As mentioned in Part 1, I visited Zé Delivery in Sao Paulo and toured their growing facilities with CEO Rudolfo Chung.

Zé Delivery is a Brazilian beverage delivery app launched by global beer giant AB InBev. It has had rapid adoption and is currently being expanded to all of Latin America.

• I talked about my visit in Podcast 139 (How AB InBev and Zé Delivery Are Changing Ecommerce in Beverages).

As a business, Zé Delivery is a fairly straight-forward mobile app that lets consumers order lots of types of alcohol and get them delivered in 15-20 minutes. Its consumer value proposition is a huge selection of beer, wine and spirits that is cheap, cold, and fast.

That’s a pretty good pitch for a mobile app.

Some other details.

• As a subsidiary of the world’s largest beer company (Ab InBev), Zé Delivery can sell a big selection at a good price.
• And they can deliver fast because they have been building  a big network delivery stations. That complement AB InBev’s already big fulfilment network. Fast delivery makes it convenient, which consumers love and usually induces demand.
• And the beverages arrive ice cold, which consumers also like. Zé Delivery has big refrigerators in its delivery facilities that are kept really, really cold.

That’s a simple value proposition. And it really works. By every measure, start-up Zé Delivery has great product market fit. And they were growing fast even before Covid spiked their demand.

As mentioned in Part 1, my assessment of this early version of the business is:

• It’s a popular service with good product market fit. The numbers are big and have grown really fast.
• The business has a serious barrier to entry against digital natives, which cannot easily replicate their physical infrastructure and their purchasing power (because of their tie to AB InBev).
• However, this beverage delivery service can probably be replicated by other large retailers (such as supermarket chains and convenience stores). These potential rivals also have significant distribution scale and purchasing power. But Zé Delivery was the first mover and is moving fast.

That’s my basic take.

In this article, I really wanted to point out 2 interesting lessons in digital strategy from Zé Delivery.

Lesson 1: Customer Improvements Never End in the Best Apps

The Zé Delivery app is still pretty basic. Its an ecommerce retailer with lots of alcohol types and expanding delivery. They are doing some personalization with their core service. Which means recommending different beverages. Maybe doing individual promotions. And doing some recommended bundles.

That is pretty standard for an ecommerce mobile app. One popular service, with some degree of personalization.

But if this is all they do, they will become vulnerable to imitation over time. By supermarkets, convenience stores and other large retailers.

So Zé Delivery needs to lean into Digital Operating Basics 2: Never-Ending Personalization and Customer Improvements. They need to keep personalizing. They need to keep improving their core service.

But they need to go further. They need to start adding experiences. They need to start expanding their services, usually starting with complements. 

Basically, they need to keep adding value to their customers.

Never-ending improvements is how you stay ahead of the competition. And that means moving up to the second and third level of the “Thrill Your Customers” Playbook. 

For Zé Delivery, this means expanding from just being a beverage store to also being in the occasions and events business. They are becoming the app you use when you are having a party. Or when there is a family get together. You get your beverages of course. But you also order food (such as meats for barbeque). And maybe small gifts. And maybe cooking or cleaning services.

Once you start to focus more on experiences, there is far greater room to innovate and improve.

If you look at Zé Delivery this way, it gets a lot more interesting as a digital company. Moving up to other forms of customer value means:

• They will deepen their relationship with their customers.
• They can increasingly specialize in operations.

Both will make Zé Delivery much harder to copy (say by supermarkets).

Lesson 2: Unfortunately, Competitive Advantages Aren’t Enough in Dynamic and Growing Markets. You Also Need Never-Ending Customer Improvements. 

I’ve written about the network effects trap. This is when network effects go in reverse. For example, if merchants stop taking American Express cards, they become less valuable to consumers. Then fewer consumers carry them. And they become less valuable to merchants. And so on. We can get a negative feedback loop (i.e., network effect).

Network effects make you highly dependent on keeping activity on your platform. If you start to lose consumers or merchants to a competitor, you can fall into a reverse network effect. So they are sort of a trap.

Yes, network effects are awesome. And can get you growth and competitive power. But you also need defenses so your competitors can’t steal your customers. And throw you into reverse network effects. A platform losing customers is like an airplane losing altitude. The pilots get really frantic.

Recall that network effects are “demand side economies of scale”. And just like “supply-side economies of scale”, they only work if there is a scale differential between the market leaders and most competitors. You need to be bigger than your rivals for this advantage to work (i.e., it’s a scale advantage).

Maintaining a scale differential is easier if the market is circumscribed. Meaning there are no lateral or related markets or services for a competitor to get large in. You want to be the biggest hospital in an isolated mountain town.

If also helps if there is slow growth and limited dynamism. That limits the space for another company to grow. If a competitor wants to match your scale, they have to steal your customers. They can’t just grow with the market. This is why network effects (and economies of scale) are stronger if there is also some form of customer capture (like switching costs). It makes customers harder to steal.

However…

This situation (a scale differential in a slow growing, circumscribed market) is usually not the case for digital services and mobile apps. These markets are often high growth. And digital services are good at moving across industry barriers. That’s a problem for businesses with network effects. They are the ones that face the network effects trap the most often.

Ant Group’s solution to this problem is to lean into DOB2. To continually add value to the customers.

In fact, the core strategy of Ant Group and Alibaba is to continually improve the user experience. They talk about this all the time as their primary strategy. That’s good business.

And it’s also how they protect their network effects in their high-growth markets with fuzzy boundaries. These companies are continually adding value to the user experience (which includes consumers, content creators and merchants / brands). Basically DOB2 is their primary defense for the network effects.

That’s why I put building moats and never-ending customer improvements in the same strategy. 

