A Platform is in the Eye of the Beholder

The distinction between whether you are building a platform or a product should be made primarily to align your internal stakeholders to a particular strategic direction, as we learned in the recent iSPIRT round table.

[This is a guest post By Ben Merton]

“So are we a platform, or are we a product?” I said last month to my co-founder, Lakshman, as we put the finishing touches to our new website.

We’d been discussing the same question for about a year. The subject now bore all the characteristics of something unpleasant that refuses to flush.

However, the pressure had mounted. We now had to commit something to the menu bar.

“I think we’re a product.”

“But we want to be a platform.”

“Okay, let’s put platform then…But isn’t it a little pretentious to claim you’re a platform when you’re not?”

Eventually, we agreed to a feeble compromise: we were building a platform, made up of products.

Job done.

At least, that is, until #SaaSBoomi in Chennai last month.

Manav Garg, who has considerably more experience than both me and Lakshman at building platforms, put up the following slide:

Product = Solving a specific problem or use case

Platform = Solving multiple problems on a common infrastructure

“Here we go again”, I could hear Lakshman say to himself after I Whatsapped him the image.

“That’s his definition. It doesn’t have to be ours,” he replied tersely, “What does he mean by ‘use case’, anyway?”

“I don’t know.”

I’m in awe of the entrepreneurs who seem to bypass these semantic quandaries.

You know, the ones who say stuff like “Stop thinking so much. Just sell stuff. Make customers happy.”

For me, these are the type of questions I need to chew over for hours in bed at night.

I was therefore excited to be invited to the iSPIRT round table at EGL last week, where the topic of discussion was “Transform B2B SaaS with #PlatformThinking”. The roundtable was facilitated by iSPIRT mavens Avlesh SinghShivku Ganesan & Sampad Swain.

It takes a lot to get 20 tech founders & their leaders to travel after work from all over the city to sit in a room for three hours with no alcohol.  Fortunately, the organisers had promised a lot.  The topic description was:  

“Enable a suite of products, high interoperability, and seamless data flow for customers. This peer-learning playbookRT will help product to platform thinkers develop an effective journey through this transformation” was the topic description.”

The meeting was governed by Chatham House rules, meaning we can’t discuss the name or affiliation of those involved.

However, along with our founder mavens of large, well-known Indian technology businesses, there were 15 or so less illustrious but equally enthusiastic founders (& their +1s), including myself.

The discussions started with an overview of the experiences and lessons that had been learned by some of those who had successfully built a platform.

“We define a use case as a configuration of APIs…” the founder of a cloud communication platform started. This was going to be interesting.

“Why did you define it that way?” I asked.

“Based on observations of our business.”

I began to understand that the term ‘use case’ was being used differently by platform and product companies.  

“A use case of a platform is usually tangential but complementary to the core business. A use case for a product is something that just solves a problem,” someone clarified, guaranteeing me a slightly more restful night.

As the discussions continued, it also became clear that there were a large number of possible markers that distinguish a platform from a product, but there was no agreement on the exact composition.

To resolve the impasse, we listed out the names of well-known technology companies to build a consensus on whether they were a platform or a product.

Suffice to say, we failed to reach any consensus.  The conversation went something like this:




“A suite of products.”


“A marketplace.”

“A marketplace built on a platform.”

Etc etc

Even companies that initially appeared to be dyed-in-the-wool platforms like Segment and Zapier eventually had someone or the other questioning the underlying assumptions.

“Why can’t they be products?” murmured voices of dissent at the back of the room.

This was going nowhere. A few people sought solace from the cashew nuts that had been placed on conference table in front of us.

“Does the customer care whether you’re a product or a platform?” someone said.

Finally, something everyone could agree on. The customer doesn’t care.  Your product or platform just needs to solve a problem for them.

“Then why does any of this matter at all?” became the obvious next question.

“I found it mattered hugely in setting the direction of the company, especially for the engineering and design teams,” the Co-Founder of a large payment gateway said.

“And investors?”

“Yes, of course. And investors. However, I think the biggest impact that our decision to build a platform had on my business was in the design more than anything else,” he explained, “For the engineering team, it was just a question of ‘we need this to integrate with this’. But the UX/UI and the…language… needed to be thought about very carefully because of this decision.”

“So, in effect, the platform/product debate is primarily a proxy for the cultural direction of the company?”


Logically, therefore, the only way you can really understand whether a company is a platform or a product is to have an insight into the direction its management wishes to take it.

A company might appear to be a product from the outside but, since it intends to evolve into a platform, it needs to start aligning its internal stakeholders to this evolution much earlier.

“So, a startup like mine should call itself a platform even if we are years away from actually being one?” I asked cautiously after I had enough time to process these insights.

“Yes,” was the resounding, satisfying response that virtually guaranteed me a full night’s sleep.

“And when should the actual transition from product to platform happen?”

“Well, Jason Lemkin says it should happen only when your ARR reaches USD 15m-20m, but that’s just another of those rules that doesn’t apply in India,” the co-founder of a marketing automation software said.

“The important thing is that this transition – when it does happen – is very hard for businesses,” he continued, “There is a lot of risk, but it opens up new revenue streams, helps you scale and build a moat.  We hugely benefited from our decision to become a platform, but it was tough.”

It’s unlikely that we completely resolved the product vs platform debate for all founders. However, I feel that all of us came away from that meeting with a deeper insight into the subject.

Ultimately, whether you’re building a product or a platform will depend on your perspective. Most companies lie somewhere in between.

Where does your company lie on this sliding scale? And if that makes you a platform vs. a product, does it make any difference to the way you think?

We want to thank Techstars India for hosting the first of the roundtables on this critical topic.

Ben Merton

Ben is a Co-Founder of Unifize, a B2B SaaS company that builds a communication platform for manufacturing and engineering teams. He is also a contributor for various publications on business, technology and entrepreneurship, including the Wall Street Journal, the Financial Times and Business Standard. You can follow him on LinkedIn here, and Twitter here.

