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Reference Price Erosion Projector

An interactive multi-period reference-price erosion projector that takes any FMCG brand portfolio's promotional calendar (depth, frequency, duration), projects the consumer reference price index out to 12, 18, or 24 months under two scenarios in parallel, and translates the gap between them into a dollar value of baseline revenue protected before the next promo plan review.

Updated 6 May 2026Extracted from the Trade Promotion Optimization module, lesson 3: Lesson 3: Promo Baseline
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Scenario walkthrough

Tap any section to explore in detail

5.1Scenario setup

The starting SKU, market, and assumptions the model makes.

You run trade marketing or RGM on a biscuits brand portfolio at a top-3 retailer. Annual baseline is 100,000 units a week at an average shelf price of $3 a unit, so the brand sits on roughly $15.6M in annual revenue at full reference price. The current calendar runs 12 promotional events a year at 25% depth and 2 weeks per event, which puts you at 46% weeks-on-deal. Your category director wants to know whether the brand is in slow erosion, and what cutting back to 8 events a year would actually buy you over the next 18 months.

Your objective

Project the reference price index out to 18 months under the current calendar, overlay a reduced-frequency scenario, and read the dollar-equivalent baseline volume the recovery would protect. The chart is a teaching device, not a calibrated forecast; the decisions it lets you walk into a board review with are real.

Key assumptions

  • Brand baseline: 100,000 units a week at $3 average shelf price. Annual revenue at full reference price is $15.6M; the dollar tile reads in revenue terms, not margin

  • The 30% weeks-on-deal fatigue ceiling is the inflection point where reference-price erosion accelerates noticeably. It is documented in the Promo Calendar lesson (TPO Lesson 8), where it shows up as the spacing-sub-score floor; the same threshold drives the decay engine here

  • Decay engine, illustrative only: monthly erosion rate scales with weeks-on-deal above the 30% threshold. Default sensitivity 0.005 per excess percentage point (a Medium-decay category) plus a small 1.2% per year base drift. Real-world erosion involves competitor activity, category dynamics, and shopper-segment effects that this tool deliberately abstracts away

  • Default current scenario: 12 events a year, 25% average depth, 2 weeks per event. Total weeks-on-deal = 24 / 52 = 46%, well above the 30% ceiling

  • Default reduced scenario: 8 events a year, same 25% depth and 2-week duration. Total weeks-on-deal = 16 / 52 = 31%, just above the ceiling. The visible question is whether 31% is enough recovery; the answer is partly yes

  • Projection horizon: 18 months by default. Switch to 12 or 24 months from the toggle to see how the gap widens with time

5.2Controls & toggles

Every input the calculator exposes, its range, and what it changes.

ControlRangeDefaultWhat it changes
Current scenario sliders (depth, frequency, duration)Depth 10 to 40%, frequency 4 to 24 events, duration 1 to 4 weeks25% depth, 12 events, 2 weeksSets the calendar shape for the Current scenario. The weeks-on-deal value updates immediately and the Current line on the chart redraws. The default 12 by 2 = 24 promo weeks puts the brand at 46% weeks-on-deal, which is well past the 30% ceiling.
Reduced scenario sliders (depth, frequency, duration)Depth 10 to 40%, frequency 4 to 24 events, duration 1 to 4 weeks25% depth, 8 events, 2 weeksSets the comparison scenario. The Reduced line updates on the chart. The default 8 by 2 = 16 promo weeks lands the scenario at 31% weeks-on-deal, just above the ceiling. The two curves together show what the frequency cut buys you over the projection horizon.
Category sensitivity (Low / Medium / High)Low 0.003 / Medium 0.005 / High 0.008 per excess ppMedium (0.005)Picks the decay sensitivity that matches your category. Commodity-heavy categories (biscuits, cereals, packaged snacks) sit in Medium. Price-led categories with frequent deal-led shopping (carbonated soft drinks, value pack frozen) sit in High. Premium categories with built-in price-protection mechanics (super-premium ice cream, branded coffee, prestige beauty) sit in Low.
Projection horizon12, 18, or 24 months18 monthsLengthens or shortens the chart's time window. At 12 months the gap between the two scenarios is small; at 24 months it widens significantly because erosion compounds. The pedagogical case for cutting frequency is sharpest at 18 to 24 months, which is also the typical horizon of an annual JBP review cycle.
Reset to defaultsSingle button12 events / 8 events / Medium / 18 monthsRestores the seed scenarios. Useful between experiments. Custom slider edits are not preserved across reload; reset just brings back the defaults during the same session.
5.3Step-by-step exploration

7-step guided exploration of the scenario.

  1. Read the starting position

    Open the tool and let it run on defaults. Note that the Current scenario reads 46% weeks-on-deal and the Reduced scenario reads 31%. Look at the two lines on the chart at month 18: the Current curve has dropped to about 87 (so 13 percentage points of reference-price erosion), and the Reduced curve sits around 97 (about 2 to 3 points of erosion). Read the KPI tiles for the dollar equivalent of each.

