The Digital Deep Dive With Aaron Conant

JD Sass is the Co-founder and CEO of Axiom Return Solutions, a reverse logistics company helping Amazon sellers and brands recover value from returns. He leads solutions for returns management, inventory inspection, reimbursement claims, product reintroduction, and resale, supported by Axiom's custom returns software. With deep expertise in Amazon reverse logistics, JD helps brands reduce losses, uncover return trends, improve profitability, and make smarter post-purchase decisions across the supply chain.

For Amazon sellers, returns can directly impact profitability, inventory recovery, and operational efficiency. They can also reveal useful insights about product quality, packaging, and listings. So how can brands build a smarter returns strategy that protects margin?

The opportunity starts with treating returns as a source of operational data rather than simply a cost center. JD Sass, an expert in Amazon reverse logistics and returns management, explains how brands can recover more value by inspecting returned inventory, identifying products that can be reintegrated, and analyzing return patterns to improve packaging and product listings. JD also highlights the costs and complexity of managing returns in-house, from staffing and warehouse space to tracking, grading, and reimbursement claims. A structured, data-driven approach can help sellers reduce waste, recover inventory, and make more informed profitability decisions.

In this episode of The Digital Deep Dive, Aaron Conant talks with JD Sass, Co-founder and CEO of Axiom Return Solutions, about improving Amazon returns management and reverse logistics. JD explores how brands can recover inventory, use returns data to improve operations, and determine when outsourcing makes sense. He also touches on profitability, product grading, reimbursement claims, and testing a returns solution.

Hannah Blackburn is the Co-founder and Director of The Hawker's Club, an eCommerce consultancy that helps brands navigate marketplace challenges, recover lost revenue, and improve profitability across Amazon and other platforms. In her role, Hannah advises sellers and vendors on Vendor Central, chargeback recovery, and marketplace operations. Before co-founding The Hawker's Club, she worked at Amazon in vendor operations, including in-stock management and profitability. She specializes in helping brands understand and optimize complex eCommerce systems.

Managing Amazon chargebacks has become a growing challenge for brands as marketplace processes evolve and profitability remains a priority. Vendors need the right systems and strategies to understand charges, respond effectively, and protect their margins. So how can brands navigate Amazon's evolving chargeback landscape?

The key is creating a proactive process to understand, manage, and recover from chargebacks before they impact profitability. Hannah Blackburn, an expert in Amazon vendor operations and chargeback recovery, explains how brands can identify opportunities, strengthen dispute strategies, and build processes that protect margins. Hannah emphasizes the importance of using accurate data, submitting strong evidence, and addressing operational issues at their source to improve long-term performance. With the right approach, chargeback management can become a more effective part of a brand's marketplace strategy.

In this episode of The Digital Deep Dive, Aaron Conant chats with Hannah Blackburn, Co-founder and Director of The Hawker's Club, about updates to Amazon's chargeback process. Hannah discusses chargeback trends, dispute strategies, reporting challenges, and ways brands can recover lost revenue. She also shares insights into preventing future issues through stronger processes and better operational visibility.

Navi Singh is the Co-founder and CEO of Sohva, a full-service TikTok Shop agency helping consumer brands grow through social commerce. With experience across influencer marketing, affiliate programs, and eCommerce, she leads the agency's strategy and growth. Her expertise spans creator activation, affiliate marketing, live selling, and TikTok Shop performance. Before launching Sohva, Navi's background with global brands and growth-stage companies gave her a brand-side perspective on building scalable, revenue-focused programs.

TikTok Shop is giving brands new ways to connect content, creators, and commerce in one platform. But success takes more than simply opening a storefront. How can brands build a TikTok Shop strategy that drives both revenue and brand growth?

TikTok Shop expert Navi Singh explains that the strongest strategies combine organic content, affiliate marketing, and consistent creator activation rather than relying on a single tactic. Brands should focus on building content volume, sampling products to the right creators, and understanding that profitability may take time as the channel develops. Navi also highlights the platform's halo effect, where TikTok activity can influence sales across DTC, Amazon, and other retail channels. By prioritizing speed, creator relationships, and realistic channel economics, brands can approach TikTok Shop as a long-term growth engine rather than a short-term experiment.