© Ben Merton 2018

Featured Image: Source: https://filosofiadavidadiaria.blogspot.com/2018/01/o-principio-mistico-da-verdadeira-causa.html

31-Jan Transforming to Platform Products B2B SaaS PlaybookRT

Traditionally, how many Indian SAAS companies have managed to become platforms so far? Very few.

Customers needs are changing as they seek more flexibility to use their data to solve a wide range of business problems. They prefer a suite of tools instead of buying multiple single point products. For SaaS startups, the way to compete with larger incumbents like a salesforce is not by doing another better CRM product, but by being a better AI-enabled platform which is based on interoperability across a gamut of systems.

Startups building platforms to enable collaboration with partners and solving a comprehensive customer problem will disrupt those building piecemeal products. This playbook will help product to platform thinkers develop an effective journey through this transformation.

If you are a SaaS startup that is ready to embark or already started on the platform approach, this playbookRT will be a great forum for sharing & learning from our Mavens and peers on the challenges and focus areas.

Click to Register for the Platform Products PlaybooksRT. (limited invites)

Our Mavens

Avlesh Singh, Founder WebEngage

There’s been a significant difference in the way we build our product now. We have unlocked a lot of value by converting ourselves into a platform from being a tool.



Shivku Ganesan, Founder Exotel

The platform approach allows us to differentiate use cases from products.



This is a product startup founder/CXO (+1) invite-only events. Venue details will be sent along with the confirmation of your registration.

RoundTables are facilitated by an iSPIRT maven who is an accomplished practitioner of that Round-Table theme. All iSPIRT playbooks are Pro-bono, Closed room, Founder (+1), invite-only sessions. The only thing we require is a strong commitment to attend the sessions completely and to come prepared, to be open to learning & unlearning, and to share your context within a trusted environment. All key learnings are public goods & the sessions are governed by the Chatham House Rule.

SaaS 3.0 – Data, Platforms, and the AI/ML gold rush

An impending recession, the AI/ML gold rush, Data as the new oil, SaaS Explosion…
The SaaS landscape is changing rapidly and so are the customer expectations!

18 months ago, I came across a message that India is a premier hub for global B2B SaaS, just like Israel is a hub for cybersecurity. At first, I did not think much of it, but after having interacted with many SaaS founders and observing their painful growth journey, I realized the potential in these words. Yet, a series of market shifts are changing the world order of SaaS putting at test India’s position as a premier hub for SaaS.


The SaaS 3.0 market shifts are changing how global customers perceive value from SaaS products:

  • Tools which provide higher levels of automation & augmentation are valued more.
  • Comprehensive solutions in place of single point products is a preference.
  • Interoperability across the gamut of systems is an expected norm.

Startups, you have to build your new orbit to solve for these evolving needs. First, focus on delivering a 5x increase in customer value through an AI-enabled proposition. Next, build your proprietary data pot of gold, which can also serve as a sustainable moat. Lastly, leverage platforms & partnerships to offer a suite of products and solve comprehensive customer scenarios.

Read more on how the convergence of market shifts are impacting SaaS 3.0.

Quick background

While the SaaS industry began over 2 decades ago, many say it is only now entering the teenage years. Similar to the surge of hormones which recently brought my teenage daughter face-to-face with her first pimple. And she is facing a completely new almost losing battle with creams and home remedies. In the same vein, convergence of several market shifts – technology, data, economics, geopolitics – combined with deep SaaS penetration is evolving the industry to a new era. This rare convergence – like the convergence of the nine realms in Thor Dark World – is also rapidly changing how customers perceive the capability of SaaS products.

Convergence #1 – SaaS penetration is exploding!

I learned from Bala at Techstars India that they received a record number of applications for their first accelerator program. 60% of these were building or ideating some form of B2B SaaS offering. It would seem to justify the message above, that SaaS in India has grown legs, building a true viral movement, replicating momentum. Yet in these large numbers, there is also a substantial ratio of repetitive products to innovations. Repetitive in say building yet another CRM, or mindlessly riding a trend wave such as chatbots. Without an increased pace of innovation beyond our existing successes, we cannot continue to be a premier hub.

In 2018 SaaS continued to be the largest contributor to cloud revenue growth at 17.8% (it was down from 20.2% in 2017). Competition is heating up in all categories of SaaS. 10 years ago, an average SME customer was using 2 apps, now it averages at 16 apps. 5 years ago, a SaaS startup had on average 3 competitors, now a SaaS startups averages at 10 customers right out the door. Many popular SaaS categories are  “Red Oceans”. Competing in these areas is typically on the basis of features or price, dimensions which are easy for any competition to catch up on. There is a need for startups to venture deeper into the sea and discover unserved & unmet customer needs in a “Blue Ocean” where they have ample opportunity to fish and build a sustainable moat.

AppZen started with an opportunity to build conversational chatbots for employees, helping them in an enterprise workflows on various aspects like sales & expenses, and several other companies are doing the same. But as they went deeper to understand the customer pains, they were able to identify an unserved need and pivoted, leveraging the same AI technology they had built, to solve for T&E expense auditing. Being a first mover to solve this problem, they are carving out leadership in this underserved space and is one of the fastest growing SaaS startups of 2018.

Convergence #2 – Impending recession in 2019/2020!

On average recessions come every four years and we are currently 9 years from the last recession. The war between the Fed vs the US govt on interest rates, the recent US govt shutdown on a frivolous $B wall, the tariff and trade war between the US and China, are all indicative reasons for an upcoming recession. In such an uncertain economy, customers experience reduced business activity and alter their behavior and preferences:

  • Customers will become crystal clear about satisfying their core needs versus nice-to-haves.
  • They will seek high automation tools to help not only cut costs but also to make strategic decisions for an upside.
  • Many will prefer a suite of tools instead of buying multiple single point products.
  • They will also slow down POC, investment, partnership activities.

