Retailers heavily depend on pricing intelligence solutions to consistently achieve and uphold their desired competitive pricing positions in the market. The effectiveness of these solutions, however, hinges on the quality of the underlying data, along with the coverage of product matches across websites.
As a retailer, gaining complete confidence in your pricing intelligence system requires a focus on the trinity of data quality:
However, the reality is that untimely data and incomplete product matches have been persistent challenges for pricing teams, compromising their pricing actions. Inaccurate or incomplete data can lead to suboptimal decisions, missed opportunities, and reduced competitiveness in the market.
What’s worse than poor-quality data? Poor-quality data masquerading as accurate data.
In many instances, retailers face a significant challenge in obtaining comprehensive visibility into crucial data quality parameters. If they suspect the data quality of their provider is not up to the mark, they are often compelled to manually request reports from their provider to investigate further. This lack of transparency not only hampers their pricing operations but also impedes the troubleshooting process and decision-making, slowing down crucial aspects of their business.
We’ve heard about this problem from dozens of our retail customers for a while. Now, we’ve solved it.
DataWeave’s Data Statistics Dashboard, offered as part of our Pricing Intelligence solution, enables pricing teams to gain unparalleled visibility into their product matches, SKU data freshness, and accuracy.
It enables retailers to autonomously assess and manage SKU data quality and product matches independently—a crucial aspect of ensuring the best outcomes in the dynamic landscape of eCommerce.
Beyond providing transparency and visibility into data quality and product matches, the dashboard facilitates proactive data quality management. Users can flag incorrect matches and address various data quality issues, ensuring a proactive approach to maintaining the highest standards.
Retailers can benefit in several ways with this dashboard, as listed below.
The dashboard helps retailers track match rates to gauge their health. High product match rates signify that pricing teams can move forward in their pricing actions with confidence. Low match rates would be a cause for further investigation, to better understand the underlying challenges, perhaps within a specific category or competitor website.
Our dashboard presents both summary statistics on matches and data crawls as well as detailed snapshots and trend charts, providing users with a holistic and detailed perspective of their product matches.
Additionally, the dashboard provides category-wise snapshots of reference products and their matching counterparts across various retailers, allowing users to focus on areas with lower match rates, investigate underlying reasons, and develop strategies for speedy resolution.
The dashboard enables pricing teams to monitor the timeliness of pricing data and assess its recency. In the dynamic realm of eCommerce, having up-to-date data is essential for making impactful pricing decisions. The dashboard’s presentation of freshness rates ensures that pricing teams are armed with the latest product details and pricing information across competitors.
Within the dashboard, users can readily observe the count of products updated with the most recent pricing data. This feature provides insights into any temporary data capture failures that may have led to a decrease in data freshness. Armed with this information, users can adapt their pricing decisions accordingly, taking into consideration these temporary gaps in fresh data. This proactive approach ensures that pricing strategies remain agile and responsive to fluctuations in data quality.
The dashboard provides users with proactive control over managing product matches within their current bundles via the ‘Data Management’ panel. This functionality empowers users to verify, add, flag, or delete product matches, offering a hands-on approach to refining the matching process. Despite the deployment of robust matching algorithms that achieve industry-leading match rates, occasional instances may arise where specific matches are overlooked or misclassified. In such cases, users play a pivotal role in fine-tuning the matching process to ensure accuracy.
The interface’s flexibility extends to accommodating product variants and enables users to manage product matches based on store location. Additionally, the platform facilitates bulk match uploads, streamlining the process for users to efficiently handle large volumes of matching data. This versatility ensures that users have the tools they need to navigate and customize the matching process according to the nuances of their specific product landscape.
With DataWeave’s Pricing Intelligence, users gain the capability to delve deep into their product data, scrutinize match rates, assess data freshness, and independently manage their product matches. This approach is instrumental in fostering informed and effective decisions, optimizing inventory management, and securing a competitive edge in the dynamic world of online retail.
To learn more, reach out to us today!
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