Product data is a functional unit of a great product and customer experience. We’d go a step further and say it’s the building block. It’s like the words we use to communicate. The same set of words that form a poetic masterpiece can also land in a cookie recipe. Thankfully Shakespeare didn’t have to worry about multiple channels and devices when crafting his masterpieces.
Product data is all about quality; this means accuracy, completeness, reliability, relevance and timeliness. While we can all agree upon what makes product data valuable, why is it that product data matters so much in the eCommerce ecosystem?
As many as 64.2% of online shoppers return products because the product doesn’t match descriptions (Source: SaleCycle)
What we’re seeing here is merely a symptom of poor product data. And that’s the case with product data; when it’s not working for you, you’ll see signs of it everywhere. When it is, you’ll see nothing but soaring conversions and sales.
But before we get to exploring the value of product data in eCommerce success, let’s understand…
What Product Data Really Is?
Product data refers to all the information, or “data”, about a product or service that describes it in terms of physical and non-physical attributes. For example, a pair of joggers can be described in terms of size, material, colour etc.; each of these attributes qualifies as product data. On the other hand, the fact that these joggers are ideal for running on particular surfaces, has shock absorbing properties etc. are also considered to be product data. The data describes the product itself, as well as the use case and value customers will get from it.
Similarly, product metadata is information about the product that may not be a direct reflection of the product itself. Location, availability, stock status, review score, related products, keyword ranking, number of sellers selling the particular product, etc. are examples of product metadata. When assessing the value of product data in eCommerce, both these aspects are equally important.
What Makes Data an Asset?
As we established with the Shakespearean analogy, data by itself guarantees nothing. It’s only when data possesses the core tenets of “quality” will it offer any real value from the lens of business outcomes. These are the five most significant traits of data that lend it high quality and integrity:
Why Product Data is More Relevant Now Than Ever Before
The global eCommerce market is expected to cross the $5.5 trillion mark in 2022. The total eCommerce market share is expected to grow to 24.5% by 2025; this is a 6.7% boom from where it currently stands. — Shopify Plus
But what has this got to do with product data? Everything. Product data forms the very foundation of all online shopping experiences. It allows companies to make direct and meaningful connections with customers. In fact, we’ll go a step ahead and say that product data takes on the role of integral elements of the brick-and-mortar shopping experience. It represents the store, the sales executive helping shoppers with the purchase, and the description of the product itself.
The value of product data is not only restricted to quality; it also involves leveraging it to its maximum potential. The right use of product data enables teams to optimize product presence by highlighting aspects that mean the most to your customers.
To be honest, the impact of high-quality product data in terms of business outcomes is hard to quantify. However, shifting your gaze to key areas it impacts gives a clearer picture of the true scale of the value of product data in eCommerce success. Here are a few of them:
Product Data Drives Customer Experience
When businesses think about customer experience, they are prone to restrict their assessment to abstractions — the bells and whistles. However, customer experience starts and often ends with the customer’s interaction with the product, and the data associated with it thereby. Everything from how a product is found — search or browse — to the information (and supporting assets) that describe the product, lay the foundation of customer experience. And customer experience can be made or broken at any of these touchpoints. For example, if a customer can’t find the products they are looking for within the first few seconds of the session, they are bound to bounce off. Even if the customer has found a satisfying journey right till the point of checkout, and finds incomplete shipping information, there’s no reason for him/her to go ahead with the purchase.
This is where it is significant to go beyond the basics. Apart from furnishing all product-related information, businesses must also leverage metadata and insights to understand customers, competitors and the ecosystem they are operating within. The end goal is to leverage data to create an emotional connect with customers, and this cannot be achieved with subpar product data.
Product Data Improves Content Marketing Efforts
While accurate data in itself gives customers the basics, it can also be the key to creating engaging content that is truly next-level. As your business expands to newer avenues, product-data-driven content enables you to create and maintain a consistent brand voice and aesthetic to closely connect customers with your brand. Content marketing is the aggregation of various moving parts including copy, images, videos and so on, and high-quality product data is what drives and connects these pieces.
Again, being in possession of product data is one thing, and understanding it is a whole other ball game. A better understanding of product data helps teams build strong product relationships and interoperability. This enables teams to build comprehensive campaigns and further the performance of a whole suite of products, and not just isolated ones scattered across catalogs. This linking can be carried out through better taxonomy, categorization and recommendations — all of which can be vital in boosting eCommerce sales.
Personalization Powered by Product Data
Apart from establishing one’s online presence, product data can play an indirect, but crucial role in differentiation. The better your product data, the higher your chances of standing out from the competition. Similarly, product data can also be leveraged to create more personalized shopping experiences, urging shoppers to return to your business more often.
80% of customers say that they are more likely to buy from a brand that provides personalized experiences — Epsilon
Take any streaming service and you’ll see exactly what we’re talking about. There is a reason that your Spotify page looks nothing like your friend’s. And this is where personalization comes to the fore. While personalized experiences give customers extremely intuitive experiences, almost feeling hand-crafted at times, the real driver of personalization is data. But how does data do this? This is what brings us to our next point.
Product Data at the Heart of Analytics & AI/ML
All personalization efforts are based on analytics of one kind or the other. Analytics is used for everything from product recommendations and market basket analysis to price optimization, demand forecasting, and fulfillment optimization. In short, if there is data being produced in any capacity, there is scope for analytics.
A Deloitte report states that 49% of companies studied stated that analytics enables better decision making, 16% believe that it enables key strategic initiatives, and 10% stated that it helps them improve relationships with business partners and relationships(though we believe the last figure is possibly much higher).
In fact, AI and ML help businesses take the power of analytics a step further. It enables organizations to assimilate analytics into their functions and provide personalized experiences, but this time, powered by automation. Similarly, functions such as forecasting and trend identification are also driven by AI-enabled automation that doesn’t just make things faster, but also smarter.
This is what brings us to the key point, without data, there is no analytics and no AI/ML. There is no doubt about the fact that analytics and AI/ML drive eCommerce sales, and it can only do so with the power of data.
Leveraging Product Data as an Internal Asset
Happy teams and stakeholders create happy customers. And not to state the obvious, but happy customers are pretty much synonymous with eCommerce success. Accurate product data is central to getting your teams and stakeholders to trust the systems they work with. Teams working with product data on a daily basis won’t be able to elevate their work and add value unless they trust the data, and view it as an effective asset to improve the quality of their work, and also the quality of customer experience.
Equally significant is the need for your teams and stakeholders to buy into the value of accurate and high-value product data. While you can provide them with systems to ensure this, true data quality can only be improved when it becomes a part of company culture. It is only at this point that product data can really drive eCommerce success. Governance is perhaps the most important way to ensure data quality and it is, in most cases, a customized framework that must be created keeping the organization’s unique requirements in mind. For governance to work, it must cover everything from data flow to data touchpoints and even data stakeholders.
Amaze PXM is a next-gen PIM SaaS that gives you complete control of product data, from ingestion to distribution. It brings together the tenets of syndication, product information management (PIM) and digital asset management (DAM) with expertise-driven product data management at the core. If you’re looking to start your journey with product data, or even finding ways to improve your business’s product data management practices, let’s speak more! Schedule a free demo today.