The path to success in eCommerce is recognizing the importance of product data quality and optimizing it with AI technology.
On July 23, 1983, passengers boarded Montreal-to-Edmonton Air Canada Flight 143, unaware of the terrifying sequence of events that would befall them. The plane’s Fuel Quantity Information System computer had malfunctioned, so the ground crew had to manually calculate how much gas to put in. Unfortunately for all, the crew forgot to take into account that this was Boeing’s new 767, the first model to fly in Canada using the metric system. When measuring the gravity of the fuel, the factor they used was 1.77 pounds/liter instead of the 0.8 kg/liter required by the new all-metric plane. Somewhere over Red Lake, Ontario the plane ran out of fuel. The engines went eerily quiet and hydraulic pressure was lost. Fortunately, the heroic captain was able to glide the plane into a safe emergency landing, sparing the 61 souls aboard with only a few injuries.
Though the advent of eCommerce would not arrive for another decade, those of us distributing product information online in today’s world can learn something from this cautionary tale. As captain of your ‘aircraft’, you should be concerned about...Data Quality. In our modern age of integrated computer systems, we are all too familiar with the disastrous consequences of incorrect data transformations, lagging data updates, and incomplete data. While we may not have lives at stake, the data that we create and distribute powers every aspect of the consumer purchasing decision and therefore our revenues.
In the highly competitive online retail space, one of the best ways to differentiate is with your product data. Companies that keep an eye toward achieving and maintaining high quality product data will have a leg up on their competition. Why? Because product data drives two very important business needs: search engine optimization (SEO) and customer experience.
SEO is the practice of increasing the amount of traffic from organic search results on search engines to your website or product listing. In many cases, multiple websites will list the same product. The consumer’s purchasing decision is often determined simply by which website appears first in their search results. By providing more robust and engaging product names, descriptions, bullet points, and keywords, you can increase the ‘findability’ of your products on sites like Google and Amazon.
When it comes to customer experience, product data is of the utmost importance. In order to make their buying decision, today’s consumers demand detailed information, such as product images and product descriptions. If it’s a food product, does it properly list the ingredients and allergen statements? Does the associated picture accurately reflect the product? These are just a handful of example data points that will have a positive or negative impact on your sales.
Data Quality can feel like such a nebulous term. In order to set data quality standards, we must first consider what are the attributes that define data quality. In order to be considered as high quality, data must be:
Companies that hope to succeed in today’s market must develop their own definitions and standards for data quality. However, even when a company finally understands the power of differentiating through data, it often struggles with how to proceed.
If product data quality is so important, why is it so hard for companies to get it right? One major reason is that company data lives in multiple software systems. The team responsible for the Enterprise Resource Planning (ERP) system is usually not the same team responsible for the Product Lifecycle Management (PLM), or the PIM, or the Digital Asset Management (DAM) systems. With a multitude of systems and owners, it’s near impossible to set consistent data quality standards across all the systems. Companies today are lacking the tools they need to define, measure, and monitor product data quality across their various systems. This is where Impira comes in.
Impira’s Data Intelligence Platform serves as ‘air traffic control’ between your various systems. Impira doesn’t necessarily replace a PIM, DAM, ERP, PLM, or logistics system. Instead, Impira tracks and monitors the information that flows between these systems. Impira’s AI technology can:
Impira provides the tools to conduct an initial product data quality analysis and operates continuously to help iterate and improve that data over time.
“If you can’t measure it, you can’t improve it.” – Peter Drucker
The business insights you need to grow your revenues and reduce costs can only come from adopting a renewed focus on data quality. In the past, this has meant hiring more people, or enforcing cumbersome workflows that delay getting a product to market. Today, those costly overheads can be reduced or even removed entirely by applying Artificial Intelligence. For example:
AI is changing the way eCommerce companies operate. At Impira, we can help you make the transition to the new age. The right combination of product data quality and AI will be your flight plan to success.