How To Build A Competitive Set For Merchants And Retail Buyers

Competitive Set refers to the group of brands or products a consumer or retailer is most likely to compare with a particular offering. Building one correctly is a repeatable process that helps merchants, category managers and retail buyers focus measurement and action on close substitutes.

This how-to guide walks through a practical workflow that fits both brick-and-mortar and e-commerce environments. The goal is a compact, defensible set you can monitor weekly and revise on a fixed cadence.

Step 1 — Define The Decision And Scope

Start by specifying the decision the comp set will inform. Is it price, promotion, assortment, or planogram placement? Also define the channel and geography: an item’s comp set for Amazon search may differ from its in-store comp set in a specific region.

Step 2 — Identify Candidate Peers

Collect a broad list of candidates using multiple sources:

• Sales Data: Top substituted SKUs from POS or marketplace orders.
• Search Terms: Marketplace and Google search queries that return your SKU and others.
• Category Reviews: Retail planogram neighbors and top-rated alternatives on e-commerce listings.
• Customer Feedback: Reviews and customer service logs mentioning alternatives.

Step 3 — Apply Filters To Narrow To 3–6 Items

Filter candidates by the criteria that matter to your decision:

• Price Proximity: Exclude items outside a defined price band unless you’re testing up-/down-trading.
• Pack Size And Format: Keep unit economics comparable.
• Channel Presence: Only include items available where you sell.
• Promotion Synchrony: Favor peers with similar promotional behavior to avoid distortions.

Step 4 — Define The Measurement Set

Agree with stakeholders on the KPIs you’ll track weekly or monthly. Practical KPIs include price gap, units per store per week (velocity), share of shelf, discount depth, and review sentiment. Limit to 3–5 KPIs to keep reports focused.

Step 5 — Automate Data Collection

Use available tools to automate monitoring. Examples:

• Scanner Data: For brick-and-mortar velocity and price gap across stores.
• Marketplace Analytics: For Buy Box competitors, pricing, and reviews on marketplaces.
• Web Scraping / Price Intelligence: For online price tracking across retailers.

Step 6 — Review And Adjust Regularly

Set a cadence: monitor weekly for volume and price signals, and formally review the comp set quarterly. Replacements are common—new entrants, private-label launches, or distribution changes often require swapping a member.

Practical Example — E-Commerce Seller

An online seller of insulated water bottles starts with 12 candidate peers from search data. After filtering for price band (±15%), pack size, and Prime availability, they select five peers. The team tracks Buy Box price gap, average weekly unit sales, and review sentiment. When one peer adds a reorder subscription discount, the seller spots a drop in relative velocity and runs a targeted ad test to regain share.

Common Implementation Challenges

Expect and plan for these issues:

• Data Gaps: Smaller retailers may lack scanner data; use panels, syndicated data or first-party sales as proxies.
• Multiple Channels: Maintain separate comp sets per channel if shopper behavior diverges.
• Competitor Noise: New SKUs and temporary promotions create noise—use smoothing windows when calculating baselines.

Checklist For Launch

• Decision Defined: Clear business question for the comp set.
• 3–6 Members Selected: Defensible selection with source notes.
• KPIs Agreed: Short list of metrics and reporting cadence.
• Data Feeds Automated: At least weekly refresh where possible.

In short, the Competitive Set is a compact, operational tool. Build it around the specific decision, use 3–6 comparable peers, automate measurement, and review regularly to keep insights timely and actionable.