In this episode of The Digital Deep Dive, Aaron Conant talks with Navi Singh, Co-founder and CEO of Sohva, about how brands are leveraging TikTok Shop for social commerce growth. Navi explores organic content, affiliate strategies, and creator-driven sales. She also covers fulfillment, the TikTok halo effect, and common mistakes brands make when scaling on the platform.

Aviv Frenkel is the Co-founder and CEO of Shuttlebase, formerly Moonshot AI, an AI-powered platform that autonomously optimizes eCommerce websites for conversion. Drawing on his experience running an eCommerce website, Aviv leads the company's efforts to remove guesswork from CRO by identifying friction, generating test ideas, launching experiments, and deploying winning variants. His expertise spans AI-driven experimentation, conversion optimization, customer behavior, and eCommerce growth.

Conversion rate optimization has long required significant time, resources, and coordination across teams. As acquisition costs rise and customer journeys become more complex, how can brands use AI to make CRO faster and more effective?

AI can automate much of the testing process while helping brands uncover the customer behaviors behind conversion gains. Aviv Frenkel, an expert in AI-driven experimentation and eCommerce conversion optimization, explains how autonomous CRO can identify friction, generate hypotheses, launch tests, and apply best-performing changes with far less manual effort. Aviv also highlights the importance of having enough traffic to support meaningful experimentation and using test results to learn what shoppers value, where they hesitate, and which messages build trust. The goal is not simply to run more tests, but to create a smarter, faster feedback loop that improves both the customer experience and revenue.

In this episode of The Digital Deep Dive, Aaron Conant talks with Aviv Frenkel, Co-founder and CEO of Shuttlebase, about how AI is replacing the guesswork in conversion rate optimization. Aviv explores autonomous CRO, faster experimentation, and turning website data into revenue growth. He also touches on customer insights, Q4 optimization, and the evolution from Moonshot AI to Shuttlebase.

Lucas Tieleman is the Co-founder and CEO of Optiversal, an AI-powered eCommerce platform helping retailers improve product discoverability and conversion through richer product data and dynamically generated content. Previously Chief Product Officer at Bazaarvoice and a serial entrepreneur, Lucas brings deep expertise in eCommerce, AI search, product strategy, and digital shopping experiences. He also represented Optiversal in winning the Judges' Choice award at Shoptalk 2024, which included an optional £100,000 investment from Commerce Ventures.

As consumers shift from short keyword searches to conversational queries, product catalogs need to evolve with them. Basic attributes and product descriptions often miss the context and language shoppers now bring to Google and LLM-powered search. So what does a product catalog need to look like to stay discoverable?

According to eCommerce and AI search expert Lucas Tieleman, brands need richer, more structured product data that reflects how consumers actually describe and search for products. That means filling catalog gaps, adding natural-language attributes, optimizing product feeds for Google and OpenAI, and creating relevant landing pages around specific shopper intent. Lucas also highlights how AI can analyze reviews, images, search trends, and catalog data to continuously improve product information at scale. The goal is not simply more content, but better signals that help search engines and LLMs connect the right products with the right queries.

In this episode of The Digital Deep Dive, Aaron Conant talks with Lucas Tieleman, Co-founder and CEO of Optiversal, about the new product catalog requirements for LLMs. Lucas explains how natural-language search is reshaping product data, why optimized feeds matter for AI visibility, and how automated landing pages can improve discoverability and conversion. He also touches on AI-driven catalog enrichment and self-maintaining eCommerce experiences.

Jonny Waite is the Co-founder and CEO of RECHO, a full-service Reddit marketing agency helping brands grow through organic community management, paid advertising, and Reddit-native strategy. With 17 years of agency-side digital experience, Jonny built SEO, paid search, Amazon, and omnichannel programs for Fortune 500 companies and high-growth startups. He helps brands navigate Reddit authentically, manage reputation, and improve visibility across search and AI-driven discovery.

