Marketing is one of the areas where the use of artificial intelligence (AI) and machine learning (ML) is growing rapidly. This marketing revolution is happening due to many reasons, but mostly because of a growing amount of customer touchpoints, combined with increasing data volumes that make it hard for humans to crunch the numbers. Secondly, micro-moments and fractured buying journeys make it necessary to optimize the marketing message in real time, something that simply cannot be done manually.
AI and ML augment already existing marketing technology, and at the same time, create completely new ways to make marketing more efficient, from real-time personalized merchandising to chatbots that can answer customer questions and take orders. The use of AI and ML within marketing is evolving and is rapidly shifting from early adoption to broad acceptance. Most modern "searchandizing engines," eCommerce platforms, and e-mail marketing tools already use some AI and ML to optimize marketing and sales effectiveness. Voice recognition services like Amazon’s Alexa, Apple's Siri, and Google Home are already assisting us with everyday tasks, including shopping.
Most companies want to sell more products and increase revenue. To do that they need to be more relevant than their competitors when presenting their products to customers in each micro-moment. Relevancy is no longer just about adapting to customer personas; it is about the person. What makes things even more complicated, it is also about the customer’s intent, as some shoppers are prepared to buy and some are only in research mode; some are looking for a birthday gift, and others a solution to a problem. You have to be relevant and tell the right product story to all of them, in their context, in real-time.
The answer to achieving real-time relevancy is not to simply just buy all the new shiny pieces of hyped-up software—especially if you do not have the content in place that can act as the fuel for the AI and ML engines. If you do not already have the content, you need to start by producing it before you can create better customer experiences by reaping the benefits of the new marketing technology. To keep up with new product launches and increasing customer expectations, creating the content is not a one-off thing either. It needs to be an ongoing process that continues to churn out high-quality product stories.
This constant production process of product stories, continuously improving itself to produce more content with higher quality is what I call a "content creation factory." Its sole purpose is to create better customer experiences, fuel all the new initiatives and take advantage of the enormous possibilities that the new AI-powered marketing technology brings. So the time has come to say goodbye to "Product Information Management" because it is no longer enough just to manage information. It needs to evolve into "Product Marketing" as the new purpose is telling better product stories that increase the customer experience by fueling and taking advantage of an AI-powered marketing tech stack.
Johan Boström, Co-founder and Evangelist, inRiver
Today, manufacturers are as responsible for their company’s product information as they are for the physical product. But, as many know, the manufacturing of physical goods is often more efficient and lean than the production of the accompanying product information. The creation of product information is mostly a chaotic and inefficient process, with enormous potential for improvement. This inefficiency in the product information management process is equally valid for managing data and digital assets, creating bundles and kits, and merchandising, publishing and syndication. The cost of the content creation chaos is enormous, and it is time to do something about it.
The lean way out of chaos
Chaotic and unstructured ways of working can cause waste in all sorts of production processes. This waste can increase production cost, cause a loss in sales, and be detrimental to the quality of the end-product. Lean production is a tool used by businesses to streamline manufacturing and production processes. Lean Six Sigma defines waste as any step or action in a process that is not required to complete it successfully; these steps are called “Non-Value-Adding.”
When all waste is removed, only the steps that are necessary to deliver a satisfactory product or service to the customer remain in the process; these steps are called “Value-Adding.” Removing actions that do not add value is, of course, common sense. Lean Six Sigma just provides some useful methods to do it in a structured way and to help refine the processes over time.
TIMWOODS for product information creation
Lean Six Sigma defines eight (7+1) primary types of waste in a process, and there is an acronym—“TIM WOODS”—to help us remember them. Nevertheless, the way that the types of waste are defined in Lean Six Sigma are not entirely applicable to the creation of product information, so we need to redefine the types of waste, so they better fit the creation of product information, rather than the production of physical products or services.
Let's look at TIM WOODS with our PIM glasses on:
The content creation factory
To make product content creation and distribution as efficient as all other production and logistics processes requires that we start looking at product content creation in the same way that we do with all other production. We need to build an efficient content creation factory combined with stellar information logistics. Looking at Lean Six Sigma can be one of many starting points to build an efficient content creation factory.
It is unwise to leap a chasm in two bounds; starting small is always advisable. However, every company that wants to win the battle of the customer must start now. Start with the people in the organization, define an efficient process, and procure the right tools. Lean Six Sigma aims to make the work simple enough to understand, execute, and manage. Having simplicity as a top priority will help you design a reliable, predictable, and repeatable process. Good luck in your endeavors to build your product content factory!
Johan Boström, Co-founder and Evangelist, inRiver
As customer interactions are rapidly moving to the digital channels, organizations need to address the inefficiencies in their content production processes. Shooting from the hip just won't cut it anymore, not even in the creative department. You have to have a disciplined approach to get the right product content produced and distributed to the right channels at the right time. Creating and distributing more content faster cannot be done efficiently using a brute-force approach or by simply adding more people. Instead, it needs to be done by working smarter rather than harder—and finding system support to help you achieve efficiency in your content production processes.
Does your organization require a solution for PIM, DAM, or both?
In their search for a solution that can help them to achieve the required efficiency, many organizations ask themselves if they need a solution to manage their product information (PIM) or one that manages their digital assets (DAM). There are some questions that we need to answer before we can decide that:
Products typically need to be described and augmented using numerous different types of information, such as specifications, USPs, descriptions, documents, up-sells, cross-sells, and much more. This information must be of high quality, be granular, and be very structured. Depending on the industry and product type it also needs to be a part of an ecosystem—for example, as a part of a bundle, solution, repair kit, look, or room. To have a complete and compelling product story it also requires an ever-increasing number of digital assets, from 360 spins and how-to-videos to regular static photos.
We can conclude that we must be able to manage product data and product-related digital assets at the same time. Thus, we cannot choose between PIM and DAM as we need both to support the creation and distribution of a complete and compelling product story. Simply put, a DAM cannot manage the product data and the product ecosystem, so as long as you're not selling images, going with just a DAM to manage your product information will not be sufficient. Do you need two separate solutions? To know that, we need to define more granular requirements.
If you do not manage large volumes of digital assets that are nonproduct-related and choose a PIM solution with strong built-in DAM capabilities, you most likely don't need a separate DAM. The built-in one will be sufficient and already tightly integrated. However, if you do manage large volumes of nonproduct-related digital assets, you should consider adding an enterprise DAM solution and integrate that with your PIM system. The integration with a PIM is necessary as it will drastically reduce the metadata maintenance and automate the distribution of the assets to the channels.
How to manage the selection and review of assets?
WIP, short for Work In Progress, usually represents the first step of the creative workflow, right after or during the photo shoot, but before final delivery to a PIM or a DAM. Sometimes I meet with organizations that believe they need a DAM, when in reality, they are need of a Work In Progress system. A tool that manages the WIP process can be used to streamline review and approval for digital assets and make the selection process easier and faster, so it makes sense that some DAM solutions have this built-in as a feature. Whether you choose to integrate a DAM or use the built-in one in your PIM, adding WIP process support can provide additional efficiency gains.
Whatever you do, don't hamper your sales by shooting from the hip in the content creation process.
Johan Boström, Co-founder and Evangelist, inRiver