Purpose: To measure a firm’s ability to convey a product to its customers.

In broad terms, marketing can be divided into two key challenges:

• The first—and most widely appreciated—is to ensure that consumers or end users want a firm’s product. This is generally termed pull marketing.

• The second challenge is less broadly recognized but often just as important. Push marketing ensures that customers are given opportunities to buy.

Marketers have developed numerous metrics by which to judge the effectiveness of the distribution system that helps create opportunities to buy. The most fundamental of these are measures of product availability.

Availability metrics are used to quantify the number of outlets stocking a product, the fraction of the relevant market served by those outlets, and the percentage of total sales volume in all categories held by the outlets that carry the product.

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There are three popular measures of distribution coverage:

• Numeric Distribution

• All Commodity Volume (ACV)

• Product Category Volume (PCV), also known as weighted distribution

Data Sources, Complications, and Cautions

In many markets, there are data suppliers such as A.C. Nielsen, which specialize in collecting information about distribution. In other markets, firms must generate their own data. Sales force reports and shipment invoices provide a place to start.

For certain merchandise—especially low-volume, high-value items—it is relatively simple to count the limited number of outlets that carry a given product. For higher-volume, lower-cost goods, merely determining the number of outlets that stock an item can be challenging and may require assumptions. Take, for instance, the number of outlets selling a specific soft drink. To arrive at an accurate number, one would have to include vending machines and street vendors as well as traditional grocery stores.

Total outlet sales are often approximated by quantifying selling space (measured in square feet or square meters) and applying this measure to industry averages for sales per area of selling space.

In the absence of specific category sales data, it is often useful to weight ACV to arrive at an approximation of PCV. Marketers may know, for example, that pharmacies, relative to their overall sales, sell proportionally more of a given product than do superstores. In this event, they might increase the weighting of pharmacies relative to superstores in evaluating relevant distribution coverage.

Related Metrics and Concepts

Facing: A frontal view of a single package of a product on a fully stocked shelf.

Share of Shelf: A metric that compares the facings of a given brand to the total facing positions available in the category in order to quantify the display prominence of that brand.

Share of Shelf(%)=Facings for Brand(#)Total Facings in the Category(#)

Store Versus Brand Measures: Marketers often refer to a grocery chain’s ACV. This can be either a dollar number (the chain’s total sales of all categories in the relevant geographic market) or a percentage number (its share of dollar sales among the universe of stores). A brand’s ACV is simply the sum of the ACVs of the chains and stores that stock that brand. Thus, if a brand is stocked by two chains in a market, and these chains have 40% and 30% ACV, respectively, the ACV of that brand’s distribution network is 30% + 40%, or 70%.

Marketers can also refer to a chain’s market share in a specific category. This is equivalent to the chain’s PCV (%). A brand’s PCV, by contrast, represents the sum of the PCVs of the chains that stock that brand.

Inventory: The level of physical stock held, typically measured at different points in a pipeline. A retailer may have inventory on order from suppliers, at warehouses, in transit to stores, in the stores’ backrooms, and on the store shelves.

Depth of Distribution: The number of SKUs held. Typically, a company will hold a wide range of SKUs—a high depth of distribution—for the products that it is most interested in selling.

Features in Store: The percentage of stores offering a promotion in a given time period. This can be weighted by product or by ACV.

ACV on Display: Distinctions can be made in all commodity volume metrics to take account of where products are on display. This will reduce the measured distribution of products if they are not in a position to be sold.

ACV on Promotion: Marketers may want to measure the ACV of outlets where a given product is on promotion. This is a useful shorthand way of determining a product’s reliance on promotion.

Purpose: To monitor the effectiveness of an organization in managing the distribution and logistics process.

