Dialogue: How Can Globalizing Companies Build a Cross-Market Adaptable Brand Creative System?

[Ebrun Original] On September 17, at the first themed forum of the "Accelerate26 Cross-Border Ecosystem Acceleration Conference · China Station" hosted by Pattern with Ebrun as its strategic partner, David Quaife, Managing Director of Pattern Middle East, and Jeffrey Dong Hongwei, Operations Director of AZDOME, delivered a session titled *Building a Cross-Market Adaptable Brand Creative System: Packaging, Creativity, and Brand Experience*, followed by a dialogue moderated by Ryan Barton, Director of International Business Growth at Pattern.

David Quaife noted that many brands assume their core challenge lies in conversion, but the problem often starts much earlier with brand perception. Product functionality, on-page messaging, visual language, and localized communication collectively shape consumer trust, and trust is the prerequisite for conversion. For this reason, a creative system cannot stop at producing more images or listing more product specs. Instead, it must start with consumer data to identify target audiences, their purchase motivations, and their top priorities, then address these needs with consistent, accurate brand messaging.

Citing operational data from AZDOME’s partnership with Pattern, Dong Hongwei demonstrated how this system translates into tangible business results: From February to August 2026, the brand’s return on ad spend (ROAS) rose from 1.1 to 3.16; after updating product imagery for its M550 model, the conversion rate climbed from 2.9% to 3.17%. In his view, truly valuable partnerships are not about short-term inventory clearance or sales spikes, but about gradually transforming platform operations that once relied on individual experience into predictable, replicable professional capabilities.

(This article is compiled from on-site speeches and dialogues, with minor edits made without altering the original intent.)

Below is the full transcript of the session and dialogue:

01 Brand Precedes Conversion: Consumers Buy More Than a Product — They Evaluate Trustworthiness

David Quaife: Today I want to discuss how to build a cross-market adaptable brand creative system, particularly how Chinese brands can leverage tailored creativity to drive stronger sales in international markets. This is not merely an issue of creative assets and materials, but a broader, revenue-generating methodology. At the end of the day, everything ties back to revenue growth.

E-commerce revenue can be broken down into components including traffic, conversion rate, pricing, and inventory supply; only the combined performance of these factors delivers stronger ROI. Higher traffic can lift potential revenue, but it also increases traffic acquisition costs; in some cases, brands can also improve returns through pricing strategies.

Many brands assume their biggest pain point is conversion itself, but the problem often lies much earlier in brand perception. Brand perception encompasses everything consumers encounter when they interact with a product. For Chinese and non-Chinese brands alike, no matter how strong a product’s features or value are, consumers will always take time before purchasing to ask: Do I recognize this? Do I understand what it offers? Can I trust this brand? Only when trust is built can conversions happen and revenue grow.

Perceptions can be positive or negative. Negative perceptions erode trust and drag down conversion rates, while positive perceptions help build a stronger brand identity, which in turn boosts consumer trust and conversions. That is why brands must first answer a core question: Do consumers have positive or negative perceptions of our brand?

When Chinese brands enter markets such as the U.S. and Europe, several recurring issues emerge.

First, the lack of a unified visual system. Brands may produce large volumes of imagery and content, but without clear connections between content pieces and consistent visual presentation, consumers will quickly develop distrust.

Second, information overload. Many products have strong functionality and long lists of specs, and brands often want to share every single detail with consumers. But Western consumers may not understand overly technical specifications. Too much information paired with cluttered page layouts leaves users confused about why they should buy, and may even drive them to exit the page immediately. What brands really need to do is distill the most meaningful, priority information from all those specs.

Third, inaccurate localized communication. When launching in a new market, errors in copy, grammar, or even spelling erode trust. Relying solely on technical specs also makes it hard to build trust, because consumers will not read, understand, or believe every piece of content on a page.

So our focus is not on blindly piling specs, data, and parameters onto product pages, but on how products land in specific markets. For example, when launching a product in Italy, you need to research what local consumers prefer, their aesthetic tastes and preferences. Brands should conduct this kind of assessment for every market they enter.

