The brand “value chain”

The brand “value chain”

Consumers need for brands and their meaning is evolving. It will change where in the value chain most value accrues.

Established consumer brands have a good run for decades, servicing the majority share of increasing consumer demand. It’s no news to anyone that first the emergence of Amazon and then the emergence of DTC brands has completely disrupted the playbook of established brands.

The need for brands and the value they create is both changing. In a decade, the landscape of brands will look completely different, both in terms of the spread of brands that resonate with consumers and what they mean for them. Established brands in some categories will be replaced by no-name brands and in some other categories by DTC brands. This will change where the brand value accrues.

Evolving brand landscape and representative players in the value chain

Many no-name brands will be either Amazon’s private label brands or new Chinese brands selling on Amazon, and Amazon obviously will capture most of the value in these cases. Also, by being the virtual equivalent of a physical retailer’s shelf-space, it will capture most of the value for established brands as well, probably outside luxury brands.

In this post, I will NOT talk about Amazon’s value capture but instead focus on other entities that can expect to see significant value accruing to them as part of the changing brand landscape. These entities are:

  1. Platforms enabling DTC brands
  2. Secondary goods marketplaces
  3. “Social brand-network” focused on building communities around brands

1. Platforms enabling DTC brands

There is a lot that DTC brands have to get right when they are starting off. Mostly, there isn’t a lot of value in trying to recreate the technology (commerce) stack for selling to the customer. Platforms such as Shopify have made that commerce stack easily accessible. Below a excerpt from a recent article on Shopify.

What Shopify does is power all of that ability — from selling to payments to marketing. “We run the gamut of a retail operating system.” Like any platform, Shopify is building an ecosystem of developers, startups and ad agencies.

This evolution of Shopify from helping small businesses get online to helping venture funded DTC brands disrupt their markets is fascinating. It reminds me of how Nvidia found that its GPUs built for gaming are perfect for AI applications. As DTC brands increase in number and scale, Shopify (and other similar platforms) will accrue a lot of brand value. They are helping brands create their own virtual shelf space, not dependent on any retailer. As the needs of DTC brands grow, so will the tools that Shopify or other platforms offer to meet them, becoming the infrastructure layer for a part of the consumer brand economy.

2. Secondary goods marketplaces

Before the internet, brands were a proxy for trust. Buying from a known brand meant that you could trust what you were buying, short-circuiting the complexity of the buying process. So, it was enough for brands to just stand for trust. Today, Amazon has centralized trust, changing what it means to be a brand; this tweet captures it beautifully. Larger brands need to do more than just build trust. They need to stand for something to make consumers choose them over a no-name or a DTC brand.

This means adopting strategies that these brands would have scarcely used historically. Two come to mind, both centered around creating spikes of activity around the brand.

  • Taking a stance on social/political issue: An example of this is Nike’s ad campaign with Colin Kaepernick which led to significant increase in sales.
  • Engaging in product drops: Drops have emerged as a great way to create buzz. Streetwear brand Supreme pioneered it many years back and now more and more brand are adopting it. It creates scarcity for marquee products released in limited volume, giving the brand an opportunity to make itself aspirational and amplify what it stands for. Couple of examples of this are Adidas’ Alexander Wang drop and LV x Supreme drop.

In acknowledgement of these trends, Shopify has launched an app “Frenzy” to make it easier for consumers to know about upcoming drops and “buy at retail, not resale”. In my opinion, this only furthers the hype that these brands are trying to create, increasing the value of the products in the resale i.e. secondary market. eBay’s new ad campaign “It’s happening” speaks to this evolving strategy of brands. Below is an excerpt from the campaign.

Designed as more than just a brand campaign, we’re aiming to express to shoppers around the world what we’ve known all along: Everything that’s current, relevant and interesting is on eBay — and your audience can buy it now

The question then, as posed in this article around Supreme, is why would a brand let secondary goods marketplaces capture a significant part of the value it is creating. The answer is that secondary goods marketplaces help brands extend the buzz around them, increasing the brand value. They help more people feel part of the community that the brand is trying to create. They create a virtuous cycle in which both they and the brands benefit.

Secondary goods marketplaces have historically struggled at capturing the most value that brands create because of concerns around trust of the authenticity of the products. However, marketplace-provided authentication services (e.g. eBay Authenticate) are increasingly becoming a standard part of their commerce stack, resolving most of the trust issues.

With trust as a barrier mostly addressed, there is an opportunity for secondary goods marketplaces to more proactively participate in this trend. An example is eBay recently organizing it’s first-ever community sneaker drop, creating an artificial incentive for its sneaker-crazy buyers and sellers to trade on marquee sneakers, in the process increasing the brand value of the sneaker brands and accruing a lot of value to eBay.

