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Building a Product from an Idea : The Lean Startup Way

We all have ideas. We all have felt the need of having something more to an existing solution or an alternate way of doing something which we often do. Startups and products are born out of this. The good part or maybe the sad part is that there are thousands of such ideas and products that spring up every day and it becomes increasingly difficult for these products to succeed in the market.

Of course having a great founding team with the right mix of technical, marketing and design skill set would go a long way in helping the product to wade through the clutter and be noticed but it still doesn’t guarantee the success of the product. It’s often easy for a founding team to lose direction early on in terms of what’s the right product that people are willing to use, or better, willing to pay for. There is an even worse scenario which I have often seen among founders when they try and convince themselves that the features and the products that they are building is the right solution based on intuition and practically zero metrics to back their claim. That’s suicidal.

It’s imperative for a startup to follow the Lean methodology’s Build-Measure-Learn loop. But before you enter the build phase, your first step should always be to do Research and understand the market you are going to target.

Research

First things first. One wouldn’t want to waste a significant amount of resource on an idea which has relatively zero market potential. So always begin by understanding the true market potential of your idea. You can start by asking yourself a set of questions initially:

  • Will my idea address a genuine pain point, if yes, what is it?
  • Who will be my potential customers and where can I find them?
  • Who are my competitions?
  • How different is my idea from what my competitions have?
  • Will I pay for a product like this? Would anyone pay for the product I intend to develop?
  • Are there are regulatory constraints?
  • What would my rough budget be and what would be the resources required for a basic product?

I’m sure you won’t get comprehensive answers to a lot of these questions but then the point of asking yourself all these questions initially is it helps you understand the market and the opportunity you are going after and sets the context right. Googling will give you sufficient inputs which will enable you to take a call on if it’s worth pursuing further. If you want to understand things a little deeper, do a survey or shortlist a set of people who will in the future be interested in the product and try and get their opinion on if they would actually pay for such a product (To be honest, at this stage it’s difficult to really understand if the users will pay for it at this stage, but do get opinion from people nevertheless.)

In already established markets there would be a fair number of research reports which you can leverage to understand in detail the market you are going after. An easier way would be to use Google Keyword Tool or Market Samurai to understand the demand for your idea. It’s always easier for a startup to build something in a space where there is an existing demand and is not fully saturated than to carve out an entirely new market. I am not saying that’s not possible but with limited resource at your disposal in your early days, trying to create a new market might not be the best option.

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Just did a search on Google KWT for the term Video Games and see the results. It has a fairly good number of searches worldwide. The KWT also gives you a set of related keywords which might help you even segment the entire market.

It’s important at this stage to try and segment the market you are going after. Having a generic solution won’t help at an early stage. Segmenting the market you are going after gives you a much better chance of validating your idea. The Idea can be expanded on to other segments as and when you grow and become mature. Also, make a shortlist of your competition and their offerings. This would give you a fair bit of understanding on the current market demand for various features and would allow you to understand how your product is different from your competition.

All of this helps you in getting a Problem/ Solution fit. It’s good to get a feel of the market even before you start prototyping and building a product. Like Eric Ries mentions in his Lean Startup methodology, it might be a good idea to just create a landing page and put up a “Register to get an Invite Option” and check how many click through to register and actually register. This is a trend followed by a lot of online startups and especially Apps. One of the most important tactics for an app’s pre-launch marketing strategy is to build up a landing page with an option for the users to subscribe to be notified when the app goes live. This would also enable you to get a feel of the solution you are suggesting for a problem. Again, the problem here is that often people without proper segmentation and without trying to get their target users to come on to the page would conclude that the idea has no demand in the market. This is why it’s important to segment your market and know your core group of audience. Hunt for them on forums, groups or anywhere they are available if you want to make people discover your webpage for free or else use Google Ad words or any of the Ad solutions to target your core group of audience. Understand if there is a demand for your solution.

The next stage in the product lifecycle is to develop an MVP (Minimum Viable Product) that would actually enable you to reach out to customers, engage with them and understand better the demand for the product.

