Every AI use case, mapped to the business.

32 use cases owners are being sold this year, sorted by where they act in a business of 5 to 100 people. Only 3 are proven in production.

Status
Pick a room to see its use cases
How we rate

Four statuses, one rule: rate the evidence, not the pitch.

Each entry gets a status for how proven it is in businesses of 5 to 100 people, and a separate rating for how strong the evidence behind that status is.

Evidence strength

StrongSeveral independent studies or large independent surveys.
ModerateAt least one independent study or credible survey, plus consistent case evidence.
ThinA handful of independent data points.
Vendor claimsOnly what sellers publish about their own products.

How an entry is made

Each entry is drafted from public sources: academic studies, regulators, independent surveys and reputable reporting. Every figure carries a numbered citation you can open. Anything a vendor says about its own product is labelled as a vendor claim.

Review and updates

Every source in this edition was opened and checked against the text in October 2026. Each entry is then signed off by a named operator and re-checked when the evidence moves. Until that sign-off, the entry is marked as a draft at the top of the page.

The full guide

All use cases at a glance

Field GuidePricing & marginDynamic pricing
In pilotsPricing & margin

Dynamic pricing

Also called algorithmic pricing, repricing, automated repricer, price optimisation, markdown optimisation

EvidenceStrong
ClassAutomation

Dynamic pricing for small retailers: what research on algorithmic pricing shows about margins, price wars and competition-law risk.

ReviewDraft, awaiting operator review
Drafted27 October 2026
Fact-checkedEvery source opened, October 2026
Key takeaway

Algorithmic pricing is well studied, and the results cut both ways. In a field experiment at one online retailer, a price-optimisation tool raised test-group revenue by about 9.7%⁠. In German petrol markets, margins rose 28% where both competing stations adopted pricing software⁠, and competition authorities flag shared pricing software as a collusion risk⁠. In e-commerce data, sellers who switched on repricing tools first cut their prices by 16.93%⁠. None of this research looks at small firms specifically.

At a glance

StatusIn pilots
What it doesChanges your selling prices automatically, using rules or a model that reacts to competitor prices, stock levels, demand and time.
Typical costVaries by vendor. One competitor price-tracking tool lists plans from 99 a month, with its dynamic pricing engine from 199 a month (currency not shown on plan prices; add-ons priced in dollars; vendor list prices, checked Oct 2026)⁠
Data it needsLanded cost per product, current prices, 12 or more months of daily sales by product, stock levels, and competitor prices for matched products.
Setup effortMedium: matching your products to competitors' listings and setting price floors takes most of the work.
EvidenceStrong. Several peer-reviewed studies and competition-authority reports; none specific to small firms.

What is dynamic pricing?

Dynamic pricing means your prices change automatically, often several times a day, in response to data. The OECD separates three kinds of pricing algorithm: tools that only monitor rivals' prices, tools that recommend or set prices dynamically, and tools that personalise prices for individual shoppers⁠.

For a small retailer, the common version is a repricer: software that watches competitors on a marketplace or their websites and adjusts your price by rule, such as matching the cheapest seller but never going below a floor. A more advanced version uses a demand model to estimate how sales respond to price, then picks the price that maximises revenue or margin.

Large online retailers already use it. In a study of the five largest online retailers of over-the-counter allergy medicines, the fastest changed prices within an hour, while the slowest updated weekly⁠.

How does it work?

A typical setup has four parts:

  • Data in: your cost prices, current prices, stock on hand and sales history, plus competitor prices collected by scraping or from a marketplace feed.
  • Rules or a model: simple rules (beat the lowest price by 1%, never go below cost plus 15%) or a demand model that estimates how volume changes with price.
  • Guardrails: price floors and ceilings, a maximum change per day, and products excluded from automation.
  • Output: new prices pushed to your shop, marketplace listing or shelf labels, with a log of what changed and why.

Most small-business tools are rule-based, and competitor prices are the main input. That is why two sellers using similar rules end up reacting to each other. Research on e-commerce repricers found some vendors use strategies that periodically raise prices to encourage rivals to follow⁠.