In marketing, logistics is where the rubber meets the road. A lot can be lost at the potential point of purchase if the right goods are not delivered to the appropriate outlets on time and in amounts that correspond to consumer demand. How hard can that be? Well, ensuring that supply meets demand becomes more difficult when

• The company sells more than a few SKUs

• Multiple levels of suppliers, warehouses, and stores are involved in the distribution process

• Product models change frequently

• The channel offers customer-friendly return policies

In this complex field, by monitoring core metrics and comparing them with historical norms and guidelines, marketers can determine how well their distribution channel is functioning as a supply chain for their customers.

By monitoring logistics, managers can investigate questions such as the following: Did we lose sales because the wrong items were shipped to a store that was running a promotion? Are we being forced to pay for the disposal of obsolete goods that stayed too long in warehouses or stores?

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Out-of-Stocks: A metric that quantifies the number of retail outlets where an item is expected to be available for customers but is not. It is often, but not always expressed as a percentage of stores that list the relevant item.

Out-of-Stocks(%)=Out Where Brand or Product Is Listed But Unavailale(#)Total Outlets Where Brand or Product Is Listed(#)

Being “listed” by a chain means that a headquarters buyer has “authorized” distribution of a brand, SKU, or product at the store level. For various reasons, being listed does not always ensure presence on the shelf. Local managers may not approve distribution. Alternatively, a product may be distributed but sold out.

Out-of-Stocks is often expressed as a percentage. Marketers must note whether an Out-of-Stock percentage is based on Numeric Distribution, ACV, PCV, or the percentage of distributing stores for a given chain.

The in-stock percentage is the complement of the out-of-stock percentage. A 3% out-of-stock rate would be equivalent to a 97% in-stock rate.

Product Category Volume (PCV), Net Out-of-Stocks: The PCV of a given product’s distribution network, adjusted for out-of-stock situations. A quick way to create this out-of-stocks measure is to multiply PCV by a factor that adjusts it to recognize out-of-stock situations. The adjusting factor is simply 1 minus the out-of-stocks figure.

Product Category Volume, Net Out-of-Stocks (%) = PCV (%) * [1 − Out-of-Stock (%)]

Alternatively, a longer method is to take the total product category sales of all outlets that have stock and divide this by the total product category sales of all outlets in the relevant retail universe.

Service Levels, Percentage On-Time Delivery: There are various service measures in marketing logistics. One particularly common measure is on-time delivery. This metric captures the percentage of customer (or trade) orders that are delivered in accordance with the promised schedule.

Service Levels, Percentage On-Time Delivery(%)=Deliveries Achieved in time framePromised(#)All Deliveries Initiated in the Period(#)

Inventories, like Out-of-Stocks and Service Levels, should be tracked at the SKU level. For example, in monitoring inventory, an apparel retailer needs to know not only the brand and design of goods carried but also their size. Simply knowing that there are 30 pairs of suede hiking boots in a store, for example, is not sufficient—particularly if all those boots are the same size and fail to fit most customers.

By tracking inventory, marketers can determine the percentage of goods at each stage of the logistical process—in the warehouse, in transit to stores, or on the retail floor, for example. The significance of this information depends on a firm’s resource management strategy. Some firms seek to hold the bulk of their inventory at the warehouse level, for example, particularly if they have an effective transport system to quickly ship goods to stores.

Inventory Turns: The number of times that inventory turns over in a year can be calculated on the basis of the revenues associated with a product and the level of inventory held. One need only divide the revenues associated with the product in question by the average level of inventory for that item. As this quotient rises, it indicates that inventory of the item is moving more quickly through the process. Inventory turns can be calculated for companies, brands, or SKUs and at any level in the distribution chain, but they are frequently most relevant for individual trade customers. Important note: In calculating inventory turns, dollar figures for both sales and inventory must be stated either on a cost or wholesale basis, or on a retail or resale basis, but the two bases must not be mixed.

Inventory Turns(I)=Annual Product Revenues($)Average Inventory($)

Inventory Days: A metric that also sheds light on the speed with which inventory moves through the sales process. To calculate it, marketers divide the 365 days of the year by the number of inventory turns, yielding the average number of days of inventory carried by a firm. By way of example, if a firm’s inventory of a product turned 36.5 times in a year, that firm would, on average, hold 10 days’ worth of inventory of the product. High inventory turns—and, by corollary, low inventory days—tend to increase profitability through efficient use of a firm’s investment in inventory. But they can also lead to higher out-of-stocks and lost sales.

