With proper big data analytics, marketing could more effectively push relevant content, drive sales, and boost productivity. Here's how.
For manufacturers, distributors, and retailers, managing the supply chain for best results is the lifeblood of the company. For at least six decades, companies have used systems to track and control the flow of goods from point of manufacture, through transport to distributors, then to retailers—and finally, into the hands of the end customer.
Meanwhile, marketing is often detached from the supply chain and often doesn't have access to data on supply chain issues such as manufacturing schedules, or returns to distribution centers, or buying trends in specific stores. Unfortunately, this can lead to lost opportunities for revenue via targeted marketing campaigns.
Rick Chavie, CEO of EnterWorks, which provides data navigation solutions for B2B and B2C distributors, describes the need for a "supply chain of content."
"Everyone working within the supply chain has one objective," said Chavie, "And that's to get product pushed out and into the stores or online sales sites as quickly as possible. However, now that retailers are operating in a more customer-centric world, they are beginning to realize that they can improve sales performance by pushing the right content to customers at the same time that they are pushing their product. They can do this if they have a better understanding of what their customers want in different retail channels."
What Chavie is referring to is a different use of big data besides its already well-established role in analytics.
Instead, in the "content supply chain" big data model, different parties at different points of the supply chain begin to collaborate with each other on content delivery that includes "big" or unstructured data like images and marketing collateral as well as product delivery.
As an example, a distributor in the southeastern United States notice that consumers in the area are getting their gardens ready earlier this season than usual. That observation would be routed to marketing, which uses a content management system that stores its non-traditional, object-based big data such as images or videos in a database. This content management system would be tightly integrated with the company's supply chain system so that content on flowers and seeds can be directly routed to the distributor. The distributor would then pass the information on to retailers in its local network.
Here are four steps to begin creating a content value chain:
1. Organize product images, marketing collateral, etc., in a big data object database that can be readily accessed by a content management system.
2. Integrate this content value chain with the supply chain system (some vendors have this ability and others have it on their roadmaps) so the two systems can begin to work close together.
3. Work with marketing, manufacturing, sales, distributors, and retail outlets to establish business process changes that create open communications lines on new product launches and sales campaigns.
4. Establish metrics that gauge whether content injections at key points in the supply chain are building revenues. (For example: Did the injection of more feature-specific information on product X that store XYZ requested cause sales to spike upward?)
"The key to making the strategy work is to have unstructured data in the form of images, collateral, etc., that you want to use, and also a way to manage this content so it can be plugged into the supply chain when and where it is needed," said Chavie. "By doing this, companies can align their marketing content with their supply chains so they can proactively act on the answers that their analytics give them to questions like: How does my product relate to this particular customer, or customer location, or store, or device?"