The 7 Secrets to Skyrocket Your Sales with Generative AI

By Charlotte Journo-Baur, Founder of WISHIBAM

What is generative AI? It’s precisely the answer to this type of bottleneck. Generative AI refers to a family of technologies capable of producing original content—text, images, video, code—from simple natural language instructions. It doesn’t just analyze existing data: it creates. And that’s where everything changes for commerce.

In 2024, according to McKinsey, generative AI already represented a potential added value estimated between $2.6 trillion and $4.4 trillion per year globally, across all industries combined.

Retail ranks among the most directly impacted sectors, with use cases touching content creation, customer personalization, inventory management, and shopping experience alike.

In this article, I’ll share the 7 secrets that the most advanced retailers are already using to transform generative AI into a concrete growth lever. No vague theory, no empty promises: real applications, identified tools, measurable results. And if you’re still wondering where to start, you’ll be in the right place by the end of this read.

Understanding Generative AI

What Is Generative AI

Generative AI is a branch of artificial intelligence that has made a spectacular leap since 2022. Unlike so-called “discriminative” AI—those that classify, detect, or predict from existing data—generative AI produces new content. It generates. Hence the name.

Technically, it relies on models trained on considerable volumes of data: billions of texts, images, sounds. These models learn structures, patterns, correlations. Then, from an instruction—what we call a “prompt”—they produce a coherent and original response.

For retail, this concretely means: generating a product description in 10 seconds, creating a lifestyle visual without a photo shoot, writing a personalized email campaign for each customer segment, or even simulating a product’s appearance in different colors without going through physical production.

What distinguishes generative AI from classic digital tools is its ability to adapt to context. It doesn’t repeat a template. It composes. And this nuance radically changes what we can expect from it in a commercial environment where differentiation is constant.

A common misunderstanding also needs clearing up: generative AI isn’t a magic tool that replaces creative teams. It’s an accelerator—a digital collaborator that handles repetitive or time-consuming tasks to free up teams for what truly requires human intelligence: strategy, taste, customer relations.

At WISHIBAM, we observe this transformation daily in the retail organizations we support. Teams that adopt generative AI don’t work less—they work better.

How Generative AI Works

Behind the apparent simplicity of an interface where you type an instruction and get a result, there’s sophisticated mechanics. Today’s most widespread generative AI models—OpenAI’s GPT-4, Google’s Gemini, Anthropic’s Claude for text, Midjourney, DALL-E, or Stable Diffusion for images—all operate on a common principle: probabilistic prediction.

For text, these models (called LLMs, Large Language Models) predict, word by word, what is the most probable and coherent continuation of a sentence, considering the provided context. For images, diffusion models start from random visual “noise” and progressively refine it until obtaining an image corresponding to the given description.

What’s fascinating—and sometimes unsettling—is that these models don’t truly “understand” in the human sense. They operate through statistical associations at a scale the human brain cannot apprehend. And yet, the results are often strikingly relevant.

The good news? This skill is quickly acquired. And platforms like WISHIBAM integrate these logics directly into their interfaces, so retail teams don’t have to become engineers to benefit from them.

AI Tools for Retail

The AI tools market for retail has literally exploded in two years. It’s become difficult to navigate, and that’s often where decision-makers get lost: by wanting to test everything, nothing really gets deployed.

Main use-cases and tools:

• Textual content creation:
  • ChatGPT (OpenAI)—writing product descriptions, emails, scripts
  • Claude (Anthropic)—effective for long and nuanced content
  • Jasper—marketing-oriented, with retail templates
  • Copy.ai—for e-commerce teams and volume generation
• Image and visual creation:
  • Midjourney—the aesthetic reference
  • DALL-E 3 (OpenAI)—integrated with ChatGPT
  • Adobe Firefly—inside Adobe suite, for already-equipped teams
  • Stable Diffusion—open source, customizable, local deployment
• Personalization and customer experience:
  • Dynamic Yield—real-time personalization
  • Nosto—AI product recommendations for e-commerce
  • WISHIBAM—retail platform integrating AI features for showcasing and shopping experience personalization

The selection criterion shouldn’t be the tool’s technical sophistication, but its ability to integrate into existing workflows and produce measurable results quickly. This is what we advocate at WISHIBAM: AI in service of commerce, not the other way around.

