TL;DR: Most forecasting tools simply extend your past sales with a bit of trend and seasonality. That works only if you plan to keep doing exactly what you did before. If you are about to ramp up promotions—BFCM pushes, coupons, bundles, relaunch campaigns—history alone is the wrong guide. You need a forecast that combines base demand with planned promo lift so your purchasing, inventory, and cash planning all line up with your strategy.
A typical Amazon forecast looks like this:
Take the last X months of sales
Remove obvious outliers
Apply a trend and seasonality model
Use that as the “expected future”
This can be fine when:
The product is mature
Your promo intensity is stable
You are not changing price, ad strategy, or channel mix
But that is not the reality for many brands. You might be:
Launching a new SKU with an aggressive coupon and PPC campaign
Trying to push a struggling SKU up the rankings with a concentrated promotion
Planning a big BFCM or Prime Day push that goes far beyond last year’s effort
Testing bundles or new price points
In these situations, “more of the same” is not the plan. If your strategy changes, the past cannot be your only predictor.
A history-only forecast will:
Underestimate demand during major promos (risking stockouts)
Overestimate demand after promos if it treats a temporary spike as the new normal
Miss the cash and inventory impact of a deliberate, short-term sales surge
You end up either overbuying, underbuying, or stressing cash because the forecast never understood the plan.
To plan properly, you need to separate two things:
Base demand
What you sell with “normal” pricing and support
Driven by rank, reviews, organic search, and ongoing ads
Promo lift
Additional demand created by specific campaigns
Coupons, Lightning Deals, heavy PPC bursts, influencer pushes, BFCM offers, bundles, price cuts, etc.
Think of base demand as the floor and promo lift as the extra traffic and conversion you layer on top.
A good promo-aware forecast looks like:
Forecast = Base demand (from history)
Promo lift (from planned activities)
That is very different from just stretching history forward.
Start by getting your base demand right:
Use historical daily or weekly sales by SKU
Exclude obvious stockout periods and major one-off promos
Smooth out noise to get a realistic “run rate”
For example, if a SKU averages 30 units/day across stable weeks with no special discounts, your base demand is roughly 30/day.
This base becomes the starting point for all future scenarios.
If you have run promotions before, treat them as experiments:
Tag historical data with promo types and dates
Coupons
Lightning Deals
BFCM/Prime events
Deep discount price tests
Aggressive PPC bursts
Then measure:
Uplift factor:
“During a 20 percent coupon + PPC push, we sold 3x our base run rate.”
“During a Lightning Deal, we sold 10x our base on that day, plus 2x for two days after.”
Duration:
How many days was the uplift active?
Did it pull sales forward from the future, or did it create lasting rank improvement?
This becomes your library of “promo profiles” you can reuse.
Now look forward. Instead of asking “what will sales be?” in isolation, ask:
What campaigns are we planning by SKU and week?
What is each campaign’s objective: rank push, inventory clearance, launch, or margin optimization?
How much promo lift do we expect from each?
Create a simple calendar:
Week 45–46: BFCM campaign on SKUs A, B, C
Week 10–12: relaunch campaign for SKU D
Week 22: Lightning Deal on SKU E
Ongoing: increased PPC on top 5 SKUs for 60 days
Attach an estimated uplift factor to each block (based on Step 2 or educated assumptions for new tactics).
For each SKU and week:
Start with base demand from history.
Add the expected promo lift during planned campaigns.
Accumulate the total units required over your planning horizon.
Then overlay:
Supplier lead times
Production capacity
Ocean/air transit times
FBA/AWD receiving lags
Desired safety stock or days of cover
Work backward from the date you need the inventory on shelf to the date you must place POs and book freight.
This is where the difference between “history-only” and “promo-aware” really matters. For a BFCM push, you may need to commit cash and production 3–6 months ahead. If your forecast never saw the promotion, your purchasing plan will always be late.
A serious forecasting process doesn’t stop at units sold.
Each promo changes:
Cash timing
Larger POs and inbound shipments
Higher ad spend or promotional fees
Margin profile
Temporary margin compression during the campaign
Potentially better long-term margin if rank improves
By connecting your promo-aware demand forecast to your P&L and cash flow, you can answer:
Can we afford this campaign at our current cash position?
How many units do we need to sell at promo pricing to justify the investment?
What happens if the uplift is only half of what we expect?
NeonPanel’s philosophy is that a forecast should be a reflection of your plan, not just a projection of your past.
In practical terms, that means:
Base-run-rate forecasting per SKU
Clean historical sales series that correct for stockouts and anomalies.
Promo event layering
A way to represent planned events (discounts, Lightning Deals, bundle pushes, rank campaigns) and apply uplift factors on top of base demand.
Inventory and purchasing alignment
Translating promo-aware demand into POs, shipments, and warehouse targets so operations can prepare instead of react.
Finance visibility
The same forecast feeds into cash and P&L projections so finance understands when promotions require extra working capital and what the expected payoff is.
When ops, marketing, and finance are all working from the same promo-aware forecast, you stop having conversations like:
“We didn’t order enough for that campaign,” or
“Why is cash tight? We didn’t see this coming.”
Instead, the promotion plan, inventory plan, and financial plan are three views of the same model.
History is still valuable. It gives you a realistic base and shows how past promotions behaved.
But strong teams treat history as one input—not the whole model.
The real question is:
“Given the promotions we plan to run, what will demand look like, and how should we prepare inventory and cash for that scenario?”
When you start forecasting that way, you are planning the lift, not just the trend.