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Alina Virstiuk
Written by
Alina Virstiuk
Guest Author

Product Content That Matters: Solving Retailer And Brand Dilemma

11 min read
Published: October 27, 2022
Updated: April 5, 2023

Product content is at the heart of every shopping experience. Innovative and rich information that influences a buyer’s journey is the goal of every retailer and brand that understands the importance of content in a data-driven world nowadays. The more eCommerce businesses grow, the more data they have to handle, which in most cases equals the growing data challenges.

In this article, we’ll closely review the most product content challenges, such as its quality, content syndication, validation, data granularity, and taxonomy management. Moreover, we will focus not only on how to create content that matters but also on how to distribute it automatically in order to improve its quality and reduce the number of errors and employees’ hours. Let’s start with the definition of product content.

What Is Product Content?

Product content is any information that relates to the product and is provided by a brand or retailer to consumers. It can include basic product information, logistics data, product features, and technical specifications, marketing texts, rich content (videos, images, manuals), product configurations, and reviews.

Key Challenges In The Content Journey

#1 Data Quality

Considering high-quality product information as a destination instead of a journey is one of the most frequent content challenges for many businesses. Improving data quality is an ongoing process that should be taken seriously. Some of the main aspects that influence data quality are the following.

Increasing data overload and manual data management

Big volumes of data, especially managed manually, create a risk of inconsistency, and inaccuracies, which results in nothing good: customers lose their trust in the eCommerce business, churn and go shopping in competitor stores. Managing product data manually leads to team burnout and human errors especially if companies do not look at things realistically and do not expand their data quality team or lack automation.

Not involving data validation tools

The product data loses its quality when it is not validated, especially when being distributed across different points of sales. As a result, such data is inconsistent and brings no value to potential customers: buyers who see product data discrepancies on the brand’s webshop and retailer’s website, lose trust in both manufacturers and retailers.

Neglecting data granularity

This measure, which shows the level of detail in the data structure, is a key to well-managed product content. Yet, managing product information on a granular level is one of the top challenges for businesses. Neglecting data granularity does not allow them to implement customer segmentation and target the right groups of customers.

Not considering digital shelf monitoring

Not automating data monitoring is a big failure for many businesses. Tracking your product content with a digital shelf analytics tool not only helps you address and detect any data issues but also ensures that you and your team catch any data inaccuracies and other problems before your end users do.

#2 A Single Source Of Truth

For every business, to ensure effectiveness and competitive advantage, and get the most out of their data, it’s critical that all stakeholders and decision-makers are using the same data. For that reason, they need a single source of truth which is one of the top challenges for brands and retailers.

Statistics prove the importance of having a single source of truth for a company: according to Autodesk, 52% of rework in business is caused by weak data and miscommunication. Yet, creating a single source of truth (SSoT) can be accompanied by such challenges as:

Not having an understanding of the issue

Due to a lack of knowledge about product information management, the employees might be underestimating the importance of having an SSoT for business, as well as not knowing how and which information to input into a system.

No proper workflow

Not having an established process for data collection and preparation before its input in the single system, together with multiple content entries and data inconsistencies might lead to misunderstandings and reduced efficiency.

Not enough experience

Lack of training leads to numerous data errors such as not having properly formatted information for the input, or not knowing how to handle the content coming from different sources. Sometimes low capacity is a blocker as it might be too much data for one person.

Data standardization issues

Having big volumes of data being input into a system in different forms and standards complicate the whole process and leaves many employees confused about what to do next and how to make the content accessible to everyone.

The solution lies in finding a system that can serve as a single source of truth offering many automated features such as data collection, verification, and standardization. What’s more, this solution should be easy to maintain and simple for onboarding non-technical users.

#3 Content Exchange And Syndication

The forced digital transformation also affected nowadays retail system: selling on multiple emerging platforms is one of the keys to successful eCommerce and, at the same time, a reason for one of the most frightening data challenges: exchange and syndication.

It’s not enough to own product content. Businesses need tools to orchestrate the product content, to share it with partners and end-users confronting the unique requirements of each channel.
Sergey Shvets
Sergii Shvets
Founder & CEO at Gepard

Some of the main challenges of data synchronization include the following.

An extensive amount of products

Businesses with hundreds and thousands of SKUs sooner or later experience difficulties in managing their product data, especially when it comes to distributing their products to different marketplaces. On top of that, they have to constantly check if the content is error-free to avoid any misunderstandings and be sure to provide buyers with enriched compelling content that boosts sales.

Too many industry standards

One of the critical issues for companies that decided to sell on many platforms is adjusting their data to a variety of standards and formats. Trying to become compliant with numerous industry standards and at the same time deliver product content in the required format puts many businesses at a loss, especially if they have not implemented an automated syndication solution yet.

