If you sell on Shopify, your prices are public, your competitors' prices are public, and your customers compare them in another browser tab before they buy. The only question is whether you see what they see.
This guide covers the four realistic ways to track competitor prices, what each one actually costs in time and money, and where each one breaks. It ends with how to act on the data - because a spreadsheet of competitor prices that nobody acts on is just homework.
Method 1: Manual checking (fine for 1-2 competitors, briefly)
Open your competitor's site once or twice a week, note the prices of the products that overlap with yours, and keep the notes somewhere. This is where everyone starts, and for a brand-new store with one obvious rival it's genuinely fine.
Where it breaks:
- It doesn't scale past a handful of SKUs. Five competitors × 30 overlapping products × twice a week is 300 price checks a week. Nobody sustains that.
- You miss the timing. Price moves matter most in the first days - a competitor's weekend flash sale is over before your Tuesday check.
- No history. Without a record, you can't tell a habitual discounter (who reverts every Monday) from a structural price cut that actually demands a response. The two need opposite reactions.
Method 2: The spreadsheet system (better, still manual at the core)
The upgrade: a spreadsheet with one row per product, columns for each competitor, and a date-stamped tab (or appended rows) per check, so you build history. Some merchants wire in IMPORTXML-style formulas in Google Sheets to auto-pull prices from product pages.
What the formula approach trips over in practice:
- Most modern storefronts render prices with JavaScript, which spreadsheet import functions can't execute. You get blanks or stale server-rendered values.
- Sites change their markup without notice; every redesign silently breaks your selectors, and the sheet keeps showing the last fetched number - the worst failure mode, because it looks like data.
- Frequent automated pulls from one Google IP get rate-limited or blocked entirely.
A spreadsheet is still the right tool for the analysis layer if you enjoy that work - but as the collection layer it's fragile.
Method 3: One useful trick - Shopify storefronts expose their catalogue
If your competitor also runs on Shopify, their storefront exposes public product data: appending /products.json to most Shopify store URLs returns the catalogue - titles, variants, and prices - in machine-readable form. This is public product information the store itself publishes for its storefront to function.
It's the most reliable way to read a Shopify competitor's prices (no HTML parsing, no selector breakage), and it's how dedicated tools - PriceSway included - monitor Shopify-to-Shopify. The catch: you still need to match their products to yours, re-check on a schedule, store the history, and notice the changes. The data access is the easy 20%.
Method 4: Dedicated monitoring tools
Price monitoring tools handle collection, matching, history, and alerting as a service. When you evaluate them - ours or anyone's - the questions that actually separate them:
- Who finds the competitors? Most tools make you paste competitor product URLs yourself - which means the two hardest tasks (knowing who your competitors are, and matching their products to yours) stay manual. PriceSway inverts this: it searches the web for each of your products and surfaces the merchants that keep appearing, ranked by how much of your catalogue they overlap.
- What happens when scraping fails? Every tool's checks fail sometimes. The difference is whether failures are flagged (“this item hasn't refreshed in 9 days”) or silently shown as fresh data.
- Alert noise. Per-change emails become inbox spam within a week. A daily or weekly digest with a meaningful-change threshold is the difference between a tool you read and a tool you filter.
- Does it tell you what to do? “Competitor X dropped 8%” is a fact. Whether to match, hold, or raise is a decision that depends on your demand curve and margins - and it's where monitoring tools and pricing tools diverge.
Acting on the data (the part that pays for all of this)
Three rules that prevent the most expensive mistakes:
- Don't reflexively match every cut. If a competitor drops 10% and your customers aren't especially price-sensitive for that product, matching just donates margin. The right response depends on your price elasticity - how much demand you'd actually lose by holding. (This is the entire reason PriceSway models elasticity instead of stopping at alerts.)
- Distinguish promotions from repricing. A price that drops Friday and reverts Monday is a promotion; a price that drops and stays is a new market level. Only the second one should influence your standing prices - which is why history matters more than snapshots.
- Watch for room to raise. Merchants fixate on undercutting, but the most common finding when stores start monitoring is the opposite: products priced meaningfully below the market median for no strategic reason. That's free margin.
The bottom line
Manual checking works for one competitor for about a month. Spreadsheets add memory but keep the fragile collection problem. If competitor prices actually influence your pricing decisions, automated monitoring pays for itself quickly - and the free tier of PriceSway (3 competitors, discovery included, no card) is a zero-cost way to find out whether the data changes any of your decisions before you pay anyone anything.