    Expected outcome: The Current scenario's annualized revenue at risk lands somewhere around $2.0M, the Reduced scenario around $0.4M, and the difference (roughly $1.6M of run-rate revenue protected) is the headline reason a frequency cut typically pays off in the second year of a calendar restructure.
  2. Lengthen the horizon and watch the gap widen

    Switch the projection horizon from 18 months to 24 months. Look at the same chart now. The Current curve continues down toward 84 or below, while the Reduced curve flattens out near 96. The dollar gap between the two scenarios grows.

    Expected outcome: The annualized run-rate recovery rises to roughly $2.0M to $2.5M at month 24, depending on the sensitivity setting. This is why annual-only thinking under-states the value of restraint: the damage compounds, and so does the protection. The tool surfaces the run-rate at the horizon month, which is the relevant figure for the next contract anniversary, not a lifetime cumulative.
  3. Switch sensitivity to High and read the same chart

    Reset to defaults. Change category sensitivity from Medium to High (0.008 per excess pp). The Current curve drops faster: 18-month CRP lands around 80 to 82 (so 18 to 20 points of erosion). The Reduced curve also drops faster but stays in the low 90s.

    Expected outcome: High-sensitivity categories (carbonated soft drinks, value-pack frozen, deal-led pack formats) live closer to the cliff. The same calendar design that produces a 13-point erosion in a Medium-decay category produces a 19-point erosion in a High-decay category. The category itself constrains what calendar shapes are commercially survivable.
  4. Cut depth instead of frequency on the Current scenario

    Reset to defaults. Drop the Current scenario depth from 25% to 18% (a 28% relative reduction in promo depth) but keep the 12 events at 2 weeks each. Read the curve. The weeks-on-deal value does not change because depth does not enter the weeks-on-deal calculation; the Current curve on the chart does not move.

    Expected outcome: Cutting depth by 28% saves trade-spend dollars per event but does not arrest reference-price erosion at all, because the number of re-anchoring exposures stays the same. The shopper sees the lower price 24 weeks a year regardless of whether the discount is 18% or 25%. This is the most common mistake in promo-frequency restructures, and the chart makes it visible in two seconds.
  5. Now cut frequency by the same proportion

    Reset depth to 25%. Drop the Current scenario frequency from 12 events to 9 events (a 25% relative reduction). Watch the Current curve flatten somewhat, landing around CRP 91 at month 18 instead of CRP 87. The weeks-on-deal drops from 46% to 35%, still above the 30% ceiling but materially closer.

    Expected outcome: Cutting frequency by 25% recovers about 4 percentage points of reference price over 18 months. Cutting depth by 25% (Step 4) recovers zero. Frequency cuts protect the baseline; depth cuts protect the per-event margin. They serve different purposes and the chart makes that clear.
  6. Test what happens when both scenarios are above the ceiling

    Reset to defaults. Push the Reduced scenario from 8 events to 11 events. Reduced weeks-on-deal climbs from 31% to 42%, well above the ceiling. The Reduced curve drops more steeply and lands closer to the Current curve at month 18.

    Expected outcome: Once both scenarios are above the ceiling, the gap shrinks because both calendars are accumulating exposure damage; the marginal recovery from going from 11 events to 8 events is large, the marginal recovery from going from 12 events to 11 events is small. The 30% ceiling is the kink point; staying below it changes the pedigree of the calendar.
  7. Walk the chart into the JBP review

    Reset to defaults. Snapshot the chart. Note the 46% versus 31% weeks-on-deal and the $1.6M annualized recovery. Record the assumptions panel: 30% ceiling, Medium decay sensitivity, 18-month horizon, $15.6M annual baseline revenue. Bring all of it to the next commercial review.

    Expected outcome: You walk in with a defensible case for cutting from 12 to 8 events. The trade-team pushback is usually that the lost depth weeks will be picked up by a competitor; the answer is the chart, plus the lesson's reminder that the trade-spend savings can be redirected into bonus-pack mechanics, which preserve the reference price by design.
5.4Reading the output

Every KPI, the formula behind it, and how to interpret a positive or negative value.

