Industrial Distribution

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1 Industrial Distribution FIVE DATA CHALLENGES FOR INDUSTRIAL DISTRIBUTION WEBSITES 1 Taxonomy 2 Product Attributes 3 Product Images 4 Product Titles 5 Feature Copy CODIFYD.COM

2 INTRODUCTION Creating a successful e-commerce website for industrial distributors is not without its data challenges. Oftentimes the budget for such projects is lower than other businessto-business (B2B) companies, even though the product offering is larger and more complex. For example, a company that sells ten styles of beach towels might spend one hundred dollars to create an e-commerce site, while an industrial distributor that sells twenty styles of pneumatic power tools will spend only fifty dollars on a similar project. WHY INDUSTRIAL DISTRIBUTORS ARE SLOW TO INVEST IN E-COMMERCE RELATIVE TO OTHER B2B COMPANIES? Low revenue per SKU (stock keeping unit). Industrial distributors tend to make less revenue per SKU than other B2B companies. It is common for a distributor with $100 million in annual revenue to carry only fifty thousand active SKUs. This creates a culture highly resistant to fixed costs per SKU, particularly for slow-moving items. Weak initial online sales. Websites expected to fund their own growth get stuck in first gear for years. Insufficient funding leads to weak initial online sales, which reinforces skepticism and cost-aversion. Oftentimes, the only way to create a C-level mandate for change is when there is a threat of losing a large customer. Lack of holistic e-commerce solutions. There are no service providers with expertise in industrial distribution that offer product data management, web platform, search technology, and analytics solutions in one package. Together with a limited budget, industrial distributors are left to cobble together solutions amid over-hyped, piecemeal technology offerings. FIVE DATA CHALLENGES FOR INDUSTRIAL DISTRIBUTION WEBSITES Although each industrial distributor faces unique challenges based on technology and budget constraints, we find there are five key areas of data and web content that customers find important when shopping online.

3 1 TAXONOMY In the context of e-commerce, taxonomy is the classification of products. It allows for easy website navigation, consistent attribute normalization, and meaningful analytics and reporting. Taxonomy is critical for keeping products organized online, but it is often the most overlooked element when building e-commerce websites. Dedicate resources to maintain a custom taxonomy based on product breadth and depth. Use the terminal node in the taxonomy to define and normalize product attributes. Optimize the taxonomy for easy, effective online navigation. Using keyword research, name products according to how customers normally search for them. This allows customers to quickly navigate, filter, and isolate relevant products. Redirect frequent search terms and common synonyms to relevant nodes in the taxonomy. This ensures relevancy in search results. Use the taxonomy to generate and analyze detailed sales reports. For example, a granular taxonomy will show sales trends by wrench type such as combination wrenches, adjustable wrenches, or box end wrenches. A taxonomy that is overly general will limit reports to a broad category, such as wrenches, and won t indicate a sales increase or decrease for a specific type of wrench. Using a third-party data structure that is inconsistent or too broad in some areas and too narrow in others. Un-normalized product attributes at the terminal node level. Reusing a print catalog index as the online taxonomy. Redundant and nonintuitive taxonomy nodes. SAMPLE WEB HIERARCHY The L2 Supplies is vague. What type of supplies exist here? It s impossible to tell without looking at the next level down. Wiring Devices appears as both an L2 and L3. Do these contain the same type of products? If not, what is the difference between the two? Proper categorization and naming eliminates these questions. FIGURE 1.

4 2 PRODUCT ATTRIBUTES Structured, normalized product attributes are essential for faceted navigation and proper classification, particularly for industrial distributors that sell hundreds of similar products with small attribute differences. For example, if a distributor sells five hundred socket head cap screws, it is important that customers not only can navigate to these products but also within them. The ability to drill down and select values from normalized attributes is a simple concept but one that is challenging for nearly every online distributor. Define a short list of navigation attributes for each terminal node that customers will use to filter with. The list should not attempt to encompass all possible attributes for a given product; rather, it should identify attributes shared by the vast majority of products in the category. Understand that navigation attributes are a subset of all possible product attributes and do not include every possible attribute for a given product. Creating a list of all possible product attributes is called an extended attribute scheme and is a much larger task. Once navigation attributes are chosen and defined, aggressively normalize and populate values for all products in the node, using manufacturer source materials when necessary. The higher the fill rate, the more effective faceted navigation will be. Lack of normalized attributes across similar products. This is caused by an overly general taxonomy or the inability to manipulate un-normalized data stored as is when received from manufacturers. This is extremely common even large Fortune 500 companies struggle to display structured attributes within taxonomy nodes. Attributes that have no values associated with them. For example, if a customer uses the attribute length to navigate through a category like drill bits, products without a value for length will not be displayed online. Attributes without values cause distributors to systematically under-represent their product portfolio (fig. 3). Using un-normalized data to create attributes for faceted navigation, i.e., If data isn t structured, just use what we have. The result is multiple fragmented attributes that have similar meanings, which prevents customers from isolating similar products. While it creates the impression of faceted navigation, it often does more harm than good and causes customer frustration (fig. 2). Too many navigation attributes. The less important an attribute is for a given product, the harder it is to consistently populate. The goal, with many exceptions, is to have 100 percent fill rate for navigation attributes.

