Price Zones: How should retailers think about different prices in different geographies?

May 28, 2024

Background

Retailers that operate in multiple states, cities or countries will eventually have to think about pricing in a region-specific way. This is important because each region they operate in might have inherently different cost structures due to different suppliers, operating costs or tax laws, or because their customer-base is different and therefore willingness-to-pay is different. 

For example, average willingness-to-pay in urban centers such as New York City or San Francisco is significantly higher than the rest of the US due to higher average household incomes, however due to plenty of alternatives available, staying price-competitive on KVIs (key value items) is crucial in order to encourage larger basket sizes.

Therefore as a retailer, calibrating your pricing strategy to a specific region is table-stakes as you scale. So how should one go about defining geographical pricing zones as a retailer, and how should one approach zone-level pricing?

What is a Price Zone?

A Price Zone is any geographical area or channel, such as online, offline, wholesale which consists of a distinct pricing strategy for a retailer. 

It is likely that the Price Zone has the same cost structure for the retailer, where delivery, manufacturing and warehousing fees are identical. It is also likely that the Price Zone has its own distinct promotional strategy. Lastly, it is also likely that a Price Zone shares the same sales tax laws to simplify pricing strategy.

What types of Price Zones do retailers set?

In our work with retailers at Luca, we’ve helped retailers set the following formats of price zones. Each of these types of zones were a function of the size of the retailer and overall complexity of their business. 

  1. Channel-based Price Zones: For omnichannel retailers, an online versus offline price zone is a simple way to think about pricing strategies, since the online consumer’s price sensitivity is likely to look distinct from an offline consumer’s price sensitivity. Accounting for those differences with small pricing differences can be an effective way to gain margin.
  2. Urban versus Suburban Price Zones: For one national retailer, we set up one price zone that mapped to the Top 20 cities in the market and the rest of the population got another price zone. For online retailers, this also captures how to think about two distinct customer bases – Customers who live in urban zones, with lots of retail density and Customers who live in sparse areas with a higher willingness-to-pay for deliveries. 
  3. Tax-based Price Zones: For one grocer we work with, the best approach to pricing was building a cluster of markets which shared the same or similar sales tax. That way, the grocer was able to think about the final pricing experience as inclusive of taxes in this price zone.
  4. Currency-based Price Zones: For an apparel brand we piloted with, one approach to pricing was generating price zones by currency. This allowed for consistent logic on costs and delivery fees, while also accounting for market-level willingness-to-pay. 
  5. Population and Income based Price Zones: For a retailer who was willing to execute a more complex zoning exercise, we were able to generate a matrix that combined a weighted average of population and income at a state level for all 50 US states. This created a pricing matrix of 20 zones, which is shared below.

Relationships between Price Zones

Once price zones have been established, the next step is to establish some principles around the mutual relationships between price zones. Most retailers wouldn’t want the same product to have wildly fluctuating prices between price zones, and establishing boundaries is one way to keep a range of price deltas between price zones.

At Luca, we support two types of relationships between price zones – 

  1. Static Price Relationships: This establishes a locked relationship between the same SKU in multiple price zones. For example, a specific 5% price delta between KVIs in price zone 1 and price zone 2. This works for price zones where there is a static difference in costs, such as a sales tax.
  2. Dynamic Price Relationships: This provides a range of potential relationships between the same SKU in multiple price zones. For example, defining a 0% to 25% price delta between KVIs in price zone 1 and price zone 2. This works for price zones where there isn’t a specific price delta that is pre-established, but the retailer wants to give their pricing team / Luca enough flexibility to find the right price in a wide range, without creating an unreasonably large delta between prices. 

Remember that this relationship doesn’t have to be defined at a catalog level, and can be assigned separately for different categories and types of SKUs in the catalog.

Simple US-based Price Zone

For someone who needs a starting point for a US-based price zone structure, this is a great starting point that sorts the country into 19 buckets based on a weighted average of income, population density and sales tax.

Price Zone States Characteristics Avg. Income (USD) Avg. Density (people/sq mile) Avg. Sales Tax (%)
1 New York, New Jersey, Connecticut, Massachusetts, Maryland High income, high density, high sales tax 70,000 1,200 6.5
2 California, Washington High income, high density, moderate sales tax 75,000 750 7.5
3 Illinois High income, high density, moderate sales tax 68,000 600 8.0
4 Colorado, Utah, Minnesota High income, moderate density, low sales tax 65,000 200 5.0
5 Alaska, Wyoming, North Dakota High income, low density, low sales tax 70,000 50 5.0
6 Pennsylvania, Ohio, Michigan Moderate income, high density, high sales tax 55,000 500 6.5
7 Texas, Florida, Georgia Moderate income, moderate density, high sales tax 60,000 350 6.5
8 Arizona, Nevada, New Mexico Moderate income, moderate density, moderate sales tax 55,000 250 6.0
9 Idaho, Montana, South Dakota Moderate income, low density, moderate sales tax 50,000 20 6.0
10 Nebraska, Kansas, Oklahoma Moderate income, low density, low sales tax 52,000 25 5.0
11 Louisiana, Arkansas, West Virginia Lower income, high density, high sales tax 45,000 200 6.5
12 Kentucky, Alabama, Mississippi Lower income, high density, moderate sales tax 42,000 150 5.5
13 Tennessee, Missouri, South Carolina Lower income, moderate density, high sales tax 45,000 200 6.5
14 Indiana, Iowa, Wisconsin Lower income, moderate density, moderate sales tax 48,000 100 6.0
15 Maine, Vermont, New Hampshire Lower income, moderate density, low sales tax 47,000 100 5.0
16 Virginia, North Carolina Mixed income, high density, mixed sales tax 55,000 300 5.5
17 Oregon Mixed income, moderate density, mixed sales tax 60,000 250 5.5
18 Hawaii High income, high density, high sales tax 70,000 1,000 7.0
19 Rhode Island High income, high density, high sales tax 72,000 1,100 7.5

Author

Tanvi Surti
Tanvi is the CEO and Co-Founder at Luca. Before Luca, Tanvi spent a decade building product teams at Uber and Microsoft. At Uber, she led the pricing team that created ~$1B in margin improvements on the ridesharing business, and now gets to help retailers solve the same problem, at scale.

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