This week, we posed ourselves a challenge:

To summarise how key ecommerce customer & technology trends like agentic commerce and AI product discovery are going to reshape ecommerce strategy, team structures & the expectations ecommerce business have of employee capabilities and partner skills.

This episode covers our main observations and insights:

• Treat product data as a growth channel.
• Have AI-native product + engineering leadership.
• Run continuous experimentation with agents.
• Properly integrate marketing + data + tech.

Ecommerce is seeing a step change from:

Humans browsing sites, clicking ads & buying products.

To:

Multi-agent systems influencing discovery, comparison and to a lesser extent checkout. More discovery will take place outside the traditional website, and agents & LLMs guide shoppers through decision paths before handover to commerce endpoints (with the website remaining the primary destination).

👉 This creates three major shifts that we explore in more detail:

1. Discovery evolves from SEO → SEO + AEO (Answer Engine Optimisation); visibility depends on machine-readable product data as well as content.
2. AI agents become a new type of shopper, and ecom platforms need API capabilities to facilitate 2-way data and logic flows; agents can compare, filter and decide based on structured data + trust signals.
3. Commerce becomes API-first + autonomous; some purchases happen inside AI ecosystems (chat, assistants, agents) & there’s a need for seamless handoff between AI agents & conventional commerce.

Find out how this is already having an impact on team structures and skill needs.

"Shopify POS is a powerful foundation, but it’s not a turnkey solution for every retail scenario. The platform's maturity is a moving target, and understanding its ecosystem gaps is crucial for strategic planning and preventing costly misalignments."

Joseph Brown, Operations Director, Kubix

Are you considering Shopify POS for your retail operations but unsure about its strengths and limitations?

You're not alone.

As one of the leading ecommerce platforms, Shopify has rapidly expanded into the retail point-of-sale space, but its product is still evolving. In this pod, we explore the realities of implementing Shopify POS backed by expert insights from Joe Brown, Operations Director at Kubix, who has direct experience implementing POS for different business models.

Whether you're running a standalone store or extensive retail estate, this episode has practical advice, product limitations and decisions that can make or break your omnichannel strategy.

The reality…

Shopify POS has become more capable for retail, especially in multistore environments with enhanced permissions and faster workflows. However, it still has capability gaps that can surprise retailers, and requires careful planning, discovery and customisation.

Key discussion points

1. Deep discovery is critical

A recurring theme is the importance of thorough discovery when planning POS projects. Retailers should map existing workflows, identify edge cases (like made-to-order products, custom packing, or complex stock movements) and assess how Shopify’s platform supports or complicates these processes.

Rushing into implementation without understanding detailed workflows can lead to costly rework or operational issues down the line.

2. Inventory management limitations

One of Shopify's gaps is in inventory management for complex use cases. For example, handling stock exchanges between stores where products are unavailable locally remains problematic.

Shopify currently supports split fulfillment orders but lacks native support for multi-quantity line items or real-time transfer workflows, which can frustrate larger or more nuanced operations.

3. Hardware cost & compatibility

POS selection is more than a software decision; hardware investment is foundational. Some issues arise when existing custom integrations, like bespoke receipt printers or scanner setups, are incompatible with new POS hardware or updates.

Testing hardware thoroughly before rollout is essential, and technical teams need to validate network setups, peripherals and existing workflows.

Practical tip: Shopify's recommended hardware kits may not suit every store. Custom hardware may be necessary, but it can add complexity and cost.

4. Ecosystem maturity and functional gaps

While Shopify's ecosystem is growing, certain functionality including multi-currency gift cards, B2B support or advanced inventory tracking, lag behind expectations.

Retailers with complex order workflows may need to integrate third-party apps or custom solutions to fill these gaps.

Chapters

[00:45] Introduction to Shopify POS and Its Evolution

[03:30] Market Positioning and Retail Challenges

[06:40] Discovery Process in Retail POS Implementations

[09:25] Hardware Considerations for Shopify POS

[12:20] Custom Development Needs in Retail

[15:10] Omnichannel Experience and Customer Journey

[17:55] Integration Challenges with Legacy Systems

[20:50] Inventory Management and Workflow Complexities

[23:15] Future Improvements and Wish List for Shopify POS

“In just an hour, I built a UI to interrogate my data, and it handled most of the heavy lifting for a client project."

Chris Marshall, Director & Co-founder, OnState.

Optimising Ecommerce Data with AI: Real-World Applications

Yes, we talk about AI a lot on the podcast. It's inevitable, AI is weaving its way into so many ecommerce processes and tasks.

This episode is highly practical.

We cover real-world examples of how AI tools are being used to speed-up product data tasks whilst reducing the need to rely on expensive licences for specialist tools.

Summary

Ecommerce businesses are increasingly turning to AI to enhance their data management processes. The pod explores how AI tools are being used to clean, enrich, and structure product data, providing real-world examples that highlight their practical applications.

