đź“Š 80% of quick-commerce orders are discounted – can it be profitable?

I have selected some of the best graphs and charts that I have seen in recent articles and newsletters.

30 to 80% of quick-commerce orders are discounted

This article provides a wealth of data on how much quick-commerce (less than 10 to 30 minutes grocery deliveries) are discounted in various countries.

It seems that the more intense the competition is, the more the players are discounting the orders made by consumers. Discount is normal in a context of rapid growth and intense competition to acquire the most consumers. Would consumers remain if the discounts were removed?

GoPuff is gaining new consumers and increasing its sales per consumer

Beyond the (many) doubts around quick-commerce players, it is interesting to look at the evolution of one of the more mature startups in this space, GoPuff. It shows how it has been able to grow fast while increasing the amount it sales to each consumer monthly. Creating loyalty, repeat orders and increasing the size of each of them are three key elements for quick-commerce is ever to be profitable.

The average size order, the holy grail of quick-commerce

These graphs (made earlier this year, previously to the current inflation context on wages and food) are a simple (yet effective) demonstration of the importance of the average order size to be profitable as a quick-commerce startup. We could add things such as the number of orders per day or economies of scale, but it gets to the main point: companies have to sell more (and more often) to each consumer.

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What we did:

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  • Education of the board through a couple of workshops to define the perimeter
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  • Creating a consensus on which categories to prioritise and how to address them.
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Use case: project for a global CPG company to develop a strategy on the healthy ageing ecosystem

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Use case: opportunity screening for an ingredient company

What we did:

  • Kick-off to define the perimeter of the ecosystem studied.
  • Mapping of the different trends shaping the innovation ecosystem of the client.
  • Analysis of the trends on DigitalFoodLab’s trend curve and other relevant frameworks.
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Results:

  • Shared view of the innovation ecosystem for the client with a view of the trends to prioritize.
  • Clear document (personalised trend curve) that can be easily shared internaly to explain the company’s innovation choices and which can be then updated each year.

Use case: scouting for an agriculture coop

What we did:

  • Kick-off to define the perimeter of the client, the goals of the scouting (partnerships) and the criteria on which startups should be evaluated.
  • Set-up scouting: we selected the first batch of 20+ key startups following the criteria of the client.
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Results:

  • Different results from traditional M&A processes with a focus on the client’s innovation strategy.
  • Identification of a good match for an acquisition.

Use case: market due diligence on sugar alternatives

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