3. “Social brand-network” focused on building communities around brands

As mentioned above, one of the biggest elements that makes brands valuable is the is sense that the customers of the brand get around belonging to the community. Historically one’s membership to the community could only come from one owning a product of the brand. That has its limitations; it can work well if you are a luxury brand but when millions of people own the brand, its hard to feel like you are a part of the community. There is a need for non-luxury brands to explore ways to build a network/community in a scalable way; this article articulates this very well.

As you would expect, internet has unique potential to help brands do that. Till date, social networks such as Instagram and Pinterest have been primarily helping DTC brands get off the ground by getting them in front of people. They haven’t built tools to continuously engage people around conversations with a brand. Glossier, a DTC beauty company that I highly admire, has been taking a community first approach to building its brand and its products, thanks to its origins from the blog Into The Gloss. It now plans to take the next step in its evolution by building a social network centered around beauty. Excerpt below from this article:

Weiss wants to build her own version of a social media and shopping mashup, something that will allow shoppers to get feedback from other users to find beauty products that are right for them. This is not a social network that sells ads for revenue: Instead, Glossier will sell its own beauty items on the platform.

While Glossier might be able to afford building a social media and shopping mashup to help it build a network of brand enthusiasts, most of the DTC brands won’t either have the resources or the category need to build a network of their own. That is where the opportunity lies for a NEW social network to think of shopping beyond lead generation and ads, and repurpose the concepts of forums, chat rooms, news feed, etc. to build a destination where consumers can truly connect with brands on an ongoing basis.

Instagram is the most likely candidate to build something like that with their new Shopping app but I am skeptical if they will be able to move beyond ads. Whoever ends up building such a destination, which I call a social brand-network, will accrue a lot of value that DTC brands are building. It won’t be a bad addition to Shopify’s commerce stack btw if they can pull it off.

 

As with any fundamental shift in any industry, there are winners and losers. Winners understand how the value chain is changing and how they are positioned to capture a large part of the value. The landscape of consumer brands is changing faster than expected. Amazon is without doubt the key driver of the change and capturing a lot of value. However, there is a lot of value to be captured elsewhere and I am excited about seeing how the different players rise up to the opportunities that exist.

The “bundled” internet

The “bundled” internet

The perfect storm of expensive subscriptions, bad ads, and the need for growth is pushing Google and Apple to break the internet into bundles, changing it forever.

Back in the early days of the internet, people paid for newspapers to get delivered to their home, they bought music CDs, and Blockbuster was thing. There were set rules for how content creation, payment and distribution worked. Internet disrupted that. Yahoo, Google and then Facebook emerged and created an internet economy, supported by ads. Consumers started expecting most written content, if not music/videos, to be freely accessible. Newspaper publishers saw their fortunes dip.

Meanwhile, companies such as Netflix and Spotify emerged, creating large subscription businesses, and laying down a template for how to monetize video and music content. Believing that their journalism was worth paying for, newspaper publishers such as NYTimes committed to building a subscription business and saw reasonable success. Now other publishers such as Bloomberg, Business Insider, etc. have followed suit, putting a lot of their content behind paywalls. They are hoping to create a future where they will no longer be slaves of the ad dollars of Google and Facebook.

The net result is that we are in subscription hell 😈 and are only getting deeper into it. A lot of good content is now behind separate paywalls. The experience of navigating the internet in search of knowledge is no longer seamless, and the “good internet” has started to become very expensive 💰.

The “bundle” opportunity

The state of the internet as a subscription hell is not sustainable; consumers deserve better. It needs to be easier and more affordable to access good content.

Imagine most of the content available behind separate paywalls becoming accessible as part of subscription bundles sold by Google and Apple, bundles that serve all your content needs —written content (news, analyses), audio (music, podcasts) and video (TV series, movies, etc.).

Evolution of content monetization

When this happens, the market for separate paywalls will shrink (at least in number of paywalls, if not the $ value), and only the richest consumers with very specific needs till buy into subscriptions outside of these bundles. The product experience of accessing content through these bundles will be much superior to the fragmented experience of browsing through good content on the internet today, and Google and Apple will be able to price these bundles low because of their large user base. It will be irrational to pay for separate paywalls unless one really has to.

What about ads?

The question, especially in the case of Google, is why would it create subscription bundles when its entire strategy is predicated on making the content freely accessible and monetizing through ads. There are two main reasons why Google would do that.