The Build vs. Buy Dilemma Is Being Reframed

Businesses often face the decision of whether to build custom solutions or purchase existing platforms.

In the context of AI for product data, building allows for tailored solutions using tools like Google Sheets and AI models such as ChatGPT for tasks including data transformation and HTML cleaning.

On the other hand, buying involves using specialized AI-enabled tools or outsourcing, which can save time but may incur higher costs.

Practical AI Strategies Discussed:

1. DIY data cleaning: AI models can automate data cleaning tasks, such as reformatting unstructured HTML and standardising attributes, saving significant manual effort.
2. Automating data structure: AI can analyse complex datasets, infer attribute types, and suggest categorisation rules, streamlining the setup of dynamic product groups.
3. Hybrid approaches: combining DIY methods with outsourcing can optimise resources, allowing businesses to handle unique projects efficiently.

Tune in to hear how AI is transforming data migration and management by automating previously manual tasks, increasing speed and allowing for continuous learning.

Chapters

[00:30] The Build vs. Buy Debate in AI Data Management

[03:20] AI in Data Migration: Practical Use Cases

[06:15] Transforming Data with AI Tools

[09:20] The Role of AI in Content Management

[12:20] Engaging with Data Structures

[15:00] Building Custom AI Tools for Specific Needs

[17:45] Tactical Middleware: A New Approach

[20:35] Speeding Up Data Transformation Processes

[23:20] Validating AI Outputs and Managing Expectations

[26:15] The Future of AI in Ecommerce Data Management

"It's not just about selling more; it's about selling smarter and more sustainably."

Oscar Rundqvist, CEO, eComID.

Summary:

High return rates are a significant challenge in fashion ecommerce, leading to financial losses and environmental harm. This podcast explores how innovative technology like eComID is helping the industry by reducing returns, personalising customer experiences and promoting sustainability.

The problem...

Returns are costly; retailers face expenses from shipping, inspecting and repackaging returned items. Additionally, unsellable returns often end up in landfills, contributing to environmental damage. It's estimated that returns cost retailers between $21 to $46 per item, highlighting the need for effective strategies to minimise them.

Change is needed

Retailers need better metrics to understand customer behaviour.

Traditional metrics like average order value (AOV) can be misleading. Instead, brands should focus on "kept order value," which reflects the revenue retained after returns. This shift in focus can lead to more accurate assessments of profitability and customer loyalty.

Emerging solutions like eCom ID offer innovative ways to tackle return issues. By creating a digital shopping passport, eComID stores individual preferences related to size, style and fit. This enables precise pre-purchase guidance and personalised size recommendations, reducing the likelihood of returns.

Data from post-purchase behaviour and return reason codes are invaluable for improving size accuracy and product fit. Brands like H&M have learned that systemic issues, such as inconsistent sizing, drive return rates. By incentivising detailed feedback, brands can refine their offerings and policies.

Innovative brands are experimenting with personalised return fees based on shopper history. This approach encourages mindful purchasing and supports sustainability by reducing unnecessary returns.

Reducing returns is not just about cutting costs; it's a step toward a more sustainable fashion industry. By utilising personalised, data-driven tools, brands can enhance customer experiences and build lasting loyalty.

Chapters:

[00:30] Introduction to Tech and Sustainability in Fashion

[02:40] Understanding eCom ID and Its Solutions

[07:10] Insights from H&M: The Returns Challenge

[12:45] Data Accuracy in Returns Management

[15:35] The Role of Size and Fit in E-commerce

[20:20] Measuring Success: Average Kept Order Value

[24:15] The Environmental Impact of Returns

[29:50] Future of Ecommerce: Agentic Commerce and Virtual Try-Ons

Why did we think this was an interesting episode?

Paul & James are regularly involved in ecommerce redesign projects, either in an advisory capacity or helping drive the design thinking.

This episode explores the reasons why brands decide to invest in a redesign:

• Brand refresh or a full rebrand.
• Brand elevation of the online UX e.g. premium positioning.
• Improved user journeys to fix legacy constraints.
• Outcome focused e.g. fix navigation and browse journeys.

It then teases out the justifications for redesign projects, sharing views on how design can and should be measured objectively.

James & Paul also dissect the intangible goal of many design projects: to elevate the brand positioning, to create a premium look & feel.

Goals like this need clear definition and framing to ensure the design outputs work towards a clear vision and execution. They also need tangible measurements of success, even if they're not conversion focused.

The key take-away is that design has to be measured, and the metrics you use need to be agreed upfront. If there are no hard & fast commercial success metrics like conversion and AOV, then take a sensible approach to measuring customer impact, for example customer satisfaction & NPS.

