Compset shopping — the competitor rate-watch routine

In lesson 14 (Compset) we saw who our competitors are — the three-tier compset architecture (primary, secondary, aspirational). In lesson 12 (A day in an RM’s life) Daniel opened the compset watch at 8:30, and that led to the Coldplay-concert event-discovery moment. Now we take the daily compset-shopping routine deeper — what we look at, how we work, what traps we fall into.

Compset shopping (rate shopping) is the industry term for the daily compset rate watch. A simple concept — we look at what competitors are asking. A complex practice — lots of daily data, for many days ahead, with multi-layered context.

The goal of this lesson is for you to understand: the difference between raw rate shopping and intelligent compset analysis, how you run the daily shopping routine, and when it’s OK to react to a competitor move.

What “compset shopping” means

Rate shopping = the daily collection of the compset hotels’ public rates. The public rate is usually the Booking.com BAR for a given room category, for a given check-in date.

Hotel Peaqplus City’s primary compset (4 hotels) for Saturday nights, over the next 28 days:

The table shows it immediately:

• 11.18 (1 week out): Hotel Peaqplus City is 5 EUR below the compset average. A small underpricing.
• 11.25 (Coldplay Saturday): Hotel Peaqplus City is 25 EUR below the compset average. Dramatic underpricing — an event-discovery signal here.
• 12.02 and 12.09: a small gap, a normal position.

This kind of table is the result of the daily compset shopping.

Manual OTA screen vs. shop-tool

The compset watch can be done two ways:

Manual OTA screen

The RM (or a junior) manually opens Booking.com, enters the compset hotels for a Saturday night, and records the rates by hand.

Pros:

• No cost (only time).
• Visual context — you can see which rate plan is active, what photos there are, whether there are featured deals.

Cons:

• Time-intensive — 4-5 hotels × 30 days × by hand = 30-60 minutes of daily work.
• Error-prone — one typo or lapse = wrong data.
• Only 1 channel — you see Booking. On other OTAs (Expedia, Agoda) the rate may differ.
• Doesn’t scale at the segment level — it’s hard to compare non-refundable, advance purchase, mobile-only.

Shop-tool

An automatic rate-shopper software (e.g. RateGain, Lighthouse) automatically scrapes the compset hotels’ rates 2-4 times a day, and returns them in a structured report.

Pros:

• Time saving — a 10-15 minute daily review instead of 30-60 minutes of manual work.
• Multiple channels — Booking + Expedia + Agoda + the hotel’s own web = a fuller picture.
• Rate-plan-level analysis — BAR vs. non-refundable vs. mobile.
• Fault-tolerant — automatic, consistent.

Cons:

• Cost — 80-300 EUR/month/hotel (depending on the tool type).
• Shows no context — only the rate. A higher rate might come with an MLOS restriction (per lesson 24), which the tool doesn’t show.

In a modern hotel the shop-tool is the starting point, and the RM fills in the context by hand.

Rate shopping vs. intelligent compset analysis

Here is the lesson’s central difference. A few examples:

Rate shopping (price only)

“The compset average rate for Saturday night is 135 EUR. We’re at 110. Let’s raise to 130.”

This is the simplest rate shopping. It tells you what you see, and reacts.

Problem: it doesn’t consider the context. It might be that:

• The compset hotels are all at 100% (Coldplay night) — a smart move.
• The compset hotels are at 60% with an MLOS = 3 restriction — here the 135 EUR is a warning figure, not a real rate. If we raise to 130, we lose the bookings.

Intelligent compset analysis

“The compset average rate for Saturday night is 135 EUR, we’re at 110. I check the context: the compset hotels are all at 90%+ on-the-books, with no restrictions set. The 135 EUR is a real higher price position. Our 110 EUR rate is genuine underpricing — worth raising to 125 EUR.”

The intelligent analysis looks at:

1. The compset’s on-the-books level — following the rate move is only worthwhile if competitors are actually booking at that rate.
2. The restrictions — MLOS, CTA, CTD settings that push up the public rate.
3. Availability — a 250 EUR “rate” often means the hotel is nearly full and is showing only a last room.
4. The rate-plan structure — beyond the public BAR, what they ask on the non-refundable / advance purchase rate.

Intelligent compset analysis also thinks in our own segment mix:

• If we are a corporate-dominant hotel and the compset average hits 135 EUR on transient leisure peaks, that isn’t necessarily relevant to us — the corporate segment doesn’t belong to that demand pool.

