The Data Revolution: Your Guide to AI-Powered Product Excellence

But here’s the truth: while AI is indeed powerful, it’s not a miracle worker. It won’t transform your business into a digital kingdom overnight, waving a wand and conjuring results out of thin air. No, the journey to AI-powered greatness begins with a different kind of magic – the art of data cleansing and organization. 

Before embarking on your AI journey, creating a centralized, organized, and up-to-date repository of product information will serve as the bedrock upon which your AI solution can execute these magical, hyper-personalized product experiences. 

So let’s dust off the cobwebs, rearrange the shelves, and discover the secret power to harnessing AI that lies within your product data.

7 Steps to Getting Started With AI

1. Product Taxonomy: Structured Organization

Imagine walking into a massive library with no labels, no order, and no rhyme or reason to the arrangement of books. You’d be lost in a sea of information, desperately searching for a specific book. Now, think of your product catalog in the same way. Without a well-defined taxonomy, your products are scattered, confusing, and hard to find, not only for you but also for your customers and AI systems.

A product taxonomy is like the blueprint of your library. It provides a clear structure and hierarchy that organizes your products logically and systematically. This structure serves as a roadmap for classifying your products into categories, subcategories, and attributes, making it easy to navigate the vast expanse of your product offerings.

A well-organized product taxonomy isn’t just for your internal benefit; it directly translates into an improved customer experience. Customers can effortlessly browse and find products, enhancing their satisfaction and encouraging more conversions. When products are logically grouped, customers can discover related items they might not have otherwise stumbled upon, leading to increased sales opportunities. Plus, when AI has a clear taxonomy to reference, it can understand your products, customer preferences, and market trends more effectively and generate hyper-personalized product recommendations and content.

2. Data Collection: Centralization is Key

When it comes to collecting product data, many organizations are dealing with a logistical nightmare. Information pours in from every which way and in every format; your suppliers may provide product descriptions in one format, while manufacturers deliver specifications in another. Some data may come in spreadsheets, others in PDFs or even handwritten notes. Each source has its own quirks and idiosyncrasies, and it’s your job to bring them all together into a structured and harmonious whole.

Centralization simplifies the management of your data. It ensures that you have a clear overview of all your product information in one place. No more hunting through email inboxes, digging through file cabinets, or juggling multiple spreadsheets. Everything is neatly organized and easily accessible. This streamlines processes, saves time, and reduces the risk of errors that can occur when handling data scattered across different platforms.

Artificial intelligence thrives on structured, consistent data. When you centralize your data, you’re providing AI with a clean canvas to work its magic. AI solutions can then understand, learn, and make informed decisions when it has access to well-organized and standardized data. This, in turn, translates into more accurate product recommendations, content generation, and overall customer experiences.

3. Data Cleansing: Accuracy Matters

Inaccurate or incomplete product data renders the whole purpose of implementing an AI solution useless. When AI relies on flawed data, the resulting product descriptions contain incorrect dimensions, outdated prices, or missing essential attributes. It’s like your artist’s palette being filled with the wrong colors – the output won’t match your vision.

In the context of AI, data cleansing means taking a magnifying glass to your product data, identifying inaccuracies, incompleteness, and inconsistencies, and meticulously rectifying them. To cleanse data effectively, you should work with your organization to create and employ a combination of validation, standardization, and transformation techniques to ensure data accuracy, consistency, and completeness, while also implementing ongoing monitoring and governance practices to maintain data quality over time.

Now, here’s a little mind-bending tip: you can actually utilize AI to cleanse your data in preparation for implementing AI solutions. AI algorithms can be used to profile and analyze the data, identifying patterns and anomalies that may indicate data quality issues. These models can automatically flag data points that deviate from expected patterns at scale, helping to pinpoint errors, missing values, or inconsistencies.

4. Data Enrichment: Transforming Data into Content

Once you’ve organized your foundational product data and attributes, it’s time to breathe life into your data by transforming it into captivating and customer-friendly content. This step is where the magic happens, turning spreadsheets and technical jargon into engaging product descriptions that resonate with your audience.