Ads have peaked

Selling ads seemed like a good strategy for Yahoo and Google to monetize the large user base that they had built by organizing the information on the internet. However, ads are mostly a nuisance and, as a result, ad blockers have increased in popularity. Google recently launched its own ad blocker on Chrome in its attempt to discipline sites showing disruptive ads and to prevent consumers from installing more aggressive ad blockers that block all ads across all sites.

Google (and also Facebook) are also trying to make ads more relevant to consumers, so that they don’t seem disruptive and can also help these companies make more money per user because of improved targeting. It’s a precarious strategy because the better the targeting, the creepier the ads can seem. Consumers now have a greater awareness of the privacy (data) they might be giving up to access the so called free services (Google search and Facebook newsfeed). According to a recent survey, 30% of respondents distrust Facebook with their personal information, not a good sign for a company that is built on having access to that information. This is a big red flag.

Ads aren’t the best way to monetize the best customers

Eric Feng put across a great argument in this article that monetizing via ads is sub-optimal because you can’t make more money off your best customers (i.e. users who use your products the most). He attributed that to two fundamental aspects of ads monetization: frequency capping and ad load.

Then he went on to argue that what makes Amazon so powerful is its ability to monetize its best customers significantly more than its average customers, calling its strategy shared-value transaction. Its best customers enable Amazon to invest in building a compelling value proposition (cost of access and user experience) for the average customer, getting more and more of them onto the platform. Google and Facebook understand that ads might not be the best business model after all, and Google specifically has been actively trying to diversify its business.

Winners and losers

The large tech companies best positioned to capitalize on this bundling opportunity are Google and Apple, and the large tech company that is set to lose the most is Facebook. The other big tech company most likely to be effected negatively is Spotify.

Google and Apple have all the raw ingredients to offer great content bundles

  • Customer touchpoint: They have dedicated user bases for written content (Google News, Apple News), audio (Google Play Music, Apple Music, Apple Podcasts), and video (YouTube, Apple TV).
  • Supply of content: They have good relationships with content publishers and are increasingly getting aggressive about creating original content.
  • User experience: They have invested in defining great product experiences for the future, Google with its focus on web based experiences (AMP and PWA), and Apple with its focus on good native experience (e.g. Apple News allows customers to add their existing subscriptions to it).

Launching bundles is probably easier for Apple than Google because Apple doesn’t have a big ad supported business that it would need to cannibalize. There is news that Apple is already gearing up to do that.

The biggest losers in the “bundled” internet economy will be

  • Subscription businesses that only offer a subset of content today that is not differentiated e.g. Spotify. These companies will lose some of their pricing power to the bundle creators, Google and Apple.
  • Facebook (it deserves to called out separately)! It will lose because while it serves a lot of ad-supported free text and video content, it is not an app that customers of bundles will see as the entry point for paid good content. It will also lose because it has failed to build good relationships with publishers; Instant Articles was a dud.

What could further extend the lead of Google’s and Apple’s bundles will be the non-content offerings (specifically storage) they are capable of adding to their content bundles. That will hurt companies such as Dropbox. Google One is a potential start in that direction.

Google and Apple need bundles as much as consumers need them. These companies have become very large and there is a need for them to find additional sources of growth. Making more money from their best customers while solving an important customer need is a win-win.

iOS and Android are the nerve centers of the biggest ecosystems in tech. If Google and Apple are able to create attractive bundles, these ecosystems will become even more entrenched. Content will play the role that apps played in building the App Store (and consequently Apple), and the internet will never be the same again.

Uber Mobility Cloud

Uber Mobility Cloud
 

Uber’s strategy has a new home — “mobility data infrastructure for YOUR city”. Blame it on competition and regulation.

There was this recent article by Eugene Wei around invisible asymptotes, defining them as the ceiling that a company’s growth curve would bump its head against if it continued down its current path. There has been a lot happening lately in the urban mobility market and it’s helpful to make a sense of the changes by thinking about the invisible asymptote of one of the key players: Uber.

Uber’s invisible asymptote has been the price of its service. Ubers are not a cheap mode of transport for vast number of use cases and a vast number of people, especially if you compare them with say the subway in New York. Uber has been aware of this invisible asymptote and has been continuously innovating to bring cheaper solutions such as Uber Pool and Uber Express Pool to market, and those have largely helped it grow at a healthy pace till date. Significant percent (though likely not majority) of Uber rides are now Pool.

While this is great, the mobility market has evolved and Uber’s invisible asymptote now seems to be more clearly visible. Uber doesn’t have many more tricks up its sleeve to continue to lower the price of its service. The result is a new strategy that is becoming the north star sooner that I had expected. Uber wants to be the mobility cloud for cities — the data infrastructure layer sitting between all the modes of transport and the apps/channels we use to access them.