In a way, this is mixed news. Companies often pursue low-cost digital products with SaaS being a natural choice. However, combined with the competitive SaaS landscape, businesses become very selective. To be recession-proof startups must:

  1. Collaborate and partner with other vendors to build a shared view of the larger customer scenarios. Innovate to share (anonymized) data/intelligence.
  2. Partner to deliver a comprehensive solution instead of solving for a gap. 
  3. Invest & experiment in building solid AI-enabled automation for improving efficiency and decision making.

E.g. Clearbit’s approach to provide API and allow customers to leverage the value it provides, by integrating with common platforms such as Slack or Gmail which customers frequently use. In this approach they are reducing app switching and embedding the niche usecase into the larger customer workflow environment.

Another e.g. Tact.ai is helping increase sales team efficiency and bring visibility of field data to the leadership team. They are not only solving the core salesforce data entry problem for field sales, but with better data in the system, businesses now get better visibility about sales activities and can take effective strategic decisions.

Convergence #3 – the AI/ML gold rush!

During the dot com & mobile rush in early 2000, I watched many a friend jump ship to build a startup. At that time the web was flush with rich content, but the mobile web was in its early growth and innovative ways to bring web content onto mobile phones were being explored. Automated conversion of HTML to WML was a hot topic. But the ecosystem conditions were not aligned for completely automated WML transformations. Several startups in this space including my friend’s startup shut for such reasons.

More recently in 2016-17 Chatbots were projected to be the next big thing and it too suffered from similar misalignment. Chatbots were the first attempt to bring AI/NLP for customer interaction. However, they lacked the depth of ecosystem conditions to make them successful. 

  1. Bots were treated as a panacea for all kinds of customer interactions and were blindly applied to problems. 70% of the 100,000+ bots on Facebook Messenger fail to fulfill simple user requests. This is partly a result of not focusing on one strong area of focus for user interaction.
  2. Bots were implemented with rule-based dialogues, there was no conversational design built into it. NLP is still in its infancy and most bots lacked data to provide meaningful interactions. They were purely a reflection of the level of detail and thought that went into the creation of the bots.

AI/ML, however, is suffering from the “hype” of an “AI/ML hype”. There is a considerable depth within the AI/ML ecosystem iceberg. Amazon, Google, Microsoft…OpenSource are continuously evolving their AI stack with higher and higher fidelity of tools & algorithms. You no longer need fancy degrees to work the AI tools and automate important customer workflows or scenarios. 

Yet it is easier said than done. Most startups on the AI journey struggle to get sufficient data to build effective ML models. Further, data privacy has increased the complexity of sharing data, which now resides in distant silos. While internal proprietary data is a rich source of patterns, often times it is incomplete. In such cases, entrepreneurs must innovate, partner, source to build complete data as part of their data collection strategy. A strong data collection strategy allows for a sustainable moat. 

AIndra multiplied 7000 stains into 7M data points by splitting into microdata records. DataGen a startup in Israel, is generating fake data to help startups train models. The fake data is close enough to real data that the use is ethical and effective. Startups like Datum are building data marketplaces using blockchain to democratize data access. 

As mentioned many of the AI tools are limited in their constraints. Meanwhile, getting familiar with the capabilities and limitations of the necessary tools will help form a strategy path to solving the larger customer scenarios. 

Tact.ai faced the constraint by the limitations of the Alexa API. However, instead of building their own NLP they focused on working around the constraints, leveraging Alexa’s phrase based recognition to iteratively build value into their product. During this time, they continue to build a corpus of valuable data which will set them up for high growth when the NLP stack reaches higher fidelity.

Solving for the Hierarchy of Customer Needs

The convergence of SaaS penetration, AI/ML, data & privacy, uncertain economy & global policies… the customer expectations are rising up the Maslow’s hierarchy of needs. SaaS 1.0 was all about digital transformation on the cloud. SaaS 2.0 focused on solving problems for the mobile first scenarios. In the SaaS 3.0 era, the customer expectations are moving to the next higher levels. They will:

  • Prefer comprehensive solutions in place of single point products.
  • Expect interoperability across the gamut of systems.
  • Need tools which provide higher levels of automation & augmentation.

For startups who want to fortify their presence in the SaaS 3.0 era :

  1. Begin with a strong AI value proposition in mind, regardless if it is AI-first or AI-second. Articulate the 5x increase in value you can deliver using AI, which wasn’t feasible without AI. 
  2. Build your proprietary data pot of gold. And, where necessary augment with external data through strategic partnerships. A strong data lever will enable a sustainable moat. 
  3. Leverage platforms & partnerships to offer a suite of products for solving a comprehensive customer scenario.

Remember it is a multi-year journey, Start Now!


I would like to acknowledge Ashish Sinha (NextBigWhat), Bala Girisabala (Techstars India), Manish Singhal (Pi Ventures), Suresh Sambandam (KiSSFlow), and Sharad Sharma (iSPIRT) who helped with data, insights and critical feedback in crafting this writeup. Sheeba Sheikh (Freelance Designer) worked her wonderful illustrations which brought the content to life. 

Interesting Reads

Beyond Google Search – The Platforms For The Internet of Actions

Beyond Google Search – The Platforms For The Internet of Actions

The below post is edited from an answer given to ET for this story. This article is 2 yr old. Republished today.

The rise of Mobile is a big shift in the way Internet is used, thereby influencing commerce over the Internet. In developed economies it is the desktop based users who have started spending a significant amount of time on mobile. For India specifically, mobile is bringing in lot of first time Internet users.

Given that Google Search is not the default starting point on mobile, there is a void waiting to be filled as the platform of the mobile internet. No, Android/iOS is not it. There are 3 services that I believe can be the platform of the mobile internet viz. maps, payments and delivery. Before looking into each of them, the hypothesis here is that the Internet of mobile is no longer about serving information but it is about enabling actions. So what happens to information related stuff? They will move to a Chat like app with a command prompt like interface. It is already happening with Wechat, Line etc. Search would be easier over chat with results showing bite-size info in cards, the blue-link click is only required to dive deeper. Why chat and not current Google search? Because the current Google search is a state-less communication. Two consecutive searches do not relate to each other. The command prompt type interface serving bite-size info will need to be state aware, just like human communication.