Inventory Days(#)=Days in Year(365)Inventory Turns(I)

Inventory Days represents the number of days’ worth of sales that can be supplied by the inventory present at a given moment. Viewed from a slightly different perspective, this figure advises logistics managers of the time expected to elapse before they suffer a stock-out if replenishment were to stop for some reason, such as a trade war or a problem in the supply chain. To calculate the Inventory Days figure, managers divide product revenue for the year by the value of the inventory days, generating expected annual turns for that inventory level. This can be easily converted into days by using the previous equation.

It is worth bearing in mind that stock levels may be atypical around the holiday period. It may be that year-end figures do not accurately represent average inventory levels.

Data Sources, Complications, and Cautions

Although some companies and supply chains maintain sophisticated inventory tracking systems, others must estimate logistical metrics on the basis of less-than-perfect data. Increasingly, manufacturers may also have difficulty purchasing research because retailers that gather such information tend to restrict access or charge high fees for it. Often, the only readily available data may be drawn from incomplete store audits or reports filed by an overloaded sales force. Ideally, marketers would like to have reliable metrics for the following:

• Inventory units and monetary value of each SKU at each level of the distribution chain for each major customer

• Out-of-stocks for each SKU, measured at both the supplier level and the store level

• Percentage of customer orders that were delivered on time and in the correct amount

• Inventory counts in the tracking system that don’t match the number in the physical inventory (to facilitate a measure of shrinkage or theft)

When considering the monetary value of inventory, it is important to use comparable figures in all calculations. As an example of the inconsistency and confusion that can arise in this area, a company might value its stock on the retail shelf at the cost to the store, which might include an approximation of all direct costs. Or it might value that stock for some purposes at the retail price. Such figures can be difficult to reconcile with the cost of goods purchased at the warehouse and can also be different from accounting figures adjusted for obsolescence.

When evaluating inventory, managers must also establish a costing system for items that can’t be tracked on an individual basis. Such systems include the following:

• First in, first out (FIFO): The first unit of inventory received is the first expensed upon sale.

• Last in, first out (LIFO): The last unit of inventory received is the first expensed upon sale.

The choice of FIFO or LIFO can have a significant financial impact in inflationary times. At such times, FIFO holds down the cost of goods sold by reporting this figure at the earliest available prices. Simultaneously, it values inventory at its highest possible level—that is, at the most recent prices. The financial impact of LIFO is the reverse.

In some industries, inventory management is a core skill. Examples include the apparel industry, in which retailers must ensure that they are not left with prior seasons’ fashions, and the technology industry, in which rapid developments make products hard to sell after only a few months.

In logistical management, firms must beware of creating reward structures that lead to suboptimal outcomes. An inventory manager rewarded solely for minimizing out-of-stocks, for example, would have a clear incentive to overbuy—regardless of inventory holding costs. In this field, managers must ensure that incentive systems are sophisticated enough not to reward undesirable behavior.

Firms must also be realistic about what will be achieved in inventory management. In most organizations, the only way to be completely in stock on every product all the time is to ramp up inventories. This involves huge warehousing costs. It ties up a great deal of the company’s capital in buying stocks. And it results in painful obsolescence charges to unload over-purchased items. Good logistics and inventory management entails finding the right trade-off between two conflicting objectives: minimizing both inventory holding costs and sales lost due to out-of-stocks.

Related Metrics and Concepts

Rain Checks and Make-Goods on Promotions: The effect on a store of promotional items being unavailable. In a typical example, a store might track the incidents in which it offers customers a substitute item because it has run out of stock on a promoted item. Rain checks or make-goods might be expressed as a percentage of goods sold or, more specifically, as a percentage of revenues coded to the promotion but generated by sales of items not listed as part of the promotional event.