Uber as the data infrastructure layer for mobility options in a city

Uber recently articulated this strategy by saying that it wants to take consumers from Point A to Point B even if it involves covering multiple modes of transport. There are multiple factors that have led Uber to this point and that make this strategy so compelling.

First, Uber has internalized the deeply geographical nature of the price competition. It found itself surrounded by deep pocketed competitors in international markets and figured that bleeding money through discounting wasn’t sustainable. It has ceded ground to Didi in China and Grab in Southeast Asia. This meant that some of the assumptions around the size of its user base supporting its valuation turned out to to be untrue, putting more pressure on it to penetrate its existing markets deeper to capture demand beyond taxis.

Second, the entry of bikes and scooters promised to substantially lower the price of short distance commute and shut Uber out. The users that scooters are going after are precisely the users that Uber is finding hard to win over because Uber is not cheap and, in this case, also not convenient. The only logical way to react to this was to acquire one of the companies and gain an entry into the market, which it did with its acquisition of Jump.

Third, it became clear that self-driving, which was Uber’s silver bullet to lowering the price of its service, won’t deliver for it. Self-driving won’t come soon enough (assuming a 2019 IPO for Uber) and Uber won’t be the one to get the self-driving technology right. In addition, there is an increasing threat that some players in the market might be able to cobble up a partnership to offer much cheaper rides to consumers w/o having to rely on Uber’s distribution. An example would be Waymo partnering with one of the big car manufacturers to have the capital muscle and expertise to deploy a fleet of self-driving cars in a city and enable consumers to hail them using Goole Maps which already has a large captive user base.

Lastly, Lyft, Uber’s primary competitor with a nicer brand image is becoming more aggressive with partnerships with cities (example Lyft’s partnership with the City of Phoenix), offering a path to lowering the price of service through subsidies. The entry of Uber/Lyft taught cities a lot about regulation and cities have realized that these new age transportation options are here to stay. They are finding that over-regulation (not allowing Uber/Lyft because of taxi unions) won’t work and so won’t under-regulation (letting city streets become scooter graveyards). Cities are increasingly trying to leverage their position in the mobility equation and are thinking of using Uber/Lyft as means to solving the urban mobility issues that the cities have always wanted to solve. If cities can subsidize Uber/Lyft rides to public transportation centers to incentivize higher usage of public transport, then its a win-win situation for Uber/Lyft and the cities, allowing them to offer a real alternate to car ownership.

This perfect storm of factors shaping the mobility market has resulted in Uber seeing itself more as the infrastructure layer for mobility, probably sooner than it might have imagined. This last point above around partnerships is the most important one because, going forward, cities will play an outsized role in defining the future of mobility. Bikes and scooters are not the last innovations in the space of urban mobility and Uber’s ability to capitalize on the future innovations will depend on whether it can be the data infrastructure connecting all the mobility options in a city which in turn will depend on whether or not cities allow it to do that.

If Uber can have all the mobility data and can offer cities a solution that optimizes the mobility options for price, convenience and utilization, then it surely will have a deeper moat than just offering a ride sharing solution. It is for this reason precisely that Uber is spending $500 Mn in ads to clean up its image and apologize for its past deeds. This campaign is not for consumers; it is to give city governments the cover to partner with Uber without the fear of a public backlash because governments don’t want to be seen partnering with evil entities.

Uber’s CEO Dara Khosrowshahi’s new positioning of Uber as a softer (less brash) is a pre-requisite for its push to be the mobility cloud. How open will this mobility cloud be is still a question but it’s now in Uber’s interest to push for a world where each city has at least one mobility cloud and it hopes that is can own the mobility clouds for most cities. In that sense, the change of guard at the top for Uber has been very timely and maybe one day, Uber will be able to tax all mobility the way AWS taxes all storage and computation.

Marketplaces and trust

Marketplaces and trust

Trust is one of the most important aspects of building a liquid marketplace, but trust is hard to quantify. Lately, I have been wondering if there is a playbook around building trust or does the answer depend on what type of marketplace one is building. I have landed on the conclusion that there is playbook as long as marketplaces can confidently answer the following question:

How likely is it that trust in a seller would influence the decision making of a buyer during a transaction?

This question is important because it helps bring clarity on how big a part of the trust equation should sellers be, resulting in a strategic decision on which of the two paths to take to build trust:

  • PATH 1: Deeply focus on building trust around individual sellers. Prominent examples are eBay, AirBnB, Thumbtack, etc.
  • PATH 2: Commoditize seller trust and build trust around the platform. Prominent examples are Amazon, Uber, etc.