Minimum Viable Product

The concept of a Minimum Viable Product was introduced by Eric Ries, the man behind the Lean Startup movement. In his own words :

“The idea of minimum viable product is useful because you can basically say: our vision is to build a product that solves this core problem for customers and we think that for the people who are early adopters for this kind of solution, they will be the most forgiving. And they will fill in their minds the features that aren’t quite there if we give them the core, tent-pole features that point the direction of where we’re trying to go.

So, the minimum viable product is that product which has just those features (and no more) that allows you to ship a product that resonates with early adopters; some of whom will pay you money or give you feedback.”

According to me, it’s always a difficult task clearly understanding what exactly is “minimum viable” as far as your product/ idea is concerned. It would be different for each idea and category. Understand that if the product is as is any other competitor and there is no differentiation then the product you are shipping is in no way a “minimum viable” product. Focus on your core value proposition and how your product is different from the rest. If your differentiation is purely the experience that you give your users then ensure that when you ship out your MVP, you enable your customers to have that experience. Minimum Viable Product does not mean that you roll out a crappy product. In fact that would be suicidal as with Social Media these days it does not take a lot of time to completely kill your product or brand with a negative word of mouth. Of course the MVP can have bugs and there would be hundreds of features that could be added later. The early adopters that you manage to get are always going to give you a leeway and that’s because they genuinely need and value the core experience or the core feature your product provides. So ensure that the core proposition is in its entirety is reflected in the MVP.

Steve Blank in his book outlines the four stages to the Customer Development process with the following success end goals:

  1. Customer Discovery – Achieve Problem/Solution Fit
  2. Customer Validation – Achieve Product/Market Fit
  3. Customer Creation – Drive Demand
  4. Company Building – Scale the Company

This is a great framework for someone operating with the Lean Startup methodology. The initial research phase and the development of the MVP falls under the first bucket where in one achieves the Problem/ Solution fit. This does involve effort however you do significantly cut down on the unnecessary resource you would have spent otherwise on trying to create something which has no demand in the market only to realize that after you have pumped in all of your money and effort.

The Second phase of Customer Validation is where one achieves Product Market fit. This is the stage where in you actually try and sell your MVP and or make your customers to use it to tweak and bridge the gap between the Product and the Market.

Achieving Product/ Market Fit:

How exactly does one determine whether you have achieved product/ market fit? Different people will give you different definitions for Product/ market fit

“Product/market fit means being in a good market with a product that can satisfy that market,” according to Marc Andreessen

Andrew Chen

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Sean Ellis has created another metric for determining Product/ Market fit. He suggests asking existing users of a product how they would feel if they could no longer use the product. According to him, achieving product/market fit requires at least 40% of users saying they would be “very disappointed” without your product.

For me the whole idea of getting a Product Market fit is nothing but getting to a point with your product when a particular segment of the market which you have identified as your initial target segment embraces your product so that you can grow your company/ product scalably. Achieving Product/ Market fit as early as possible is crucial for any product as it allows you to then focus on company growth and not on iterating and pivoting the product. Spending significant money and effort on growth and marketing at this stage before product/ market fit is not an advisable strategy.

It’s important for startups to constantly measure during this stage and understand the behavior of their users. One needs to craft and test several value propositions, user flows, conversions, user interactions to effectively achieve a product/ market fit.

The priority here is to focus on the macro metrics, the right ones. Understand that optimization of micro-metrics comes at a later stage once we achieve product/ market fit. There are various macro metrics that matter; you may refer to Dave McClure’s AARRR model.

  • Acquisition – How many people landed on your website coming from a marketing campaign or through viral channels that you are tracking and then you acquire the user.
  • Activation – The user uses your product and completes a core action on the platform.
  • Retention – What is your churn? How many of the users you have in your user base are active? How many stopped being active and why?
  • Referral -How many of the users that are using your product are willing to refer to others?
  • Revenue -How many users are willing to pay you of the ones that are using the service?

