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The Art, Science & Software Behind (Optimal) Retail Pricing - Par...
The Art, Science & Software Behind (Optimal) Retail Pricing - Part 3
November 20 2009
Part 1 of this blog post series
expanded on some of
’s earlier articles about companies’ need for better pricing management and optimization practices. This series, which focuses on the complexity of
, was inspired by
’s recent “edu-nouncement” on leading retailers' consumer-centric pricing and promotions strategies
’ recent (and still ongoing) educational series of Web-seminars
Part 2 of this blog post series analyzed some common retailers’ practices and explained some of the frequently used vernacular
. Then the post went into the building blocks of pricing optimization, starting with setting optimal initial (everyday or base) prices.
Part 3 of this blog post series will analyze the two other building blocks of pricing optimization: promotions and markdowns. Then, the article will go into the next generation of pricing optimization according to JDA: "Lifetime Pricing."
Increasing Sales with the Proper Promotional Pricing
When used in a smart way, promotions can be powerful tools for increasing customer demand and thus sales and revenue. As is the case with setting
basic initial prices from Part 2
, to set optimal promotional prices, retailers need to understand a wide range of variables. In addition to the phenomenon of the
“cross elasticity” of demand
, competitive activity, and
, retailers need a thorough understanding of the uplift of demand on other products.
Price changes and the marketing associated with them can have enormous impact on demand. Companies using advanced pricing systems have the ability to proactively plan for this lift, ensuring that inventory is readily available during the promotional period, and that sales opportunities (and customers) are not lost. Forward-thinking retailers use
promotion planning and optimization
solutions to also evaluate and forecast the likely results from incoming vendor offers, as well as to plan
and other promotions.
Promotion planning and optimization solutions enable retailers to create and simulate multiple scenarios based on mathematical forecasts of results in order to evaluate tradeoffs among various promotions such as discounts, advertisements, and in-store displays. The optimizing process should be able to predict consumer reaction in terms of what items the retailer should promote, what exact offer it should run, and what its expected sales, margin, profit, and ad loss will be.
Moreover, the retailer could be able to discern how different optimization strategies would impact the forecast as well as to determine the actual versus forecasted results. Key features of promotion planning and optimization solutions typically include:
category plan and master calendar management
-- the ability to generate, view and forecast promotional calendars, taking into account factors such as cannibalization of regular priced items, concurrent promotions, and the pantry-loading effect of successive promotions (as explained in
promotion offer support
-- the ability to enter key promotion performance details that drive promotion response, as well as
consumer packaged goods (CPG
) vendors’ allowances that drive financial performance for individualized promotions
event and tactic management
-- the ability to plan and manage different promotional events and capture individual performance details such as holidays, in-store features, and in-store displays
pre-configured outbound interfaces
-- the ability to export promotional forecast information to
supply chain management (SCM)
systems, promotional details to advertisement execution systems, and other details to other customer systems
Optimizing Markdowns: A Tricky Balancing Act for Retailers
Even without the current economic turmoil leading to decreased consumer spending, consumers (myself included) have long been accustomed to mostly buying when items are marked down or are on
. Thus, retailers should strive to shift the consumer mindset in terms of markdowns.
Because they create a continuous cycle of lost margin on sales, markdowns should be the last thing that any retailer does in order to get goods off the shelves. The reality, however, is that inventory occasionally must be cleared in order to make room for new items, but retailers need to assess the true profit margin impact. Typical candidates for markdowns are the following: seasonal merchandise (e.g., Halloween paraphernalia or sun-tan lotion), discontinued merchandise or assortment changes, dated products, store closings or department liquidation, inventory resets or forward buys, aged product packaging, and in-and-out inventory sales opportunities.
In other words, retailers must carefully assess the true margin impact of markdowns and partake in the ultimate balancing act in price setting. Tailoring markdown plans by store/location, factoring in the price sensitivity of the customer base, and understanding opportunity costs are essential.
software solutions enable retailers to optimize plans and prices for those items they intend to remove from their assortments, such as end-of-season items, discontinued product lines, or overstocked merchandise.
Retailers use markdown optimization software to eliminate excess inventory by a specified date after which an item will no longer be sold and to maximize profitability of items sold before that date. Retailers should be able to monitor inventory and pricing for selected products and date ranges so that they can achieve the desired liquidation of inventory.
They should be able to view forecasted sales, sell-through, and expected margins. For example, knowing how a 25 percent markdown today will prevent a 50 percent markdown in two weeks is critical to the decision-making process.
Having a comprehensive view of demand with the right pricing optimization solution can make this possible. Equally important is setting localized markdowns based on customer demand at the individual store level. According to a
recent survey from the
National Retail Federation (NRF)
Wall Street Journal (WSJ)
, 33 percent of retailers surveyed said they plan to install markdown optimization software systems over the next 18 months to help calculate discounts according to local demand.