Lesson 3: Economies of Scale in Geographic Density Are Gaining Power with Machine Learning

I have written a lot about how Meituan and Grab are both focused on achieving economies of scale based on geographic density (CA13). This is an increasingly important competitive advantage in B2C services (like Zé Delivery).

Really in any service where delivery and logistics are combining with machine learning to achieve tech-driven cost efficiencies.

Here is my standard definition for CA13: Geographic and Distribution Density.

“Geographic density is a competitive advantage that results from having greater customers, volume, nodes, and/or routes within a geographic area than a competitor. For distribution businesses, this can result in:

• Lower costs
• Greater coverage
• Faster distribution times

Superior geographic and distribution density can be an advantage of the larger players. It’s a scale advantage.”

This one can be kind of confusing.

When people think about economies of scale, they usually think of fixed costs (which is definitely one type of economies of scale). Having greater scale means your fixed costs (like IT spending and R&D) drop as a percentage and you get increasing operating leverage.

But geographic density is a scale advantage that impacts delivery costs, which is usually a big variable cost. The goal is lower delivery fees per order. 

For food delivery (Meituan, Grab), we can see a required time and cost for each activity of a typical order.

1. Riders go to lots of different restaurants. When receiving an order, they move around within a 7-10 kilometer radius from their location. They can be close or far from a specific restaurant. And they are often going to different places to pick up orders.
2. At the restaurant, the rider usually waits while food is being prepared. Or the restaurant is waiting for them.
3. They eventually pick up one or more orders from that specific restaurant.
4. They then go to deliver the order(s) to one or more homes, which can be anywhere within a fairly large radius.
5. At the point of delivery, they often must wait for the customer. Especially if they are getting paid in cash.
6. They then accept another order and go off to pick up at another restaurant,

There are lot of steps. And that is the simple version. And drivers can also pick up orders at other restaurants as they are in the process of delivering already picked up orders.

Now, think about how the time and cost of each activity changes with:

• Increasing customer density in a geographic area. Doesn’t that make the average trip shorter? And therefore cheaper?
• Increasing restaurant density in a geographic area. Doesn’t this decrease time and cost as well? 
• Increasing order volume in a geographic area. Drivers spend less time waiting for the next order. Orders can be group together. Are drivers now carrying 5 or 6 orders one on route? But wouldn’t that change the optimal delivery route?

In the simple version, a company with greater geographic density of orders has drivers that are closer to their next restaurant when they receive an order. And the spatial distances for pick-up and delivery decrease with increasing orders, restaurants, customers, and driver density.

But the routes the riders take are not fixed. Riders can change the streets they take to decrease the time to reach the restaurant and then the customer. And as riders are increasingly combining different orders (batch size), they can then optimize their routes for a particular order combination. That’s why machine learning and technology are an important part of this competitive advantage.

Overall, what we should see with increasing geographic density and other tech-driven cost efficiencies is:

• Decreasing average delivery times.
• Decreasing average delivery costs.
• Increasing geographic coverage for both customers and restaurants.

For example, Grab talks about three metrics that increase driver productivity with increasing scale.

Now, think about how this competitive advantage changes for beverage delivery.

First, Zé Delivery is not a marketplace platform (yet). It is a pipeline business that provides a service. It has economies of scale in purchasing power (via AB InBev) and a big supply chain (lots of warehouses). But it is not a marketplace with network effects.

I visited several Zé Delivery distribution hubs in Sao Paulo. Some were co-located with AB InBev warehouses. Others were more specialized fulfilment centers. And then there were partner distribution centers blanketing the smaller neighborhoods of Sao Paulo. Here is a one of the specialized fulfilment centers.

For Zé Delivery, the delivery guys (on motorcycles) are mostly going back and forth between one specific center and one neighborhood (usually where they live).

That is different than Grab. They are not migrating across town serving lots of different restaurants. They stay local in one part of town and work out of one distribution center. This means they know the neighborhood well and can lots of fast trips. There is much less need for machine learning to do batching and route optimization.

There is also very little waiting time for pick-up. The distribution center works fast assembling and bagging the orders. They are optimized to do this. That is different than tons of small restaurants doing food preparation and packaging. Here the orders are systematically prepared.

The the delivery guys just grab the order and go.

So, what are the advantages of having greater geographic density in this type of model?

• Greater order density is the key.
• Which enables having more distribution points than a rival.
• More distribution centers means they will be closer to customers. Which means being faster and cheaper.
• Greater order density also should mean larger distribution centers carrying more types of beverages. 
• Larger distribution centers should have greater efficiency.
• Larger distribution centers will have greater ability to combine orders.

This linear distribution (not marketplace) model is a lot more about opening lots and lots of facilities all over town. Both directly and with partners. And then specializing those facilities, their technology and their drivers for cold beverage delivery.

It’s a pretty cool operating model. But I’m not sure it is really a competitive advantage. At least not nearly as strong as in Grab food delivery. 

This raises interesting questions.

• Are we going to see increasingly specialized distribution and delivery services? Some for beverages? Some for hot food? Some for pharmacy?
• Are we going to see combinations of marketplaces (like Grab) and specialized distribution (like Zé Delivery)? What if iFood (the Grab of Brazil) and Zé Delivery coordinated their services?
• In which B2C service models does greater geographic density have the most power?

Note: here is a distribution point for iFood. Note the order complexity on the screens. 

Anyways, it’s a really interesting business. And I thought it had 3 pretty good digital strategy lessons.

Thanks for reading. Cheers, Jeff

And for fun, here are some more pictures of murals in Sao Paulo.

I write, speak and consult about how to win (and not lose) in digital strategy and transformation.

I am the founder of TechMoat Consulting, a boutique consulting firm that helps retailers, brands, and technology companies exploit digital change to grow faster, innovate better and build digital moats. Get in touch here.

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