During this stage out of the 5 macro metrics Dave suggests, there are only two that needs to be tracked comprehensively. They are: Activation and Retention.  Of course Acquisition is important as well because for measuring and optimizing activation and retention there needs to be sufficient users. But then the idea here is to not spend and focus on acquisition but to focus on Activation and retention in a core segment by minimizing your acquisition cost and optimizing it. Try and figure out the best and most effective channels to let your target audience discover your product and allocate a budget accordingly. Social Media these days provide a great channel for enabling your target users to discover your product, so utilize it to the maximum effect possible.

Try and map out the important actions on the platform that corresponds to the macro metrics : Activation and Retention.

Activation:

Activation rate, in a nutshell, is the percentage of users who stick with your app long enough to experience the value it offers.

For a project management application, the point of first value might be when an account achieves these things:

  1. Account created
  2. Invited 2+ team members
  3. Created project
  4. Uploaded 2+ files
  5. Created 3+ calendar events
  6. Created 1+ tasks
  7. Completed 1+ tasks

And these actions can be taken in any order – a non-linear experience – so measuring them as a funnel is a mistake.

In this case, you should be measuring Activation as a percentage – not a linear funnel. You need to measure, how many of these steps have been completed (regardless of the order). If a new user or account needs to complete 5 steps to become fully activated and has only completed 2 of those steps – they are 20% Activated. If it completes 4 of 5 steps – they are 80% Activated.

This view of number of criteria for activation fulfilled by the end user gives a clear picture of how well New accounts are able to complete the list of activities you have defined as activation criteria.

Retention:

Retention is nothing but getting the users back on the site regardless of the engagement they have on the site. You can define retention as mentioned or tie it to certain key actions on the platform. In general for a consumer product which is both creation and consumption based, it might be good to just consider the activity of the user coming back to the site as retention. For eg: Facebook or twitter might consider retention as the case of users just logging back in to the site. Engagement, however, is a different concept where a platform like Facebook or twitter would want the user to perform any major/ core user action on the platform like sharing content, liking or updating status or tweeting etc.

A good retention rate would be different for different consumer products/ apps depending on the nature. It would also depend on the customer usage cycle which tends to be shorter for a social gaming app while it tends to be a little longer for a platform like Snap, TikTok etc. So based on your product’s customer usage cycle and general trend in your niche/category decide on your target retention number/ time frame ( 1 Day, 7 days or 28 days) to achieve.

Measure and iterate on both these macro-metric to get to Product/ Market fit. Use Funnel and Cohort analyses to better understand the user flows and the churn at each stage so that you can identify and improve/ rectify the non-required or wrongly crafted features and flows. Breakdown each user flow to understand in depth any issue there is. The idea here is not optimization for efficiency but the idea here is to validate your MVP. People often relate A/B testing with changing colors of the Sign Up button, yes, that might be a good way to improve on the conversions in some cases, but getting to product Market fit is all about validating your MVP, to get people to buy into the features or the experience it provides and then make them repeatedly come back to the platform. There would various broad scenarios:

Have high arrivals but low Conversions: Tweak your messaging and positioning to check if that helps in conversion. Also, ensure that the incoming traffic is composed of people you assume to be your target audience.

Have low arrivals but high conversions: Work on the channels to bring in more targeted traffic. Groups, Forums, Meetups etc of target community would be a great start. Try and improve on the keywords you chose for your PPC campaigns.

Have high conversions but low activation: Ensure people understand the interactions on the platform. Is it too difficult to understand or complete the core action on the platform? Would an interactive guide in the beginning help the user understand user actions on the platform?

Have low conversions but high activation: Are you bringing in the right traffic on the platform? Is the messaging right on the front page? Is the signup process easy enough or have you made it too difficult? Is there a clear call to action on your landing page?

Have low activation but high retention: A good sign to have a high retention number. However lower activation would mean either people are not interested in the core activity you have considered or people are not given an easy enough option to complete the core activity on the platform.

