Use case · Pack-Price Architecture

Price, pack, and channel are one decision. They are almost never optimized as one.

In an affordability-driven market, the pack-price ladder is the single highest-leverage lever a beverage business has, and the hardest to reason about, because every move trades volume against margin against retailer economics against competitor gap.

Step

01 of 03

Answers

what happened

Engine

Analytics Engine

Status

available today

Step 01 · Analytics Engine

Available today

What happened?

Revenue and gross margin per litre by pack, channel, and region, last 12 months.

Where the mix is trading down. Which packs carry the margin. What the retailer actually earns per pack, by channel.

Pack mix by channel Illustrative figures
GT
MT
HoReCa

Terms on this page

GT, MT, HoReCa
Sales channels: general trade (independent shops), modern trade (supermarkets and chains), and hotels, restaurants, and cafés.
Trading down
Shoppers shifting toward cheaper or smaller packs.
RGB, PET, CAN
Pack types: returnable glass bottle, plastic bottle, and can.

How the Analytics Engine gets there

  1. 01Our proprietary agentic orchestration interprets the intent and translates it into structured SQL. Nothing else is asked of the model.
  2. 02Generated SQL is validated against the live schema before it runs, connected read-only to the databases, ERPs, and CRMs already in place.
  3. 03The database executes the query and returns rows, deterministically, from the company’s own records.
  4. 04Results render as charts, get pinned into living dashboards, or carry alert conditions that run against fresh data.

Available today. Live and deployable today, cloud or on-premise.

Explore the Analytics Engine

What changes

The relay today

Leader → analyst → database team → dashboard → review. Days later, a chart answering last week’s question.

With Theovya

The person with the question gets the answer directly, in seconds, from live data.

This is the decision most FMCG businesses make once a year, in a room, with a spreadsheet. It can be made continuously, with the trade-offs computed instead of debated.

Use case · Pack-Price Architecture

Price, pack, and channel are one decision. They are almost never optimized as one.

In an affordability-driven market, the pack-price ladder is the single highest-leverage lever a beverage business has, and the hardest to reason about, because every move trades volume against margin against retailer economics against competitor gap.

Step

01 of 03

Answers

what happened

Engine

Analytics Engine

Status

available today

Step 01 · Analytics Engine

Available today

What happened?

Revenue and gross margin per litre by pack, channel, and region, last 12 months.

Where the mix is trading down. Which packs carry the margin. What the retailer actually earns per pack, by channel.

Pack mix by channel Illustrative figures
GT
MT
HoReCa

Terms on this page

GT, MT, HoReCa
Sales channels: general trade (independent shops), modern trade (supermarkets and chains), and hotels, restaurants, and cafés.
Trading down
Shoppers shifting toward cheaper or smaller packs.
RGB, PET, CAN
Pack types: returnable glass bottle, plastic bottle, and can.

How the Analytics Engine gets there

  1. 01Our proprietary agentic orchestration interprets the intent and translates it into structured SQL. Nothing else is asked of the model.
  2. 02Generated SQL is validated against the live schema before it runs, connected read-only to the databases, ERPs, and CRMs already in place.
  3. 03The database executes the query and returns rows, deterministically, from the company’s own records.
  4. 04Results render as charts, get pinned into living dashboards, or carry alert conditions that run against fresh data.

Available today. Live and deployable today, cloud or on-premise.

Explore the Analytics Engine

What changes

The relay today

Leader → analyst → database team → dashboard → review. Days later, a chart answering last week’s question.

With Theovya

The person with the question gets the answer directly, in seconds, from live data.

This is the decision most FMCG businesses make once a year, in a room, with a spreadsheet. It can be made continuously, with the trade-offs computed instead of debated.