Holiday pricing for retailers

TL;DR

In the holiday season, shoppers see the same product from many stores and from the brand's own shop, side by side on Google Shopping, marketplaces and AI assistants. Retailers control less of that choice than ever.

That makes the store's brand the reference point for the holiday price, and the first thing to find out is whether shoppers come because they want to shop there or because the store is cheap.

Share of demand set against share of purchases answers that, and shows how much room the store has to hold its prices.

The competitor to compare prices with is the store your shoppers would switch to, usually a store of the same kind.

Most of these answers are already in the brand tracker, so pricing can start from data the store already collects.

From Black Week to Christmas, more holiday shopping now starts on storefronts no retailer owns. Google Shopping, price comparison sites, marketplaces, TikTok Shop and AI assistants list the same product from several stores, often at almost the same price, and more often than before from the brand's own web shop too.

For a retailer, that changes what the shopper compares. The product is often the same in every listing, so what differs is who sells it, at what price and with what discount. Pricing and category teams know their margins and their competitors' prices, insight and brand teams know the brand tracker, e-commerce runs the feeds, and product or social commerce teams follow the ratings. Each works from strong data of its own, and the holiday plan is where it pays to put that data side by side.

Brand tracking can answer three questions the holiday plan depends on: whether shoppers choose the store because they want to shop there or because it is cheap, which store they would go to instead, and whether gift buyers think of it at all.

Holiday shopping on storefronts no retailer owns

Last year's figures show how fast this is moving:

Visits to US retail sites from AI assistants rose by 693% on the 2024 holiday season and converted 31% better than other traffic (Adobe). Adobe expects a further 130% rise in 2026.
Prisjakt, the Nordic price comparison site, sent 132.8 million clicks to retailers in 2025, against 109.3 million in 2024 (Prisjakt).
47% of Swedes bought most of their Christmas presents online in 2025, against 35% in 2019 (Svensk Handel).

On these surfaces a store is reduced to a name next to a price, a delivery time and a rating.

Competing with other stores and with the brands themselves

A retailer now competes on two fronts. Other stores list the same products, and many brands sell the same products in their own web shops, often at the recommended price and with holiday offers of their own.

When the same product is listed at similar prices, the store's brand decides. Shoppers pay a little more to buy from a store they know and trust, with delivery and returns they can rely on.

The brand's own shop changes the comparison in two ways. It shows the recommended price next to the retailer's discount, and it competes for the shoppers who would rather buy directly from the brand. What the retailer has that the brand's shop lacks is range across brands, advice, loyalty benefits, delivery and gift sets made for the store.

Do shoppers choose the store, or its prices?

The most useful number before setting holiday prices is the gap between how much a store is wanted and how much it is used. Share of demand measures the first: the share of category shoppers who would choose the store if every store had the same prices and range. In our trackers it is calculated from each respondent's ratings of the stores they would consider, and its results follow market share closely.

Set against the store's share of purchases, it places the store in one of two positions. Take two stores with 10% of the market each, in an invented example:

Store A has a share of demand of 14%. More people would like to shop there than do, usually because of price or reach. It has room to hold its prices, and a well-chosen offer can convert demand it already has.
Store B has a share of demand of 7%. Shoppers use it for its prices or its convenience more than for the store itself. It is exposed when a store that people want more matches its prices during the holiday season.

A strong brand gives a store room to charge more. Kantar finds that one point of what it calls pricing power justifies about four points of higher relative price (Kantar, 2026). Shoppers still react when prices change, so a store with a strong brand also loses some shoppers when it raises its prices.

Which store shoppers would switch to

Holiday discounts are often benchmarked against the cheapest offer for the same product. The stores that shoppers consider as alternatives tend to be of the same kind as the one they prefer, close to it in price and in what it offers. That makes the nearest store of the same kind the competitor to watch on price.

On a list sorted by price, the order matters as much as the gap. Passing a competitor's price moves more shoppers than narrowing the gap to it.

A tracker can identify the store to watch. Look at which other stores the people who prefer your store would also consider, compared with all category shoppers.

What beauty retail data shows: stores wanted more than they are shopped at

In our beauty data, both positions and the stores shoppers would switch to show clearly in Sweden, the UK and Germany.

Source: Odyssey Beauty Signal, Sweden, UK and Germany. Beauty shoppers, January to September 2026.

The department stores and beauty specialists in the chart have a share of demand 15 to 27% above their share of purchases, and most others in the group are above 100 too. Space NK in the UK (86) and Notino in Sweden (90) are the exceptions. Grocery stores in all three markets and pharmacies in Sweden and Germany are used more than they are wanted. Among pharmacies, the British chemists are the exception: Boots, Superdrug and LloydsPharmacy are all above 100.

Shoppers describe the two groups differently. In Sweden, 46% of the shoppers who rated Sephora called it luxurious, against 7 to 10% for the pharmacies. In the UK, 44% of those who rated grocery stores called them the cheapest, against 14% for Selfridges.

In each case the other store is of the same kind: a beauty specialist, a pharmacy, a perfumery or a department store.

The gift buyer chooses differently

In December many purchases are made for someone else, often in a category the buyer does not buy for themselves. About one in five US consumers bought fragrance as a holiday gift last year, and December accounts for about 60% of fourth-quarter fragrance sales (Circana).

Gift buyers are less sensitive to price than when they buy for themselves, especially when they are unsure of the recipient's taste (Wang and van der Lans, 2018). Many read a higher price as a sign of a better present. With little knowledge of the category, they lean on names they recognise, of brands and of stores.