The 3 platforms:


In the long term, Maps are going to be default page for most of our local needs, like movies, cabs, handyman or anything related to offline commerce. Different reports suggest that about 40-50% of all mobile search is local. Instead of a page with blue links, maps will become our search engine on mobile. China is already seeing this change with Baidu Maps driving all-things-local. Google Maps also recently integrated Uber to show estimated pickup time if you have uber installed (http://blog.uber.com/googlemaps). When you have more than 1 cab app installed, Google Maps will influence which one you choose. In the long run it will also mean that you will not need to install the app but the app will just be backend integrated with Google Maps.

Users currently find it easier to search for “Zomato Pizza Hut” on Google and then go to Zomato’s Pizza Hut page, as compared to first going to Zomato.com, and then searching for “Pizza Hut”. In the same way, people will not look for a cab on a map inside Ola or Uber’s app, instead Ola and Uber’s cabs will be visible together on a single instance of Google Map.

The future of mobile local search is Apps on Map, and not maps inside apps. Just like now we don’t need to bookmark every restaurant site on the web browser, in future we may not need to install every cab booking app. This is the most important and defensible product of Google in the long term. Individual Apps as an interface is an intermediary stage of the mobile evolution until platform level aggregation and deep integration does not come into action again.


We do not see payments as a platform because it is generally not the starting point or in most cases we don’t even realize if it has an interface. It just happens, and that is how it is supposed to be. Apple and Samsung are working towards that. In India, the wallet feature in apps is being accepted. Mobile carriers and large banks are trying to get into the space. Paytm seems to be moving fastest in this space though. There are still licenses to be issued in this space by RBI and rightly so because this space is more about enabling trust and insurance, the core of commerce, than anything else.

Indian consumers do not relate to payment systems and insurance directly, but in developed economies one can ask their credit card company for a complete refund if the service by a vendor is not satisfactory. So they not only act as a credit and payment company but also an insurance company. Being on a universal trusted payments platform will mean more business. Micro-transaction will happen over a payments app and each little vendor need not have their own app with payment gateway. I should be able to use a plumber’s service and pay via a payments app that both of us use.


Delivery of physical goods is a big platform opportunity. What we generally see as an ecommerce company is a delivery company. A lot of commerce, new and used, B2C and C2C, is being limited by the physical movement of goods. While intercity delivery is controlled by large courier companies, the hyper local delivery of goods is still an unsolved problem. Uber is dominant in this space for people movement and now starting for food but their platform doesn’t yet allow movement of small goods from B2C or C2C. In India, Delyver and Grofers are trying to capture this space. Entering the C2C delivery space will be a big move for them. It’s human delivery network now but from what we see, it will evolve into a drone network.

Platform Metrics: the core metric for platforms, networks and marketplaces

You become what you measure. From my experience working with clients across enterprises and startups, the most common reason for failure and inefficiency is the focus on convenient, but inappropriate, metrics. Your technology doesn’t determine the business you build. Neither does your organizational capability. The metric you optimize for is the single biggest factor that determines which business you end up building.

Metric Design

The importance of choosing the right metric is more far-reaching than we often believe. A metric is a bit like a commander’s intent in an army. At battle, there are a lot of variabilities and unexpected contingencies which cannot be pre-planned for. The Commander’s Intent is a simple rule of thumb that helps soldiers take local, individual decisions towards a cohesive, larger goal.

Metrics work in much the same manner. Once you set a metric, the entire team organizes its efforts around it, and works relentlessly to optimize the business for that metric. It’s often fancy to have a large dashboard with multiple graphs tracking hundreds of things. But to be truly effective, an organization/team/individual should be solely focused on optimizing for one metric.

As a result, identifying and designing the right metric is critical for business success. More often than not, I’ve seen the following general observation to hold true:

If you’re asking someone to optimize for more than one metric, you’re setting them up for failure. 

Often, ratios help capture multiple movements in one metric. Whether you think of the financial ratios that traditional business managers track or the DAU/MAU that app developers relentlessly track today, ratios tend to be important as they explain concentration rather than quantity.

Pipe Metrics

This discussion of metrics is especially important in the world of platforms and networked businesses. Platform businesses are a lot more complicated than traditional pipe businesses. Pipes optimize unidirectional flow of value. Hence, metaphorically, releasing bottlenecks at any point should help with the flow. The Core Metrics for pipes, naturally, then, measure smoothness of flow and/or removal of bottlenecks. Inventory turnover is one such metric to check how often the flow of goods/services moves through the pipe. All forms of Output/Input ratios for intermediary teams on the Pipe are, again, checks to understand rate of flow and identify creation of bottlenecks.

Platform Metrics

But this tends to be much more complex in the case of platforms where flows are multi-directional. Moreover, they are interdependent because of network effects. E.g. optimizing activity on the producer side may have unexpected implications on the consumer side. On a dating network, allowing over-access to men may be unattractive for women. Hence, even if you have two different teams optimizing for two different metrics on the producer and consumer side, the activities of one team may adversely impact the pursuits of the other team.

How then does one go about deciding on platform metrics?

The Business Of Enabling Interactions

This takes us back to a theme I repeatedly talk about. If I had to condense the essence of Platform Thinking in one line, here’s what it would be:

We are in the business of enabling interactions.

This is much like the Commander’s Intent I mentioned earlier and has important implications. Irrespective of how big your firm is, how complex the operations are, the goal should always be to optimize the core interaction.

1. Identify the Core Interaction that your platform enables

2. Remove all bottlenecks in the Core Interaction to ensure that it gets completed across Creation, Curation and Consumption

3. Ensure that the Core Interaction is repeatable and repeats often

From a metrics perspective, this essentially means that the Core Metric that rules everything should measure interactions.

If you’re running a platform business, you need to start measuring and optimizing your core interaction. 

Metrics Design Around The Core Interaction

So we get the fact that we need to measure interactions. However, we still need a measure, a number that shows the Core Interaction is working well. As with all metric design, it is still possible to choose the wrong metric despite understanding the importance of measuring the Core Interaction.

