Trade promotion optimization (TPO) is the practice of measuring each past trade promotion and using the result to plan the next one. It settles which offer to run, how deep, when, and in which outlets. For a Philippine brand, it answers the question from every quarterly review: the distributors took the stock and the discount went out, so did the promo actually pay?
Every TPO method asks what the stores would have bought with no promo, how much more they bought with it, and what each extra case cost. The answers send the next peso of trade spend to schemes that buy new volume cheaply.
The numbers are the easy part. The hard part is knowing what happened in the field: which stores heard about the scheme, which supermarkets put up the display, and what the distributor invoiced to each store. A model fed only shipments and guesses will rank your promos with confidence and still get them wrong.
How trade promotion optimization differs from TPM
Trade promotion management (TPM) is the admin side of promos: budget, calendar, setup and claims. Trade promotion optimization is the judgment side: which promos deserve the budget next time.
| Trade promotion management (TPM) | Trade promotion optimization (TPO) | |
|---|---|---|
| The question | Was the scheme set up, run and paid the right way? | Which scheme do we run next, in which outlets, at what depth? |
| What you get back | Schemes live with distributors, accruals, claims paid | A baseline, an uplift forecast, the return on each promo, a better next plan |
Sort out TPM before you pay for optimization. TPO learns from the records TPM leaves behind, and those do not exist while schemes live in Excel and Viber threads. For scheme types and how to run one, see our trade promotion guide.
Sari-sari stores vs supermarkets: two different TPO problems
Modern trade. You negotiate each promo with a few supermarket, convenience and drugstore chains, some of which share till data, so TPO can work by account, SKU and week. The levers are depth, timing against the chain’s promotional calendar, and display fees. Shoppers see the deal only through your promodisers and shelf checks.
Traditional trade. Here volume reaches sari-sari stores through distributors, wholesalers and van sales, with no scanner data. One store is too small to measure, so group stores by type, size and area, such as a set of barangays in Quezon City or a provincial town in Mindanao, and compare each group with look-alike stores that did not get the scheme. The levers are quantity slabs, free goods and period purchase schemes. Watch the price point: shoppers buy sachets by the peso, so a scheme that changes the shelf price can matter more than the percentage off.
Read the two channels separately: a promo that pays in a supermarket chain can lose money in sari-sari stores, and the reverse happens too.
The five records to collect before any analysis
- Normal-week sales by SKU and outlet. A full year of no-promo weeks, covering the Ber months, fiesta season and the rains.
- What the distributor sold to each store. Shipments to the distributor show who stocked up. Secondary sales to each store show what moved toward the shopper.
- The promo record. Mechanic, depth, dates, SKUs, target outlets, funder.
- Proof it ran. Offered at the order, display up, claim filed.
- The full cost. Discounts, free goods, display fees and paid claims, each tied to its promo.
For sari-sari stores, the distributor’s invoice to each store is the nearest thing to sell-out you will get. That is why a distributor management system that records secondary sales is a sensible first data project in a TPO program.
Check execution before you judge the offer
A TPO model assumes a promo planned for a list of outlets ran there. In traditional trade it often did not. The rep never mentioned it. The display stayed in the bodega. The model cannot tell a scheme nobody heard about from one nobody wanted, so it advises you to drop a promo that was never really tried.
Put every weak result beside its execution rate.
- A poor return with high execution means the offer itself is wrong.
- A poor return with low execution points to the field: fix the execution and run the promo again.
Three records settle it:
- The scheme on the order screen. The rep’s sales force automation app shows the store’s live schemes and applies them during the order, before the owner picks a quantity.
- A geo-tagged photo of the display. A photo from a retail audit proves the display went up. BeatRoute’s VM Audit AI Agent scores those photos at 80% lower cost than manual audits, and is now in field runs with customers.
- Claims checked against secondary sales. Each claim is matched to the distributor’s invoices before payment.
Coverage counts too: a scheme cannot work in a store no rep visits. A leading paints brand in the Philippines reached 30% higher sales productivity on BeatRoute (read the case study). Reps who sell more per day reach more of a scheme’s target stores.
Measuring promotion performance: baseline, post-promotion review, then forecasts
Trade promotion optimization works in three steps. Do them in order, and get the first two right on your own data before you pay for any predictive model.
- Baseline and uplift.
The baseline is what the same outlets would have bought with no promo, given the season and the trend. Uplift, or sales lift, is sales minus the baseline. A typhoon that keeps the vans off the road, or a payday week, can move sales more than the scheme. Set the baseline too low and every promo looks like a winner. - Post-promotion review.
When the promo closes, sort its volume by source: new buyers, switching from your other SKUs (cannibalization), and stock pulled forward (stock-loading). Distributors forward-buy and owners stock up, so check the weeks after too. - Forecasts and scenarios.
Once baselines hold, a predictive model can compare mechanics, depths and dates before money goes out. Past a certain depth, a bigger discount mostly pays shoppers who would have bought anyway. The model learns from your past promotions, so it repeats what your records got wrong and says little about a mechanic you have never run.
Judge each promo on all four measures, since any one alone can flatter a loser.
| Measure | What it shows | The math |
|---|---|---|
| Incremental volume | The extra the promo really brought in | Promo-period sales less the baseline, less the dip in the weeks after |
| Promotion ROI | Whether the trade spend earned its money back | (Gross profit on the incremental volume minus total promo cost) divided by total promo cost. Above zero, the promo made money |
| Cost per incremental case | What each extra case cost you | Total promo cost divided by incremental cases |
| Execution rate | Whether the trade ran it at all | Outlets where the scheme was offered or the display verified, divided by outlets targeted |
Compare mechanics on the same SKU with cost per incremental case. Compare across SKUs with promotion ROI: a cheap extra case of a thin-margin product can still lose money.
Test TPO on one promo cycle, then pick your tools
- Choose a category you promote often in one province or distributor territory, and two or three mechanics to compare: a price-off, free goods, a display payment.
- Split look-alike stores into test groups and one control group with no scheme, and write down the bar a winner must clear.
- Run the full cycle and record the execution rate for each group.
- Compare the result with the control group, including the weeks after the promo ends.
Ask any TPO software vendor two things: can your team see the baseline, and does the tool work from secondary sales when sari-sari stores give you no sell-out data?
Where BeatRoute fits. BeatRoute covers the execution and secondary-sales side of TPO; it is not a forecasting suite. It puts live schemes on the rep’s order screen and records secondary sales and display checks. A promotion planning tool linked through integrations then learns from what really ran.
BeatRoute suits brands that run trade schemes across many distributors and outlets; if you only track a few schemes for one distributor, a spreadsheet may do.
If execution data is the weak link in your trade promotion optimization, book a demo to see schemes applied at the order.
Frequently Asked Questions
What is the difference between trade promotion optimization and trade promotion effectiveness?
Trade promotion effectiveness (TPE) looks back and measures how well each past promo worked. Trade promotion optimization uses those results, with forecasts, to choose the next promo, so the TPE read comes first.
How do you align trade promotions with the overall business strategy?
Build the sales plan on the promo calendar: set each distributor’s monthly target with the schemes running that month, so reps sell the scheme instead of around it. Then agree who owns each number. One split that works: trade marketing owns the baseline, finance the cost, and sales the execution rate.
What if our distributors will not share their invoice data?
Start the first post-promotion review with the distributors whose billing you can already see. Add the others as they bill in a distributor management system your team can also read, so secondary sales stop arriving as a late Excel file on Viber.