Mis-shipments: The number of shipments that failed to arrive on time or in the proper quantities.

Deductions: The value of deductions from customer invoices caused by incorrect or incomplete shipments, damaged goods, returns, or other factors. It is often useful to distinguish between the reasons for deductions.

Obsolescence: A vital metric for many retailers, especially those involved in fashion and technology, that is expressed as the monetary value of items that are obsolete or as the percentage of total stock value that comprises obsolete items. If obsolescence is high, then a firm holds a significant amount of inventory that is likely to sell only at a considerable discount.

Shrinkage: Typically a euphemism for theft. It describes a phenomenon in which the value of actual inventory runs lower than recorded inventory, due to an unexplained reduction in the number of units held. This measure is typically calculated as a monetary figure or as a percentage of total stock value.

Pipeline Sales: Sales that are required to supply retail and wholesale channels with sufficient inventory to make a product available for sale (refer to Section 6.5).

Consumer Off-Take: Purchases by consumers from retailers, as opposed to purchases by retailers or wholesalers from their suppliers. When consumer off-take runs higher than manufacturer sales rates, inventories are drawn down.

Diverted Merchandise or Diverted Goods: Products shipped to one customer that are subsequently resold to another customer. For example, if a retail drug chain overbuys vitamins at a promotional price, it may ship some of its excess inventory to a dollar store.

Purpose: To assess the effectiveness and profitability of individual product and category sales.

Retailers and distributors have a great deal of choice regarding which products to stock and which to discontinue as they make room for a steady stream of new offerings. By measuring the profitability of individual SKUs, managers develop the insight needed to optimize such product selections. Profitability metrics are also useful in decisions regarding pricing, display, and promotional campaigns.

Figures that affect or reflect retail profitability include markdowns, gross margin return on inventory investment, and direct product profitability. Let’s take each one in turn.

Markdowns are not always applied to slow-moving merchandise. Markdowns in excess of budget, however, are almost always regarded as indicators of errors in product assortment, pricing, or promotion. Markdowns are often expressed as a percentage of regular price. As a stand-alone metric, a markdown is difficult to interpret.

Gross margin return on inventory investment (GMROII) applies the concept of return on investment (ROI) to what is often the most crucial element of a retailer’s working capital: its inventory.

Direct product profitability (DPP) shares many features with activity-based costing (ABC). Under ABC, a wide range of costs are weighted and allocated to specific products through cost drivers—the factors that cause the costs to be incurred. In measuring DPP, retailers factor such line items as storage, handling, manufacturer’s allowances, warranties, and financing plans into calculations of earnings on specific product sales.

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Markdown: A metric that quantifies shop-floor reductions in the price of a SKU. It can be expressed on a per-unit basis or as a total for the SKU. It can also be calculated in dollar terms or as a percentage of the item’s initial price.

Markdown($)=Initial Price of SKU($)−Actual Sales Price($)Markdown(%)=Markdown($)Initial Price of SKU($)

Gross Margin Return on Inventory Investment (GMROII): A metric that quantifies the profitability of products in relation to the inventory investment required to make them available. It is calculated by dividing the gross margin on product sales by the cost of the relevant inventory.

Gross Margin Return on Inventory Investment(%)=Gross Margin on Product Sales inPeriod($)Average Inventory Value at Cost($)

Direct Product Profitability (DPP): A metric that represents a product’s adjusted gross margin, less its direct product costs. Direct product profitability is grounded in a simple concept, but it can be difficult to measure in practice. The calculation of DPP consists of multiple stages. The first stage is to determine the gross margin of the goods in question. This gross margin figure is then modified to take account of other revenues associated with the product, such as promotional rebates from suppliers or payments from financing companies that gain business on its sale. The adjusted gross margin is then reduced by an allocation of direct product costs, described next.

Direct Product Costs: The costs of bringing a product to customers. They generally include warehouse, distribution, and store costs.

