FMCG Price Intelligence
by Gadiel Analytics

Case study · Revenue growth management · Pricing analytics

How Coca-Cola and Pepsi price soft drinks in Ireland

A daily shelf-price study of SuperValu Ireland: price-pack architecture, promotions, Ireland's sugar levy and the price gap to Pepsi, recomputed from the data every day since June 2026.

The short answer

Coca-Cola charges a full-sugar premium on every pack; Pepsi undercuts it on eight of ten matched packs.

+4% to +24%
Coca-Cola full-sugar premium over Zero Sugar per litre, across 8 packs
5 of 7
pack sizes where Pepsi and Pepsi Max cost the same today
8 of 10
matched cola packs where Pepsi is cheaper at today's price
125 of 125
days the Coca-Cola Zero Sugar 2 L bottle was on promotion

What the data shows today

These findings are regenerated on every daily run, with explicit rules on how strongly each one may be stated. Each links to the exhibit behind it.

  • The full-sugar premium exceeds the sugar levy on six of eight packs, and triples it on the 330 ml can.

    See exhibit 1
  • In the one day since Budget 2027, no Coca-Cola pack changed its full-sugar premium; no change to the levy was announced.

    See exhibit 2
  • On 1 Oct, Coca-Cola moved its Zero Sugar and Diet Coke 2 L bottles from 3 for €6.75 to 3 for €6.

    See what changed
  • Pepsi is cheaper than Coca-Cola on eight of ten matched packs; Coca-Cola is cheaper on the other two.

    See exhibit 7
  • Coca-Cola is the only brand pricing full sugar clearly above no sugar: a median +15% per litre, against 0% for Pepsi.

    See exhibit 8
  • Four Coca-Cola SKUs were on promotion on at least 90% of days, all of them 2 L bottles.

    See exhibit 5
  • One Coca-Cola pack costs more per litre than a smaller pack of the same range.

    See exhibit 4
  • Red Bull costs about 2.1× Monster per litre at the median price.

    See exhibit 10

Why this matters for revenue growth management

Revenue growth management works through four levers: price setting, pack and mix, promotion and trade investment. The shelf makes three of them visible from outside any company: the everyday price a shopper sees, the way price per litre steps down as packs get larger, and the promotions that sit on top. Trade investment stays invisible, and this study never claims to measure it.

Ireland adds a policy lens. Drinks with eight grams of sugar or more per 100 ml carry a levy of about €0.30 per litre at the shelf, while Zero Sugar and diet ranges carry none. Comparing the full-sugar premium with the levy, pack by pack, shows how a brand prices its taxed and untaxed ranges. It is a benchmark rather than a measured pass-through: each pack's premium also reflects its own pricing strategy.

The competitive read separates two kinds of gap. An everyday price gap is a positioning choice; a promotional gap is a tactical one. Many of the competitor discounts in this data require SuperValu's Real Rewards card, so the study keeps prices open to every shopper apart from Rewards prices and marks which comparisons depend on them.

For a commercial team, the same daily read supports concrete decisions: a price-gap corridor to the main rival for each hero pack, a check that larger packs never cost more per litre than smaller ones, promotion planning against a calendar of rival activity, and a disciplined read of policy events such as the Budget, with every confounding promotion or range change flagged rather than mistaken for a response.

How it works

  • Collection: once a day, an automated job reads SuperValu Ireland's public search results for cola, lemon-lime, orange and energy drinks, at human rate and without logging in. Nothing personal is collected.
  • Quality: a run that returns fewer than half the products of the past week is refused, so a broken page never enters the history; re-running a day replaces it.
  • Pricing model: regular and promotional prices are separated, every price is normalised per litre, and packs are matched like for like by size, count, container and sugar tier.
  • Narrative with guardrails: every headline is generated from the data with tested rules. Changes are reported, never attributed: a change after an event is described as a change, and a ratio to the levy as a benchmark.
  • Stack: Python, DuckDB and Parquet, versioned daily in git; GitHub Actions for orchestration; D3 for the exhibits. The infrastructure costs nothing to run.

What it does not show

Shelf prices are not sales. Without volumes there is no price elasticity and no promotional return on investment; the study is the shelf-side complement to scanner and shipment data, not a substitute for them. It covers one retailer, competitor history began on 27 September 2026, and prices are read from search results as a shopper would see them online.

About the author

Gadiel Guadarrama, M.Sc.

Analytics, data science and AI strategy leader whose work focuses on the design of decision systems, structural metrics and enterprise data architectures. More than a decade of enterprise experience, including commercial-analytics work inside one of the world's largest FMCG beverage ecosystems and enterprise analytics across finance and insurance.

Founder of Gadiel Analytics, decision intelligence and enterprise AI advisory, including commercial analytics and revenue growth management. Author of The Analytics System: Designing Data Foundations, Metrics, and AI for Better Business Decisions (Wyckham House, 2026).

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Built and maintained by Gadiel Guadarrama, M.Sc. — analytics, data science and AI strategy leader, founder of Gadiel Analytics and author of The Analytics System. For decision intelligence, pricing and revenue growth management advisory: hello@gadielanalytics.com