To design the right metric, let’s revisit what the Core Interaction on a platform actually entails.

From earlier essays in this series, we note the following:

1. A platform enables exchange of information, goods/services, money, attention etc. between the producer and consumer. For a visual guide to how this works, check the article here.

2. The exchange of information always occurs on the platform. The other exchanges may or may not occur on it.The exchange of information enables every other exchange to take place. To understand the mechanics of this, refer this article.

3. The exchange of information is the key source of value creation across all platforms and can be visualized as the Core Interaction of the platform. To understand the structure of the Core Interaction in detail, check the article here.

4. The Core Interaction has three parts: Creation, Curation and Consumption of the Core Value Unit

Let’s now look at the different types of platforms and tease out relevant key metrics.

Transaction Capture

Some platforms capture the transaction between producers and consumers. These platforms typically track actual transactions. Platforms like the Amazon marketplace may measure gross value of transactions. Those like Fiverr (which have fixed value per transaction) may simply measure number of transactions. Airbnb tracks number of nights booked. This is a better indicator of value creation than simply tracking number of transactions. At the same time, it doesn’t care about value of transactions (spare mattress being booked vs. castle) as the goal is simply more value created irrespective of type of customer.

Transaction Tracking

Some platforms can track the exchange of goods and services in addition to capturing the exchange of money. ODesk, for example, can track number of hours of work delivered by the freelancer (producer), a key measure of value creation. Clarity.fm can track duration of the consulting call between an expert and the information seeker.

Market Access

Some platforms are unable to capture the transaction, the exchange of money. They create value by allowing producers access to consumers. In these cases, one of the common metrics tracked is the platform’s ability to generate leads. OpenTable specifically tracks reservations. These are not the actual transactions at the dinner table, but serve as a proxy for the value created. Some platforms may track overall/relevant market access. Dating and matrimonial sites often talk about number of women registered as that determines the value that a user can expect to get.


One of the key properties of platforms is the fact that external producers can add value. Whether it is new apps on an app store, new videos on YouTube or new pictures on Flickr. In these cases, one is tempted to solely track these co-created Value Units. However, Creation forms only one-third of the Core Interaction. The proof of the pudding, in such cases, lies in repeat Consumption. Some platforms may track the total consumption, some may track the percentage of Value Units that cross a minimum threshold of Consumption. I tend to favor the latter as measuring and increasing the percentage of units that get minimum consumption ensures that the platform focuses on getting more producers who create relevant units that will be consumed. It also ensures that, over time, the feedback loops (in the forms of notifications to producers) will encourage creation of the kinds of units that get greater consumption.

Quality as Value

Some platforms may create value largely by signaling quality. Reddit is one such example where Curation is more important than Creation or Consumption. Such platforms may track reputation of users and create feedback loops that encourage users to participate often, gain karma and use that to participate further in the curation process.

Market Attention

Platforms where the Core Value Units are content e.g. YouTube, Medium, Quora etc., the engagement of Consumer Attention serves as a key metric. Measuring number of videos or articles uploaded or number of videos viewed or articles read is often not enough. These give indications of Creation and Consumption but not of Curation. We need some indicator of quality as well. This is why many such platforms track the percentage of content which gets a minimum engagement. Medium tracks views and reads separately indicating that it requires a minimum commitment from the Consumer to determine quality of the content.

The Easy Metric Fallacy

While working with companies on this, I’ve often noted the following:

1. Creation is the most common metric tracked. Number of apps, number of videos, number of sellers etc. This is misleading.

2. In the case of Market Attention category platforms, Consumption is the most common metric tracked. This is an improvement but still not a measure of quality.

3. Curation is rarely tracked and is often the most important metric that determines the health of the platform.

4. The measure of transactions that should be tracked varies with type of platform. In some cases, number of transactions may suffice, in other cases, volume of transactions may matter.

5. The metric that best explains interactions will change over the life cycle of the platform and it’s critical to identify points at which these transitions occur. Companies often make the mistake of sticking on with an older metric when their business has scaled. Identifying and vetting the Core Metric at every point is very important.

Counter Metrics

While measuring the platform’s ability to create interactions is important, it is equally important to measure its failure to close interactions. I will explore this further in a subsequent post.

The Way Forward

The discussion on metrics is deep and cannot be done justice in one post. I’ll cover this more as we move further in the series. The key point, though, remains:

On a platform, the Core Metric that rules them all must measure and optimize the Core Interaction.

Tweetable Takeaways

For platforms, the Core Metric to be tracked must measure and optimize the Core Interaction.Tweet

The goal of a platform is to repeat and optimize the Core Interaction that creates value. Tweet

This article was originally published on Sangeet Paul Choudary’s personal blog Platform Thinking – A blog about building early stage ventures from an idea to a business, and mitigating execution risk.

The Three Design Elements for Designing Platforms

What does the traditional world of manufacturing have in common with the way networked platforms work? How can a basic understanding of factory design help us change the way we think about designing internet platforms, marketplaces and social networks?

I’ve written previously about the distinction between pipes and platforms. If you haven’t already read it, you must definitely check it out. It lays out many of the basic principles that underlie the strategies I discuss on this blog.

The fundamental shift, I believe, the world has seen, is the move from linearity to networks. Putting 3D printers and other recent maker movement trends aside, factory-based manufacturing has traditionally remained the same. And that’s what I refer to as Pipes, as captured by the graphic below:

Pipes are characterized by the firm as the producer and a linear flow of value.

In contrast, Platform Thinking allows for users as co-producers. Value doesn’t flow linearly from a firm to the consumer. Producers and consumers are connected with each other over a network. The platform’s role, unlike a Pipe’s, isn’t production. The platform connects producers and consumers over a network and provides them the tools to interact with each other. It then uses data to match them with each other.

Business Design for Fifth Grades

Let’s look at business design at a very high level. At a fairly abstract, stratospheric level, the goal of business is the creation of value and the capture of some part of it to generate a profit.