To answer the question above, marketplaces need to have a good understanding of the uniqueness of the inventory on the marketplace as the buyers perceive it. PATH 1 is the natural choice if the perceived uniqueness of the inventory is high whereas PATH 2 is the natural choice if there are many sellers selling almost indistinguishable goods/ service. Below are some examples to illustrate the point.

eBay: Pioneer of PATH 1

eBay started as a P2P marketplace for selling unique items. Even if the item on sale was a Motorola Razr phone, there were many of them in many different conditions (on the spectrum of new and used). These conditions increased the perceived uniqueness of the inventory, effectively resulting in buyers treating them as different SKUs. In the absence of objective criteria for decision making, trust on the person who is selling (i.e. seller) became much more important. Buyers defaulted to sellers with higher positive feedback under the assumption that those sellers were honest about describing their products with details such as “the phone has a scratch on its back” as opposed to newer sellers who might be selling the phone for lower price but might be hiding something.

The figure below shows how eBay likely viewed its inventory. It considered that only a small minority of exact same items would be sold by multiple sellers. Given this view of its inventory, eBay defaulted to building a trust machinery centered around the seller and the platform receded in the background.

eBay: Only a small minority of exact same items would be sold by multiple sellers

Amazon: Pioneer of PATH 2

From early on, Amazon behaved like a retailer. It figured that by almost always selling new products, it can push seller trust to the sidelines and still kickstart a liquid marketplace. This made sense because if all the sellers on the platform were selling brand new Motorola Razr phone, the buyer decision making would simply be around price and possibly shipping. There would be no subjectivity around the SKU since it is brand new. That would put the platform in a position to commoditize seller trust as long as it was able to get enough sellers to create perfect competition among them.

The figure below shows how Amazon likely viewed its inventory. It considered that a large majority of the exact same items would be sold by multiple sellers. Given this view of its inventory, Amazon defaulted to building a trust machinery centered around the platform and the seller receded in the background. It built products such as Amazon Buy Box to truly commoditize seller trust.

Amazon: Large majority of the exact same items would be sold by multiple sellers

AirBnB: Best adopter of PATH 1

AirBnB almost replicated eBay’s model of building trust because the perceived uniqueness of inventory on AirBnB is as high as it gets. There is no SKU (room) that is listed by two or more sellers (hosts). Host has an information advantage and therefore, having trust in the host is important.

The figure below shows how AirBnB likely views its inventory. It considers that no exact same item (room) would be sold by multiple sellers. Given this view of its inventory, AirBnB adopted PATH 1, leading to it launching trust programs such as AirBnB Superhost.

AirBnB: No exact same item (room) would be sold by multiple sellers

The important question is that if AirBnB’s trust model is exactly like eBay’s trust model, then why do we trust AirBnB more in its category (travel accommodation) that we trust eBay in its category (goods)? The answer is that AirBnB is in a category that is hard to standardize; there isn’t an Amazon play possible at scale. And with features like Trips, AirBnB is trying its best to further deepen the uniqueness of inventory and make decision even more subjective. That is the reason I call AirBnB as the best adopter of PATH 1.


Now, how does this thinking about trust translate to services marketplaces like Thumbtack? Does it matter if the buyer is getting interior design from Service Provider A or Service Provider B? Yes, it does. How about plumbing? Maybe not, depending on how complicated a plumbing job it is. So, it is likely that some services might lend themselves to the Amazon model of commoditizing Service Provider trust while others won’t. Thumbtack has taken the approach of building trust via PATH 1. No surprise that Amazon Home & Business Services has defined the services (SKUs) very specifically and has adopted PATH 2, leveraging the trust it has already built as a platform.

For context, eBay has seen its focus shift towards selling new items and is experimenting with PATH 2 as evidenced by these fancy new product pages, applying the Amazon Buy Box concept.

eBay tweet.png

Overall, the decision of how to build trust comes down to the perceived uniqueness of the inventory of the marketplace. Being thoughtful about it, with an eye on how the category and the competition are evolving can make all the difference.

Marketplaces and pricing

Marketplaces and pricing

An approach to building for growth through pricing

Marketplaces help demand and supply connect and transact, and in return, they extract some value from the transaction. One of the biggest levers that marketplaces have to acquire and retain demand is pricing. When the supply is still scaling and the low price — high demand flywheel hasn’t yet kicked in, pricing is typically hacked and has no correlation with reality. However, to build a sustainable business, marketplaces need to invest in understanding the pricing dynamics of their marketplace sooner rather than later and they need to be methodical about it. “Pricing products” can help them build this understanding and in the process, they can make pricing a differentiator.

