The opportunities and challenges associated with product catalogs and product information management (PIM) have never been more pronounced than they are today. Omni-channel initiatives and “long-tail” approaches to product catalogs have placed a new level of expectations on businesses, and on the merchandising, content, online, product, and marketing teams that support them.
The issues arise in various initiatives undertaken in this process: product catalog expansion; Product recommendations; Cross-referencing; Cross-sell; SEO; Online content attribution; Navigation; Mobile and omnichannel marketing.
Yet these various initiatives reveal a common theme – utilizing PIM best practices can offer tremendous ROI, unleash hidden potential, and enable a number of initiatives. Strong technology is crucial to highly effective PIM strategies, however, the approach to people, process, and data are the true keys to success.
Product data is essential for companies across all industries, and the emergence of online and mobile shopping are influencing and continuing to reshape how shoppers interact with product data in profound ways. Traditionally, products presented themselves in the aisles and upon the shelves.
Product data and content was an important part of shopping and the checkout process but in much more limited ways than supporting the demands of omni-channel marketing and merchandising. It isn’t just a mandate for the Amazons and newer age e-tailers anymore.
According to a report by Forrester Research, Inc. 44% of all retail purchases are influenced by online product content. To put this into perspective, of roughly $3.1 trillion in retail sales in 2013 (per eConsultancy, US Census and others), $1.4 trillion in sales are influenced through online and omnichannel research in addition to the nearly $400 billion million in ecommerce revenue. A total of $1.8 trillion in revenues influenced through online product research.
Many companies which conduct only small percentages of business online have huge percentages of their business at stake, and yet commonly, these companies also have low investments in online and mobile product content marketing. Rich and consistent product data which can be easily consumed across channels and devices, transforms consumers’ merchandising and shopping experiences.
Conversely, data quality issues and gaps in data and attributes either limit initiatives such as faceted navigation or manifest themselves as marginalized experiences. With e-commerce penetration currently at only 7-8% of sales, and projected to grow at a compound annual rate of 8% to 10% over the next five years, the influence will only grow more dominant.
With so many aspects to address, the quandary for many is determining where to start.
Defining “current state” and “end state” in the master data management journey are relatively easy.
Navigating from point A to point B in a cost-effective manner, and with a cadence that produces positive business impacts is the real challenge to address. Many plunge into architecture and execution of product catalog initiatives without a clear understanding of what their data profile is and what the resource needs are for managing their initiatives.
Some pursue data cleansing initiatives followed by data augmentation only to realize they have thus created a new problem with inconsistent taxonomy, metadata and attribution. Further down the road, these problems only compound efforts needed. A proper data profile is the ground zero of success in PIM. Taxonomy, Product Hierarchy, Attribution & Enrichment, Cross-Reference, etc. will be enabled by a deep understanding provided by a profile of your product data.
According to many consultants and experts across the industry, product data error rates range between 15 and 30%. The subsequent question becomes, “Which 30% is in error, and what caused it?” The answers vary widely – duplications, inconsistencies, null values and inaccuracies can occur at the product summary level and across the more detailed data and content attributes. Determining how those errors arrive leads to more questions. A comprehensive data profile serves as both a map and compass for your journey.
The demands for compelling marketing through informative, comprehensive and valuable product data are increasing and to meet these needs and drive competitive success requires a strong PIM framework, bringing together the best of in-house and third party subject matter experts and execution, in combination with leading technologies.
Utilizing an experienced, process-focused partner to augment, accelerate, and improve quality of data management activities for PIM and content initiatives, is a cost effective way to complement in-house resources and augment capabilities.
Your customers are already out there searching, comparing and buying, and your competitors are trying to solve the same PIM problems that you are. Is your product data ready to take on the market?
John Stephens is practice lead for data management and business unit lead at eClerx.