Category Management is undergoing a quiet revolution. Gone are the days when a category manager could trust in intuition and experience alone. The new generation is embracing Retail Science to make better price, promotion, merchandise and assortment decisions. Retail Science applies sophisticated data analysis to help better understand what customers want. Data sources include Point-of-Sale (POS), Transaction Log (TLOG), competitive pricing, panel, syndicated, weather, demographic, and location attributes. Data cleansing, quality assurance tests and outlier analysis are essential for measuring causal relationships. The result is a demand model that accounts for price elasticity, promotional lift, merchandising, seasonality, cannibalization, affinity, space, and assortment. Category managers use this demand model to evaluate and compare scenarios. For example, a supplier may offer a incentive to promote Cheerios. The category manager can evaluate the category profit accounting for vendor incentives, cannibalization, and affinity.  This analysis shows how cannibalization of private label erodes category margin. Even the impact on loyalty customers can be evaluated in terms of basket size and trip frequency by customer segment.

Other examples where Category Managers are leveraging Retail Science include:

Store-Zone Clustering.  Stores in proximity to competitors, population density, household income, median age, and other factors influence customer behavior and sensitivity to price. Store zone clustering identifies the optimal store zoning and can improve profit by 1% of sales for some retailers (higher profits have been realized and this benefit is above and beyond that from price optimization alone). This analysis is based on category-store price elasticity and takes into account demographic data, competitor data, and store attributes. The principal components driving a store into one cluster versus another are evident from this analysis.  For example, zone one may be characterized by highly price sensitive, middle-income, densely populated, customers with a given ethnicity ratio and strong competition from Walmart within 2.5 miles. The strength of each of these factors in driving a store into a given zone is evident from the analysis.

KVI Items. Key Value Items (KVI) have the greatest influence on customer price perception and represent an important segment of a retailer’s business. Frequently, just 10% of a retailer’s items account for 90% or more of customer price perception and have the greatest influence on traffic. These items can come from many different categories and there can be multiple groupings. Examples include highly sensitive items, competitive items, traffic drivers, and basket builders. Retail Science can be applied to identify the top KVI items combining item profit and sales with price elasticity, market-basket analytics, and syndicated data. Understanding which items are the “true KVIs” and positioning them aggressively yields the most return while allowing the freedom to price non-KVI items in line with margin targets.

Pricing. Price elasticity relates the change in units to the change in price as indicated in the table below.

Price Elasticity      Price Change      Unit Change

1.0                          -10%                     +10%

2.0                          -10%                     +20%

0.5                         +10%                        -5%

Retailers can realize more profit and sales by increasing the price on items with low price elasticity and decreasing the price on items with high elasticity. The first step is to identify the category role and strategy. For example, some categories are identified as Convenience, Traffic Drivers, Margin Enhancer, and Turf Protector in this source from AC Nielson:

Consumer-Centric Category Management.  Hoboken: John Wiley & Sons, Inc., 2006

Willard Bishop is especially strong in working with retailers to identify how best to define category roles and map those roles into strategies that can leverage Retail Science. These strategies and the science account for Private Label to National Brand Gaps, Good-Better-Best relationships, Ending Numbers, Price Chance Frequency, Minimum/Maximum Price Change rules, Price-Per-Unit relationships, Margin Targets and Competitive Price Index. Competitive prices can be collected or purchased from Rival Watch.

Promotion. Promoting the wrong product or the wrong offer erodes category profitability. As mentioned earlier, Retail Science can be used to evaluate supplier incentives. It can also be used to recommend the best items to promote and at what offers. During the planning stage a Category Manager can use the Demand Model to evaluate “what if” scenarios. For instance, which is the best item to promote on the front page in a major feature? What is the impact of merchandising the item in an end cap or a display? Is BOGO better than 10 for $10?  In all of these comparisons the Retail Science accounts for supplier funds, cannibalization, and affinity.

Category Managers are now using Retail Science to segment loyalty customers and identify the best one-to-one offers that will drive basket profit and trip frequency. Market Basket Analysis is applied to identify item-level affinity to understand how much a promotion on meat will drive sales in produce.

Retail Science benefits Category Managers best when it is imbedded in tools that support Supplier Collaboration and Ad Planning including pre-press layout with integration to publication tools such as Adobe InDesign or Quark.

Markdown. Simple clearance strategies such as 25%, 50%, and 75% markdown spread across three months leave money on the table. Too often items are marked down when demand is sufficient to clear inventory. Similarly, there are items with large inventory that require deeper or earlier markdown to maximize profit. Retail Science identifies the best markdown amounts and dates. Category managers can specify strategy objectives such as clear inventory or maximize profit. Coherence rules can be applied to simplify signage and shelf tags.

