> Source: https://www.k-stra.com/solutions/loyalty-card-analysis/ > Updated: 2026-11-05 Solutions · Loyalty card analysis # What can loyalty card data tell me about a store? A loyalty programme is the only map of your real customers you already own. Most businesses use it for vouchers; it can also tell you where each store’s market actually is. In short Loyalty card data shows where a store’s customers live and how much they spend. Mapped by postcode and projected to the store’s total, it gives turnover and cards per area, the share of local household spending the store takes, the share of households it reaches, and how much its cardholders spend in the chain’s other stores. [Map your card data](https://www.k-stra.com/a/?src=solutions-loyalty-card-analysis) What makes this hard ## Why is loyalty data hard to read on its own? Card data comes as millions of rows by card and month. It says who spent what, but not where the store stands against the area: a postcode that brings in a lot may simply be large, and a quiet one may be full of people who shop elsewhere. It is also a sample. Some customers never scan a card, some cards have no usable postcode, and the share varies by store. Read raw, the data favours the stores where staff push the card hardest. And customers do not belong to one store. The same household may shop at two branches of the chain, so a store’s results include spending its neighbours could claim, and the reverse. Almost 90% of Australians are members of at least one loyalty scheme, according to the competition regulator. Membership is wide, but card data still covers only the sales that carry a card. Australian Competition and Consumer Commission (2019), “Customer loyalty schemes — final report”, accc.gov.au. *[Image: K-Stra Customer Loyalty for a sample store in Braddon, Canberra ACT: postcodes of Canberra shaded by loyalty-card turnover, and the store’s turnover, operations, cards and market share on the right.]* Sample data · Canberra A$7.19M from 4,682 cardsA sample grocery store in Braddon: the darker the postcode, the more loyalty-card turnover it brings. The store’s own postcode is not the largest; 2602, next door, is. Method ## How do you analyse loyalty card data, step by step? 1. Step 01 ### Export the card data by store and month One row per card, store and month, with the amount spent and the number of transactions. An anonymised card code and a postcode or suburb are enough. 2. Step 02 ### Keep the people out Use an anonymised card code that cannot be traced to a person, never a name, email, phone number or home address. A postcode places a customer well enough for every measure on this page. 3. Step 03 ### Map cards to areas Add up turnover and cards by postcode. The map shows where the store really draws from. 4. Step 04 ### Scale the sample to the store Not every sale carries a card. Project the cardholders’ figures to the store’s total, so each area gets its fair weight. 5. Step 05 ### Compare with what the area spends Divide the store’s turnover in each area by the residents’ spending in the category: that is its market share there. 6. Step 06 ### Count the households you reach Cards per hundred households is penetration. A strong share with low penetration means few, loyal customers. 7. Step 07 ### Look across the network Check where the same cardholders also shop, inside your chain. It tells you which stores share customers and how much. Data ## What data do you need for a loyalty card analysis? Your card file does the work; the population and spending figures that turn it into shares come with K-Stra. - ### Card transactions by month Store code, card code, month, amount and number of transactions, from your loyalty system. A template is in the app. [File formats and limits](https://www.k-stra.com/product/system-requirements/) - ### A postcode per card The location of a card: a postcode, or a suburb. Never a name, an email, a phone number or the street address of a private individual. [Postcodes in K-Stra](https://www.k-stra.com/product/data/territory/) - ### Households and residents ABS population estimates at 30 June 2025 and families from the 2021 Census, to measure penetration. [Population data](https://www.k-stra.com/product/data/population/) - ### Food spending of the area Residents’ yearly spending on food from the ABS national accounts for 2024–25, to measure market share. [Income and spending data](https://www.k-stra.com/product/data/work-and-income/) K-Stra runs on a dedicated server in Sydney: your datasets, your analyses and your results stay in Australia. Map tiles, payments and sign-in never see your files. Three steps can: geocoding sends only the address text, and only after you confirm; the AI assistant reads column names and values when you ask it about a dataset; email notifications carry figures from your analysis.[Where your data lives](https://www.k-stra.com/product/coverage/#where-your-data-lives) . Mark a dataset “session only” and it is deleted 24 hours after upload. *[Image: K-Stra Customer Loyalty results for the sample Braddon store: where else its cardholders shop in the chain, and how its cards split across spending classes.]* Where else the Braddon cardholders shop: A$1.84M of their spending goes to the chain’s other two stores, most of it to Woden. Below, the cards by yearly spending class. In K-Stra ## How do you analyse loyalty cards in K-Stra? Customer Loyalty is a module of the What step. Import the card file from the module, pick a store and a period, and choose how to group the cards. 1. ImportImport loyalty data turns the file into monthly transactions and store totals. Each import costs 1 credit per 10,000 rows. 2. ZonesThe 20 postcodes with the most cards for cards with a postcode, or catchment bands from 5 to 30 minutes for records placed at the address of a business or other place. 