Have high activation but low retention: Low retention could be due to lack of interest in the product and it’s core feature. A product which genuinely solves a problem for a sect of people would have high retention numbers. Products which are not a must but is a luxury like Quora would need to constantly remind people and get through the clutter to improve on their retention numbers. Work on either.

The whole cycle would look something like the figure below. Keep measuring all the important metrics, learn and iterate on important features/ flows till you get to product/ Market fit. The earlier, the better.

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Post achieving Product/ Market fit, the company can focus on user growth and leverage their marketing spend to speed up the entire process. Utilize the best and the most effective channels to scale further. You can now utilize Funnel analytics and Cohort analysis to measure each of the important macro-metric defined in the framework above.

AI Products

SaaS products built without data and AI offer generalized solutions to their customers. We are in the business of creating AI based business applications and one common theme I have seen across the board is for people to have this notion that AI will solve all their problems instantly. The reality is AI businesses more closely resemble a services business or consultancies because they provide solutions that become tailored to that customer’s specific needs. Like services providers or consultants, an AI product improves as it knows a customer better.

AI businesses are not scalable right out of the gate: AI models take time and require data to train. Moreover, not all AI businesses will scale. Here are the metrics you can use to tell the difference early on.

Intervention ratio

It is very difficult to build a high-performing MVP version of an AI model without data from customers. In order to demonstrate value right out of the box and be competitive against other vendors, you might automate which processes you can right off the bat using a rules engine, and provide a human operator to perform the rest of the work while simultaneously labeling the collecting data in order to train the AI.

The ratio of human interventions over total automated tasks should be decreasing over time.

ROI Curve

Should increase over time. With AI products once the AI’s performance ramps up, it could very quickly exhaust all low-hanging fruit opportunities. If the AI cannot continue to provide value to the customer, the difference in value from one renewal cycle to the next may seem stark to the customer, who may decide to not renew.

Rev-up Costs

AI products incur more significant rev-up costs than a typical SaaS product rollout and may have as much impact on margins as customer acquisition costs (CAC). You should carefully track how much time these rollouts and ramp-ups take, and how much it costs for each new customer. If there are true data network effects, these numbers should decrease over time.

Data Moat

  • Accessibility: how easy was it to get?
  • Time: how quickly can the data be amassed and used in the model?
  • Cost: how much money is needed to acquire and/or label this data?
  • Uniqueness: is similar data widely available to others who could then build a model and achieve the same result?
  • Dimensionality: how many different attributes are described in a data set?
  • Breadth: how widely do the values of attributes vary, such that they may account for edge cases and rare exceptions?
  • Perishability: will the data be useful for a long time?

AI models perform better with more data, but that performance may plateau over time. You should take care to track the time and volume of data necessary to achieve an incremental unit of value for your customer, to make sure that the data moat continues to grow. 

The higher upfront work necessary to launch an AI business means that most will look more like services businesses. A small subset of AI startups will resemble SaaS businesses from the beginning, before AI is deployed in the product. In order to collect data for their AI models, some businesses first sell SaaS workflow tools and can even achieve meaningful revenue from that workflow tool alone. By SaaS metrics, that company may be blowing the competition out of the water. Without the reinforcement loop generating a compounding volume of data and an increasingly powerful AI over time, however, that company’s product remains vulnerable to copycats and will eventually be commoditized.

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Customer Engagement – What are the key metrics to track and why?

B2B SaaS is extremely competitive especially for horizontal SaaS products. If you are in the SMB space then that makes it even more challenging for you to survive and then grow. There are a few important metrics the product needs to track assiduously –

  • CAC ( Customer Acquisition Cost)
  • LTV ( Customer Lifetime Value)
  • Payback Period
  • Churn
  • NPS ( Net promoter Score)
  • Sales Velocity

I’m sure most SaaS companies do track these numbers. The key to success is to reduce Churn, CAC and to increase LTV, NPS. One of the key factors that enable a SaaS product to achieve this is customer engagement. But how do you define and measure customer engagement?

