby optimizing SEO rankings and enhancing product discoverability. 

Highlighting the value of AI beyond product descriptions, Stabler said the potential which can lead to personalized storefronts using Google’s recommendation AI to tailor product suggestions to individual tastes. The concept extends to seamless checkout experiences with alternative payment methods like Google Pay and Apple Pay. 

Stabler envisions AI-powered insights as a crucial aspect of BigCommerce’s future. By integrating with tools like Google Big Query, the platform aims to offer comprehensive business performance reporting, enabled by AI-driven analytics. The integration would enable merchants to gain deeper insights into their operations and receive AI-backed recommendations based on factors such as seasonality, supply and demand dynamics, and shipping challenges. 

Who Will Get Access? 

Initially, Stabler said the focus will be directed towards enterprises and larger corporations due to the intricacies associated with their operations.   

The rationale underlying the approach is to begin with the more complex scenarios encountered by larger enterprises.  

“It’s really about, what these larger companies embracing AI, with their extensive data infrastructures, data lakes, warehouses, etc., are seeking. What are they in need of from the integration of eCommerce components into the CRM [customer relationship management] and email systems? And then see how that can filter down,” Stabler said.  

By doing so, BigCommerce aims to establish a framework that can be adapted and tailored to suit the needs of businesses operating on a smaller scale. The sequence is designed to prevent potential limitations that could arise if the approach were reversed.