KPIFormulaHow to read it
Weeks on deal % (per scenario)frequency events × duration weeks / 52 weeks × 100**Above 30% the curve breaks.** Below 20% the brand is essentially in price-protection mode; between 20 and 30% the erosion is shallow but cumulative; past 30% the re-anchoring accelerates and the chart's slope steepens noticeably. The single most actionable number on the page.
CRP Index at horizon (per scenario)100 × (1 - monthlyDecayRate)^horizonMonths**Read the gap, not just the level.** The Current scenario at 87 and the Reduced scenario at 97 read as 'ten points of recovery', and that ten-point gap is what the dollar tile then translates into baseline volume. Compounding makes this a dollar-amount mistake, not a rounding mistake.
Cumulative CRP erosion (basis points)(100 - CRP at horizon) × 100**The lesson cites 15 to 25 percentage points (1,500 to 2,500 bp) of baseline erosion as typical for heavy-TPR FMCG categories over 18 to 24 months.** The default Current scenario lands inside that band; the Reduced scenario falls well below it. The bp framing is what your CFO will recognise from the brand health deck.
Annualized revenue at risk ($M)(100 - CRP at horizon) / 100 × baselineWeeklyUnits × 52 × listPrice**Translates the index erosion into a single dollar number.** A 13pp CRP drop on a 100k-units-a-week brand at $3 average list price runs to roughly $2M of annualized revenue at risk. Stated in run-rate, not lifetime, because the relevant question for trade marketing is what the run-rate looks like at the next contract anniversary.
Recovery dollars (Current minus Reduced, $M)Annualized revenue at risk (Current) - Annualized revenue at risk (Reduced)**The headline number for the JBP conversation.** The default scenarios produce roughly $1.6M of annualized recovery; the cumulative number over the 18-month horizon is closer to $2M. This is the dollar value you can quote in the trade-spend reallocation case, and it scales linearly with the brand's baseline revenue.

The chart is the teaching device; the dollar tile is the conversation-starter; the assumptions panel is the audit trail. The decay engine is illustrative, not calibrated, and that is the right way to use it: plug in your category's typical sensitivity, your brand's actual baseline volume, and your current calendar shape, and read what direction the math points. Real reference-price erosion will be modulated by competitor activity, retailer pressure, and shopper-segment effects this tool does not model. The order of magnitude is what matters at this step; the precise number lands in the marketing-mix model later.

5.55 common mistakes to avoid

Diagnostic patterns that catch most misuse of this calculator in practice.

  1. Mistake 1Scoring promo events on event-level ROI without measuring the post-event CRP drag
    Symptom: Each event lands a clean +25% incremental ROI on the post-promo report. The annual brand-health deck shows baseline volume slipping 4% a year. The two stories never meet on the same page.
    Fix: **Track event-level ROI and the CRP drag together.** A Promo ROI that ignores the 4 to 6-week reference-price drag following each event over-reports the win by the size of the drag. Tool #3 (Promo ROI Calculator) and this tool together are the two halves of a defensible promo-evaluation deck.
  2. Mistake 2Cutting depth instead of frequency when trying to arrest erosion
    Symptom: Trade spend per event drops year over year as depth cuts compound. Weeks-on-deal stays flat at 45% because the events themselves are still scheduled. CRP keeps drifting down. The post-mortem cites 'mechanic execution' as the cause.
    Fix: **Frequency drives the number of re-anchoring exposures; depth drives the per-event margin loss.** They protect different things. Cut frequency to protect the baseline; cut depth (or shift to bonus-pack mechanics) to protect per-event profitability. The chart shows this in two slider moves.
  3. Mistake 3Expecting recovery within one quarter
    Symptom: Trade marketing announces a calendar restructure in Q1 and is asked for a Q2 brand-health update showing the recovery. The recovery has not happened. The reset is reversed in Q3 'because it did not work'.
    Fix: **Recovery takes 12 to 18 months per year of damage.** The shopper's reference price re-anchors slowly in both directions, and a brand that promoted at 46% weeks-on-deal for two years before the restructure cannot be expected to recover in a single quarter. Set the review cadence at 12 months at minimum, ideally 18.
  4. Mistake 4Treating the 30% ceiling as a hard cliff
    Symptom: You push the calendar to exactly 30.0% weeks-on-deal and record it as safe. Two years later the baseline is down 6 percentage points and no one can explain why.
    Fix: **The 30% ceiling is where erosion accelerates, not where it begins.** Below 20% the brand is essentially in price-protection mode; between 20 and 30% the erosion is shallow but cumulative; past 30% it accelerates noticeably. Pushing to 29.9% does not buy what you think it buys; 30% means 'less damage', not 'no damage'.
  5. Mistake 5Reading the CRP curve without the dollar tile
    Symptom: The chart looks worrying but the conversation stalls. The CFO asks 'so what is this in dollars' and the team does not have an answer. The case for the calendar restructure dies in the meeting.
    Fix: **The dollar tile is the case.** A 13pp CRP erosion on a 100k-units-a-week brand at $3 average list price translates to roughly $2M of annualized revenue at risk. State the number; explain the assumptions panel below it; show the chart. The chart by itself does not close the room.
Related concepts

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Go further inside Trade Promotion Optimization

This calculator is the sandbox slice of Lesson 3: Lesson 3: Promo Baseline. Each of the other 7 Trade Promotion Optimization lessons teaches a complementary concept that sharpens how you read the output above.

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