Generative AI Applications in Commerce

Using AI to Create Visuals

Concretely, here’s what AI image generation tools enable today:

• Generate lifestyle visuals for existing products (sofas, clothing in diverse settings)
• Create new color variations of a product without physical production
• Produce seasonal campaign visuals in hours
• Adapt visuals to different ad formats (social, display, print)
• Create visual atmospheres consistent with the brand

Notably, retailers like Zalando, H&M, or IKEA have already integrated these practices at scale. IKEA announced in 2023 the use of generative AI to produce a part of its catalog visuals, freeing up its photographers for higher value-added creative projects.

AI also allows testing visual concepts before investing in production—20 campaign variations in one morning, panel-tested, and only producing what proves effective. That’s a revolution for creative risk management.

Result quality remains highly dependent on instruction precision and tool mastery. Limitations persist—especially for unique products or consistent hands/faces—but these are rapidly receding.

AI Image Creation

AI image creation is probably the most visible and immediately impactful application for retail teams.

The process: describe, in natural language, exactly what you want—the subject, style, mood, colors, framing—and the model generates corresponding images. The more precise your description, the closer the result to your vision.

Are these images royalty-free? Mostly yes, but conditions vary. Adobe Firefly trains only on royalty-free content, making it safer for large retailers.

Generative AI’s Impact on Commerce

Generative AI’s impact goes far beyond visuals. It transforms the structure of retail organizations and their ability to satisfy ever-more demanding consumers in terms of personalization and speed.

• By 2026, over 80% of companies will have used generative AI in production (Gartner)
• Retailers using generative AI for content creation reduced production timelines by 60–70% (BCG, 2024)
• 51% of consumers now expect personalized experiences (Salesforce)

The real revolution: true mass personalization at a marginal cost approaching zero—emails and offers tailored to each customer’s profile, history, aspirations. Science fiction yesterday, operational today.

Beyond the front end, generative AI drives more precise demand forecasting, stock-out scenario simulation, and assortment optimization. The boundaries between AI families are blurring on the most innovative commerce platforms.

At WISHIBAM, the best results come from integrating generative AI into a holistic digital transformation vision—not using it as a one-off gimmick.

Maximizing Sales with Generative AI

France AI That Generates Images: The Local Ecosystem to Know

American giants dominate the discussion—OpenAI, Adobe, Google—but France has a strong AI ecosystem, with some solutions uniquely suited to EU retailers: proximity, GDPR compliance, and French-language support.

• Mistral AI—leading French LLMs, used widely for text apps
• Photoroom—auto-staging & background removal for e-commerce product images
• Skeepers—AI features for customer reviews and UGC
• Contentsquare—behavior analytics for optimizing journeys

Photoroom, founded in Paris, is especially popular for turning basic product photos into pro-level visuals (background removal, auto-generating context, format adaptations). Thousands of French merchants use it for affordable, high-quality imagery.

France is heavily investing in AI, with €1 billion committed in 2024, focusing on industrial and commercial uses. French retailers should embrace this homegrown ecosystem.

What Is the Best AI Image Generator

The frequent question: “Which AI image generator is best?” The answer is: it depends—on your needs, context, and workflow.

Recommendations for 2024:

• Midjourney: best for creative, stylish campaign visuals
• Adobe Firefly: safest for legal/IP concerns, seamless with Adobe suite
• DALL-E 3: accessible, precise, ideal for e-commerce sheets
• Photoroom: high-volume e-commerce product visuals, especially in France

Key selection criteria:

• Production volume: 10 or 10,000 images per month?
• Customization: do you need strict brand adherence?
• Technical integration: connect with your PIM, CMS, or commerce platform?
• Legal/IP security: copyright exposure?
• Team skill: designer/tech comfort, or need for simplicity?