Assortment & Space.  Space and price are inseparable. Suppose that demand is high for a particular item, so high that the retailer often has a whole in the shelf. Is it better to increase the price, or to add another facing?  Retail Science can be used to jointly optimize space and price. In some cases the recommended number of facing is zero—meaning that it is recommended that the item be removed from the assortment. Retail science can also leverage syndicated data from IRI to recommend new items to add to the assortment. At a macro level, categories that need more or less linear space are identified.

Price, Promotion, Markdown, Assortment, and Space impact category profit and sales. A single Product Lifecycle application that integrates all of these applications is extremely useful to Category Managers. For one, a single integrated platform can identify and resolve pricing conflicts. Such as, a 10 for $10 promotion on August 1 would be in conflict with an Everyday price change from $1.19 to $0.89 on July 25. An integrated platform can also provide a single unified forecast which can be compared with the financial plan and actual profit and sales.

At Revionics we specialize in a SaaS-based Product Lifecycle platform that is putting the power of Retail Science into the hands of the next generation of Category Managers.

Ideas are like tomatoes. They start out small and green, but if the circumstances are right, they grow and ripen until they bear fruit. That is definitely the case for Revionics’ idea to provide retailers with One Integrated Forecast.

The idea was born years ago. At the time retailers had multiple contradictory forecasts: one forecast was used for financial planning; another for replenishment; another for workforce management. There was a store forecast for all categories and a category forecast for all stores—but the two did not match at the enterprise level. There were forecasts at daily, weekly, monthly, quarterly, and annual levels—when rolled up these didn’t match either. None of the various forecasts provided the accuracy necessary to make good business decisions. Retailers could not accurately or consistently predict their business. If a business is not predictable, then how can it be managed?

The idea was to provide retailers One Integrated Forecast that is accurate and meets all planning requirements. Let’s break this down into three components:

One. Replace the set of disparate forecasts with one forecast.

Integrated. Include all planned price and promotion activities. This includes merchandising activities such as displays and signage; and advertising such as circulars and flyers. It also must account for direct marketing such as email and offers to loyalty card customers.

Accurate. There are three measures of accuracy:
1.    Bias. The aggregate across all items and stores is unbiased.
2.    MAPE. The mean average percent error is small.
3.    Confidence. The accuracy of the confidence interval is high.

The factors that can influence the forecast accuracy include:
1.    Seasonality. Monthly, quarterly, bi-annual, and annual cycles.
2.    Holidays. Flexible calendar of holidays and events with pre- and post- holiday lifts. Ability to define custom events.
3.    Trends. Year-over-year trends either up or down in sales.
4.    Cannibalization. Substitution effect where a promotion on one item takes sales from another similar item.
5.    Affinity. Drag along sales where a promotion on one items drives sales of another item.
6.    Weather. Factor in the impact of weather.

Revionics offers One Integrated Forecast with unparalleled accuracy because it accounts for all the factors listed above.

We recently were working with a grocery retailer who wanted to reduce shrink in his produce section. He frequently promoted tomatoes and believed that with a more accurate forecast he could avoid ordering too much—leading to higher shrink, and he could avoid ordering too little—leading to stock outs. He knew that when he promoted red roma tomatoes it reduced the demand for hot house tomatoes, but he couldn’t quantify the amount until he used Revionics Promotions Planning module. He was able to forecast both the red roma and the hot house sales during the promotion with more accuracy. The result—no stock outs and less shrink. Revionics Forecast, delivering One Integrated Forecast to retail, is an idea that is ripe on the vine and ready to harvest.

I was recently reading Supermarket News, and came across this article that spoke to the state of the state within the grocery vertical. It speaks well to what it takes to succeed in today’s environment.
Food retailers are turning to analytical systems that can help them survive the harsh economy, according to SN’s latest technology survey.

Faced with the worst economic downturn in decades, U.S. food retailers are using technology to gain a better understanding of their position in the marketplace — and to optimize that position in respect to inventory, pricing, labor and a host of other business-critical elements.

Profit analysis is an application many worried retailers are turning to these days. While it ranked high on the list of priority items for 2008 at 25.5%, its popularity jumped to 36.2% on the 2009 list. Closely aligned with profit analysis is the expanding area of price and promotion planning and optimization.

Pricing has been an especially complex issue in the past year as retailers have grappled with rising commodity prices, as well as the need to lower retail prices to help out struggling consumers. Survey respondents consequently were prone to select promotion planning (30.9%) and price management (29.8%) as high-priority applications for 2009. Likewise, among applications that will be tested or launched in 2009, trade promotion management (16%) and price optimization (13.8%) ranked second and third.

Price optimization applications give retailers a forecast of what consumers are likely to do — and how profit margins will be impacted — when prices are raised, lowered or left the same. Without this scientific approach to pricing, retailers “are not going to find margin improvement,” said Scott Langdoc, chief strategist, Retail Centric, South San Francisco, Calif.

