This strategy revolves around much more than product. We have always said that the customer is king. While this is the theory among retailers, the systems we use and the hierarchy around them all revolve around product categories and not around consumer intelligence and segmentation.
Customer-centric merchandising involves taking granular demand intelligence and weaving in high level financial planning. Decisions made at the home office must be executed at store level in a seamless manner.
An AMR Research survey of 150 merchants found that only 59 percent of product and promotional decisions are executed in the intended fashion. That 41 percent that is not working equals about $1.1 trillion in sales that are at risk. Using granular information will allow us to build a plan that makes sense.
What is different now in concept? First of all, we are looking at future demand versus retail history alone. We are using internal information about what we know. We are leveraging customer and loyalty program information as well as external data from suppliers, partners and other data sources.
Three components are emerging that connect the corporate level to the store level. The first, assortment management, is the business driver behind localization of product offerings. The second, lifecycle pricing and promotion, is an integrated way to look at the initial price, the promotional price and the markdown price. The third, common demand forecasting, involves pulling all of this together to drive decisions involving everything from forecasting and pricing to replenishment and even labor.
The first component, assortment management, involves localization. It is not just about justifying a buy quantity. Macy's, for example, is opening a regional buying office in Indiana. Macy's realized that what consumers are buying in Indiana, along with the sizes and colors they want, is a lot different than what is happening in the rest of the country. How can New York or Pittsburgh make decisions about what is happening in that local area?
We are looking at the idea of clustering stores. It is really difficult to get to store and SKU level granularity -- although we use that information to understand how we can package products and get them to the store to optimize inventory. We are all thinking about pulling back inventory levels. We can confidently do that if products are in the right place.
Pricing decisions should be thought about in a way that infuses the base, promotional and markdown pricing phases into the planning process. This looks at the optimal price of a product -- or a group of merchandise -- through each stage of its existence.
"Whay if" analysis is used to explore scenario planning based on potential decisions. What if I put Oreo's on sale at this price? What is that going to do to my milk? What if I put diapers near beer? Will that have a halo effect?
Supplier trade funds should be factored into the equation. Should I take that product supplier's offer or should I consider taking that offer in another week or should I negotiate and try to find something better to do?
Price execution also is a critical component. It is good that we are coming up with the best price. But if we can't get it down to the register, if we can't get it down to the shelf level, if we can't use that information to build a bottom up demand forecast, all our labor will break.
Ad placement is essential as well. What happens if we put an ad or product in the top right corner of the front page of a circular? What impact will that have on demand? What if we put a product on the home page? Those decisions need to be brought together in the execution.
Proactively handling markdowns will allow retailers to drive behavior and ensure that markdown initiatives are optimizing margins and making room for seasonal merchandise as demand comes into play. We are certainly seeing a blurring between the initial, promotional and markdown prices.
Then, there is demand intelligence that is infused in a common and standard way throughout each merchandise process. Rather than generating and using consumer insights in a disjointed manner, retailers should use a unified intelligence and forecasting technique so various constituents in the extended retailer ecosystem are making decisions from a common set of data.
In this hyper competitive retail environment, organizations may leverage consumer insights to make product, labor, marketing and real estate decisions. Applying this intelligence to
assortment planning, pricing, promotions and forecasting activities will lead to consumer-