Brand consistency is crucial. “Generic” AI art generators may not adhere to your brand style. Most advanced providers now support fine-tuning—training models on your own visuals for tailored results.

Where to Find an AI Image Generator

Most AI image generators are directly available online, with free or affordable entry options.

• Midjourney: Discord access (midjourney.com) — from $10/month
• DALL-E 3: Via ChatGPT Plus (chat.openai.com) — $20/month
• Adobe Firefly: firefly.adobe.com — free tier or with Creative Cloud
• Stable Diffusion: DreamStudio or local install
• Photoroom: photoroom.com — freemium, pro from €9.99/month
• Runway: runwayml.com — trial + from $12/month

Tip: Test free versions or trials first; all tools have a flavor, and what works best is often discovered in context.

The 7 Secrets to Boosting Your Sales

Secret #1: Hyper-Personalize the Customer Experience at Scale

Advanced retailers use generative AI to personalize every touchpoint—moving from segmentation to true individualization.

• Personalized product descriptions based on browsing history
• Unique email campaigns for each segment, tailored by preference
• Adaptive homepage imagery matching visitor profile
• AI-powered personal recommendations, with contextual copy

Example: A fashion client at WISHIBAM creates three versions of each product description: for price-shoppers, for quality-seekers, and for trend followers. AI displays the right one per customer profile—raising page conversion rates by 23%.

The key is strategic intent: know what, for whom, and why you personalize—the AI is the means, not the strategy.

Secret #2: Accelerate Content Production Tenfold

AI multiplies content output—without multiplying teams or budgets.

• Product descriptions
• Category pages & buying guides
• Blog, social, ads copy
• Email & campaign variations

Case: A home goods retailer produced 500 new product descriptions in two days (versus two weeks humanly possible). Clear templates, precise prompts, and final human review keep quality high and save 70% in time.

Secret #3: Test and Iterate at Lightning Speed

Generative AI allows infinite creative A/B testing—at vanishing cost.

• Generate 20 ad visuals in a morning, test on micro-budgets
• Identify data-proven winners before full spend
• Apply the same to emails, titles, social posts—let data, not gut, decide

Example: A sports brand launched a shoe campaign: 30 visuals made in a day, tested via Facebook ads, and professionalized only the top 3. ROI rose by 40%.

Secret #4: Optimize the Product Catalog in Real Time

AI enables dynamic, ongoing catalog improvement.

• Analyze weekly conversion rates
• Trigger alerts for underperformers
• Auto-suggest new descriptions, visuals, or positioning

Result: An outdoor retailer’s conversion lifted 18% with weekly AI-guided optimizations. Coupling AI generation with clear analytics is the winning formula.

Secret #5: Reduce Returns Through Better Product Presentation

Returns hurt profits and the environment. Many stem from misaligned expectations created by poor product pages.

AI can generate contextual, realistic visuals: products in varied settings, worn by diverse models, in real-life situations. Better visualization means better decisions—and fewer returns.

Case: A furniture retailer cut return rates by 15% by offering three interior staging options per product.

Secret #6: Automate Customer Support While Improving Quality

Conversational AI handles routine questions, providing ultra-fast personalized support.

• Order tracking
• Sizing advice
• Product availability
• Returns & exchanges

Impact: A fashion merchant’s chatbot handled 70% of tickets unaided, cut average response time from 4 hours to 30 seconds, and raised satisfaction by 12%—freeing human agents for complex issues.

Secret #7: Transform Data into Actionable Strategic Insights

AI goes beyond content—it converts massive, messy commerce data (transactions, browsing, feedback, returns) into strategic insights invisible to humans alone.

In short: retailers who combine human creativity, customer empathy, and generative AI execution not only survive—but lead the transformation underway in commerce. The best time to start was yesterday. The second best is now.

FAQ – Generative AI for Retail