Not having a proper data syndication strategy

There’s no chance for a consistent buyer experience if the business does not plan thoroughly its data syndication strategy. Without proper data analysis and preparation, setting expectations, and preparing a checklist for your future content syndication solution, any attempts to imply a successful data delivery and synchronization will go down the drain.

How can businesses anticipate the constantly changing requirements of different marketplaces? A flexible PIM solution with a content syndication feature, like Gepard, can solve this problem by offering data delivery to multiple sales touchpoints and adjusting to the necessary formats.

Content Journey Challenges

#4 Company-Specific Challenges

As the eCommerce market constantly grows, so does the number of data regulations for different business industries. Handling regulatory requirements is not easy, especially if there are many amendments to them. Companies have to keep abreast of any upcoming data regulation updates in their industry and apply prompt changes to their data.

Adjusting to industry-related standards, such as EPREL for any products with an energy label, Pi-Standard for the manufacturer and home appliances, ETIM for global industrial manufacturing, and many more is a must for the sellers who want to keep pace with the competitors and be able to legally sell their products to a wider audience.

Product Data: Brand And Retailer Dilemma

When two parties are involved in the process of product data management and exchange, there are always different views and expectations. So what do brands and retailers expect from product data, and what are the common pain points for them?

Brand Side: Consistency In Everything

Consistency in everything is one of the most important things for a brand and should be implemented in the following things:

  • The content itself has to be of the same quality across different sales channels and marketplaces;
  • Great product governance across new and existing goods;
  • Product data delivery across multiple platforms should be simple and with minimum manual efforts: brands do not want to spend time on manual product information distribution, and would rather use an automated system for product push.

Retailer Side: Product Content Adapted To Their Needs

When it comes to retailers and marketplaces, they have different expectations from product content, where one of the top-priority matters is getting the data adapted to their requirements and needs. The following list of things is of high importance for retailers:

  • High coverage of engaging content to convince potential customers;
  • The data intake process should require minimum efforts from retailers;
  • Product data should be already adjusted to retailers’ requirements, so they won’t have to manually standardize and edit it.

Instead of managing manually endless product data sheets, retailers actually want to add a personal marketing touch to the content, so they can feel that they own it. Retailers can get more free time for this creative task if the above-mentioned tasks are automated and running smoothly.

Reaching Common Ground: How To Solve The Data Challenges Of Brands & Retailers

So how do we sort out these different content expectations of brands and retailers? Here are some ideas that help to improve the data flow for both sides.

1. Maintaining data on a granular level

This point is important to both parties, as the high level of data granularity is key to well-managed product data. Looking at content through a granular lens ultimately increases the efficiency of your data which should be accessible for further analysis. It allows brands and retailers to go deeper into detail, examine their business performance and make more targeted adjustments to their product content that which leads to boosted profits.

2. Bringing marketing into the taxonomy development lifecycle.

This includes listening carefully to consumer expectations and adapting content and product taxonomy to them. For brands, it means also adjusting content to the requirements of retailers, while the latter have to better communicate with brands and explain their data expectations, especially if they want to receive unique product information from brands.

3. Involving a taxonomy manager.

A key to successful data entry for brands and retailers is hiring a professional responsible for product taxonomy development, keeping the data structured and organized, and bridging the gap between different taxonomies of brands and retailers. Involving a taxonomist works in tandem with the other important step – employing a flexible PIM solution.

4. Setting up a product information management system.

Having a PIM solution flexible enough to support taxonomy requirements and automate content delivery and intake is one of the critical things for brands. At the same time, it’s equally important for retailers to have such a system that can automate data import from brands and other suppliers.

Implementing PIM is one of the recent trends in product content management that we’ll review closely in the next section of the article.

Content For Brands And Retailers

Key Trends In Product Content

The growth of product data challenges for retailers and manufacturers results in new product information trends. They all are inevitably connected with content enrichment, automation of content delivery, and employment of product information management systems. Let’s have a closer look at some of the major product content trends.

#1. The Growing Popularity Of Rich Content

An eye-opening statistic about B2B content consumption is not good news for content makers. According to research by Influence & Co, readers spend an average of 2 minutes and 2 seconds on a resource they’re interacting with. Moreover, they only consume approximately 53% of the offered content. So how difficult is it now to keep the attention of a potential audience? This is a tough row to hoe, especially considering the amount of marketing noise surrounding the users.

High-quality yet static product content is not convincing enough for a picky audience. That’s why rich content is growing in popularity. Rich data refers to different media types such as images, videos, sounds, animations, and any other visual or interactive elements, used simultaneously and in the same place.

