Sellforte MCP Use Case Library

Ask Sellforte MCP: Was our Shopping Week worth repeating?

Written by Juha Nuutinen | Nov 12, 2026, 10:11:07 AM

Welcome to the Sellforte MCP Use Case Library. Each post takes one question that marketing teams really ask their AI assistant through Sellforte MCP, which is now in general availability and accessible to all marketers worldwide. It strips out anything customer-specific and walks through what the assistant does with it, step by step. We run every question on our demo account so the numbers you see are illustrative, not anyone's real results. The idea is simple: steal the prompts, try them on your own model, and see what you get back. We hope you find this series inspiring!

-Juha, CEO at Sellforte

Looking back at a promotion before planning the next one

A promotion has just ended and the next one of the same kind is already on the calendar. If you plan promotions, this is the moment to learn from it, while the details are fresh: what did it actually add, how did it sit next to media, and was it better or worse than last time? Without a model, you usually end up comparing gross sales during the promo with the week before, which mixes in everything else that happened.

What you ask

Our Shopping Week ran from 2026-10-05 to 2026-10-11. How much incremental sales did it drive compared with media, and how does it compare with last year's Shopping Week from 2025-10-06 to 2025-10-12?

Break this year's Shopping Week down by discount level. Which discounts paid back?

What Sellforte MCP does

We ran both prompts on our demo account. All figures below are illustrative demo data in USD.

Finds the promotion by type and dates

Sellforte's promotions data is organized by promotion type, discount level, product category, customer segment, sales channel and country, by day. There's no single "promotion ID", so the assistant looked the promotion up by its type and dates. A quick daily check confirmed Shopping Week had activity on exactly those seven days in both years.

Puts it next to media and base

Next it split total sales for 2026-10-05 to 2026-10-11 into base, media, promotions and weather:

ComponentSales
Base1 555 203
Media1 117 419
All promotions846 650
of which Shopping Week170 660
Weather-56 443
Total3 462 828

 

Media brought in 32.3% of the week's sales and promotions 24.4%. But Shopping Week wasn't the only promotion running. Product promotions (472 766), vouchers (130 062) and a Sale Sunday (73 161) overlapped with it. So Shopping Week itself added 170 660, a fairly small slice of a busy week.

Compares it with last year

MetricShopping Week 2025Shopping Week 2026Change
Promo investment54 051108 087+99.97%
Incremental sales73 865170 660+131.04%
Incremental margin27 29063 170+131.48%
ROI1.371.58+15.54%
Margin ROI0.5050.584+15.76%

 

This year's Shopping Week was roughly twice as big and a bit more efficient. Every dollar of promo investment brought back 1.58 in incremental sales, up from 1.37. On margin, though, the picture is more sober: margin ROI was 0.584, so each dollar invested returned about 58 cents of incremental margin.

Splits it by discount level

The follow-up is where the planning advice comes from. Shallow discounts did the heavy lifting:

DiscountPromo investmentIncremental salesROIMargin ROI
10%5 16514 0702.721.27
15%44 089110 7412.511.09
20%10 50421 0422.000.801
60%26 99310 0870.374-0.0747

 

The 15% discount alone produced 110 741 of the 170 660. The 60% discount took a quarter of the investment, returned 10 087 in sales and slightly negative incremental margin. Every discount level from 50% upward came in below 1 on ROI.

Why it matters

A promotion can look like a hit on the sales chart and still be the wrong one to repeat. Here, the headline says "twice as big as last year", but the useful answer is narrower: keep the shallow discounts, and question the deep ones before the next Shopping Week goes into the calendar.

There's a second check worth adding. A sales event can pull sales forward from the days around it rather than create new ones. Comparing the event window with the days before it, and the days after, is the simplest way to see whether that happened.

One limit to know: because promotions are found by type and dates, two promotions of the same type running at the same time can't be told apart. Name the type, dates and any category or market up front.

Try these follow-ups

  • Show daily total sales for the two weeks before and after Shopping Week. Did sales dip afterwards?
  • Split Shopping Week by customer segment. Was it driven by members?
  • Compare Shopping Week's margin ROI with our vouchers and product promotions over the last 12 months.
  • Which product categories had the deepest discounts during Shopping Week?

Related

Try it yourself

Want to review your own promotions this way? Book a demo, or if you're a Sellforte customer, follow these steps to connect Sellforte MCP to your LLM client. More use cases are added to this library regularly.