Typical features of Markdown Optimization suites should include:
-- the ability to create and forecast multiple scenarios in order to evaluate tradeoffs between the timing and depth of markdown prices, as well as other factors such as the number of markdowns taken within a time period;
-- the ability to configure markdown-specific rules; and
-- the ability to re-optimize plans and prices on a weekly basis to adjust for changes in demand and inventory position.
In addition to increased sales volumes and profit margins (from increased income on clearance items and vendor promotion dollars), potential benefits from everyday price optimization could come from reduced out-of-stocks due to more accurate forecasts of promotional lift. Improved forecasting also helps with fine-tuning promotions to hit financial objectives in advance, while productivity can also be improved by learning from the promos of the past and the associated automated reports.
Looking Into Next-generation Price Optimization Solutions
The aforementioned price optimization building blocks can set initial, promotional, and markdown plans while factoring in demand, consumer demographics, cross-product relationships, and convenience sales. Sure, it’s also critical that pricing decisions are not made in a competitive vacuum. By leveraging competitive pricing intelligence these companies have the opportunity to improve the price optimization decision-making process and to drive more effective revenue generation.
Once the areas of initial, promotional, and markdown prices have been addressed, they form a solid foundation for effective lifecycle pricing. Namely, the next step is to integrate price determination with promotional planning and advertising execution strategies to create streamlined
within the retail organization.
JDA Software refers to this next evolutionary step as
, which plays an essential role in creating a valuable customer-centric retail environment. A united planning and execution platform – from accurate price management to advertising and promotional planning – can easily adjust to shifting customer demand and challenging economic conditions.
Most retailers agree that customer-centricity is a top priority to achieving success and competitive differentiation in today's crowded marketplace. One key component of a customer-centric experience is to successfully implement lifecycle pricing. Along with well-defined pricing strategies, these lifecycle pricing initiatives provide retailers the opportunity to streamline workflows, customize promotional strategies and deliver a consistent price message to their customers.
As a result, retailers can improve customer satisfaction and, ultimately, revenue generation even in tough times. They’re also gaining new insights into how customers shop and respond to pricing, which enables them to align inventory levels with baseline and promotional demand.
Explaining the Pricing “Rocket Science" (Sort Of)
Most advanced science-based lifecycle pricing software applies advanced
in several areas. For example,
Consumer Demand Management (CDM)
is available in versions tailored to the needs of retailers and consumer packaged goods (CPG) manufacturers. The vendor’s applications, which include tools for managing pricing, promotions, and markdowns, leverage the following sophisticated statistical analytics methods:
. The CDM software uses complex
models designed to predict more accurately the sales volume of products under varying merchandising conditions and at various prices, which enables retailers to determine the factors that influence consumer demand for a given product and location, and to what extent. The vendor’s proprietary demand models quantify consumer response to different merchandising and marketing activities, environmental factors and elements of consumer behavior across various consumer segments.
models are able to capture the complex underlying relationships between consumer demand and the factors that influence that demand.
Consumer-centric Merchandising and Marketing
. As mentioned many times before, individual consumers and particular consumer segments respond differently to price changes for different items. By applying various
and statistical techniques to analyze sales data and combining the results with additional data such as demographics, buying histories, and item affinities, DemandTec software enables retailers to understand consumer and
more fully, to determine more effective product assortments, and to design more individualized promotion offers. These techniques enable retailers to make more granular, and therefore more effective, merchandising and marketing decisions.
Forecasting and Simulation.
DemandTec’s forecasting software enables retailers to determine the likely revenue, profit, and sales volumes for specific product categories, brands, or promoted groups at the store/item level for a given set of prices and merchandising conditions. The software does this by incorporating and analyzing factors such as localized merchandising categories, product distribution, assortment and complementarity, cannibalization, stockpiling by consumers, equivalent volumes and discrete events such as holidays. The software also includes an
activity-based costing (ABC)
model to quantify and forecast the store/item level margin impact caused by varying supply chain costs.
Optimization and Rules Enforcement.
While demand modeling is a powerful tool that can provide quantifiable benefits, achieving those benefits would be difficult if the CDM software relied solely upon modeling, because of the large number of possibilities that models generate. DemandTec’s optimization science uses a combination of complex
to help customers determine prices, promotions and markdowns that best accomplish their objectives, while complying with their
. These algorithms are designed to ensure accurate results and incorporate rule relaxation that automatically resolves conflicts in business rules according to the customer’s preferences.
Part 4 will continue the blog post series by analyzing the pricing optimization vendor landscape and various vendor approaches to the next generation of pricing optimization solutions. Your views, comments, opinions, etc. about any above-mentioned pricing solution and about the software category
are welcome in the meantime. We would also be interested in hearing about your experiences with this nascent software category (if you are an existing user) or your general interest in evaluating these solutions as prospective customers.
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