Fixing e-commerce stagnation without business disruption
The Data Bottleneck in E-Commerce
The highest leverage point in e-commerce optimization lies in product data, specifically where category and detail pages intersect—where user intent shifts from navigational to commercial.
Optimized category filters improves user guidance, leading to higher engagement and conversion. Given online users’ short attention span, better product data optimization drives higher engagement. Engaged users have a significantly greater chance of converting, making effective filters crucial for e-commerce success.
Result-Sneak-Peek
The before-and-after comparison highlights the overwhelming positive impact of product data optimization.
An almost 100 % conversion rate uplift, using the product data optimization workflow I created using Knime.
The challenge of change
Does your business still operate with product data structures designed for print catalogs and human consumption, rather than modern, digital-first commerce where data and technology are driving success?
While many companies claim to have embraced digitalization, their underlying product data processes remain largely unchanged, leading to inefficiencies and lost opportunities.
How to Strike a Balance Between Print and Digital?
Renowned for its exceptional quality and advanced search capabilities, modern on-site search engines such as FactFinder necessitate structured, machine-readable formats such as Color=Red|Yellow|Blue instead of Red/Yellow, Red/Blue.
Understandably, reworking the entirety of print-optimized product data and embracing digital-first processes is a major business challenge.
This discrepancy between product data’s historical origins and the needs of digital processes results in an extremely poor user experience. The consequences are threefold:
- Reduced conversion rates
- Increased maintenance efforts
- Higher hosting costs
Four real-life examples of product data optimization challenges
Why Fixing Product Data Seems Impossible?
Despite the clear benefits of structured, optimized data, businesses rarely correct the issue due to several key barriers:
- High Investment in Human Capital – Manually restructuring product data is labor-intensive and expensive and so is training product managers or merchandisers.
- Misalignment with Business Initiatives – Product data improvements are often not a priority compared to revenue-driving activities.
- The Chicken-Egg Problem – The promise of increased conversion rates is often not enough to justify upfront investments, especially when core changes could trigger a domino effect.
- The “We’ve Always Done It This Way” Mindset – Resistance to change is a major roadblock in many organizations.
- The Need for Stakeholder Buy-In – Aligning multiple departments (IT, marketing, product management) is a slow and difficult process.
What many businesses fail to realize is that staying static in the face of evolving digital commerce trends leads to stagnation. As the Forbes article states: “Companies that stay static don’t succeed.”
Unlocking Your Product Data’s Full Conversion Potential
Regardless how awesome and expensive the tools your business uses are, if the data ingested lacks quality, the user experience and thus your business revenue will diminish!
By leveraging Knime, businesses can:
- Eliminate the friction of change processes – Automating transformations reduces manual effort and resistance.
- Advance without disrupting core operations – Existing workflows remain intact while optimizing product data in parallel.
- Standardize, harmonize, and enrich product data – Fix typos, auto-translate terms (e.g., color to colour), convert units (e.g., mm to cm), and fill in missing or incorrect values.
- Integrate disparate data sources – Merge information from Product Information Management (PIM) systems like STEP from Stibo Systems, ERP platforms like SAP, and external sources such as on-site search engines like FactFinder.
- Enable dynamic, real-time product ranking – Process delta updates and full transformations without waiting for upstream data refreshes.
Conclusion – Product Data Optimization with Ease
Instead of optimizing around bad product data, your business can now fix it at the source.
Knime empowers your business to modernize the product data while sticking to existing workflows—bypassing the biggest challenges to change and unlocking your business’s full conversion potential.
Worth noting, the Knime Workflow saved the business the communication overhead, including but not limited to a five-digit, perpetual expenditure compared to a complementary service.
Every moment you wait, bad data is costing you. Let’s fix it now, together!
Product Data Deserialization and Optimization
Knime Example Workflow
Optimizing product data, especially in a multi context and multi language constellation, only adds to the aforementioned business challenges.
As product data is entered and maintained by humans, the possible combinations, disjoints and product data errors are infinite.
The product data optimization example workflow is an excerpt of one that is used in production since years. It is optimized to showcase how to interactively, using a dashboard, deserialize and optimize product data on an iterative basis.
The Knime workflow is compromised of five steps, following a top to bottom approach:
- Step 0 – Customer Pre Cleaning
- Step 1 – Deserialize
- Step 2 – Number Ranges
- Step 3 – Numbers & Fraction Notation
- Step 4 – Measurement & Dimension
- Step 5 – Measurement / Dimensions Sequence
Within each step it is possible to:
- Set custom rules / separator for deserialization
- Preview the final applied rules
- Preview the optimized data
Start optimizing your product data today!
The example Knime workflow displays how to:
- Split product data optimized for print
- Harmonize number ranges
- Align different value and measurement notations
Do you want to your businesses product data get optimized? Reach out to me!