Chapters:

[00:30] Introduction to Redesign Metrics

[03:40] Understanding Brand Elevation

[06:10] Balancing Design and Ecommerce

[09:00] Defining a Premium Experience

[12:30] Measuring Redesign Success

[15:25] The Role of User Testing

[18:15] Navigating Redesign Challenges

[21:10] The Importance of KPIs

[22:46] Final Thoughts on Redesigns

"No-code is getting a lot better, and there's a lot of tools. No-code tools will soon start to drive personalisation and dynamic content. That's going to take off pretty quickly."

Navigating Ecommerce Technology Trends.

In the latest episode of our podcast, James and Paul share their views on how emerging technologies are reshaping the industry. From AI-driven content generation to dynamic personalisation and integrated loyalty programs, this episode offers helpful insights for anyone working in ecommerce.

What you'll get:

• How the latest ecommerce trends are impacting which technologies ecommerce teams are investing in.
• Practical advice for adapting your tech stack to leverage AI and personalisation for better customer experiences.
• The challenges and opportunities in delivering smarter CRM and loyalty strategies.
• Explanation of the vendors ecommerce teams are turning to to help improve their ability to execute.

Chapters:

[00:30] Emerging Ecommerce Trends and Tech Priorities

[03:30] AI in Content Generation and Product Data Management

[06:00] AI Governance and Data Compliance

[08:50] Dynamic Content and Personalisation in Ecommerce

[12:20] The Evolution of CRM and Loyalty Programs

[25:00] Data Analytics and Marketing Tracking Accuracy

Understanding these trends can help you make informed decisions on where to focus your budget and how to enhance your CX.

We hope you find it useful.

You're probably using customer reviews on your website but are you using them effectively?

Customer reviews are more than just feedback; they're a powerful tool for building trust and driving sales. In this episode, we delve into the current landscape for online customer reviews, exploring how retailers can leverage review data, avoid common pitfalls and utilise cutting-edge technology.

What you'll get:

Leverage review data -

Discover how to transform customer feedback into actionable insights that can improve product offerings and enhance customer satisfaction.

Avoid common mistakes -

Understand the impact of fake reviews and learn strategies to combat them. We discuss the importance of monitoring review patterns and collaborating with vendors to ensure authenticity and trustworthiness.

Embrace technology -

Explore the role of AI in review management. From sentiment analysis to review segmentation, find out how technology can provide deeper insights and drive business improvements.

Chapters:

[00:30] The Importance of Customer Reviews

[05:25] Navigating Fake Reviews and Trust Issues

[12:20] Leveraging AI for Review Insights

[18:20] The Rise of Video Reviews

[23:45] Unboxing and User-Generated Content

[27:00] Managing Negative Reviews Effectively

[33:35] Choosing the Right Review Technology

[38:25] The Trustpilot Debate

"AI is enabling us to deliver more sophisticated and seamless payment experiences, allowing consumers to shop in a more frictionless way. However, it also presents challenges, such as combating AI-powered fraud, which requires us to continuously innovate and adapt our solutions."

Global Payment Trends & How Agentic AI Could Redefine Online Shopping and Payment Acceptance.

In this episode, we cover emerging payment trends in ecommerce and the role of AI in enhancing payment security and preventing fraud. Understanding these trends is crucial for merchants aiming to optimise payment authorisation and secure transactions.

Our guest is Ed Harries, VP Ecommerce Global SMB for market leader Worldpay. Ed brings a wealth of experience having being on the leadership team of leading ecommerce agency Visualsoft before joining Worldpay to lead their SMB solution.

What you'll get from this podcast:

• Equip yourself with knowledge about emerging trends and technologies that will shape the future of ecommerce payments.
• Keep up with the latest developments in AI and payment security, ensuring your business remains competitive.
• Learn practical strategies to protect against fraud.
• Understand how to build trust with your customers, leading to increased loyalty and sales.

Key discussion points:

• AI's Role in Fraud Prevention: how AI technologies are being leveraged to detect and prevent fraudulent activities, ensuring safer transactions for merchants and consumers.
• Enhancing Payment Authorisation: learn about the latest advancements that are improving payment authorisation processes, reducing declines and increasing approval rates.
• Consumer Trust and Security: how payment solutions are building consumer trust by providing secure and seamless buying experiences.
• Future Trends: insights into future trends in payment security, including the integration of AI with other technologies to create more robust security frameworks.

Chapters:

[00:30] Introduction to Ecommerce Payment Trends

[04:15] Current Trends in the Payments Landscape

[06:40] Regional Payment Patterns and Consumer Behaviour

[08:30] The Role of AI and Agentic Commerce

[11:55] Balancing Fraud Prevention and Acceptance Rates

[18:15] The State of Open Banking in Retail

[23:45] Marketplace Commerce and Payment Challenges

[28:20] Worldpay's Technological Direction and Innovations