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AI ecommerce that boosts your revenue

Grow smarter, you stay in control

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author
Tim Sol
Business Consultant

Three situations we encounter every day

Why AI in Your Online Store Gets Stuck

  • The data is there, but the results aren’t

    Your online store has been collecting click, search, and order behavior data for years. As long as that data remains in separate systems, AI can’t do anything with it. We’ll start by connecting the store, PIM, and CDP, because that’s where the fuel lies.

  • Everyone sees the same store

    Having a single product overview for both returning customers and new visitors leaves revenue on the table. Personalization only works when the rules are tailored to your own product range. We’ll set that up together, based on what you know about your market.

  • A tool that no one can explain

    A recommendation module that can’t be monitored will be shut down after a few months. We document what the model is based on and what results it delivers. That starts with an honest baseline assessment of what’s currently in place.

AI e-commerce as the engine behind your online store

AI isn’t just an add-on to your online store. It’s the engine that runs on your own data: order history, search behavior, inventory, and margin. The cleaner the fuel, the more power you get out of it.

What a model takes over is the manual work. Product descriptions that used to have to be rewritten for each variant, recommendations that someone used to compile by hand, inventory alerts that only stood out in the weekly report. Those tasks keep running while you’re reviewing the numbers.

You remain in control throughout the process. You can see in the dashboard what the model is doing and why, and in the monthly meeting, we decide together where to make adjustments. You work with a dedicated specialist who knows your store, not with a rotating team.

  • 22+ year experience
  • 9,3 Customer care
  • 55+ Kiwi specialists

What does AI e-commerce entail?

We start with your data layer. What events does your store track, where is your product information stored, and what data comes from your CDP? Then, for each use case, we choose the model that fits: personalization of the product range, generative product content for variants that are currently left blank, or predictions for inventory and repeat purchases. You won’t get a one-size-fits-all package, but rather the two or three use cases that drive the most revenue for you.

From a standalone experiment to a production system

A pilot that works isn’t a result in itself. We integrate the application into your existing stack, link it to your conversion goals, and measure it against a control group. That way, you know what the model is actually contributing, and not just what the season did. During the monthly meeting, we’ll review those numbers together and decide whether to scale up, make adjustments, or stop. No black box, no model that runs just because it’s there.

Together with our commerce specialists

Combining AI e-commerce with your platform

AI’s performance depends on the quality of the underlying environment. If your architecture is sound and your product data is complete, a model will quickly pay for itself. If that’s not yet the case, that’s where we’ll start. We’ll decide together which path to take based on the findings of the baseline measurement.

From baseline measurement to a system that keeps learning

How AI e-commerce works at Redkiwi

  • 1. Baseline Assessment

    We examine what your store is currently tracking and where the data has gaps. You’ll get an honest assessment of what’s possible today and what needs to be addressed first.

  • 2. Implementation and Measurement

    We’ll launch the chosen solution and compare it against a control group. You’ll know exactly where we stand, because the results appear in the same dashboard as your other channels.

  • 3. Scaling

    We’ll expand what works to more categories and channels. What doesn’t work, we’ll phase out. We’ll make that decision together during the monthly meeting, based on the numbers.

Three Examples of AI in Practice

Results with AI in Commerce

  • Case over EK88look.nl, een AI driven actie van Redkiwi

    EK88look case

    3 million visitors, €0 media budget

  • Esbjaerg Vodka

    AI brings brand identity to life

View all our case studies View all our case studies

Independent advice, no bias

AI tools we use

Conversational AI and content creation that makes an impact for your brand

Conversational AI for customer engagement and sales growth

Visual AI for brand stories, campaigns, and content creation

Create visual content with confidence and speed

AI video and avatars for compelling marketing and communication

Moving images for concepts and campaigns, without a shoot day
View all our partners View all our partners

Curious about what AI can do for your store?

Submit your question, and Paul will schedule a half-hour call within two business days. During the call, we’ll review your current data and give you an honest assessment of whether AI is the right move for you right now.

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Agreement 

Your dedicated specialists for AI in commerce

Sander van der Hoff
Digital Consultant
Lukas Roeling
Head of Performance Branding & Digital Strategist
Meet the whole team Meet the whole team

How much does AI for e-commerce cost?

That depends on the condition of your data, the number of applications you deploy, and the platform your store runs on. Implementing a personalization module on a clean catalog is a different process than building a data layer from scratch.

What you always get: a dedicated specialist who knows your store, a measurement setup with a control group, results in your own dashboard, and an honest discussion if we think a different approach would work better.

Want to know where you stand? Tell us briefly what you’re currently running, and we’ll take a look.

Schedule a call Schedule a call

Frequently Asked Questions About AI in E-commerce

01/ What exactly is AI e-commerce?

Applying models to your own online store data to automate tasks and inform decision-making. Think of recommendations, product content, and inventory forecasting. You determine what the model focuses on and can see its performance in the dashboard.

02/ Where does AI really pay off in e-commerce?
In areas where you do the same work a thousand times over: product descriptions for a large product range, image variations per channel, translations, and the first draft of your content. That’s where it saves time and reduces workload. When it comes to one-time decisions and strategy, a specialist is faster and better.
03/ Does AI e-commerce work on my platform?

We work with Shopify, Magento, Craft Commerce, and headless setups. The application adapts to the platform, not the other way around. During the initial assessment, we’ll determine what your stack can handle and what needs to be integrated first.

04/ How soon will I see results from AI e-commerce?

If your data is in good shape, an initial application will be up and running within a few weeks, and you’ll be able to measure its performance against a control group. If the data layer needs to be sorted out first, it will take longer. We’ll let you know upfront which of the two applies.

05/ How much does AI cost in e-commerce?
That depends on where you use it and your volume. In addition to our hourly rates, you’ll pay subscription fees for the tools you use. Every collaboration is customized, so we start with a single application where we can measure the impact rather than with an AI program.
06/ What do I need to do myself during an AI project?

You provide the market knowledge and make decisions about your product range; we provide the technology and the measurement setup. During the monthly meeting, we go over the numbers together. Other than that, we don’t bother you with it. That’s what ownership means to us.