Pricing has long been—and will continue to be—a core capability for retailers. Executives and merchants alike recognize it as one of the key value levers, and, accordingly, retailers have worked to refine their pricing strategy, tactics, and tools over the past several decades in hopes of optimizing their approach. Despite recent advances in analytics, decision-support tools, and methodologies, retailers are finding that the traditional approaches are not keeping pace. Indeed, the new digital era stemming from big data, mobile commerce, and the explosion of omnichannel retailing has meaningfully changed the environment and requires an overhaul of retailers’ pricing strategy and capabilities.
This article—our first in a series on pricing in retail—focuses on key value categories (KVCs) and key value items (KVIs) and the relevance and evolution of these concepts as a core part of price strategy in today’s digital retail environment. We offer our views on three topics:
- the traditional role of KVCs and KVIs in retail price strategy
- how today’s digital retail environment is changing the game
- key implications for creating a winning price strategy
The traditional role of KVCs and KVIs in retail price strategy
To understand the role of KVCs and KVIs in strategy, let’s first define what price strategy means. Simply put, we believe price strategy can be articulated as purposeful pricing by channel and customer to maximize value perception and business results (for example, traffic, basket, sales, and margin) and to increase customer engagement and loyalty.
This statement of strategy can lend itself to an everyday-low-price or high/low approach, or a hybrid of the two. The price strategy must answer the following questions: What is the target price position versus reference competitors by category, channel, and geography? What is the optimal mix of price and promotion by category and channel? Which customers and trip missions matter most? How do the most attractive customers shop? What drives value perception?
A common element across these three questions is the role that categories and items play in the overall strategy. The first step is to identify the retailer’s KVCs—these are the categories that drive value perception the most and have a higher mix of KVIs. Then KVIs—the items that drive value perception the most—are identified. To optimize value perception, a retailer will price KVCs and KVIs most sharply relative to the relevant competition. Economists, academics, and retailers have long known that that shoppers recall prices only for a small number of items. While these recollections are typically for those products that shoppers purchase most frequently, they tend to be directional rather than precise. As such, retailers have been able to effectively shape shoppers’ value perceptions by pricing competitively on the items that matter most.
How retailers use KVCs and KVIs in their price strategy
Tactically, retailers use their KVC and KVI lists to help govern item-price decisions against reference-competitor price indexes—these lists are foundational elements to the effective price index that the retailer is targeting. These price decisions could be to match exactly or to price slightly higher or lower, depending on the competitive and customer dynamics of the geography or price zone in question, as well as the specific category objective and product segment of the item in question. Beyond pricing, KVIs are often treated differently than non-KVIs across other merchandising levers, including in-store space allocation, safety-stock position, and promotional and marketing activity.
While competitive price indexes are often the main factor in pricing KVIs, retailers typically balance other considerations, including margin goals, price elasticity, range architecture, and market-share targets.
How retailers set KVC and KVI lists
How do retailers determine which categories and items become part of their KVC and KVI lists? In the approach employed by many retailers, these lists are created with these three types of inputs:
- Transaction and basket data. Retailers can analyze and rank order category and item-level performance, including sales (by dollar or volume) and number and size of baskets including item, elasticity, and market share.
- Shopper price-perception data. Through primary research, retailers can identify the categories and items that most drive value perception.
- Merchant judgment. Experienced merchants can then review and add strategic items with high degree of competitive intensity (that is, where competitors’ space allocation or marketing spending is high).
Through these lenses, retailers can establish four types of KVIs. These types are balanced to reinforce a retailer’s value proposition and support the overall pricing strategy:
- Value-perception drivers. Memorable items that typically shape traffic over longer time frames (for example, bananas and milk for grocers; socks and basic T-shirts for apparel retailers).
- Assortment-perception drivers. Items that highlight a retailer’s merchandise authority—that is, distinctive product selection that gives customers a point of view on what they should buy. For example, remote-control toy cars may be critical to a specialty electronics retailer; similarly, a distinctive prepared-foods and meal-replacement selection are critical to higher-end and organic grocers.
- Traffic drivers. High-velocity items that inspire incremental shopping trips (for example, beer and diapers).
- Basket drivers. Low-velocity items that inspire incremental purchases in a shopping trip (for example, 16-ounce pasta sauce, which drives pasta, vegetables, and meat).
Rather than remaining content with a static corporate KVC and KVI list, best-practice retailers have been refreshing their lists at least annually and flexing their KVC and KVI lists by price zone or geography.
How the new digital retail era has changed the game
Several trends in the way consumers are shopping are reshaping retail, and pricing in particular, including these:
- Cross-channel customer decision journeys. Sixty percent of customers are making toy and baby purchases online, accounting for 15 percent of spend; Amazon is getting top scores on key buying factors versus multichannel players. Customers are often starting online even for in store purchases; for example, 50 to 70 percent of shoppers are checking prices on their mobile phones, depending on the category.
- Price transparency. Customers no longer need to rely on memory to compare prices across retailers, as price-comparison shopping engines instantly display competitors’ pricing in a single view. More sophisticated price-comparison engines track prices over time or even forecast future price changes. Retailers are also integrating price matching into the mobile-app price-comparison experience.
- Dynamic pricing. Online pure plays, including Amazon, are increasingly sophisticated in managing price, reacting to competitor prices in as little as one hour. Top-selling items are often repriced 3 or 4 times per day and can be repriced up to 12 times daily. Sophisticated multichannel leaders are following suit, changing the prices on 10 to 20 percent of their online assortment daily.
