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At The Founder, we aim to uncover the transformative ideas shaping industries worldwide. Today, we’re thrilled to explore how artificial intelligence is reshaping the e-commerce landscape with Simon Yencken, CEO and co-founder of Fanplayr. Since its inception in 2012, Fanplayr has been a pioneer in behavioral data-driven e-commerce optimization, empowering businesses to deliver tailored experiences and enhance customer journeys.
With a global footprint and cutting-edge innovations, Simon and his team have positioned Fanplayr as a leader in AI-driven personalization. In this interview, Simon shares his vision for the future of e-commerce, insights into AI advancements, and strategies for creating privacy-conscious, personalized customer experiences.
Fanplayr has been at the forefront of e-commerce optimization since 2012. What inspired the founding of Fanplayr, and how has its journey evolved over the years?
The Fanplayr Founders had all previously worked in FinTech in building and deploying market data systems and financial markets trading systems. We believed when we founded the company that traditional B2C commerce would increasingly move online, and that the most efficient markets would be driven by real time systems delivering optimised and personalized experiences, backed up by economically driven analytics and insights. We believed that the experiences gained in the financial trading markets would become very relevant to online B2C commerce. Hence, that was why we founded the company.
How is AI-driven personalization transforming online shopping experiences for customers and businesses?
The increasing use of AI in personalization is one step in the journey of optimizing online ecommerce experiences from the end user perspective, together with improving the economic performance of such platforms from a business standpoint.
It has been understood for some time that increased user engagement online leads to better business performance. It has been said that ‘online consumers have the attention span of a goldfish’, meaning that people easily get distracted for reasons such as: if they can’t find what they are looking for, the prices seem too high, shipping is too expensive or too difficult, if the payment process is cumbersome, etc.
Accordingly, the first push, at the time we founded our company, was to enable online personalization in ecommerce by tailoring the shopping experience to individual customers based on their preferences and past behavior, leading to increased engagement. It was found that this increased user engagement in turn leads to higher conversion rates, improved customer satisfaction, and ultimately, greater sales and customer loyalty.
Several years ago Fanplayr and other vendors started to use AI to provide the most relevant product recommendations for individual customers. We have found that the use of AI models such as ‘recommended for you’ and ‘others you may like’ significantly increases user engagement and revenue for our brands and other businesses. The feedback from consumers has also been very positive as these AI recommendations typically provide relevant personalized recommendations which are helpful and engaging.
The use of AI in eCommerce is currently being extended to encompass functionality such as chat bots and virtual assistants, search, dynamic pricing and customized content.
Recently Fanplayr launched an industry wide first in eCommerce which we call “Personal Shopper”. This functionality enables our clients to add an AI driven personal shopper for all their individual online consumers. Our vision and foresight with this ground breaking AI initiative has brought the old world in store experience of a personal shopper - previously reserved for very few high end consumers - to the mass market of all online consumers. This is a significant new development in the world of AI powered commerce.
Q. What challenges do companies face when implementing AI for personalization, and how does Fanplayr address them?
It is important to have a detailed implementation plan for AI technology that is adapted and relevant to the customers' businesses. I will therefore answer this question by using the area of AI based product recommendations as an example.
There are 4 common AI models used in product recommendations, namely: ‘others you may like’, ‘recommended for you’, ‘frequently bought together’ and ‘recently viewed’.
Challenges in implementing these to be overcome include:
- The time taken to train the models
- The cost of running the AI technology, and the frequency of updates of the data
- The need to have up to date product catalogues
- The need for dynamic relevant displays of the most appropriate recommendations to each consumer in real time
When Fanplayr first launched AI product recommendations several years ago, we initially relied on Google AI Services for the AI engine. We found that the time taken to train the models was relatively long, and the external cost was very high.
Accordingly, we developed our own AI technology called ‘Verada AI’. Verada AI is considerably cheaper, faster and in many cases produces materially better results than using the external service.
In order to provide the most effective product recommendations it is highly desirable to have the recommendations synched, in as near real-time as possible, with the business’ product catalogue. We normally recommend automating this process thus ensuring that the catalogue is updated daily. A further Fanplayr refinement of this process is what we call the ‘colour chip’ technology: this ensures that the recommendations show the product item colours and sizes that are in-stock and available. Again this technology has been shown to increase end user satisfaction and engagement, along with our customers’ revenue.