I define “Pricing products” as products built in the service of using pricing as a lever to drive GMV growth

“Pricing products” manifest themselves in three levels:

The pyramid of “pricing products”
  • Level 1: These are products focused on removing lack of pricing transparency as a barrier to decision making for customers
  • Level 2: These are products designed to opportunistically deploy pricing tactics and influence customer decision
  • Level 3: These are products designed to offer guaranteed pricing consistently on certain goods/ services, thereby locking-in customers

Level 1: Removing lack of price transparency

Bringing price transparency is the first step for marketplaces to start adding value beyond the obvious “allowing demand and supply sides to connect”. By doing this, they abstract away the noise in pricing inherent in a fragmented supplier base, and present the supply-side goods/ services to customers in a more consumable form. The idea is to make sure that pricing noise doesn’t become a barrier in customers choosing to use the marketplace.

The earliest scalable implementation of this was Amazon Buy Box which allowed ‘n’ sellers, all selling the same product ‘a’ to offer low price in result of their listing showing up as the default buying option whenever product ‘a’ showed up in search results. It was simple but it took off the burden on part of the customers to find the best price for the product ‘a’ they wanted to buy. eBay, on the other hand, still requires customers to figure out the best deal, thereby, earning the reputation of a flea market.

A more nuanced example is Amazon removing lack of price transparency across thousands of SKUs of CPG goods by distilling all pricing down to one specific unit of comparison — ounces. This is powerful because it has not only allowed Amazon to minimize decision remorse among buyers, but has also enabled it to successfully demonstrate to buyers the value of opting for CPG subscriptions as opposed to one-time purchases. Subscriptions, as anyone can guess, is a great business, leading to a much more stable revenue stream.

Amazon showing “per ounce” price for all toothpaste SKUs

Level 2: Deploying pricing tactics opportunistically

Pricing tactics are a collection of opportunities where marketplaces consider that by inserting themselves into the supplier pricing, they can fundamentally influence the customer decision. These are opportunistic insertions meant to drive goals on customer acquisition and retention, while maximizing the value they can extract from customers.

Uber/ Lyft, with their approach to surge pricing, have long been the visible leaders in pricing tactics. Their switch to upfront pricing is an extension of that tactic, giving them even more leverage. Not only does it address the problem of price transparency referred to above, but it also acts as the foundation for loyalty programs such as algorithmic push of promo codes that can make a customer’s ride to destination ‘x’ on Uber cheaper than that on Lyft, resulting in him/ her choosing Uber for that ride. Underlying that pushed promo code is the understanding that converting the customer to choose Uber for that ride is net positive (higher LTV) for Uber.

Level 3: Acting as a price guarantor

Pricing guarantee is the act of marketplace offering fixed pricing for certain goods/ services. It differs from the pricing tactics above in that these price guarantees persist for days or months and are intended to lock-in customers for those goods/ services, and possibly beyond.

While Amazon Prime has been one of the earlier implementations of a price guarantee (in this case shipping price), Uber/ Lyft are more interesting examples. Uber launched a monthly pass while Lyft caps the price of rides in SF. These are initiatives designed to build/ retain the demand base with the hope that supply base will scale to meet the demand, in process reducing inefficiencies and creating an incentive for suppliers to fund the discounts inherent in guarantees themselves.

Lyft’s fare fencing in SF

The ability of a marketplace to execute on the three levels of pricing products mentioned above would typically increase as it matures and captures more data. However, if done the right way, these products should be built in a particular sequence. It is hard to become a price guarantor without having experimented with pricing tactics to understand customer response. Similarly, it is hard to experiment with pricing tactics without removing price ambiguity in decision making. The first step in removing price ambiguity is to understand what the marketplace is selling and how suppliers are pricing it. The earlier marketplaces get started on that, the better.

American local buying & selling startups will soon hit the monetization wall

American local buying & selling startups will soon hit the monetization wall
 

There has been a lot of buzz lately about a new breed of Craigslist killers. OfferUp and letgo are the leaders in that pack and are into the business of facilitating local buying & selling. They have collectively raised more than $300 million in VC funding. The thesis is that with the emergence of mobile, there is finally a clear gap in Craigslist’s product strategy and that gap is good enough for these startups to exploit and build their own network effects.

While I agree with this thesis, I believe there are some market truths because of which these local buying & selling startups will never be big businesses. They surely will be relevant and will be used by millions of users but they will never make the kind of money that will guarantee their rapid growth once the VC money is gone.

