Supercharge your e-commerce with our data enrichment strategy

Author

Matt Harris
October 28, 2024

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Data enrichment will help you supercharge your e-commerce and turn messy product data into a competitive advantage

This framework helped a client close a $10,000 deal in 7 days.

(If you’d prefer video to text click here)

Most distributors struggle with inconsistent, incomplete product data.

It kills your customer experience and operational efficiency.

Here's the 3-step framework we use to fix messy product data FAST:

1️⃣ Normalize data

Standardize formats, units, and values across all products. 

Let's break this down with a real-world example:

Imagine you're selling bolts on your e-commerce site. Your product data might look like this:

  • Bolt A: 1/4 inch

  • Bolt B: 0.25 inch

  • Bolt C: quarter of an inch

These are all the same size, but they're written differently. This inconsistency makes it hard for customers to find what they need and impossible to filter or sort products accurately.

Normalizing this data means choosing one standard format and applying it across all products. For example:

  • Bolt A: 0.25 inch

  • Bolt B: 0.25 inch

  • Bolt C: 0.25 inch

Now, customers can easily compare products, and your site can offer better search and filter options.

2️⃣ Enrich data

Fill in missing info and add valuable details. 

Here's what this looks like in practice:

Let's say you're selling power tools. Your initial product data might be bare-bones:

  • Product name: Cordless Drill

  • Brand: PowerPro

  • Price: $79.99

Enriching this data means adding more useful information that helps customers make informed decisions:

  • Product name: PowerPro 18V Cordless Drill

  • Brand: PowerPro

  • Price: $79.99

  • Battery voltage: 18V

  • Chuck size: 1/2 inch

  • Weight: 3.5 lbs

  • Includes: 2 batteries, charger, carrying case

  • Warranty: 3 years

This enriched data gives customers a complete picture of the product, reducing questions and increasing confidence in their purchase decision.

3️⃣ Validate accuracy

Use AI + human review to ensure data quality at scale. 

Here's how this works:

First, AI algorithms scan your entire product catalog, flagging potential errors or inconsistencies. For example, it might identify:

  • Products with missing crucial information

  • Unrealistic values (like a 1000-pound handheld drill)

  • Inconsistent units (mixing metric and imperial measurements)

Then, human experts review these flagged items. They can:

  • Cross-reference with manufacturer data

  • Apply industry knowledge to spot errors AI might miss

  • Make judgment calls on ambiguous cases

This combination of AI speed and human expertise ensures your data is not just complete, but also accurate and trustworthy.

The results?

✅ Better customer experience: Shoppers can find and compare products easily, leading to higher satisfaction and fewer returns.

✅ Increased operational efficiency: Accurate data means fewer customer service inquiries and smoother order fulfillment.

✅ Competitive edge in your market: High-quality product data helps you stand out in search results and marketplace listings.

One client implemented this framework and closed a $10,000 deal within 7 days of optimizing their data.

Why?

Because their newly organized and enriched product catalog made it easy for a large customer to find exactly what they needed and place a bulk order with confidence.

Want to learn more?

Check out the video below:

See you next week,

Matt Harris

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Whenever you're ready, here's how we can help you:

Harris Web Works is a digital transformation agency that helps supply chain partners (manufacturers, wholesalers & distributors) meet new generational buyer demands & expectations by installing streamlined e-commerce systems.

To learn more about how we can help you future-proof your business, click here.