 

What is Customer Engagement?

Customer engagement is the interaction/ activity of your customer on the platform. The customer engagement could be a positive or a negative one and it’s equally important to understand the nature of this engagement.

  • A negative engagement increases the risk of Churn, so there are immediate actions that need to be taken to ensure the customer stays.
  • Similarly, a happy and engaged customer provides you with an opportunity to up-sell or cross-sell.

 

So, how do you measure Customer Engagement?

Measuring customer engagement inside the product is the same process as lead scoring at the top of funnel. I had covered lead scoring earlier. Lead scoring is a top of the funnel score that we use to qualify leads based on their activity or interaction with various assets/ touchpoints of the product. You could measure customer engagement with either of the two options:

(1) Use 3rd part software tools that let you define and analyse various events inside the product. Here are a few tools you could consider

(2) Setup your own system where you log various datapoints in your DB and run queries to analyse the same.

In either case, you would have define the important events of engagement and also assign points for these events which would help you calculate the all important engagement score. The events that need to be tracked would be based on the application. For eg:

Helpdesk Software: Add support email, setup forwarding rules, setup DNS, Added Agent

A/B Test SaaS App: Create Test, Start Test, End Test, Share Results

Online Billing APP: Create Invoice, Send Invoice, Receive Payment

Once you have defined the events you can log them and also assign weights to each of these events to calculate your Customer engagement score.

Customer Engagement Score = (wt1*e1) + (wt2 * e2) + … + (wt# + e#)

where wt is the weight assigned and e represents the event being tracked.

Along with the consolidated user engagement score, you could also monitor certain specific or low level metrics that again define user engagement. A few examples are:

  • Daily Active Users ( DAU)
  • Weekly Active Users ( WAU)
  • Monthly Active users ( MAU)
  • DAU/ MAU Ratio
  • User Retention – Day1, Day7, Day30

The core metric that you need to track varies from product to product/ app to app. It’s for you to decide what numbers matter for your product.

 

What next?

Capturing and understanding these metrics defined above is the first step. Setting up steps to improve on these metrics is the next step. This entire process can be automated using a comprehensive automation tool like Marketo, Autopilot, Hubspot Enterprise etc. The right set of messages at the right time goes a long way in optimizing each of the above metrics.

An example:

Pipefy is a great tool for workflow/ process management. It lets you organize all your processes in one place. On signup up with Pipefy, they send you a set of emails to increase engagement.

One of the first emails that they send is a library of pre-existing templates ( most used ones) which would enable the users to get started immediately.

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They track weekly retention and send out a mailer to engage the inactive users. This is the second email they send out to inactive users –

customer-engagement-2

Then they follow it up with this email within a few days:

customer-engagement-3

Another example is how Groove improved customer activation using customer engagement data. Grove is a helpdesk software and one of the first things that a user should do after signing up is to setup a support email. They also measure the avg. time it takes for the user to setup the initial support email and if that doesn’t happen then they send an automated email. Here’s the template they use :

customer-engagement-4

They also track user retention and sends out mailers to inactive users to re-engage them. Here’s the template they use for that.

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These are proactive measures you can take to increase engagement and user engagement. You can personalize these messages/ automated communications that go out further by segmenting the data. An eg: For Horizontal SaaS products you get registrations from a bunch of industry verticals. You can further segment the user data based on industry vertical and send relevant use case for the industry/ use terminologies that the prospect could relate to. At FieldEZ, we segment prospects based on Industry and the use cases differ across Industry. FieldEZ is used as a Lead/ Sales management tool in industries such as BFSI, Pharma while it’s primarily used for Ticket Management in the Consumer Durables or Manufacturing industry segments.

Other than this customer segmentation also helps in:

  • Identifying what features matter most to a particular segment
  • Measure LTV, CAC, Payback Period, Churn, NPS etc for each segment and work on optimizing the same
  • Measure profitability of each segment
  • Test separate user onboarding techniques for each segment – Messaging and Core interactions based on what matters to the segment
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What Are the Ingredients of a great SaaS Business?

