Terno-AI Reveals how Promotions Really Drive Sales, Profit & Revenue in FMCG Domain.
Introduction
Every week, stores run discounts and special offers on many products, but finding out which deals really boost sales, profit, and revenue usually means hours of spreadsheet work. I wanted a simple, fast way to see how promotions affect each product and each store without writing any code. So I used Terno-AI, an AI-powered assistant. By asking in plain English, it did all the number-crunching, made clear charts, and even wrote up the results—in just minutes.
Curious how Terno-AI did all this analysis so fast? Check out my Conversation with Terno
Why is it important?
When you compare how things sell, how much money you make, and how much you bring in on days with and without promotions, you can:
- See which products and stores really benefit from discounts
- Focus on deals that actually increase your profit, not just your sales.
- Put your promotion budget where it will do the most good.
- Match each offer to the right stores and customers.
- Order just the right amount of stock for popular deals.
- Make choices based on real numbers instead of guessing.
Here’s what we are actually doing, step by step:
- First, I gathered FMCG Sales Data containing Sales volume, Selling price, Supplier cost, and promotion-flag data for every product in each store from Kaggle.
- Then, I attached the dataset to Terno-AI and asked to plot charts and give the detailed insights along with average sales, average profit ((Selling price - Supplier cost) x sales_volume), and average revenue (Selling price x Sales_volume) by product, by location, and by product × location on promotion and non-promotion days.
- This analysis focuses on five product categories—Beverages, Dairy, Household, Personal Care, and Snacks and three locations—Rural, Suburban, and Urban.
- At the end of the Blog, we conclude the results based on the insights gained.
Starting with the Terno-AI:
In this section, we will see how Terno-AI gives useful insights and visuals with the help of a few prompts.
Before that, have a clear view of the order in which we will find insights and visualizations.

Step 1.
So, let’s get started with Step 1 to plot the graph for average sales for each product category on promotion and non-promotion days.
Prompt: Can you give me the visualization for the average sales of each product, comparing promotion and non-promotion days?
Response from Terno:


Quick Summary of Insights:
- Promotions boost sales across all categories except for Personal Care(-121.9).
- Gives the highest rise in Household(+89.7), followed by Dairy(+80.7), Beverages(+43.3), and Snacks(+42.2).
Step 2.
Next, following the product-wise analysis, we will plot the graph for average sales for each location, comparing promotion and non-promotion days.
Prompt: Now, can you give me the same visualization for average sales for each location, comparing promoting and non-promoting days? Give the insights also.
Response from Terno:


Quick Summary of Insights:
- Promotions increase sales across all locations, with Rural stores gaining the most(+33.0 units).
- Suburban stores are seeing moderate improvement(+28.3 units).
- Urban outlets showed the smallest lift(+14.0 units), indicating lower responsiveness to promotions.
Step 3.
Next, following the location-wise analysis, we will plot the average sales for each product–location combination to gain deeper insights into how promotions impact both products and locations.
Prompt: So, now can you calculate the average sales for each product * location category and plot the graph for it as you have done for the above prompt? Also, give the insights along with.
Response from Terno:


Quick Summary of Insights:
- Promotions impact products differently across locations
- In rural areas, Snacks see the biggest uplift when promoted(+177.5 units), followed by Dairy(+107.8 units), Household(+82.0 units), and Beverages(+4.1 units), while sales for Personal Care decline(-225.1).
- In suburban stores, Dairy leads the uplift(+130.7 units), followed by Beverages(+88.1 units), Personal Care(+58.0 units), and Household(+12.9 units), but Snacks declines(-225.9).
- In urban outlets, Household shows the strongest gain(+200.3 units), followed by Snacks(+126.5 units) and Beverages(+13.2 units), whereas Dairy(-57.5 units) and Personal Care(-195.8 units) perform worse during promotions.
Step 4.
After examining sales patterns, we move to profit analysis at the product level to identify which categories benefit or lose from promotions.
Prompt: Now, can you plot the graph for the average profit for each product, comparing promoting and non-promoting days? Also, give the insights along with
Response from Terno:


Quick Summary of Insights:
- Household sees the biggest uplift(+$605.4) in average profit, followed by Beverages(+$432.8) and Snacks(+$295.2).
- In contrast, Personal Care(-$626.9) and especially Dairy(-$1325.5) suffer losses during promotions..
Step 5.
Now, let’s check the average profit for each location to see how promotions impact earnings in Rural, Suburban, and Urban markets.
Prompt: Now, calculate the same thing that you have done for the product category. Calculate the average daily profit for each location, comparing both days when they are promoted and when they are not. Also, give the insights along with.
Response from Terno:


Quick Summary of Insights:
- Promotions increase profits in Rural areas by $254.33.
- While in Suburban(-$86.58) and Urban locations(-$480.01) experience profit declines, with Urban stores being the most negatively impacted..
Step 6.
Now, let’s check the average profit for the combination of product x location to see how location affects the profit of each product.
Prompt: Now, calculate the average daily profit and plot the graph for product_category X location comparing promoting and non-promoting days. Also, give the insights along with.
Response from Terno:



Quick Summary of Insights:
- Rural stores: Snacks gain the most(+2648.82), followed by Beverages(+$1124.99) and Household(+$900.91) while Personal Care(-$1656.23) and Dairy(-$1892.64) decline.
- Suburban stores: Personal Care leads(+$988.30), followed by Household(+$547.00); other categories like Beverages(-$314.67), Dairy(-$652.73), and Snacks(-$1090.60) decline.
- Urban stores: Beverages lead(+$428.18), followed by Household(+$397.69) while other categories like Snacks(-$661.23), Personal Care(-$1139.99) and Dairy(-$1281.07) decline...
Step 7.
Following the profit patterns, we shift focus to revenue, comparing product-wise averages on promotion and non-promotion days.
Prompt: Now, can you calculate the average revenue for each product and plot the graph for the same by comparing the promoting and non-promoting days? Also, give the insights along with.
Response from Terno:


Quick Summary of Insights:
- Household: Strongest gain from promotions (+$1479.90).
- Beverages: Small positive lift(+$186.06).
- Dairy: Small loss (-$5.23).
- Snacks: Revenue declines under promotions(-$228.07).
- Personal Care: Revenue declines under promotions(-$1502.68).
Step 8.
Next, we analyze average revenue by store location, comparing promotion and non-promotion days for rural, suburban, and urban stores.
Prompt: Now, can you calculate the average revenue for each location, the same as you did for the product_category, by comparing promoting and non-promoting days? Also, give the insights along with.
Response from Terno:


Quick Summary of Insights:
- Rural stores: Promotions drive the largest revenue lift (+$322.12).
- Suburban stores: Promotions provide only a small boost (+$59.91).
- Urban stores: Promotions reduce revenue (–$448.68), suggesting discounts may hurt sales value.
Step 9.
Next, we analyze the combined impact of promotions by product and location, showing average revenue per transaction in faceted bar charts for Rural, Suburban, and Urban stores.
Prompt: Now, can you calculate the average revenue for each product x location-wise? Also, plot the graph for the same by comparing promotion and non-promotion days. Also, give the insights along with.
Response from Terno:

Quick Summary of Insights:
- Rural stores: Snacks(+$1503) and Household(+$1307) show strong gains, followed by Beverages(+$660) and Dairy(+$625); Personal Care(-$2836) drops sharply.
- Suburban stores: Personal Care(+$1456) and Dairy(+$1328) benefit most, with smaller gains in Beverages(+$365) and Household(+$279); Snacks(-$4277) decline heavily.
- Urban stores: Household(+$3194) and Snacks(+$1302) perform well, while Beverages(-$737), Personal Care(-$3159), and Dairy(-$3357) lose revenue under promotions.
Conclusion
In short, promotions work best when you match the right products with the right stores. We found that discounts on beverages, household items, and snacks boost both sales and profit—especially in rural shops. By contrast, deep discounts on dairy and personal care can actually cut into your margin. Focusing your promo budget on those winning product-and-location combos, setting the right discount levels, and timing offers to customer demand helps you grow revenue without losing profit. That way, every promotion dollar delivers clear, measurable value.
Curious how Terno-AI did all this analysis so fast? Check out my Conversation with Terno