02 Data Guides Creative Direction, But Consistency, Emotion, and Proof Build Trust

David Quaife: Data is the foundation that informs content and creative decisions. We analyze product engines to track how consumers search, click, and purchase on platforms including JD.com and Amazon; we study search engines like Google to map where consumers enter and exit during their shopping journey; we analyze social platforms to see what content audiences engage with, and what creates emotional connection and resonance. Today, large language models are receiving unprecedented attention. We also need to study what AI models such as ChatGPT and Claude mean for the industry, and how consumers search for and receive recommendations based on their needs and interests.

Digital shelf research is also built on massive volumes of data, but the key is not how much data you have, but what questions that data can answer. The question we want to answer is: Why are consumers buying competing products instead of yours? After data is collected, it must be tagged and categorized, otherwise the data itself is useless. We compare page views, click-through rates, search volumes, and keyword performance between a brand and its competitors to inform digital shelf and bidding strategies. After consumers click, we also analyze their interactions with product detail pages (PDPs), using tools like eye-tracking to observe which sections, positions, and information on the page they actually pay attention to. It is important to emphasize that we focus on what matters to consumers, not what matters to the brand.

Across the entire consumer journey, we analyze search behavior, audience attributes, and product attributes, then categorize and match these insights. Post-purchase ratings and reviews are also extremely valuable: they are direct feedback from consumers that can in turn guide creative strategy.

Based on these insights, we build our strategic framework around three questions: Who are they? Why do they buy? What do they value most? The first question establishes the core audience profile, while the latter two address purchase motivation and core needs respectively. We not only rank product features and consumer needs, but also identify what benefits products deliver, and how consumers form emotional connections with those products.

I believe every decision should be guided by data as much as possible. But if you only focus on data, the messaging delivered to consumers can sometimes feel flat, emotionless, and easily forgettable. That is why we also incorporate human-centric brand analysis: What does the brand stand for? What is its positioning? What problem does the brand and product aim to solve, or what opportunity does it create? Combining data-driven strategy with more emotional, human-centric brand strategy is what truly builds consumer trust.

Brands first need to define their unique value and value proposition, then build their content strategy around that; they also need to provide proof, using product features and advantages to back up their claims, rather than asking consumers to take the brand’s word for it.

We also conduct brand audits from the perspective of Western consumers, reviewing brand-related elements including logos, color palettes, typography, brand names, imagery, and icons. The goal is not to find fault with the brand, but to identify areas for improvement. After completing the audit, brands can develop clearer style guides to ensure logos, fonts, brand names, and visual assets remain consistent across every output. The more consistent a brand’s presence is, the easier it is for consumers to build trust.

AI can significantly speed up asset production, but accuracy remains critical. When AI lacks full context about a product, it will guess at scenes, materials, and details. At first glance, generated images may look nearly identical to the real product; but on closer inspection, fonts, spacing, label angles, bottle materials, and opening and closing mechanisms may be incorrect. Each small edit can trigger additional changes, gradually pulling assets further away from the real product. These discrepancies may seem minor, but they can erode consumer trust. If consumers receive a product that does not match what they saw online, brand reputation suffers.

For that reason, we first shoot real products in our Photo Studio to capture high-resolution images from every angle, then combine those assets with AI to generate visuals for different use scenarios and user-generated content (UGC)-style assets. This approach improves content production efficiency while ensuring the most accurate possible product presentation.

Creative optimization is also not a one-time task. We feed data back into our software and platforms, conduct ongoing brand analysis, and test optimized assets on platforms again to measure whether sales conversions improve. In the ASTI case study shared at the event, after the brand optimized its content and visual presentation, relevant search volume rose by 84%. The core of this methodology is to continuously validate creative work with data, then move into the next round of iteration.

