Folio3 Interview with BigCommerce’s Manager Global Partner, Patrick Williams
Last Updated | November 13, 2023
Table of Contents
Patrick’s Introduction:
Patrick Williams leads BigCommerce’s Partner Solutions Engineering team globally. His team supports BigCommerce Agency partners from a technical enablement and consultancy perspective, helping them better understand how to leverage BC’s technology to serve merchant needs. Patrick has a deep interest in AI, participating as a judge in BC’s Google AI Hackathon, and writes about more technical AI topics on his blog.
Hey Patrick, we really appreciate this opportunity to have a chat with you and share the Insights on this trending topic.
[Q1] With all the AI buzz, we’ve heard that BigCommerce is gearing up to introduce some exciting Google Cloud AI-powered features. Could you please provide more details about these exciting features?
Absolutely! We are very excited about the new core AI features we’ll be releasing this year.
Just last week (Oct 23.) We made our first GenAI core platform release with the launch of BigAI Copywriter
BigAI Copywriter is a free application that lets brands easily generate engaging and SEO-friendly product descriptions with the click of a button, directly in their BC Admin Panel. There are even some great controls in the app to let you choose the tone or style of the text, have the AI include your brand voice in the descriptions, and even the ability to fully rewrite the system prompt to the AI for more advanced control.
Next up, we are working on native Product Recommendations via Google’s Recommendations AI engine, which should be released into beta before the end of the year. This will automatically surface real-time, 1:1 personalized product recommendations.
Another item on our roadmap we have not widely announced is the BigQuery ML Starter Kit integration into BigCommerce. This will bring the power of predictive analytics and modeling to brands without the need for ML expertise. Some example use cases we’re already thinking of include predictive inventory modeling and predictive LTV bands for new customers.
We also have a host of partner solutions in our App Marketplace already leveraging AI across a number of categories (search, email, content, etc) With our Open SaaS approach, we’ll continue to build both native AI features into the platform and capabilities partners and developers can leverage to integrate custom or 3rd party AI tools.
We will continue driving AI features into the platform through native releases and events like the BigCommerce Google AI Hackathon, through efforts by our Partners and Developer Relations and Product teams.
[Q2] What are some of the key AI-driven capabilities that online merchants can expect with these features?
A big theme of the AI tools we’ve begun building and seen built through events like the Hackathon is increasing merchant efficiency, improving the shopping experience, and creating personalized shopping experiences.
BigAI Copywriter empowers brands of all sizes to easily generate unique and engaging content in their preferred style and brand voice and is available directly in the edit product screen in the BigCommerce Admin.
There’s also a great opportunity for data enrichment here, particularly for B2B brands and brands with large catalogs, where product descriptions may not follow best practices or be very descriptive.
True personalization is historically something we only see very sophisticated brands take advantage of because of the barriers to entry in terms of data, building a logic engine, verifying results, etc. Product Recommendations will make this much more turnkey and bring near-automatic personalized recommendations to BC brands of all sizes.
Recommendations will also be open via API, allowing larger and more sophisticated brands to customize and configure the experience.
[Q3] How will these AI-powered features enhance the overall shopping experience for customers?
We are expecting some stellar results based on Google’s data including a 90% increase in click-through rate and a 40% increase in conversion when users interact with recommendations.
With Product Recommendations, We’re making it easier to create real-time personalized shopping experiences using industry-leading AI technology from Google which will enable brands to increase their user experience, engagement, and conversion rates by surfacing more relevant products to their customers.
BigAI Copywriter is _very_ configurable and will let brands ensure things like their brand voice and product features are represented in generated descriptions. This will help make the site experiences richer, improve search, and allow brands with lean content teams to have more time to work on new campaigns, landing pages, etc instead of cleaning up product catalog data. This can also help drive better SEO and in-site search results, and help improve return rates
We have also open-sourced the foundations for the Big-AI Copywriter app, so partners and merchants can build on top of the tool and create even more unique or use-case-specific implementations.
[Q4] Are there specific industries or verticals of e-commerce businesses that can benefit the most from these AI-powered features? For instance, fashion, automotive, healthcare, etc?
We think most companies will benefit from adopting AI features into their workflows as time goes on to stay competitive in the market. The empowerment of AI data, user-facing features, and insights AI tools can provide to all types and sizes of brands means teams that do not adopt these tools will begin to fall behind compared to their competitors who do.
That being said, I think certain industries have an outsized opportunity to take advantage of these tools now and have a huge impact on their business.
B2B brands or D2C brands with large, supplier-driven catalogs have a great opportunity to improve their data hygiene and discoverability with tools like BigAI Copywriter. Enriching product data can help with everything from SEO/discoverability to conversion, decreased returns, and more.
For Product Recommendations, brands eager to get started with personalization but have not yet implemented a solution will be a great fit due to how turnkey the setup and integration are. Since we are surfacing personalized product recommendations to users, brands with larger product catalogs (100s+) also are ideal to take advantage of this tool.
[Q5] We are eager to hear your thoughts on the ideas that emerged from the recent AI Hackathon that BigCommerce hosted in partnership with Google?
The AI Hackathon we ran a few months ago with Google was one of the most exciting events I’ve been involved with in my 5 years at BigCommerce. The engagement and excitement from all our participating agencies, our partners at Google, and our Developer Relations team were incredible!
The guidelines were very broad and only required teams to use our new feature to extend the control panel, and App Extensions, and integrate that with Google’s GenAI tools to improve the shopper and/or merchant experience. We were blown away by all the incredible ideas and projects teams were able to build and demo with just 10 days of dev time.
You can read more about the event here:
Unfortunately, I’m not able to share specific project details as many of these are currently in active development to be integrated into the platform as apps, but I can share some of the major themes we saw:
- Data enrichment tools – Enriching store, product, and user data using AI using generated text and/or images
- Data insight tools – Empowering brands to query or automatically pull
- Data automation tools – Pushing enriched/generated data to 3rd party services
If you want to learn about upcoming betas, please join our dev community!
[Q6] Is BigCommerce considering adopting any ideas from the Hackathon to incorporate them into the core features of BigCommerce or collaborating with agencies to launch them as public apps on the marketplace?
A big part of our overarching Open SaaS strategy is the combination of our native features and the infrastructure/APIs we’ve exposed that partners and brands can leverage to customize the platform and implement new features and integrations.
We are pursuing this same approach with AI and are excited to see a number of 3rd party AI solutions begin to be released to the app marketplace at the same time as we begin releasing the native functionality we’ve announced so far.
My team, Partner Solutions Engineering, interacts with our partner ecosystem regularly to provide updates on the roadmap and interact with our product and engineering teams on opportunities to collaborate.
If you’d like to stay up to date with the latest announcements and features around AI and the BigCommerce platform, make sure to join our quarterly town hall webinar
Patrick’s Final Verdict:
Thank you so much to the Folio3 team for the opportunity to talk about our AI strategy and upcoming features. We can’t wait to see how partners and brands leverage GenAI tools with our platform in 2024!