5 FACETED NAVIGATION The attribute Type allows customers to navigate, or filter, within the 326 products in the terminal node Hammers. Un-normalized values show both ball peen and ball pein hammers. Are these the same type of hammer? What s the difference? The same issue is repeated here with blacksmith and bricklayer hammers; a customer must click both values to see the full selection of products. Additionally, the node label is too long, and breaks the navigation frame. FIGURE 2. FILL RATE The navigation attribute Microns is important for these products, but the data has a does not have a high fill rate. Of the 556 products available in this category, only 481 have data for this attribute, which means the remaining 75 products become invisible and the distributor underrepresents its product portfolio. FIGURE 3.

6 3 PRODUCT IMAGES While consumer goods retailers see the impact that in-use images and image zooming have on their conversion rates, industrial distributors struggle to simply have a representative image for each product. Product images instill confidence in the customer that a product is what the text says it is, and they are valuable cues in faceted navigation. The higher the image quality, the higher the customer s perception is of overall website quality. Create, define, and enforce image specs and governance procedures for both print and the web.» Directly and systematically work with manufacturers to obtain the most up-to-date and highest resolution product images. Use digital asset management (DAM) tools to streamline image management and deployment. Take pictures of key items that have missing images if manufacturer source materials have been exhausted. Product managers responsible for their own images within specific departments. This results in inconsistent image specs and quality across a distributor s overall product offering. Completely relying on subscription services, which vary greatly by industry. This inevitably results in high rates of missing images and often achieves lowest-commondenominator image quality.

7 4 PRODUCT TITLES Along with images, product titles are immediate visual cues for online shoppers. Also called short descriptions, product titles should provide as much information in as few characters as possible while avoiding unclear abbreviations. Create programmatic rules to generate product descriptions automatically. Rules can vary by product category so the rule for a power tool product title is different than one for nuts and bolts. After automatically generating product descriptions, copyedit product titles to ensure clarity and consistency. This one-two punch of structured logic and human touch can dramatically improve the look and feel of product navigation. Reusing product titles from manufacturers with little to no editing. These pass-through product titles lack consistency and make it hard for customers to quickly scan lists of titles to find the item they need. Reusing legacy supply chain data with little to no editing. Legacy supply chain data often contains unclear abbreviations and suffers from a paralyzing lack of consistency, accuracy, and completeness. This type of data was not created and intended for use on e-commerce websites. PRODUCT IMAGES & TITLES Missing product images and lack of product titles make it difficult to quickly scan search results. FIGURE 4.

8 5 FEATURE COPY Not all product information can be captured with images, product titles, or structured product attributes. Most manufacturers provide some form of product information in paragraph or bullet form that contains important information about a product, its applications, and restrictions. However, this content (and its usefulness and quality) varies widely by manufacturer. Capture all feature copy from manufacturer source materials, carefully extracting key information to use in structured attributes. With the remaining copy, eliminate language that is marketing focused ( The screwdriver all contractors prefer! ) or overly fluffy ( When was the last time you reached for your tool belt to find your screwdriver was missing? ). Absence of feature copy. This usually happens when there are limitations in web platforms or product information management. Manufacturer-centric or extremely long paragraphs that contain unhelpful or unclear information. This dilutes the quality of overall site content and has a negative impact on SEO. Feature copy from manufacturers published as is to the website without editing. FEATURE COPY Every reseller is using identical feature copy from the manufacturer, which provides little or no SEO benefit. Marketing jargon makes the copy less effective; does an ordinary consumer know what adaptive wash action means? FIGURE 5.

9 CONCLUSION In an online environment, customers don t see the products they buy or the aisles and shelves on which products are stored. Taxonomy and structured attributes are the aisles and shelves, and product titles, product images, and feature copy are the products. Much like brick-and-mortar stores, the organization and presentation of products (together with pricing) will win or lose customers and ultimately drive revenue. The data elements described in this document (taxonomy, attributes, product images, product titles, and feature copy) should be thought of as components in an overall strategy not one-off projects. They are highly interdependent, and distributors that struggle with one of these elements often struggle with many or all elements. In the end, the concept is simple: allow customers to find what they are looking for as quickly and easily as possible. Once they find it, provide the information they need to make a confident purchasing decision. ABOUT CODIFYD Codifyd (formerly ByteManagers) is the leading provider of product content solutions. Codifyd s technology-enabled consulting services and cloud-based solutions enable manufacturers, distributors, and retailers to increase revenue, improve customer service, and gain organizational ability. Headquartered in Chicago, the Codifyd team is fortified with industry domain experts who understand the strategic objectives of data sourcing and normalization initiatives. With more than five hundred projects executed successfully since 1999, Codifyd is dedicated to repeatable, predictable, and sustainable results. For additional information about Codifyd s Product Content Solutions, please contact your Codifyd sales consultant. us at sales@codifyd.com or visit codifyd.com E sales@codifyd.com T F codifyd.com 800 W. Huron Suite 200 Chicago, IL 60642

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