What it needs to work

Dynamic pricing needs accurate costs, clean sales history and a reliable match between your products and competitors' products. Without a cost-based floor it can sell at a loss.

  1. Landed cost per product (supplier price plus freight and duties), updated whenever a supplier changes price, held in your stock or accounting system
  2. At least 12 months of daily sales and price history per product, so the tool can see how volume responded to past price changes
  3. Stock on hand per product and location, synced at least daily from your shop or stock system
  4. A checked list matching each of your products to the identical product on competitor sites or marketplace listings
  5. Written price floors, ceilings and a maximum daily change for every product the tool may touch
  6. A change log of every automatic price change, kept for audit and for answering customer complaints

Most use cases in this guide succeed or fail here, on the data underneath them, before any AI is involved.

What does the evidence show?

The research base is unusually strong, but none of it looks at small firms specifically.

  • Revenue: a field experiment with an online retailer of discounted designer clothing found a price-optimisation tool raised test-group revenue by an estimated 9.7% (90% confidence interval 2.3% to 17.8%)⁠.
  • Margins: in German retail petrol, margins rose 28% in two-station markets where both stations adopted pricing software; in two- and three-station markets, margins rose only when every station adopted⁠.
  • Prices: a model calibrated on five online retailers estimated algorithmic competition raised average prices by about 5%, compared with a benchmark where all firms set prices at the same time⁠.
  • Price wars: in e-commerce data, sellers who switched on repricing cut their prices by 16.93% on average; in markets with fewer than six serious competitors, some strategies later pushed prices up 11.4%⁠.

Adoption is lower than the hype suggests. In a 2020 Norwegian survey of 51 businesses, 55% used software to monitor competitors, but only 20% let algorithms set prices automatically; the authority cautioned the sample was small⁠. OECD analysis of competition-authority surveys found the same pattern⁠.

Algorithmic repricing vs manual price reviews

Compared onAlgorithmic repricingManual price reviews
Speed of responseMinutes to hoursWeekly or monthly
Effect on marginMixed in research: up where competitors also automate⁠, down where repricers chase each other⁠Depends on how often someone looks
Main riskPrice wars, selling below cost, competition-law exposureMissed margin when costs or competitors move
Cost modelMonthly subscription, often by number of products trackedOwner or buyer time
Best forMany SKUs sold on marketplaces against identical listingsSmall ranges, own-brand or differentiated products

Status and evidence

StatusIn pilots
Evidence strengthStrong

Rated pilots because strong independent research shows algorithmic pricing moves prices and margins⁠, but the effects are mixed and none of the studies looks specifically at 30-person businesses. Survey evidence shows far more firms monitor rivals than let software set prices⁠. The evidence is strong in quality and volume, though not about small firms.

Where does it go wrong?

  • Race to the bottom. Two repricers chasing the cheapest price can drag a product to its floor within hours. In one e-commerce study, adopters' first move was a deep price cut⁠.
  • No floor, no margin. A rule without a cost-based floor will sell below cost when a competitor clears stock or lists an item at the wrong price.
  • Bad competitor matches. Matching your 5 kg bag to their 2 kg bag produces nonsense prices. Product matching is where most setup time goes.
  • Shared software, shared risk. The UK CMA said rivals using the same pricing algorithm, for example from one third-party supplier, was likely to be the most immediate collusion risk⁠. South Africa's Competition Commission has warned that if most firms in an industry follow a tool's recommended prices, a collusive outcome is likely⁠.
  • Customer backlash. Fans believed the Oasis ticket sale used dynamic pricing. The CMA found no evidence of that, yet still secured commitments from Ticketmaster to warn fans in advance about tiered pricing⁠.
  • Stale costs. If supplier price rises reach the repricer late, it sets prices against yesterday's margin.

Numbers it should move

Gross marginSales minus the cost of the goods sold, as a share of sales.
Stock turnsHow many times a year your stock sells through.
Average discountThe average discount given off list price.