Think of data enrichment as the art of storytelling. Your data, in its raw form, might be a list of product features, specifications, and numbers. However, to truly connect with your customers, you need to craft a narrative around your products. This narrative is what captures attention, stirs emotions, and ultimately drives purchasing decisions. Rather than stating that a smartphone has a 12-megapixel camera, you can describe how it captures vibrant memories with stunning clarity, allowing users to relive their favorite moments in lifelike detail.

Data enrichment isn’t just about making content appealing to humans; it’s also about making it discoverable on search engines. Implementing SEO techniques helps your product descriptions rank higher in search results, increasing visibility and driving organic traffic to your site.

5. Information Localization: Tailored for Different Markets

In the realm of global business, information localization is your passport to successfully navigating diverse markets by customizing your product content to resonate with audiences in different regions.

To effectively engage with customers in different regions, your product content should be in their native tongue and using location-accurate metrics. This includes translating product descriptions, marketing materials, and SKU titles or categories, along with ensuring that dimension, weight, and pricing metrics are regionally appropriate. 

Localization and translation is more than just swapping words; it’s about capturing the nuances and idioms that make your message relatable. What may be a humorous slogan in one culture could be offensive in another; adapting your content to the cultural nuances and sensitivities of each market ensures that your messaging resonates positively.

It’s also important to remember that different markets have different regulations. From Natasha’s Law to GDPR, the EU has been steadily passing more and more regulatory legislation, and they aren’t slowing down. Starting in 2026, you’ll likely have to start providing a Digital Product Passport for every product you sell in the EU. While DPP represents a wonderful step forward in data transparency, it requires organizations to have access to a centralized record of up-to-date, accurate, and organized product information which, as we’ve outlined above, is no easy task. But it serves as the backbone for personalized customer experiences in any market or channel.

6. Information Distribution: Breaking Down Silos

Information distribution is about breaking down the walls that separate different parts of your business. It’s about ensuring that everyone involved in the product journey has access to the same, up-to-date information because silos can lead to inefficiencies, miscommunications, and disjointed customer experiences.

When suppliers and manufacturers have access to the right data at the right time, they can streamline their processes, reduce errors, and align their production with your demands. When sales, and marketing teams are aware of the features in your latest product release, they’re better equipped to respond to inquiries and create outreach campaigns.

All your customer-facing channels, including your website, mobile app, and customer support, need direct access to your centralized product information. Regardless of where a customer interacts with your organization throughout their shopping journey, be it a Google search, Instagram browse, or a peruse of your mobile app, they should be able to access the same information and make the same decision. 

7. Information Optimization: Tailored for Each Channel

Every marketing channel has its own unique characteristics, audience behaviors, and expectations. What engages customers on social media may not work for an email newsletter or a product listing on Amazon. Information optimization recognizes these differences and tailors your content accordingly. 

Think about the difference between an SEO title on Amazon and a headline for a social media post. An Amazon title needs to be concise, packed with keywords, and focused on product details to improve discoverability. In contrast, a social media headline should be catchy, attention-grabbing, and include a hashtag or emoji. In a visual platform like Instagram, your product description might take a back seat to eye-catching visuals that tell a story or convey a mood.

While optimizing content for different channels, it’s crucial to maintain consistency in your brand’s voice and messaging. Your brand’s identity, like your sustainability initiatives or your buy-back and resale program, should shine through even as you adapt to the unique requirements of each platform. This consistency builds brand recognition and trust with your audience.

The Foundation for AI-Powered Success

In the realm of AI-powered product experiences, data is the linchpin. No matter how advanced your AI technology, it can only deliver exceptional results when fed high-quality, well-organized data. Building a strong foundation of product information is the essential first step to harness the full potential of AI for your business.

So, before you dive into the tantalizing world of AI-driven product experiences, take a step back, evaluate your data, and create a PX Strategy that ensures your product information is primed and ready for the AI revolution. With a solid data foundation, you’ll be well-equipped to create efficient, hyper-personalized product experiences that will propel your brand to new heights of success.

Ready to start preparing your data for AI implementation? Reach out to an Akeneo expert today to get started on your journey towards product experiences that turn browsers into buyers.