Direct Product Costs($)=Warehouse Direct Costs($)+TransportationDirectCosts($)+Stoer Direct Costs($)

As noted earlier, the concept of DPP is quite simple. Difficulties can arise, however, in calculating or estimating the relevant costs. Typically, an elaborate ABC system is needed to generate direct costs for individual SKUs. DPP has fallen somewhat out of favor as a result of these difficulties.

Other metrics have been developed in an effort to obtain a more refined and accurate estimation of the “true” profitability of individual SKUs, factoring in the varying costs of receiving, storing, and selling them. The variations between products in the levels of these costs can be quite significant. In the grocery industry, for example, the cost of warehousing and shelving frozen foods is far greater—per unit or per dollar of sales—than the cost of warehousing and shelving canned goods.

Direct Product Profitability ($) = Gross Margin ($) − Direct Product Costs ($)

Data Sources, Complications, and Cautions

For GMROII calculations, it is necessary to determine the value of inventory held, at cost. Ideally, this will be an average figure for the period to be considered. The average of inventory held at the beginning and end of the period is often used as a proxy and is generally—but not always—an acceptable approximation. To perform the GMROII calculation, it is necessary to calculate a gross margin figure.

One of the central considerations in evaluating direct product profitability is an organization’s ability to capture large amounts of accurate data for analysis. The DPP calculation requires an estimate of the warehousing, distribution, store direct, and other costs attributable to a product. To assemble these data, it may be necessary to gather all distribution costs and apportion them according to the cost drivers identified.

Inventory held, and thus the cost of holding it, can change considerably over time. Although one may usually approximate average inventory over a period by averaging the beginning and ending levels of this line item, this will not always be the case. Seasonal factors may perturb these figures. Also, a firm may hold substantially more—or less—inventory during the course of a year than at its beginning and end. This could have a major impact on any DPP calculation.

DPP also requires a measure of the ancillary revenues tied to product sales.

DPP has great conceptual strength. It tries to account for the wide range of costs that retailers incur in conveying a product to customers and thus to yield a more realistic measure of the profitability of that product. The only significant weakness in this metric is its complexity. Few retailers have been able to implement it. Many firms continue to try to realize its underlying concept, however, through such programs as activity-based costing.

Related Metrics and Concepts

Shopping Basket Margin: The profit margin on an entire retail transaction, which may include a number of products. This aggregate transaction is termed the “basket” of purchases that a consumer makes.

One key factor in a firm’s profitability is its capability to sell ancillary products in addition to its central offering. In some businesses, more profit can be generated through accessories than through the core product. Beverage and snack sales at movie theaters are a prime example. With this in mind, marketers must understand each product’s role within their firm’s aggregate offering—be it a vehicle to generate customer traffic, or to increase the size of each customer’s basket, or to maximize earnings on that item itself.

Purpose: To determine how easy it is to get to find a product on an online site.

Since we wrote the first edition of this book, published 2006, the idea of omni-channel strategy, specifically for retailers, has become a key component for many marketers. There are several senses in which omni-channel is used. The marketers can be working to create synergies across distributional channels or across promotional channels. Both of these senses of the word can produce valuable insights, emphasizing coordination of strategy to work with the realities of modern marketing. In this section we look at metrics that capture how easy it is for consumers to find products and information about them in an omni-channel environment.

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A couple general terms that are worth discussing:

• Search engine results page (SERP): This describes what is shown as a result of an online search. Placement on the first SERP can have very different consequences from later placements, given that many people see only the first page. When consumers are using their mobile devices, they are especially likely to see only the first screen displayed.

• Above the fold: This idea comes from newspapers. In the print environment, any story above the fold could be seen when the paper was folded and stacked. In online marketing, above the fold refers to anything that is visible on a web page without the need to scroll to it; that is, it is displayed without the need for human intervention, greatly increasing the chance that it will be viewed.

In online stores, there are metrics that capture whether an offering was actually seen. The following are some of them.

Rank of App in App Store (#): A number that captures where a retailer’s app appears when displayed in an app store. Generally, placement higher in the rankings is useful in ensuring that the app is visible to more potential customers. Number of downloads (#)—that is, popularity of the app with other consumers—often drives this metric.