03 From "Talent-Dependent Sales" to Systematic Growth: Creative Optimization Must Form a Replicable Operational Closed Loop

Jeffrey Dong Hongwei: Founded in 2010, AZDOME focuses on the in-vehicle electronics vertical. After 16 years of development, we have expanded globally, with operations covering more than 100 countries and regions, over 200 SKUs, and cumulative sales exceeding 2 million units. We positioned ourselves in the automotive electronics sector from our founding, launched cross-border operations under the AZDOME brand in 2011, and established an R&D center in Shenzhen in 2016 to bring our R&D system fully in-house. Our competitive differentiation stems largely from our capabilities in image processing, video processing, thermal management, and structural design. Beyond functionality, we also invest continuously in product design to build competitiveness in product appearance and consumer appeal — all of which form the foundation of strong ad performance and conversion.

We began our partnership with Pattern in February 2026. By August, our ROAS had risen from 1.1 to 3.16, nearly three times the initial level. For every dollar spent on advertising, we saw a clear improvement in returns. In July in particular, we achieved simultaneous growth in sales volume and efficiency while keeping ad spending under control. We also invested in DSP advertising, which accounts for 6% of our total ad spend.

On-site data shows that in the seven months since the partnership began, total ad-driven sales grew 6.8 times, and conversion rates rose by 31.5%. We also saw gains in click share and brand share for several non-branded search terms: "dual dash camera" share rose 25%, and "wireless car dash camera" share rose 20%. These improvements in non-branded term performance indicate that more consumers are choosing AZDOME during generic product searches.

For on-page asset optimization, we selected several products to run before-and-after comparisons. The M550, our flagship model, had a 2.9% conversion rate before imagery updates; after the update, the rate rose to 3.17%, an increase of roughly 9%. The M63 also saw a significant conversion lift from its 0.8% baseline after optimization. High-quality images have a direct impact on main image performance, A+ content, and conversion rates.

But our partnership with Pattern is not just about swapping out a few images. It is about redesigning content based on actual consumer decision factors: adding scenario-based presentation to improve relatability, refining core features and selling points, and using comparison charts and close-up detail shots to address consumer trust concerns. Going forward, we will roll out this methodology to more products and SKUs.

David Quaife:What was AZDOME’s biggest platform operational challenge before partnering with Pattern?

Jeffrey Dong Hongwei: Our biggest pain point was transforming overseas operations from a talent-dependent model into a systematic, scalable model. When we first started selling on Amazon, our in-house team built operations from scratch, manually monitoring individual stores and individual sites. But as our product categories and channels expanded, operational complexity rose sharply. Algorithms vary across platforms and regional sites, and listing localization, ad placement, promotion cadence, and platform strategy all relied on manual work and individual intuition — making operations hard to replicate and hard to institutionalize. At the same time, ad spending kept rising, but core keyword rankings and conversion rates did not see meaningful improvements. We lacked a methodology to turn complex platform operations into predictable, replicable capabilities, which was the core reason we chose to partner with Pattern.

David Quaife: What specific results have you seen since partnering with Pattern?

Jeffrey Dong Hongwei: It has been a systemic change, not a single-point improvement. The most obvious gain is that our core operating metrics have stepped up to a new level: core keyword rankings, conversion rates, and ROAS have all improved significantly. With the same budget, our operations are more solid and more sustainable than before. For us, Pattern is not a traditional e-commerce service provider that acts as a third-party operator. It partners with us on a distribution model, sharing sales responsibility directly with our team. When both parties’ incentives are aligned, it creates a far stronger foundation for win-win results.

David Quaife: What advice would you give to brands that are considering partnering with Pattern?

Jeffrey Dong Hongwei: First, be clear on why you want to partner. If your only goal is short-term inventory clearance or a temporary sales spike, that mindset is not a good fit for a partnership with Pattern. This kind of partnership is better suited for brands pursuing long-term development and systematic brand growth — you should view the partnership as a long-term investment, not a one-time outsourced service purchase.

Second, be patient, and give both sides time to validate results. Improvements in platform performance are not immediate; you cannot draw conclusions based only on very short-term metrics.

Third, make sure you have strong products ready to launch, and continuously amplify your product strength and brand equity. At the same time, both parties need to be willing to share data openly and communicate transparently to first build trust as the foundation of cooperation. Only then can product, creative, ad placement, and operational data truly feed into the same continuous optimization closed loop.

This article was first published on the official website of Ebrun.