Corey Mellick, CEO at Amplifi
By now we all understand that MDM is a journey; it is an on-going program for improvement of data to satisfy business objectives best. Many customers of MDM for Product, or PIM, often ask us how they will measure the effectiveness of the data, and how they will identify areas that need further improvement once they are up and running. Of course, it varies by engagement and by the intended use of the data, but we frequently tell them to listen to the data. Let the data use itself guide your improvement efforts. This is particularly true when the target use case is a digital channel.
Your online channels are likely only one intended use for your MDM program, but frequently it’s a use that has quite a bit of management attention, and it is often a primary driver when justifying the program. The reason most executives focus on this use is that it affects the top line. It’s about increasing revenue through the use of MDM to optimize the data, and, as you will see, it is relatively straight-forward to assess and prioritize on-going performance.
In an online channel, there are two primary things you are trying to accomplish: you want customers to find the products they are interested in, and you want them to purchase them when they do. We call that “hits” and “conversions.” And, nothing is going to have a more significant impact on hits and conversions `than accurate, complete, compelling product data.
To begin the discussion, we want to think about the end user of the data, in this case, potential customers. In “The Forrester Wave: Product Information Management Solutions, Q2 2018”, the analyst firm Forrester presents a model that describes the customer purchase journey. They talk about the journey in terms of “Discovery, Knowledge, Conversion, and Usage.” In other words, finding the product, learning about the product, buying the product, and using the product. At each step, they illustrate the type of data supporting the customer journey, such as part numbers, descriptions, copy, features videos, images, etc. Thinking about your customer’s journey is a great way to begin to identify the data you will need to manage in your MDM system. Putting it into practice will also provide great insight into how well you are supporting that journey, and, therefore, which areas you need to focus on for improvement.
When the use case is an online channel, we have the benefit of collecting constant feedback on the efficacy of the data through the same metrics you are probably using to measure the site – hits and conversions. Here we can let the data inform us about what is working, and where we need improvement. The figure below illustrates a model for grouping products into four quadrants where conversions are along the x-axis and hits along the y-axis.
By identifying which products fall into which quadrants we gain valuable insight into the effectiveness of the data.
Lower Left (Low Hits, Low Conversion) Potential customers have to find the product before they can purchase it. Products that fall into this quadrant are likely just not being found on the site. Most often this is a function of the search engine, and the search engine is simply using the data from the MDM system. Search engines tend to use part numbers, descriptions (short, long, marketing, etc.), keywords, features, etc. when trying to match results to a customer query. Try reworking those data elements to better align the products with the terms being used or adding keywords such as industry slang terms. The emphasis here should be to get the hits up first, then follow-up on conversions once you have additional experience with them from the increased hits.
Upper Left (High Hits, Low Conversion) These products are being found, with some frequency, but for some reason, the customer is not purchasing. There may be several factors in play. First, the descriptions may be misleading, i.e., it’s not what the customer thought it was. Look a bit deeper and examine the search terms that lead to the product if there is a disconnect between those terms and the product, fix-it, most likely in one or more of the descriptions. The other thing that could be going on is that there just may not be enough data for the customer to confirm this is the product they want. You may need more specifications, documentation, product FAQS, or digital assets, such as images or videos. Examine those products in the high conversion quadrants to understand what content is driving success there.
Lower Right (Low Hits, High Conversion) Here we see that if we can get customers to the products, we have the content, or data, that sells, we’re just not getting many people there. Similar to the first quadrant we looked at, this is likely an issue with descriptions, keywords, features, etc., i.e., data being used by the search engine. Again, we want to focus on driving the hit rate up by aligning the data to customer search tendencies. We can look at what they search for when they find the product for clues into necessary changes.
Upper Right (High Hits, High Conversion) Nirvana, the sweet spot, we have the right data to support the entire customer purchase journey, and the results are increasing revenues. Many will treat these products as good to go and focus attention in the other quadrants. But there is low-hanging fruit here, and data to be fine-tuned in the MDM system, that should not be ignored. These products are highly desired and are getting high visibility, and they are ideal candidates for aggressive associations, such as up-sells, cross-sells, accessories, etc. Spend time in the MDM system building those relationships to see even greater revenue opportunity.
What we are doing here is “listening to the data,” we’re letting end-user behavior and experience with the data inform our MDM program. This is a relatively simple product data to digital channel example, however, whether it is Product, Customer, Employee, or other business data object, view you MDM program as a journey, and let the data usage tell you how effective the program is, and what areas need your attention.