- Personalization. Consumers are increasingly expecting personalized deals, and some retailers are able to deliver these based on past shopping history. This is not limited to online players only—for example, Safeway has done this with its Just For U app, which users can download to their mobile phones to receive tailored deals and coupons. In some cases, these personalized offers are linked directly to consumers’ loyalty cards or user accounts and applied automatically.
- Big data. Real-time data updates (from sources such as mobile search and product reviews) generate terabytes of data, and global data generation is projected to grow at a rate of 40 percent annually. Armed with this data, retailers are hiring new talent, buying or building sophisticated tools to harness the data, and going after potential new margin increases of up to 60 percent, according to the McKinsey Global Institute.
Implications for creating a winning price strategy
The dynamics we are seeing today require a revamped approach to pricing strategy, beginning with KVCs and KVIs.
Relevance of KVCs and KVIs in the digital era
The dynamics of the new digital retail era may tempt retailers to treat every item as a KVI and price it low to keep up with competitors and empowered customers. We have seen this approach result in an unprofitable “race to the bottom” as each competitor notches down its price to stay below the competition. Conversely, a dynamic, segmented approach to item-level pricing will allow retailers to optimize across multiple objectives (for example, margin, price perception, and market share) and across customer journeys (such as impulse purchase and big-ticket researched purchase). This approach should be grounded in a price strategy that identifies those categories that matter most strategically to the retailer.
New approach to selecting KVCs and KVIs
We believe retailers need to transform their approach to selecting KVIs in the following ways:
- Leverage new data sources. In addition to the traditional data used (transaction and basket data, shopper price-perception data, and merchant judgment), there is an abundance of new sources of information unique to online channels. This includes structured information such as user reviews, search, click-through, bounce, and purchase rates. It also includes unstructured information such as tweets or comments on social sites. New digital teams armed with tools can extract and clean these insights and help organizations harness them.
- Create a set of item segments. Segmenting items into a small set of price groups (for example, KVIs and non-KVIs) is typically not sufficient online. Instead, to balance customer demand, competitor actions, and economic considerations, retailers will need to create a flexible and manageable number of price segments. The key is to make them granular enough that they can stand alone but not so granular that management of price segments becomes unwieldy.
- Refresh KVIs more frequently. KVCs and KVIs can be updated much more frequently online—even dynamically. Initially, most retailers will want to refine the process manually. Once the inputs, weightings, and algorithms are set, they can be applied in real time, moving items in and out of different item segments as dynamics shift. As this approach evolves, it will be important for brick-and-mortar retailers to build in acceptable tolerances for price decoupling between stores and online, given most stores aren’t yet exclusively using digital shelf tickets.
Bringing all of these changes together, a typical retailer might move from a single, static KVI list with around 200 to 300 items to a dynamic list of more than 1,000 KVIs that fit into multiple segments, even controlling for a similar number of items across channels (Exhibit 1). Not all KVIs will be KVIs across channels, and a variety of factors will drive items to move across KVI segments dynamically.
Key value items have changed in many ways.
For many retailers, we imagine that there will be a small group of super KVIs (those with more than 100 items) where the retailer will deliver a competitive price to every customer in every channel every time.
Executing a new, more dynamic pricing strategy
We see retailers applying several analytical approaches to setting pricing strategy and price decisions for KVIs and other items:sophisticated econometrics, heuristic scoring, and rapid test-and-learn experiments. In the rapid-test-and learn approach, retailers develop questions and hypotheses and use real-time online feedback to create outputs and make decisions. These “price experiments” are generally faster, lower risk, and effective.
In the heuristic scoring approach, several factors are scored and weighted, typically across these four dimensions (Exhibit 2):
- consumer demand (for example, price elasticity, price perception, and basket-building power or attachment rates
- competition (for example, store or zone rules, price gap to competition, and market-share trend)
- economics (for example, target retail margin and cost pass-through rate)
- category dynamics (for example, inventory levels, markdown effectiveness, and out-of-stock impact)
Heuristic pricing factors span multiple dimensions.
Much as in a traditional KVI world, historical price elasticity remains a critical input for optimizing prices. It is, however, only one factor to reflect short-term shopper response, and we have found high value in combining this analysis with other measures and indicators of customer response that act as lead indicators of traffic change over time.
In addition to the above factors, a set of guardrails is typically defined in a heuristic model to preserve assortment architecture (for example, private-label to national-brand gaps, size and flavor or color relationships) and pricing strategy. For example, retailers should include competitive guardrails to avoid pricing items too far above competitors. Even on “background” items, a price gap larger than 30 to 50 percent can turn off the customer for future trips.
The advantage of heuristic scoring is that is allows for an analytically sophisticated yet easily understandable and therefore implementable price-setting approach. And different factors and weightings can be used for different item segments (Exhibit 3).
Different item segments will have different weighting across metrics.
KVCs and KVIs will remain an important pillar of pricing strategy, but to drive traffic and profit in the new retail era, retailers will need to revisit their current approach. Even more is at stake in today’s dynamic digital retail environment, and those that do not adapt to today’s reality and highly competitive marketplace will open themselves up to greater risk. Failure to effectively price can lead to rapid loss of customers and margin; however, retailers who build an effective pricing capability can expect lasting top-and bottom-line impact.
Retail pricing leaders should be taking these immediate next steps:
- Refine and dynamically manage KVC and KVI lists going forward, using new sources of insight and analytical capabilities.
- Establish dynamic price-gathering and price-optimization capabilities; these are a requirement for success in today’s digital retail environment.
- Expand the competitive set and improve the sophistication with which competitive-pricing rules are defined and maintained.