As AI-driven search changes how consumers discover products, brand-owned content is no longer the only influence on buying decisions. More people are turning to online communities for candid perspectives that validate what they find elsewhere. How can brands build trust when those conversations are already happening beyond their control?

Reddit marketing and digital search expert Jonny Waite explains that brands can earn credibility by participating in communities authentically instead of relying on overt promotion. Success starts with listening to how users communicate, respecting community norms, and contributing expertise where it genuinely adds value. Jonny emphasizes the benefit of pairing organic engagement with targeted advertising while recognizing Reddit's long-term search impact, since indexed conversations can influence discovery and purchase decisions for years. A thoughtful Reddit strategy can strengthen trust, improve visibility, and create a lasting advantage across both search and AI-driven discovery.

In this episode of The Digital Deep Dive, Aaron Conant welcomes back Jonny Waite, Co-founder and CEO of RECHO, to build on an earlier discussion about Reddit's rising importance and examine why every brand needs a Reddit strategy. Jonny covers AI search, community trust, and advertising opportunities. He also shares how authentic participation can create long-term brand value.

Rohan Philip is the Product and Strategy Lead at MetricsCart, a digital commerce intelligence platform that helps brands monitor and improve performance across online retailers and marketplaces. In his role, he shapes product strategy around pricing, availability, content health, search visibility, ratings, and reviews, translating complex shelf data into practical actions for brands. Rohan specializes in holistic digital shelf management, review intelligence, automation, and the emerging impact of AI-powered shopping.

The digital shelf is shaped by far more than product titles and images. Pricing, availability, reviews, search visibility, and advertising all affect conversion. How can brands manage these interconnected signals without overextending their teams?

Rohan Philip, an expert in product strategy and digital shelf intelligence, recommends treating every performance signal as part of one system. Brands should prioritize the retailers driving the most revenue, automate monitoring across secondary channels, and use reviews to uncover product issues, improve marketing language, and guide development. Rohan stresses that pricing, content health, ratings, availability, and search performance must be evaluated together, especially as AI agents reshape discovery and purchasing. A coordinated, insight-led approach helps teams protect profitability while preparing for a more automated shopping journey.

In this episode of The Digital Deep Dive, Aaron Conant talks with Rohan Philip, Product and Strategy Lead at MetricsCart, about taking a holistic view of the digital shelf. Rohan explains how to prioritize top retailers, connect pricing and content signals, and turn reviews into actionable insights. He also examines automation, AI shopping agents, and the future of product discovery.

Lauren Livak Gilbert is the Executive Director of the Digital Shelf Institute, a community of more than 11,000 brands and retailers navigating eCommerce and the digital shelf. She leads research, education, and industry collaboration on emerging commerce trends. Lauren specializes in agentic commerce, product content, citations, measurement, and helping brands turn complex digital shifts into practical strategies that drive customer acquisition and growth.

Max Sinclair is the Founder and CEO of Azoma (formerly Ecomtent), an agentic commerce platform helping brands improve visibility and performance across AI-powered shopping. He leads company strategy, growth, and enterprise partnerships while advising brands on product discovery, content, and conversion across ChatGPT, Amazon Rufus, Walmart Sparky, and Google Gemini. Max also co-hosts The New Frontier: The Agentic Commerce & Answer Engine Optimization podcast.

Agentic commerce is becoming a priority for brands, but many teams are still defining how it fits into their eCommerce strategies. Rather than replacing the digital shelf, it expands how AI systems discover, evaluate, and recommend products. How can brands turn this shift into measurable growth?