According to statistics, 57% of data consumers are more confident about their purchase after watching a video. Another impressive statistic by Drip says that 3D product images increase conversions by 250%. That’s why investing in visual content is crucial for businesses that want to engage more audiences. Apart from that, there are numerous tactics for enriching your product data, such as organizing it into categories, providing certification information, and product attributes, using tags, and more.

Read more about data enrichment tactics:

What Is Data Enrichment In eCommerce?
8 min read
Yuliia Honcharova
Product Information Management

What Is Data Enrichment In eCommerce And How Can You Benefit From It?

What is data enrichment and why does your eCommerce need it? Find out the key benefits of product data enrichment and how you can put it to practice.

data enrichment product content product data

One of the most effective ways to enrich your product data is investing in a product information management solution.

#2. Implementing A PIM Solution

Product information management solution is not a new word in the eCommerce world, yet its popularity is constantly growing: it’s forecasted that the PIM market will reach $59.25 billion by 2027.

Managing hundred and thousands of SKUs, enriching product information, and standardizing and validating it can be a daunting task, even with the best set of resources at your disposal. That’s why brands and retailers add PIM solutions to their technology stack. What are some product data challenges that are solved with the help of PIM? Let’s use the Gepard PIM tool example to review the most important features of product data management software.

  • Data validation feature that prevents businesses from costly data errors, boosts product information management flow and helps brands to send accurate data to retailers.
  • Data standardization allows retailers to regulate the data coming from different sources and ensure it’s automatically adjusted to the universal standards.
  • Data enrichment option helps sellers to optimize product content coming from various channels, improve its quality and SEO performance, and enhance the shopper experience with the help of compelling rich content.
  • Automated content collection feature for seamless data gathering from multiple brands and webshops, without manual efforts.
  • Content syndication for automated data input and content distribution to various sales platforms, while conforming to dissimilar retailers’ requirements.

#3. Automating Product Data Delivery

A PIM solution that serves as a single source of truth is a worthwhile investment, though for eCommerce players that want to build an effective omnichannel presence it’s not enough. The ever-growing amount of eCommerce platforms and marketplaces and the desire to outpace competitors and sell through a variety of sales channels made it crucial for businesses to automate their content delivery.

That’s the reason why seamless data syndication is a big trend among brands. More and more manufacturers are searching for a PIM solution that can syndicate their product content, which means their product fees will be automatically delivered to any chosen marketplaces, adjusted to their unique taxonomy, and standards & formats requirements, and regularly updated. Automated product content delivery becomes a trend for companies who appreciate their human resources: instead of manual data push, their employees bring value to the business with their strategies and new ideas.

Key Product Content Trends

Product Content FAQ

What Is Data Granularity?

Data granularity is defined as the level of detail in the given information. The more granular your data is, the better the results of data analysis, insights on sales, and overall business performance. It is especially important for more precise customer segmentation in eCommerce. Brands and retailers that want to develop better business strategies, have to focus on making their product data more granular.

Do I Need Product Taxonomy Development?

If you are a brand or retailer, it’s vital for you to pay attention to your product taxonomy development. In eCommerce, it refers to organizing all your available products in a certain hierarchy to make it easier for customers to find them. A Forrester research uncovered that sales platforms with poor product structure sell 50% less than well-organized ones. Improved product taxonomy boosts customer experience and results in better sales.

How To Create Product Taxonomy For My Business?

Taxonomy development includes two important steps: implementing a flexible PIM solution that can support your taxonomy requirements and centralize this process and employing a seasoned expert – product taxonomist who specializes in classifying information based on established hierarchy. An experienced taxonomy developer can integrate PIM and other data systems to develop new categories insights and improve data quality.

Gepard PIM Solution: Handle Content That Matters

McKinsey Global Institute Research found that data-driven businesses are 23 times more likely to get new customers and 6 times more likely to retain customers. How to keep being creative and work productively on strategic tasks with the ever-growing amount of product data that brands and retailers have to manage? Automating data-related tasks with the help of a PIM system such as Gepard can solve this challenge. With its extensive functionality, including data validation, standardization, content enrichment, seamless data synchronization, and digital shelf monitoring, Gepard PIM is a universal tool for both brands and retailers.

Are you ready to fully embrace the power of product information management solutions and provide your customers with content that matters? Request your personalized demo now and Gepard specialists will consult you about your special business needs.

How To Solve My Product Data Challenges?

Alina Virstiuk
Written by Alina Virstiuk
Guest Author
Passionate about travelling, books & photography. Enjoy working with new things and meeting people from all over the world.

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