Rank of Brand/SKU (#): A number that captures where a brand/SKU appears when goods are searched for. Appearing on page 5 of the Amazon listings when a search for your product is made will have very different consequences than appearing on the first page. Clearly, suppliers can work with online retailers to improve their rankings.

Brand on Landing Page (#): A number that captures whether a brand is featured on an online retailer’s landing page.

Clicks to Product (#): A measure of how easy it is to get to a product on an online retailer’s site. Marketers consider how many clicks it takes a consumer to reach their product with the understanding that the fewer, the better. Marketers also monitor if there is a “buy” button beside the product. Other considerations include the presence of an Amazon Dash button and the ability to order a product with voice-activated devices.

Data Sources, Complications, and Cautions

Many metrics that consider how easy it is to find a product online vary considerably between products and businesses. In an online store, such as Apple’s or Microsoft’s, apps for relatively niche retailers are unlikely to appear high on the main listing—not because they aren’t good apps but because only a subset of the population actually wants them. Marketers may therefore be more interested in how an app compares in a certain category or against given rivals.

The different ways consumers access information in an omni-channel world mean that one has to dig into what is reported to better understand the implications of metrics. Furthermore, what is below the fold will be different on a mobile device than on a large-screen PC. Given that screen sizes and resolutions differ considerably across devices and even within the same class of device, what is visible will differ considerably. Always clarify how a metric is constructed and what the assumptions are behind the metric, such as assumptions about what will be visible.

Purpose: To understand online accessibility of products and information about them.

The percentage of organic sites stocking a brand indicates how well represented the brand (or SKU) is among sites that appear on the first page of search engine results. Marketers for the supplier will be interested in ensuring that they are stocked by the internet retailers who are most seen by the public when they search for the product.

Similar metrics can be created for sponsored sites and product listing ads (PLAs).

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Organic search is the result of marketing that does not have a direct cost. Search engine optimization (SEO) is marketing work that helps get a top listing on search results. Retailers that appear high on such search rankings are likely to be popular and probably employ better online marketers. Marketers working for the suppliers will be interested to know that they are well represented on sites that appear on the first page of organic searches.

%of Organic Sites Stocking the Brand(%)=Number of Original Sites on the First SERP ThatStick the Brand(or SKU)(#)Number of Organic Sites on the First SERP(#)

Sponsored sites appear in search engine results, such as Google results. These listings result from paid advertising called search engine marketing. Placement on sponsored sites can be influenced by how much is paid. A manufacturer will be interested in knowing whether it is stocked by the retailers that pay for this form of advertising. Presumably these are more aggressive online advertisers.

%of Sponsored Sites Stocking the Brand(%)=Number of Sponsored Sites on the First SERPThat Stock the Brand(or SKU)(#)Number of Sponsored Sites on the First SERP(#)

Product listing ads (PLAs) are ads displayed in search results in Google and Bing. Typically, they include a product image, title, price, store name, and link. A similar metric can be constructed for PLAs.

%of PLAs Stocking the Brand(%)=Number of PLAs on the First SERPThat Stock the Brand(or SKU)(#)Number of PLAs on the First SERP (#)

Data Sources, Complications, and Cautions

The metrics just discussed simply show whether a product is available on sites that the consumer has easy access to. They do not capture whether any purchases were made.

The search results gained depend on the keywords entered. A firm will be interested in specific keywords, such as 4K TV, and will want to be well represented in such searches. Other keywords will be of much less interest to the manufacturer. Deciding what keywords you care about is a key skill for online marketers.

Purpose: To show the role of each channel member.