In retail, there is a key piece of information that contains a lot of power, that piece of information is the price sensitivity of a given item in a given store. Obtaining that piece of information is a very difficult thing to do.  If it weren’t for seasonal effects, holidays, promotions, out of stock conditions, low unit movement and a variety of other challenges, it actually would not be too difficult to determine.  After all, it is simply a prediction of how much the unit sales will change given a change in price.

With this information in hand, there are a variety of tasks that can be done more efficiently. One example is the identification of key value items, or KVI’s.   For retailers without optimization technology, the way this is accomplished today is by looking for the items that have the highest turn.  Unfortunately, this method shows items that are hot sellers, but these items may also be insensitive to price changes.  When retailers are able to obtain actual price sensitivity by leveraging optimization science, it is very interesting to review the sensitivity of these high moving items; there are always items in that list that are not price sensitive.  What does that tell you?  Often there are low margins on high moving items that could easily withstand a price increase without impacting consumer demand.   Retailers could be making up valuable profit dollars on these items.

Another key insight that can be gained from retail data is more accurate forecasting of revenue, profit and inventory requirements when making price changes or promoting items.  This accurate forecast is used when modeling and planning merchandising strategies for a category, department or banner.  Retailers can maximize margin dollars by charging a little more for items whose unit movement is not impacted much by the price increase, and reducing the price on items where the unit movement will increase more in proportion to the price decrease.

Information is power, and a good price optimization environment empowers the retailers with both recommendation and reporting that allows them to improve profits, price image, and customer satisfaction.  Revionics solution delivers both advanced price optimization and price strategy services to help retailers accomplish their goals.  For more information, please visit www.revionics.com, or email us at info@revionics.com.

According to Antony Karabus, President and CEO of Karabus Management these five strategies for retailers are important in order to emerge as a strong retailer.

1. Optimize cash and cost management
2. Understand what is relevant and motivates your customer
3. Use science to improve gross margins and inventory productivity
4. Invest in technology correctly and on the right projects
5. Get your supply chain right

There is a lot here to do.  I want to focus on item number two.  This strategy is rapidly gaining attention as a key initiative for 2010.  How are you planning to accomplish that?

How do you determine what is relevant and what motivates customers?

Your data is rich in insights into these questions.  Have you spent the time and resources to mine that data and discover what makes your customers tick?  This is equity that you own.  Use it.

Determining your Key Value Item list is a critical place to start.  It sets the stage for your pricing, promotional, and merchandising strategy.  Here are a few tips.

Key Value Item lists should not be defined from:
1.    A top mover list in units and/or dollars.
a.    Store can sell a lot of Ramen noodles…….
2.    Items your competitors have chosen to price at low margins
a.    You may not be buying right
3.    Items your competitors promote frequently
a.    They may be wrong
4.    Items only your best customers purchase
a.    You cannot live off of them alone
5.    What your seasoned executives carry around in their heads
a.    They may not be there tomorrow

Key Value Items should exhibit several of these criteria:
1.    Items that exhibit a high penetration rate in the basket
a.    Key in on key times of the month or week
2.    Items that drive traffic into the store
a.    Loyal customers make more trips for what items
b.    Non loyal customers come into your store for which items?
c.    When?
3.    Items that create bigger basket purchases
a.    Key in on important items that require additional products to prepare
4.    Items that exhibit significant demand shifts when the price is changed
a.    Both in units and dollars
5.    Items that are top of mind due to rising costs
a.    These items can come and go as the market dictates

Develop a list for each of these criteria
It is important to note that these lists do not necessarily contain the same items.
If you have only one list you have not done enough homework.

The key to improving your customer relevance starts and ends with what they tell you each and every trip they make into the store.  Someone once said: “We really don’t know what we don’t know.”  Ignorance is not bliss in this competitive world.  Get into your customer’s baskets and find out what you don’t know.

Looking back, when Revionics first developed the Promotional Planning module, we really did not know the exact capabilities we were going to be featuring. However, Revionics truly has cultivated a distinct Promotion Planning modeling module. In all reality, we were hoping to help customers take the guess work out of determining which items to promote and at which price to promote them at. Conversely, Revionics’ Promotion tool possesses more than that.

The great thing about the Revionics Planning tool that really sets it apart from the competition is that it not only offers assistance in establishing which products should be promoted at what price, but it also aids in distinguishing which are the best offers to feature in addition to where placement would be most beneficial for these products within the ads.

Our promotion optimization not only takes the risk out of running a promotion, but our customers are better able to reach their goals by planning their own events and having the ability and flexibility to make their own recommendations for the right price, right offer, as well as the right time to promote before the ad even goes out!

Revionics has the best promotional planning module in the industry! Our competitors simply do not have this capability. There is no question about it that our Planning tool sets us apart from our competition. Our goal at Revionics is to offer a unique, incredible, one of a kind service that takes the services we offer for pricing one step further in not only bettering us as a company, but in our customers efforts as well.