If we get back to Pipe Thinking, and take the example of manufacturing, value is created in a factory or on an assembly-line.

The factory’s goal is value creation. 

The factory does this by setting up a set of value creating actions that add value on to the product.

There is an end-to-end process that is responsible for value creation.

But here’s the most important, yet obvious, bit. There is a unit of production and consumption which moves through these processes AND gathers the value that is added to it by the factory. Finally, in the hands of the consumer, this unit delivers value to the consumer.

We call it the product, the object that is manufactured in a plant. It’s the car running through Toyota’s assembly line or toothpaste tube getting filled out at Colgate-Palmolive.

This object is the basic unit of production and consumption in the industrial world. 

So if we think of it, the design of a manufacturing plant goes about in the following manner:

  1. Start with the object you’re creating; the product.
  2. Lay out the steps required to create it (value-creating actions)
  3. Design the process that encapsulates this flow of action
  4. Design the factory (and organization) that can execute this process.

The factory design enables the process.

The process design enables value creation.

But all of this starts by first looking at the unit that is being created, determining what value needs to be created on it and designing the entire business in a way to facilitate that value creation.

It doesn’t work the other way round. You don’t start with building a factory and an organization and then deciding how you structure the process. Any change in the organization or factory infrastructure is started by a change in the process which is started by a change in the need for value creation (often because of customer feedback owing to which you tweak the product).


So all this sounds great, you say! You just told us a bunch of obvious things using some fancy words. Where are we going with this?

I believe the fundamentals of business never change whether you’re in an agrarian economy, an industrial economy or an information economy. Let’s use what we already know from the above and figure how this applies to platforms.

Business design, as we just noted, doesn’t start with the factory, it starts with the unit that is produced. Unfortunately, in the design of a lot of networked platforms, we see the design process start from the factory i.e. the website or the app. That, instead, should be the last step in the design phase.

Let’s take a step back and get back to the Pipe:

Now, let’s watch it change when we talk about Platforms:

There are two key changes that happen as we move from pipes to platforms.

  1. The value creation shifts from inside the Pipe to outside the Platform.
  2. The producer role shifts from inside the Pipe to outside the Platform


These are the two fundamental shifts captured in all the talk about Open Innovation. And these are the two fundamental shifts we need to be aware of while designing platforms.

(Note: The platform can be the producer in many cases but most platforms will allow for external production in some way or the other.)

So let’s go about the job of designing platforms.



As in the case of Pipes, let’s start with the unit that is produced or consumed. This is the most interesting part. When we think of platforms or any form of internet businesses, we rarely think of what is being produced or consumed, we think of it in terms of a website or an app, or some other physical/visual manifestation. In actuality, since we’re talking about information businesses, the unit being produced and/or consumed should be content/information.

Seed and Parties, no Platform

What is YouTube? A website? An app? A platform for the hosting (production) and viewing (consumption) of videos?

Kickstarter? A platform for the hosting (production) and backing (consumption) of projects!

Twitter? A platform for the creation (production) and consumption of tweets!

Etsy? A platform for selling (production) and buying (consumption) actual physical products leveraging information about them (listings)!

Uber? A platform for booking a car leveraging information (car availability) to match producers (taxi drivers) with consumers (taxi seekers)!

Irrespective of the actual exchange being physical or digital, the unit that powers the matchmaking of producer with consumers (on the platform) is an information unit.

Start with the unit! If you’re designing the Twitter for X, look at what the Tweet for X looks like.

If there is one thing that’s central to Platform Thinking, it’s this. Large platforms look clunky, you don’t know where to start. Start with the unit that is being produced or consumed – I like to call this the Seed – build out from there. More on this in one of my subsequent posts.

Start with the Seed!


Great! So we started with the unit. What’s next?

In the case of Pipes, one moves from the unit to the process that adds value to the unit all through.

There’s one interesting difference between Pipes and Platforms though. Consumers don’t typically add value in real-time to this unit. They just consume. On platforms, consumers may add value as well. A creator may take a picture on Flickr but consumers may tag it. A creator may upload a video on Youtube but consumer votes determine how often it gets consumed. There are various ways in which consumers add value.

So what’s the counterpart of the process in Pipes? A set of actions involved in the creation and consumption of value?

I like to think of this as the Interaction. Every Platform has at least one Interaction.

Seed, Parties, Interaction

Creator uploads video, Consumer watches it, votes upon it. This is the primary interaction of YouTube.

Creator starts a project, Consumer consumes it, backs it etc. The primary interaction on Kickstarter.

The interaction is essentially a set of actions required for the creation and consumption of Seeds on the Platform. (This is an incomplete view but I’ll get further into it in a subsequent post, to avoid detracting from the main point.)

Note that a platform may have multiple seeds and multiple interactions but there will specifically be one that is core to the value proposition of the platform. YouTube is not a place where you go to create and consume comments, it’s a place to create and consume videos. In most cases, the primary seed and interaction are fairly obvious. In subsequent posts, we’ll look at a few cases where these are not.


Finally, we come to the platform. Once you know the seed and design the interaction as a set of actions, platform design is a lot simpler.

You’re just creating a network and an infrastructure that enables this interaction. 

Seed, Parties, Interaction, Platform

Well, there’s a lot more depth there but for the purposes of this article (remember, we addressed this to fifth graders somewhere up there), the key point here is that platform design should start with the seed, flesh out the interaction and then design the platform as a consequence. Not the other way round.

Even with platform design, one must distinguish between the system and the interfaces. YouTube is a complex system but has many different interfaces/functionalities for creators, viewers, brands, advertisers, media houses etc. on different channels like web and mobile.

The design of the interfaces should be true to the design of the system. And that is achieved when one starts by focusing on the seed and the interactions it enables.

I’m going to be digging into this in detail over the next 2-3 months to lay out a detailed framework for designing and running networked platforms. I’d love to hear your thoughts first up, whether you agree or disagree.


Let’s quickly recap the three key principles of platform design:

1) Platform design should start with defining the value that is created or consumed, the Seed.