Ask the demo business

Northgate Supply is a fictional wholesale distributor of catering and packaging supplies: 28 staff, R46.6m in sales over the last year. Its data is generated for this demo, to 30 September 2026.

Fictional data
What is our gross margin by month, and which category is slipping?
22.9%in September 2026

Gross margin was 22.9% in September, against 24.4% last October. Packaging slipped most, from 26.1% to 22.9%, after a supplier raised prices and our sell prices stayed where they were.

OctNovDecJanFebMarAprMayJunJulAugSep22.9%
How this was worked out

(Sales minus cost of goods sold) divided by sales, per month. Cost uses the supplier price on the day each line was sold.

Answered in 10 msScanned 15 959 rowsFrom invoice lines
Want this on your own numbers, in the AI tools you already use?Book a demo

Where the data usually lives

ShopifyWooCommerceTakealot Seller PortalCin7Excel and Google Sheets

Where the records this use case needs are usually kept in a small business. It is not a list of recommended tools.

Frequently asked questions

How much does dynamic pricing software cost?

One competitor price-tracking tool starts at 99 a month for up to 100 products, with its dynamic pricing engine from 199 a month for up to 1,000 products⁠. Its plan prices show no currency, though add-ons are priced in dollars (checked Oct 2026)⁠. Other tools price differently, so compare on the number of products and channels you need.

Do I need a developer to set up dynamic pricing?

For a marketplace repricer, usually not: most connect to your seller account and you set rules in a dashboard. For your own website, your shop platform must accept automatic price updates, and someone must check product matches against competitors. Model-based optimisation using your own sales history generally needs an analyst, at least to set it up.

Is it legal to use the same pricing software as my competitors?

Using pricing software is legal, but it carries competition-law risk. The UK CMA said rivals using the same pricing algorithm, for example from one third-party supplier, was likely to be the most immediate collusion risk⁠. South Africa's Competition Commission has said that if most firms in an industry follow a tool's recommended prices, a collusive outcome is likely⁠. Never share non-public prices with rivals, directly or through a vendor, and take legal advice if unsure.

Do I have to tell customers my prices change automatically?

Be open about it. In the UK Oasis ticket case, the CMA's concern was that fans were not told prices would rise once cheaper tickets sold out. Ticketmaster committed to give 24 hours' notice of tiered pricing and to show the price range in the queue⁠. Since April 2025 the CMA can fine firms up to 10% of turnover for consumer-law breaches⁠. This is not legal advice.

Can I set different prices for different customers using their data under POPIA or UK GDPR?

That is personalised pricing, and it uses personal information, so data protection law applies. POPIA gives people a right, in certain circumstances, not to be subject to decisions based solely on automated profiling⁠. UK GDPR has specific rules on solely automated decisions with legal or similarly significant effects, and the ICO published updated draft guidance in 2026⁠. Regulators found little evidence of personalised pricing in practice⁠. This is not legal advice.

More in pricing & margin

AI quote generationUnprovenEvidence: ThinDiscount-creep detectionUnprovenEvidence: ThinSupplier price-change monitoringUnprovenEvidence: Thin

Sources

  1. 1
    Analytics for an Online Retailer: Demand Forecasting and Price Optimization
    Manufacturing & Service Operations Management (via MIT DSpace), 2015Study
  2. 2
  3. 3
    Competition in Pricing Algorithms
    University of Michigan working paper (published in American Economic Journal: Microeconomics, 2023), 2021Study
  4. 4
  5. 5
  6. 6
  7. 7
    Survey shows that several companies use monitoring algorithms
    Norwegian Competition Authority, 2021Government
  8. 8
  9. 9
  10. 10
    Prisync pricing
    Prisync, 2026Vendor
  11. 11
    Protection of Personal Information Act 4 of 2013
    South African Government, 2013Government
  12. 12
    Automated decision-making, including profiling
    Information Commissioner's Office, 2026Government

This entry is educational. It is not legal, financial or professional advice, and it does not recommend any vendor. Figures attributed to vendors are their own claims.

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