Finally, a dynamic effective real time display of the AI recommendations is most important. Our technology understands where and how the dynamic recommendations widgets should be placed on a page, to optimize engagement while taking care not to degrade page load speed.
The Fanplayr WYSIWYG creative editor is a key self service and flexible design tool to allow creation of the latest in display designs, without the need for front end coding. Equally the Fanplayr real-time infrastructure (built with the market data heritage) ensures the real-time delivery of the most personalized AI recommendations to all users, and is light years ahead of competitors who use so called ‘micro batching’.
In an era where consumer privacy is a major concern, how does Fanplayr strike a balance between leveraging customer data and protecting privacy?
Fanplayr has recently been granted global patents for its ground breaking PrivacyID service:
FanplayrⓇ is pleased to announce the issuance of patents in the United States and Hong Kong and pendency of applications in Europe, Australia, Japan and the United States for its innovative PrivacyIDTM solution, developed to enhance user identification while ensuring the protection of privacy across web servers. Across two families, Fanplayr® currently holds more than a dozen patents in six countries and the European Union.
PrivacyID’s groundbreaking technology features a novel software design that enables websites to reliably identify both new and returning users without relying on third-party cookies or client-side technologies that are increasingly restricted by browsers. Additionally, it ensures consistent identification across multiple third-party services on a website, eliminating the need for server-side integration, preserving user privacy, and avoiding cross-site tracking.
“As global privacy regulations such as GDPR, CCPA, and increasing browser restrictions on user behavior tracking continue to evolve, Fanplayr’s patented technology offers a compliant solution that meets these challenges head-on,” commented Simon Yencken, CEO and Co-founder of Fanplayr. “This breakthrough will empower websites to identify users while adhering to stringent privacy standards.”
Fanplayr Inc. has already begun piloting its commercially branded "PrivacyID" technology with select customers, assisting them in delivering consistent and compliant user identification. The company is planning a broader rollout for websites that rely on user identification to deliver their services, providing a future-proof solution that aligns with current and forthcoming privacy regulations.
In addition, Fanplayr has recently developed an optional enhanced privacy feature called ‘Transient Sessions’ that allows customers to use the full power of personalization, but then to expire the ‘transient sessions’ within a defined period, for even greater privacy protection.
Predictive algorithms play a critical role in e-commerce. Can you explain the science behind AI merchandising and its impact on user engagement and sales?
See discussion above under questions 2 & 3 above.
How does Fanplayr ensure that its recommendations remain relevant and unbiased?
See discussion above under questions 2 & 3 above. Plus:
- Use of the latest product catalogues, automatically updated daily
- Fanplayr real-time infrastructure
- Fanplayr’s Verada AI technology has been crafted to operate on an unbiased basis
Small and medium-sized enterprises often lack resources compared to retail giants. How does Fanplayr empower SMEs to remain competitive? Can you share a success story where AI helped an SME achieve remarkable growth?
This is a very good question. Most competitive services addressed to the SME market are simplistic widget companies which provide almost no intelligence, segmentation or analytics, along with zero customer service.
Fanplayr has recently partnered with Italiaonline in Italy which is the country’s leading internet based services company with a huge installed base of SME customers. Fanplayr and Italiaonline plan to roll out a cost effective self service version of the Fanplayr platform broadly to the SME market in Italy. Based on feedback from that market rollout we would intend to extend the offering more broadly to other countries, such as the US.
With the decline of third-party cookies, how can businesses create cohesive cross-channel experiences in the post-cookie era?
See answer above relating to Fanplayr’s patented service, PrivacyID: https://privacyid.ai/
As a CEO, how do you foster innovation within your organization to stay ahead in the competitive e-commerce industry?
At Fanplayr we encourage innovation in the product and engineering teams. In addition, we receive a string of innovation and new product development requests from our customers. These are carefully evaluated and where appropriate rolled into our product roadmap.
In prior companies we have used a patent incentive program to encourage employees to come forward with new patentable inventions, and this is something that we may implement at Fanplayr in the future.