Digital shelf strategist Lauren Livak Gilbert and agentic commerce entrepreneur Max Sinclair answer by organizing the challenge around five C's: completeness, context, citations, correctness, and customer acquisition. Their framework shows brands how to strengthen product data, answer detailed shopper questions, build trust through credible sources, and correct inaccurate information across AI platforms. Lauren recommends treating agentic commerce as an extension of existing digital shelf work while developing a deeper understanding of shopper needs. Max emphasizes monitoring the entire category, identifying the sources AI tools rely on, and connecting visibility efforts to conversion and incremental revenue. Together, their guidance offers a practical way to prepare internal teams, prioritize investments, and measure meaningful business impact.

In this episode of The Digital Deep Dive, Aaron Conant talks with Lauren Livak Gilbert, Executive Director of the Digital Shelf Institute, and Max Sinclair, Founder and CEO of Azoma, about decoding agentic commerce through the five C's. Lauren and Max show how brands can improve data completeness, add richer context, strengthen citations, ensure correctness, and drive customer acquisition. They also discuss AI shopping behavior, brand accuracy, and practical measurement.

Christian Rich is the Founding US Sales Lead at Azoma, an agentic commerce optimization platform that helps brands improve visibility across AI-powered search and shopping experiences. Working with consumer brands, he focuses on how product content is discovered, interpreted, and recommended by ChatGPT, Amazon Alexa, Walmart Sparky, and other AI assistants. Christian specializes in digital shelf strategy, conversational search, content structuring, and LLM-driven product discovery and conversion.

Amazon's shorter title limit reflects a broader change in how consumers discover and evaluate products online. As mobile shopping, conversational prompts, and AI assistants reshape search, brands must create content that works for both people and algorithms. How can they adapt without sacrificing visibility or conversion?

The answer is to treat concise titles as part of a wider shift toward prompt-based, agent-assisted shopping, according to Christian Rich, an expert in agentic commerce and digital shelf strategy. Brands should write clear, human-friendly titles, move valuable keywords and product details into structured content, and identify the category questions AI tools are prompting shoppers to ask. Christian also recommends making product pages specific enough for assistants to confidently match products with detailed consumer requests. By connecting marketplace content with broader AI-discovery strategies, brands can improve their chances of being surfaced, recommended, and selected.

In this episode of The Digital Deep Dive, Aaron Conant talks with Christian Rich, Founding US Sales Lead at Azoma, about Amazon's new 75-character title limit and the rise of AI-assisted shopping. Christian explores cleaner titles, structured item highlights, and prompt-ready product content. He also examines Alexa-driven discovery and the connection between retailer pages and ChatGPT visibility.

Kevin Williams is the Founder and CEO of Ascend AI Labs, an AI enablement firm that helps organizations build AI literacy, governance, and implementation strategies. A serial entrepreneur with roots in DTC brand building and digital marketing, Kevin helps companies align leadership, improve workflows, and implement practical AI strategies. His expertise spans enterprise AI adoption, governance, agentic workflows, and transformation for brands. Kevin is also the President of KDF Aegis LLC, a consulting and private equity firm.

Many brands are racing to adopt AI, but the biggest barrier may not be the technology itself. Before teams can improve workflows or build automation, leaders need to define what AI means for the organization. So where should companies begin when the pressure to move fast collides with uncertainty and unclear direction?

As an AI adoption and digital transformation expert, Kevin Williams argues that AI strategy has to start with leadership before data, tools, or technical infrastructure. His approach is to create alignment at the top through a clear AI manifesto, practical governance, and a shared roadmap that helps teams understand how AI will support the business. Rather than waiting for perfect data, Kevin recommends building literacy, giving employees the right connected tools, and identifying high-value workflows where AI can reduce friction. The strongest AI strategies come from the leaders who combine vision, communication, and practical execution.

In this episode of The Digital Deep Dive, Aaron Conant talks with Kevin Williams, Founder and CEO of Ascend AI Labs, about why AI strategy starts in the C-suite, not in the cloud. Kevin shares how leadership maturity, AI manifestos, and connected workflows shape adoption. He also touches on agentic automation, implementation costs, cybersecurity risks, and why context makes AI tools more valuable.