When we ask AI assistants where to buy a beauty gift, most often a luxury one, a small group of well-known stores appears again and again: NK and Åhlens in about a third of the Swedish answers, and John Lewis, Boots and Selfridges in about four in ten of the British ones. Some of the questions name a department store themselves, which explains part of the pattern. Asked where to buy beauty cheaply, the assistants name other stores: online specialists such as Lyko, in half of the Swedish answers, and Boots and Superdrug in the UK.

In Sweden the two seasons overlap. In Svensk Handel's survey, 64% expected to buy Christmas presents during Black Week (Svensk Handel), so from Black Week to Christmas the same price list meets both a deal seeker and a gift buyer. For the gift buyer, the measure that counts is how well the store is known among people who do not buy the category.

Ratings, delivery and product data in AI shopping

On marketplaces and in AI assistants, a store is presented through its product data, its ratings and its delivery terms. These signals carry a lot of weight in AI shopping.

In a study of skincare recommendations, AI assistants always picked the well-known brand when the products were otherwise identical, and stopped doing so once a competitor's rating was less than 0.1 star higher (Chu and Hou, 2026). Strike-through prices and countdown timers, the usual holiday sale tools, had no consistent effect on the AI shopping agents tested in a recent study (Sabbah and Acar, Harvard Business Review, 2026).

For a retailer, the ratings that count include delivery, returns and service. They belong in the season's plan next to the brand tracker.

What to look for in your own data before the holiday season

Most of the answers are already in data the teams have. These are six signals to read, and what each means for the holiday price.

1. Share of demand against share of purchases

Divide the store's share of demand by its share of purchases in the tracker and multiply by 100.

Above about 110: more shoppers want the store than use it. Hold prices on the products where you are the preferred store, and use offers to convert shoppers who already want you, for example with added value or targeted offers in the categories where your preference is strongest. Discounts across the whole range give margin away to shoppers who would have come anyway.
Around 100: shoppers use the store about as much as they want it. Follow your nearest competitor on the key products, and leave it to others to start the price war.
Below about 90: your share rests on price or convenience. Keep your price position on the products shoppers compare most, and watch the store above you: if it cuts to your level, you lose shoppers. Delivery and ratings are what you can compete on besides price.

2. Price associations

Compare how many shoppers call your store "lowest price" and "value for money" with the figures for your nearest competitor.

If you are the store most often called cheapest, your discounts set the market price and competitors will follow them. Plan your second move before the season starts.
If few call you cheapest but many call you luxurious or high quality, a deep discount gives away the reason shoppers come. Add value at full price instead, with gift sets, samples, wrapping or free delivery.

3. The store your shoppers would switch to

Among the shoppers who prefer your store, find the other store they consider much more often than shoppers in general.

The store with the highest ratio is the one to watch. Beauty shoppers consider many stores, so the share alone says little: more than half of those who prefer Lyko also consider Kicks, Apotea and Normal. Kicks stands out because they consider it 1.3 times as often as shoppers in general, and its prices are the ones to watch on the key products.
Decide product by product whether to sit just above or just below that store. Whether you pass its price matters more than how large the gap is.

4. Awareness among people who do not buy the category

Compare the store's aided awareness among people who rarely buy the category, such as beauty shoppers who never buy fragrance for themselves, with awareness among its regular shoppers. Many trackers interview only category buyers, so this group may need to be added.

If the two are close, gift buyers will find you. Price gift sets at levels that read as a good present, and keep them out of the deepest discounts.
If awareness among non-buyers is much lower, gift buyers will go to the stores they know, often the department stores that AI assistants recommend. In the run-up to Christmas, reach among this group is worth more than a bigger discount.

5. Ratings against your nearest competitor

Compare your ratings for the key products, delivery and returns with those of the store your shoppers would switch to.

If yours are higher, you can hold a small price premium, because AI assistants and marketplaces that rank by rating favour the better-rated offer.
If yours are lower, even by 0.1 star, AI assistants may pass you over for that competitor. Improve the ratings before you cut the price. Ask recent buyers for reviews and answer the critical ones before the season starts.

6. What AI assistants say about your store

Ask the assistants the questions your shoppers ask, such as where to buy a beauty gift and where to buy beauty cheaply.

If you are named for price questions but not for gift questions, you are seen as a price store, and December's gift demand goes elsewhere.
If you are named for neither, a shopper who starts with an assistant is unlikely to see your price.

Planning the season together

Put these signals on one page per key category and go through them in one session with pricing, brand, e-commerce and the teams that follow ratings, before the promotion calendar is fixed. For each key product the choice then comes down to three options: hold the price, follow the nearest competitor or lead with an offer.

Ask the main suppliers early which products they plan to discount in their own web shops, and which gift sets they can make for the store. Where a brand discounts in its own shop, match it on the products shoppers compare most, and compete on range and service on the rest.

After the season, compare sales with the tracker's November and December waves to see which choices held.

For next season: put a number on it

A price test is hard to fit in before this season, but it is worth planning for next year. A direct price test shows which prices shoppers accept for a product from your store. Showing the same offer with and without the store's name to two comparable groups measures what the name is worth when a shopper sees only the name and the price. In one of our checkout studies for a payment option, the brand doubled preference in one market, while the unbranded version won in another.

Choice-based conjoint shows where demand goes when a price changes, store by store, and is the most reliable method for pricing decisions.

Holiday pricing for retailers when every store sells the same product