In the matrix below, I have plotted local buying & selling startups in the broader e-commerce landscape. Ads and listing fees are the two prominent ways of monetization for companies in each of the quadrants.

Matrix showing the position of local buying & selling startups in the broader spectrum of e-commerce firms

My argument in that local buying & selling startups won’t be able to monetize enough if they were to stay in their current quadrant (1) and that it will be extremely hard for them to move into the other quadrants (2, 3 and 4) which are better suited for monetization.

Quadrant 1 is difficult to monetize

History and future of depressed prices

This year, OfferUp is likely to facilitate $14 billion in e-commerce transactions but it will make almost no revenue because it has not started to monetize yet. Craigslist facilitates a significantly higher $ value of transactions and earns only about $400 million in revenue. One reason for this low revenue is the nature of local buying & selling as a business. Given that most of the transactions happen offline, it is hard for Craigslist or anyone else to make money on transaction fees because of significant leakage. Another reason is that Craigslist doesn’t want to make more money than required to meet its costs and it has been open about that. Because of both these reasons, the market for local buying & selling has had artificially depressed prices with consumers assuming that listing should be free.

One might argue that if provided with a better product experience, customers will pay. That could have been true had it not been for the emergence of the unique phenomenon called Facebook. Facebook groups for local buying & selling have been pretty active and are free. The problem for the startups is that Facebook makes money from ads and ad platforms swear by one principle: ensuring a high level of engagement on the platform. By allowing consumers to buy & sell on Facebook, it is giving them another reason to come back to its increasingly utility oriented platform. It will never charge them for buying & selling because ads will allow it to monetize their presence much better. Sure, selling on Facebook might be a bit harder but it already has a highly liquid marketplace which works on mobile. So, it is good enough and sometimes that is all you need.

Limited value proposition for advertises

Local buying & selling startups in their current avatar are not attractive for advertisers. Users come to these platforms only for one narrow use case of buying & selling of used goods and given that this need doesn’t arise as often, the engagement levels on the platforms are low. This is a structural problem and is unlike any other major ad platform (Google, Facebook, Snapchat, Pinterest, LinkedIn, etc.). Successful ad platforms mean different things to different people and even different things to the same person at different times.

Moving into Quadrants 2, 3 and 4 is hard

Attractive local categories are now taken

Given the leakage we talked about earlier, the safest monetization bet for local buying & selling startups is to charge upfront listings fees i.e. fees for putting a listing on the platform irrespective of whether it sells or not. Only a certain type of seller putting a certain type of listing would see the ROI in paying that fee. Majority of Craigslist’s revenue comes from listing fees in three categories: employment listings, real estate listings and car listings. People get that and therefore, there are already startups that are targeted specifically towards these categories (example: Upwork, Zillow, Beepi, etc.). Like local buying & selling startups, these startups are designed to take advantage of the gap in Craigslist’s mobile strategy. They have already built a sizeable user base and offer a user experience that eases the friction in the specific category they are in.

Even if local buying & selling startups were to diversify into these categories, they would not be able to offer the desired user experience. The result would be an inventory with a selection bias. A quick look at cars on OfferUp vs. Beepi would tell you the difference. OfferUp has cheap old cars that few would want to buy whereas Beepi has real good cars. There is a direct correlation between the amount of effort one is willing to put in and the value of her item. Even if Beepi is more work, one would be willing to go through that if it means she can earn more for her valuable car. However, when one knows that her car is crappy, she would rather limit her agony, put it up on OfferUp in 10 seconds and make whatever she can. Sooner or later, buyers would realize this selection bias in the inventory of these startups, resulting in these startups capturing only a small part of these more monetizable categories.

Traditional e-commerce is a different ball game

eBay has been trying a transition from a P2P marketplace to a more traditional e-commerce business and it has been incredibly hard. Even if we assume that local buying & selling startups won’t make the same mistakes as eBay, some real problems will remain, making the transition extremely hard.

One, to scale up, these startups need to be acceptable to more buyers and that is possible only if they provide them with a significantly more structured in-app product experience and also with a significantly better service in terms of delivery and return. Both of these can be accomplished only if these startups get small and large businesses and not consumer sellers to become the dominant part of their seller base. As they make this transition, they will need to change their feedback policies and products (e.g. listing tools) to suit these larger sellers. How do you think that will make the consumer sellers feel? Marginalized and unimportant. All the promises of these platforms being a free land where users can list anything in 10 seconds and sell immediately would fall apart, leading to an outflux of these sellers.