The undercut and the “race to the bottom”

The classic compset trap: the undercut and the race to the bottom.

The undercut

The undercut = when a competitor drops its rate and we feel obliged to follow. A hotel was at 115 EUR, the competitor cuts to 108 EUR. Do we go to 107? And then the competitor to 105?

This is the race to the bottom — a price spiral that drastically lowers the whole market’s ADR.

When is it OK to follow an undercut?

Only in 3 situations:

1. Strategic positioning — our hotel targets the discount segment, and the competitive price position matters more than the higher ADR.
2. Structural pace shortfall — if pace is −10 pp behind and the pickup isn’t arriving, the competitor reacted first (and is right).
3. A cancelled event-driven occasion — an event we had priced for was cancelled. The competitor reacted first.

When do we NOT follow the undercut?

In most cases:

1. Pace is going well — there’s no reason to cut the rate.
2. The compset member overshoots — a hotel decides emotionally and underprices itself. We don’t follow.
3. The competitor targets a different segment — e.g. a 3-star compset member is less relevant to our 4-star segment.
4. Brand-value damage — every rate cut also causes a long-term effect (per lesson 7).

The daily compset-shopping routine

A mature RM’s daily compset-shopping routine:

1. Morning 8:30 — review the automatic report (5-10 min)

The shop-tool refreshed overnight. I look at the top 3 anomalies:

• Where is the compset average +15 EUR higher than our rate? An opportunity to raise.
• Where is it −10 EUR lower? A warning — is it worth following?
• Where are compset members dramatically out of line? It might be an event-discovery signal.

2. 8:40 — examine the top 3 warnings deeply (10-15 min)

For the 3 anomaly days:

• I check the compset on-the-books (if we have STR access).
• I check the restrictions (MLOS, CTA, CTD).
• I check the event calendar (is there a conference, concert, holiday?)
• I also apply the context learned in lesson 4 (TRevPAR) — which segment do I reach on that day?

3. 8:55 — Action (5 min)

For the 3 anomaly days:

• Rate revision: I raise or cut.
• Restrictions setting: MLOS or CTA.
• No action: everything stays as is.

This is the daily 20-25 minute routine. Compset shopping is not information-gathering but decision-oriented.

The difficulties of compset shopping

A few difficulties a mature RM often faces:

1. Non-public rate differences

The compset hotels also work on non-public rates — corporate contracts, member rates, mobile-only deals. We don’t see these on Booking. The actual market position is only partly visible.

2. Manipulated compset positions

Some hotels strategically manipulate their rates — e.g. a very high BAR + a very aggressive non-refundable discount. The public rate misleads.

3. Compset members’ different segment targeting

As we saw in lesson 14: two 4-star hotels can serve completely different segments. A “compset average” often misleads if the two hotels are in different markets.

4. STR vs. real-time gap

The STR report shows with a 2-3 day lag. Real-time compset shopping is immediate. Aligning the two is the mature RM’s practical task.

Event-discovery — the main value of compset shopping

In lesson 12 we saw: Daniel found the Coldplay concert through compset shopping. This is the main value of the compset-shopping routine.

The classic event-discovery process:

1. 3-4 compset hotels are +25 EUR higher for a specific Saturday.
2. I can’t find the reason in my event calendar.
3. A quick search turns up an event (concert, conference, sports match).
4. Rate increase — Hotel Peaqplus City raises the BAR too.

This is 2-3 second detection + 1 minute of verification = immediate revenue uplift. In lesson 12 this was +1,200 EUR for a single Saturday.

A mature RM treats the event-discovery moments as the main goal of compset shopping — the rest is incremental rate revision.

Key takeaways

• Rate shopping = the daily collection of the compset hotels’ public rates. Intelligent compset analysis interprets it in context (on-the-books, restrictions, availability, segment mix).
• Manual OTA screen vs. shop-tool — the modern hotel uses the tool as a starting point and fills in the context by hand.
• The undercut trap — you should follow a competitor’s rate cut only in 3 situations (strategic, structural, event cancellation).
• The daily compset-shopping routine is 20-25 minutes — automatic report + a deeper look at the top 3 anomalies + action.
• The main value of compset shopping is event-discovery — spotting Coldplay-like missed events.