2) The Seed should lead to the actions that enable the creation and consumption of that value.

3) Only in the last step should one go about designing the system and interfaces that enable those actions.

There is a fourth key element missing here, the role of data. I will be covering that in future posts. For this post, in particular, I wanted to focus on the contrast between pipes and platforms. The role that data plays on a platform is very unique to a networked world.

It’s been a late start to the year but I’ve spent the last three weeks bringing a lot of my thinking on platforms together in an effort to start creating a structure around it. I’m getting that stared with this post.

Everything old is new again! Hopefully, the magic lies in using the old to interpret the new!

This article was first featured on Sangeet’s blog, Platform Thinking (http://platformed.info). Platform Thinking has been ranked among the top blogs for startups, globally, by the Harvard Business School Centre for Entrepreneurship

Why #Hashtags are the future of monetizing social media

You can’t invite people to a party and try to sell them stuff. Pretty much every starry-eyed startup that went after eyeballs gets it by now. Over the last seven years the web has moved away from a consumption medium (think NY times) to a creation-consumption medium (think Twitter, Facebook). But we’ve been very tardy in reshaping business models for this new model of the web. Interestingly, the solution to this monetization problem may lie with a small insignificant key on your keyboard. Read on.

Why are we failing at monetization today?

Traditional online media worked on a Pipe model, targeted only consumers and got away with monetizing eyeballs. Social media works on the Platform model, supports both creators and consumers, and has tellingly failed with trying the same old monetization strategies. 

Media Monetization 101

The monetization of any form of media is driven by mining of context and using that (or some other consumer action) as a proxy for intent. Advertisers then pay to have their ads matched with the right intent. Here are a few examples:

Keywords on a page: Context E.g. AdSense

Search query: Intent E.g. AdWords

Location: Context E.g. FourSquare

Monetization works by harvesting user intent and serving messages/information relevant to that intent. The better you are at harvesting intent, the more effective your monetization is going to be. 

Why is this model breaking down?

Mining context and intent goes for a toss in the world of social platforms. Users are the new content creators and content isn’t necessarily structured. With the older media model, the content creators (typically the media houses) were creating content to cater to search engines. The content was designed for text mining algorithms right at the point of production. With social media, the creators of content (all of us) don’t care about structure. In fact, online conversations are getting more unstructured by the day. Consequently, mining these conversations for context and intent is a crazy task, riddled with false positives. And false positives always lead to spam.

This is why the Hashtag is so important to the future of the web. 

Enter the Hashtag

Engineers would like to be known for the tech innovations that they engineered but Chris Messina will probably go down in history as the guy whose random blog post helped structure a new era of media. In a 2007 post, Messina suggested the use of Hashtags for the first time for Twitter.

This week, Facebook rolled out Hashtags.

It’s interesting to revisit that original blog post and figure out how Platform Thinking is so rare (and important) and how most of us just prefer to think in Pipes. 

Hashtags and Platform Thinking

If you think of media as a Pipe where content creators create stuff and push it out for us to consume, the content creator takes great pains to structure the content. Every piece of content will be carefully drafted in a category, will be peppered with keywords for search engines to gobble and will be structured so that the context can be easily mined.

If you look at the proposals from Stephanie and Brian, they advocate the use of pre-defined groups to regulate conversations around certain contexts. This is a typical Pipe Thinking model. Provide the constraints and force the creators to work within those constraints. It works very well when media is created within the boundaries of a firm.

When media is created by users, as it is today, one cannot afford to think in terms of constraints anymore. This is where Messina’s advocacy of the Hashtag is so brilliant. If you’re thinking in terms of Platforms, you’d want to make the creation process as easy as possible for users, yet ensure that they leave you with enough hints around intent and context. This is what Flickr did when it allowed users to tag pictures instead of forcing them to fit pictures into pre-defined categories. This is what Messina advocates in this post when he argues against users having to operate within groups and allows users to define context and intent on the fly.

Through Hashtags!

Top-down classification and forcing creators to fit within categories or groups is a hangover from Pipe Thinking; an editorial view of the web. A social view of the web requires a more bottom-up approach.

If you think of the social web as a flow of information, pre-defined categories and groups limit the channels in which information can flow. Hashtags, instead, allow creation of channels on the fly to suit the needs of the information creator. 

If you’re still thinking Semantic search alone, you’re in the wrong game

When the world first saw an explosion of user-generated content, people realized that Google’s keyword and link-driven approach to ranking information wasn’t going to work forever. Semantic search was hailed as the next savior.

I have nothing against semantic search. I just believe algorithms are still fairly limited in mining human intent from unstructured conversations. And the web is gradually, but definitively, moving towards unstructured conversations.

The solution to mining unstructured information doesn’t lie in creation of more sophisticated algorithms alone. It lies in, first, solving the problem at the point of production and allowing the new creators to easily append some structure to the information.

That is exactly what the Hashtag does!

If you’re building a platform that enables and promotes unstructured conversations, and you want to go beyond just being a communication tool, to creating a corpus of sticky content, hashtags can help transform unstructured conversations to structure, right at the source.

Tweetable Takeaways

Hashtags are the new keywords, and the key to monetizing social media.

Tags are the new categories, hashtags are the new keywords!

This article was first featured on Sangeet’s blog, Platform Thinking (http://platformed.info). Platform Thinking has been ranked among the top blogs for startups, globally, by the Harvard Business School Centre for Entrepreneurship

Why Business Models Fail: Pipes Vs. Platforms

Why do most social networks never take off?

Why are marketplaces such difficult businesses?

Why do startups with the best technology fail so often?

There are two broad business models: pipes and platforms. You could be running your startup the wrong way if you’re building a platform, but using pipe strategies.

More on that soon, but first a few definitions.

Pipes have been around us for the last 400 years. They’ve been the dominant model of business. Firms create stuff, push them out and sell them to customers. Value is produced upstream and consumed downstream. There is a linear flow, much like water flowing through a pipe.

