The most attractive opportunity for enterprises is to sell products through digital commerce. Manufacturers, retailers, and other industry are prioritising their budget for newer products and customer service innovation. Research conducted by McKinsey & Co. indicated that 44% of companies are in the process of rerouting their research and development (R&D) budgets towards newer products. This evident expansion rate in the digital product portfolio is creating complexities to the extent that businesses without adequate strategies are failing to withstand.
Once companies understand the full scale of an expanding product portfolio, they realize the importance of figuring out ways and means of handling product information (PI) better than they did. A robust product information management can lead to increased profits, automation-led flexibility, and economies of scale. On the other hand, if a business’ current product information management capability is such that it limits the handling of dynamic product data expansion over time, it stands to impend the company’s digital commerce growth. Ergo, it boils down to a simple decision—scaling the digital assets at their disposal, enabling them to handle product information (inclusive of SKUs) at a rate that corresponds to growth in the product portfolio.
That being said, managing expanding digital product information can be quite the challenge for most organizations – manual processes create opportunities for error and even run the risk of poor execution and engagement across channels. Here are 9 simple tips that can help you deal with the increasing number of products with ease:
1. Streamline Product Variants
Digital commerce helps businesses grow at scale while allowing multi-channel selling. As product portfolio expands, you must have the capability to store and upgrade all kinds of product data, including size and colour characteristics, sourced from a myriad of sources. In addition, it gives organizations an edge by making room for customer-centric product catalogues and quick marketing promotions. With the right set of digital solutions in place, inventory specificities can be managed from various locations to optimize shipping and automate routine tasks associated with product variant handling, eg. size, colour, dimensions.
2. Build Customized Data Flow Modelling
Data modelling empowers operational teams to manage product data and keep their respective SKUs organized through attributes such as category or family. Customised data models can be created for building a more detailed data schema. It can also be connected with the entire business ecosystem through an application programming interface (API)-driven architecture, allowing easy access to all the data throughout the whole product lifestyle. GUI-based data models are mostly preferred that enable to configure new data models within minutes.
3. Improve Data Ingestion / Loading Speed in Real-Time
Data ingestion is a key step in improving product data management strategy. Considering the burdens associated with warehouse management, it is essential that product data management platforms facilitate data loading quickly, efficiently, and accurately. Since PIM platforms serves as back-end systems, an uncomplicated product data ingestion facility allows operational teams (non-technical) to load product catalogues in real-time, irrespective of the product data size and volume. Quick data loading also improves workflow management, minimizes unplanned delays, and optimizes information management across the enterprise.
4. Implement Bulk Data Handling for Different Data Sources
As the product landscape transforms, enterprises need solutions and capabilities to gather and standardize product data from multiple sources. It is crucial to leverage solutions capable of profiling, cleansing, and matching data in a format-agnostic manner. Once product data is fetched, an import schedule can be set in motion, which automatically allows incoming data to be merged within the existing product architecture feed. The idea behind this is to essentially deal with expanding product portfolios in a unified and standardized method by working on new content within the pre-existing operational structure.
5. Ensure Robust Versioning Capability to Provide an Audit Trail
As businesses navigate their growth path and increase their portfolio of products, they need data management solutions that ensure robust versioning capability for smoother audit trail. They need a system wherein a single change within a product record creates a newer version of the same record for an audit trail. Solutions of that sort can be used to compare different versions of each SKU and highlight the differences segregated by field categories. They also allow product teams to accept/decline new versions, restore previous versions, and track modifications throughout the product lifecycle.
6. Keep a Tab on Performance, Scalability, and Availability
Businesses dependent on omnichannel commerce understand the importance of tracking user experience journeys. With an increased digital product portfolio, it is vital to address performance, availability, and scalability issues. Make sure how your system is performing with expanding SKUs, how you can track product availability across different touchpoints from a single place, and how easy the solution is to scale with increasing demands. The in-placed system should be able to address these questions. If the system is slow to perform and hard to scale, it can adversely impact business growth.
7. Ensure Multi-Currency and Multi-Lingual Data Management
Expanding to new geographies demands multi-currency and multi-lingual product data management capability. The power to manage product data with capabilities, such as different currency and language translation, improves business results, and enhances customer’s digital experience in their preferred location. When a standardized authoring, delivery, and analytics process is in place, it will further speed up multi-lingual product content optimisation. The global demand for multi-currency and multi-lingual product data management is rising in priority as large MNCs realize the significant ROI with global expansion.
8. Leverage Automation to Publish Product Information to Multiple Channels
Companies dealing with a massive number of products cannot completely rely on manual processes. They must incorporate automation capabilities to improve product content management, speed up the publishing process, and eliminate manual errors. Not only do businesses stand to gain from automated data uploads but also from the simultaneous publishing of this data across channels which makes the entire scheme of product management cost-effective and efficient.
9. Ensure Smooth Product Data Syndication
Businesses need to navigate their growth by taking complete control of their product experiences. This is where smooth product data syndication comes into the picture. Empowering back-end operations with capabilities of data integration, standardization, product data customisation, and content tailoring lies at the heart of this. A high-performing information management architecture equips systems with all the tools required to execute product data channel strategies. In addition, seamless data synchronization across multiple shopping, marketing, and business channels helps organizations expand on a global level to generate extra revenue.
To Sum Up
Mastering the task of dealing with an expanding product portfolio need not be an arduous endeavour. An advanced framework of handling dynamic product data should help businesses deal with an increased number of products. When companies adopt the right strategy, deploy robust technologies in line with the same, and work upon it relentlessly to improve the scheme of things, the results are out there for grabs that include competitive advantage, customer satisfaction, new or enhanced products, or services, and increased ecosystem value.
Author Bio: Vandana Singal is Director, Solution Consulting at Pimcore Global Services (A Happiest Minds Company). Pimcore is an open-source platform for product information management (PIM/MDM), digital asset management (DAM), content management system (CMS), and eCommerce. She has extensive experience in managing presales, product development, and multifunctional teams.