One of the complexities of retail strategy is that retailers and suppliers must work together. Much debate has been conducted about the issue of showrooming. This is where physical retailers perform a service to the consumer by displaying a supplier’s product, but the consumer then purchases online—either from a different retailer, such as Amazon, or from the physical store’s associated online presence, such as Walmart.com. The consumer gains valuable information from the physical store, the supplier benefits as the product is purchased, and the online retailer making the sale also benefits. Unfortunately, the physical retailer does not benefit directly from providing the information to the consumer. The physical retailer will want some way to show the benefit it is providing. If the online retailer is the same company as the physical retailer—such as Target and Target.com—rewarding the physical store can be managed internally by sales attribution. Where the online retailer is different from the physical retailer, the physical retailer will want to show the benefit it is giving to the supplier to, hopefully, extract more favorable terms from the manufacturer or other supplier.

While most attention has been paid to showrooming, a similar issue can occur in the opposite direction: A consumer may research at an online retailer or a supplier website and then purchase from a physical retailer. This is known as webrooming. The online presences are providing vital support to the purchase that the physical retailer is not necessarily rewarding the online entity for.

Understanding consumers search versus purchases can allow for better management of this relationship by helping to quantify the benefits provided by the party that does not gain the final sale. The metrics can be useful because the physical retailer wants to know how it is helping the supplier through things such as showrooming. These metrics provide discussion points for negotiations. The supplier may also want to know what retailers are most useful to them.

Similarly, a physical retailer may also want to know what suppliers are most useful to it—by supporting the product being sold by the retailer. In traditional channel settings, this support provided by the supplier would involve cooperative advertising and similar activities. Indeed, thinking more widely, any brand advertising by the supplier, such as advertising by Cadbury, can be seen as a form of support to the retailer that eventually sells the product. Strong brands will be able to make more demands of the retailer because of the support they provide to the final sale. There are a number of ways to promote a brand/SKU online by those not directly involved in the final sale the product, and both retailers and suppliers must work to know what this activity is and its impact. In summary, strong upstream marketer pull efforts can stimulate reseller push downstream.

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Retailers provide a physical presence allowing the retailer to perform services for the customers that virtual venues cannot. The following metrics help show the contribution of a physical retailer to the value delivered to the customer where the physical retailer will not necessarily get credit given that it does not end up making the final sale to the customer.

Cross-Channel Conversions (#): The number of sales that happen in another channel, such as online, where the customer was served by the physical retailer. This metric captures the contribution to a sale made from showrooming. When it is used to look at sales influenced by online presences that lead to physical retailer sales, it captures the contribution of webrooming to sales. Of course, these estimates of cross-channel conversions are typically difficult to measure with precision.

Cross-Channel Delivery or Returns (#): The number of any given activity (such as a delivery to a store or a return accepted by a store) that is done by a physical retailer and benefits the online retailer. For example, a consumer might buy at IKEA.com and have the product delivered to a local IKEA store for pickup. If IKEA.com gets credit for the sale, IKEA needs a way to compensate the physical store (which may just be notional transfers) to show the full benefit provided by the store. These return figures are considerably more reliable than cross-channel influences on orders and may add insight to the latter.

Cross-Channel Support ($): A record of the payments made by a supplier for cross-channel conversions, delivery, or returns.

Data Sources, Complications, and Cautions

We have noted that within a single organization—such as Target and Target.com—attribution can give credit to any part of the organization that generates sales (such as by providing a venue for showrooming) but does not finalize the transaction. Determining where to give this credit is not easy in practice and often requires considerable effort on the part of management. Internal credit is a complex political process, and it can get especially contentious when two independent organizations are involved in the discussions.

Further Reading

Ailawadi, Kusum L., and Paul W. Farris. (2020). Getting Multi-Channel Distribution Right, Wiley.

Ailawadi, Kusum L., and Paul W. Farris. (2017). “Managing Multi-and Omni-Channel Distribution: Metrics and Research Directions,” Journal of Retailing, 93(1), 120–135.

Wilner, Jack D. (1998). Seven Secrets to Successful Sales Management, CRC Press.

Zoltners, Andris A., Prabhakant Sinha, and Greggor A. Zoltners. (2001). The Complete Guide to Accelerating Sales Force Performance, AMACON.