We see pipes everywhere. Every consumer good that we use essentially comes to us via a pipe. All of manufacturing runs on a pipe model.  Television and Radio are pipes spewing out content at us. Our education system is a pipe where teachers push out their ‘knowledge’ to children. Prior to the internet, much of the services industry ran on the pipe model as well.

This model was brought over to the internet as well. Blogs run on a pipe model. An ecommerce store like Zappos works as a pipe as well. Single-user SAAS runs on pipe model where the software is created by the business and delivered on a pay-as-you-use model to the consumer.

Had the internet not come up, we would never have seen the emergence of platform business models. Unlike pipes, platforms do not just create and push stuff out. They allow users to create and consume value. At the technology layer, external developers can extend platform functionality using APIs. At the business layer, users (producers) can create value on the platform for other users (consumers) to consume. This is a massive shift from any form of business we have ever known in our industrial hangover.

TV Channels work on a Pipe model but YouTube works on a Platform model. Encyclopaedia Britannica worked on a Pipe model but Wikipedia has flipped it and built value on a Platform model. Our classrooms still work on a Pipe model but Udemy and Skillshare are turning on the Platform model for education.

So why is the distinction important?

Platforms are a fundamentally different business model. If you go about building a platform the way you would build a pipe, you are probably setting yourself up for failure.

We’ve been building pipes for the last few centuries and we often tend to bring over that execution model to building platforms. The media industry is struggling to come to terms with the fact that the model has shifted. Traditional retail, a pipe, is being disrupted by the rise of marketplaces and in-store technology, which work on the platform model. 

So how do you avoid this as an entrepreneur?

Here’s a quick summary of the ways that these two models of building businesses are different from each other.

User acquisition is fairly straightforward for pipes. You get users in and convert them to transact. Much like driving footfalls into a retail store and converting them, online stores also focus on getting users in and converting them.

Many platforms launch and follow pipe-tactics like the above. Getting users in, and trying to convert them to certain actions. However, platforms often have no value when the first few users come in. They suffer from a chicken and egg problem, which I talk extensively about on this blog. Users (as producers) typically produce value for other users (consumers). Producers upload photos on Flickr and product listings on eBay, which consumers consume. Hence, without producers there is no value for consumers and without consumers, there is no value for producers.

Platforms have two key challenges:

1. Solving the chicken and egg problem to get both producers and consumers on board

2. Ensuring that producers produce, and create value

Without solving for these two challenges, driving site traffic or app downloads will not help with user acquisition.

Startups often fail when they are actually building platforms but use Pipe Thinking for user acquisition.

Pipe Thinking: Optimize conversion funnels to grow.

Platform Thinking: Build network effects before you optimize conversions. 

Creating a pipe is very different from creating a platform.

Creating a pipe requires us to build with the consumer in mind. An online travel agent like Kayak.com is a pipe that allows users to consume air lie tickets. All features are built with a view to enable consumers to find and consume airline tickets.

In contrast, a platform requires us to build with both producers and consumers in mind. Building YouTube, Dribbble or AirBnB requires us to build tools for producers (e.g. video hosting on YouTube) as well as for consumers (e.g. video viewing, voting etc.). Keeping two separate lenses helps us build out the right features.

The use cases for pipes are usually well established. The use cases for platforms, sometimes, emerge through usage. E.g. Twitter developed many use cases over time. It started off as something which allowed you to express yourself within the constraints of 140 characters (hardly useful?), moved to a platform for sharing and consuming news and content and ultimately created an entirely new model for consuming trending topics. Users often take platforms in surprisingly new directions. There’s only so much that customer development helps your with. 

Pipe Thinking: Our users interact with software we create. Our product is valuable of itself.

Platform Thinking: Our users interact with each other, using software we create. Our product has no value unless users use it.

Monetization for a pipe, again, is straightforward. You calculate all the costs of running a unit through a pipe all the way to the end consumer and you ensure that Price = Cost + Desired Margin. This is an over-simplification of the intricate art of pricing, but it captures the fact that the customer is typically the one consuming value created by the business.

On a platform business, monetization isn’t quite as straightforward. When producers and consumers transact (e.g. AirBnB, SitterCity, Etsy), one or both sides pays the platform a transaction cut. When producers create content to engage consumers  (YouTube), the platform may monetize consumer attention (through advertising). In some cases, platforms may license API usage.

Platform economics isn’t quite as straightforward either. At least one side is usually subsidized to participate on the platform. Producers may even be incentivized to participate. For pipes, a simple formula helps understand monetization:

Customer Acquisition Cost (CAC) < Life TIme Value (LTV)

This formula works extremely well for ecommerce shops or subscription plays. On platforms, more of a systems view is needed to balance out subsidies and prices, and determine the traction needed on either side for the business model to work. 

Pipe Thinking: We charge consumers for value we create.

Platform Thinking: We’ve got to figure who creates value and who we charge for that. 

If the internet hadn’t happened, we would still be in a world dominated by pipes. The internet, being a participatory network, is a platform itself and allows any business, building on top of it, to leverage these platform properties.

Every business on the internet has some Platform properties.

I did mention earlier that blogs, ecommerce stores and single-user SAAS work on pipe models. However, by virtue of the fact that they are internet-enabled, even they have elements that make them platform-like.  Blogs allow comments and discussions. The main interaction involves the blogger pushing content to the reader, but secondary interactions (like comments) lend a blog some of the characteristics of platforms. Readers co-create value.

Ecommerce sites have reviews created by users, again an ‘intelligent’ platform model.


In the future, every company will be a tech company. We already see this change around us as companies move to restructure their business models in a way that uses data to create value.

We are moving from linear to networked business models, from dumb pipes to intelligent platforms. All businesses will need to move to this new model at some point, or risk being disrupted by platforms that do.

Note: I intend to use some/all of the ideas here as part of an introductory chapter to the book I’m working on and would love to have your feedback and comments.

This article was first featured on Sangeet’s blog, Platform Thinking (http://platformed.info). Platform Thinking has been ranked among the top blogs for startups, globally, by the Harvard Business School Centre for Entrepreneurship