MySales Labs

The myth of a “baseline promo-effect library.”

I keep seeing forecasting vendors promote the idea that promo lifts can be estimated using some global, aggregated “library” of effects across retailers and countries.

Let’s be honest: this simply doesn’t work.

Promo effects are not universal. They are hyper-local and depend on dozens of dynamic factors:

• competitive pressure within a 1–3 km radius
• local demographics and income sensitivity
• store layout, display quality, POSM and end-caps
• weather overlap
• promo conflicts in the same week
• seasonality interaction
• brand power in this exact store
• inventory sufficiency and ex*****on quality
• current market shifts (inflation, private label growth, promo fatigue)

A “-20% discount = +55–75% lift” average might look good in a slide deck, but it’s meaningless in real retail operations. For one store, lift might be +12%. For another, +230%. For a third — negative because a competitor went deeper that week.

Relying on a universal promo library is not just inaccurate — it’s dangerous. It leads to bad forecasts, wrong replenishment, and misleading profitability projections.

# # # What we do differently at MySales

Instead of guessing promo effects from generic global averages, we use real local signals.

In MySales, a retailer can:

✔️ Scrape competitors’ prices directly from the web (fully automated)
✔️ Upload their own price-monitoring data
✔️ Use these real competitive signals as inputs into promotional forecasting
✔️ Adjust for local elasticity, competition pressure, and store-level specifics

This means the promo forecast isn’t “based on what works somewhere in Europe” —
it’s based on what actually happens around your stores, this week, in your market.
Promo modeling must be SKU–store–context specific. Anything else is just storytelling.

Let’s build forecasting on real competition data, not on global average

💭 “Nobody was fired for hiring IBM…” Remember this quote?

For decades, IBM was the safe bet. The ultimate shield for executives — because:
1️⃣ You couldn’t blame IBM for inefficiency.
2️⃣ You couldn’t question IBM’s advice.
3️⃣ Even if projects failed, the decision was unquestionable.

But let’s be honest: safe bets no longer win in retail.
Margins are shrinking. Consumer behavior is shifting daily. Supply chains are more fragile than ever.

Retail leaders today need more than “safe.” They need smart.
AI-driven automation. Forecasts that explain themselves. Decisions that optimize the P&L in real time.

That’s why companies like Dr**as (A.S. Watson Group) chose MySales — to replace “safe” with:
✅ 97%+ on-shelf availability
✅ Up to 40% profitability growth
✅ Up to 90% less manual effort 

👉 The future of retail doesn’t belong to safe bets. It belongs to smart bets. That’s why it belongs to MySales.