3. MeasuresTurnover, operations, cards and average ticket, potential and market share, all in one run at one price per store. The results add the monthly trend, the spending classes of the cards, and wallet share: how much of each card’s spending stays in the store, and how much goes to your other stores. [Try it in the app](https://www.k-stra.com/a/?src=solutions-loyalty-card-analysis) Video ## What does a loyalty card analysis look like in the app? [Download the video (0:49)](https://www.k-stra.com/_astro/kstra-howto-loyalty.Bh4MN8Ct.mp4) Video · 0:49, voice and subtitles. Customer Loyalty narrated in under a minute, on the same sample chain in Canberra: anonymised card data, the card turnover of a store by postcode, its share of the residents’ spending and how much of each card’s spending stays in the store. Transcript Customer Loyalty shows where your customers come from, using the loyalty cards of your own stores. Load your card data: an anonymised card code, its store, what it spent and its postcode are enough — no names, no addresses. Here, a sample chain with three stores in Canberra. You see the store's card turnover postcode by postcode, how far its customers travel, and its share of the spending of the residents around it. And Wallet share shows how much of each card's spending stays in this store, and how much goes to your other stores. Exploring and setting up are free. You only spend credits when you run the analysis. Example ## What does a loyalty card analysis show? A sample grocery chain with 3 stores in Canberra and 9,986 cards, November 2025 to October 2026. The Braddon store had 4,682 cards, A$7.19 million of turnover and an average ticket of A$74. Its cards reach 4.1% of the families in its 20 postcodes, and it keeps 79.6% of what its cardholders spend in the chain. Loyalty-card turnover and market share of the sample Braddon store in its four largest postcodes Postcode Turnover (A$ million) Share of the store’s turnover Market share of food spending 2602 1.73 24.2% 0.8% 2612 1.44 20.2% 1.2% 2600 0.52 7.4% 1% 2601 0.49 6.9% 1.2% Sources: sample loyalty data of a fictional chain in a K-Stra sample account, projected to the store total; ABS population at 30 June 2025, Census 2021 families, ABS national accounts 2024–25 for food spending. K-Stra analysis of 1 November 2026. Reading the numbers ## What do these numbers say about the store? The store draws more from 2602 than from its own postcode: 24.2% of its turnover against 20.2%. Its market share is highest close by, about 1% of food spending in 2612 and 2601, and falls to 0.3% across all 20 postcodes. Most cards are light: 3,710 spend under A$2,500 a year, and only 18 spend A$7,500 or more. On average a cardholder spends here 8.8% of the food spending the model expects from a resident of their area. 1,443 of the 4,682 cards also shop at another store of the chain, taking A$1.84 million there: 57.4% to Woden and 42.6% to Gungahlin. That is spending the chain keeps either way; moving it between stores is not growth. The chain, its stores and its cards are invented for this example and loaded into a K-Stra sample account; the population and spending figures are real ABS data. Cost ## How much does a loyalty card analysis cost? The analysis has one price per store and run: the length of the period and the measures you look at do not change it. Another store or another period is a new run at the same price. The import is paid once, and every run can then start from the same file. Records that carry the address of a business or a place can be geocoded at the geocoding tariff; the import shows that cost before you confirm. [How credits work](https://www.k-stra.com/pricing/how-credits-work/) - Customer Loyalty, one store20 credits per store analysed 20 credits - Import of 88,466 card rows1 credit per 10,000 rows 9 credits - Reopening, maps, tables and exports Free - Total\= 29 credits - ≈ A$44 at the Single report pack rate of A$1.53 a credit; less with larger packs and monthly plans. A new free account’s 40 welcome credits cover it. The cost appears before anything runs; a run that fails costs nothing, and an interrupted import pays only for the rows already loaded. FAQ ## What else do people ask about loyalty card analysis? ### Do I need customers’ addresses? No. An anonymised card code with a postcode or suburb is enough to map cards, measure share and penetration by postcode, and compare stores. Do not upload the street addresses of private individuals: K-Stra datasets must not contain personal information. ### What if only some sales carry a loyalty card? That is normal. K-Stra projects the cardholders’ figures to the store’s total turnover, operations and cards, and shows the scale factor it used. Where too few cards can be placed, it does not project and says so. ### How is market share calculated? As the store’s turnover in an area, from your loyalty data projected to the store total, divided by what the area’s residents spend on food in a year, from ABS data. It is your share of residents’ spending, not a share of competitors’ sales. ### Can I analyse several stores at once? Yes. Each store analysed costs 20 credits, and the chain-wide tables show how cardholders split their spending between stores. Related pages - [Market share and penetration](https://www.k-stra.com/geomarketing/market-share-and-penetration/) - [For marketing teams](https://www.k-stra.com/for/marketing-teams/) - [Customer mapping](https://www.k-stra.com/solutions/customer-mapping/) - [Importing your data](https://www.k-stra.com/product/my-data/) - [Cannibalisation analysis](https://www.k-stra.com/solutions/cannibalisation-analysis/) - [Catchment area analysis](https://www.k-stra.com/solutions/catchment-area-analysis/) - [Income and spending data](https://www.k-stra.com/product/data/work-and-income/) - [What is a catchment area?](https://www.k-stra.com/geomarketing/catchment-area/) - [Coverage and data residency](https://www.k-stra.com/product/coverage/) Your turn ## Your customers are already in your data. Download the template, import your card file and see where each store really draws from. [Open the app — free to explore](https://www.k-stra.com/a/?src=solutions-loyalty-card-analysis) Import 1 credit per 10,000 rows