Two, as these startups scale, their brand will turn from an asset into a liability. The effort that their marketing departments are putting to position these platforms as go-to destinations for local buying & selling will come back to bite them. Perceptions are hard to break and play a big role when buyers are deciding which platform to do what kind of shopping from. eBay has had this perception problem; people still refer to it as an auctions website for used goods when only 15% of its GMV now is from auctions and more than 80% of the goods sold on it are new.

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There could be some monetization tricks that these local buying & selling startups might have up their sleeve. However, as things stand right now, I am skeptical of how the future will pan out for these startups. Monetization winter for these startups might be around the corner.

Leveraging the right User Generated Content (UGC) for your product

Leveraging the right User Generated Content (UGC) for your product
 

User Generated Content (UGC) is not new and is a pretty self-explanatory term. In fact, this post is an example of UGC. Companies have leveraged UGC in various ways to enhance their product and the world has quickly moved from seeing UGC as an innovative idea to facing a glut of UGC. The question now is, how does one decide what kind of UGC is good for their product?

In my mind, there are three lenses through which one could evaluate UGC for product fit. Note: In this post, I will limit the discussion to UGC for product focused use cases and not consider UGC for use cases in aligned activities such as marketing or customer service.

Impact on Serviceable Available Market (SAM)

Serviceable Available Market is defined as the part of the Total Addressable Market (TAM) that can actually be reached by the product (wiki). One’s choice of UGC can fundamentally change the nature of the product, thereby impacting its SAM. For example, eBay allows all kinds of HTML and Javascript in its item descriptions (example here); this makes sellers feel more in control and has historically helped eBay on-board sellers across multiple categories much faster, thereby expanding its SAM.

Example of product description on eBay

However, as online shopping has moved closer to retail standard, these differently structured descriptions for different items have led to a bad buyer experience. It is akin to navigating a flea market. While this experience still makes eBay feel like home to a certain segment of buyers, it severely limits its SAM because many buyers (especially millennials) are not comfortable with this user experience.

Alignment with the product and brand philosophy

The best way to explain this is to look at the contrasting levels of UGC on three e-commerce platforms: Amazon, eBay and Poshmark. Amazon behaves like a true retailer and makes sellers link their items to a product in Amazon’s catalog. The description for any given product in its catalog is user generated, with Amazon doing the final curation. This leads to a clean and consistent item description, resulting in a standardized buyer experience. eBay on the other hand was conceived as a true marketplace, designed to make any transaction feel more like a buyer-seller transaction than a buyer-eBay transaction. This led to it allowing all kinds of product descriptions, an example of which was shown above. Poshmark is a social e-commerce marketplace and therefore, it shows a range of buyer-seller chat content, from offers to emojis, on the listing page. It allows this content because it believes that this makes buyers feel part of a community and builds repeat purchase relationships. Something like this would be unthinkable for Amazon because retailers live and breathe standardization and elimination of distraction.

Example of buyer-seller interaction on Poshmark

Fit with the scale of the platform and the nature of its offerings

In the world of e-commerce, UGC is integral to the product and plays a key role at various points in the conversion funnel. However, what kind of UGC would work depends on the scale of the platform and the nature of its offerings. For example, user generated buying guides (example: this buying guide on antiques) are an amazing tool for platforms that sell items that involve significant upfront research from the buyer. Having good guides increases the probability that the buyer will buy from the platform whose guide he/ she read. Similarly, user generated collections (example: this collection on plush), which are a prominent part of eBay’s home page and are based on one’s search history, are great but only if the platform has enough breadth and depth of inventory across categories to be able to justify such prime real estate for them. They increase the probability of the buyer seeing something exciting enough that he/ she will buy it.

Plush collections on eBay homepage based on plush focused searches by the buyer

In contrast, Customer reviews, which generally are an awesome piece of UGC, could be a big problem for a mass platform trying to get into a niche category. Given it’s mass buyer base, platform’s niche items are likely to get bad or no reviews, which its buyers are trained to treat as a sign that an item is not worth buying. This could lead to such items getting into a vicious cycle that inhibits their future sale. Eventual result will be that the sellers in niche categories that the platform might have courted with a lot of effort will move elsewhere and the platform will be unable to diversify. To appreciate this scenario, think about why niche stuff sells so well on eBay. eBay buyers are trained to trust and experiment and not to rely on customer reviews because there weren’t any customer reviews on eBay till early this year! So, the choice of not having that critical piece of UGC (i.e. customer reviews) did work to reinforce eBay’s niche fabric.

Overall, while UGC is great, the decision on what kind of UGC to leverage is not straightforward. UGC can be immensely powerful as long as you leverage the right one and carefully harness it.