SaaS as a business model has existed long enough and there are compelling value propositions for Organizations to adopt this model as can be seen with the large increase in SaaS products over the last few years. This theme is not specific to any vertical but is something that can be seen across the IT landscape, although the speed of adoption across different industries have been different. No wonder, there is more and more money being pumped into these SaaS companies. Coupa, a SaaS company that I track on a daily basis for eg is trading at an all-time high valuation of $5.5 Billion and a Fwd P/E of 446. That’s incredible.

The SaaS business looks attractive but if you were to build one, what are the key components of an effective and valuable SaaS business?

  1. Product should be fundamental to how the business runs: A great SaaS product is something that is fundamental to how the organization functions and is relied on a daily basis. Eg: Coupa for procurement, Concur for expense management or Freshdesk for customer support. There are incremental/ value add systems that you can build, but they are always going to be a hard sell if it’s not business critical. Net result, these incremental products would never turn into a multi-billion dollar businesses.
  2. Easy to understand/ visible value proposition: Cost reduction, increased efficiency, productivity, sales or whatever is the core value proposition of your product is something that is easy to understand and is experienced instantly. Intangible benefits are often a hard-sell.
  3. Moat: How easy or difficult is it for the client to replicate the value proposition you are delivering? If it’s cheaper for them to build it at their end, then you probably don’t have a market. Or if your technology is easy to replicate, then soon enough you are going to have a very commoditized market that in turn drastically reduces your profitability.
  4. Shorter time to Market: You probably start with the SMB segment where the compliance, security and the complex integration requirements are much lesser and with more customers, you end up getting more feedbacks during the initial days. This is critical as early feedback helps you course-correct with minimal investments.
  5. Revenue model: I had previously written about how startups by tweaking their subscription revenue model can have significant cash flows, interest free cash that can drive product development and growth during the early stages. Upfront revenue collection and if it’s done annually is a great way for SaaS companies to work with negative working capital.
  6. Customer Breakeven Period: Can you have a customer breakeven period of less than a year. This includes all cost associated with customer acquisition and management. If you are able to charge the customer upfront annually then, you are nullifying any loss you can have with customer churn before breakeven. The longer you are able to retain your customer, the better the ROI.
  7. Market Share: What’s the relative market share you have in whatever market you have defined for yourself and how big is that market? The lower you are in the list, the higher your CAC gets. Momentum, customer references and WOM helps you drive down CAC as well as increase your top and bottom lines.

If you are planning to build a SaaS product or already have one, ensure you tick most of these criteria listed above. If you aren’t ticking a good number of these criteria, maybe it’s time to rethink your SaaS strategy.

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Pricing for Startups

“You’ve found market price when buyers complain but still pay” – Paul Graham

Pricing is a crucial component of any successful business. Most companies, especially startups tend to under-price fearing losing out on an account resulting in leaving significant money on the table when they finally come away with a customer win. Offering free products, free trials, fremium etc are different strategies startups employ in winning customers and they all work for some and don’t work for the rest. In fact, there is no clear cut, ready-made, cut-out pricing strategies for any company to emulate or follow. Startups work in a highly dynamic environment with constantly changing market dynamics.

An Ideal Pricing is an art that results from a series of experimentation and also in knowing and understanding the true value and positioning of your product. Startups must, hence, use a framework to chalk out the best pricing scenarios and also analyse the feedback/ response from the market to tweak it. The broad framework for startups to work on their pricing should consider the following factors:

Positioning:

Brand positioning is one of the most important factors that influence pricing strategies for any product. In fact, both goes hand in hand. Pricing strategy does reflect on the brand as well. Imagine buying a Ferrari for the price of a Toyota or buying an iPhone for the price of an entry-level Android phone. Same goes for technology products as well – In the FSM (Field Service Management Software) segment, a product like Servicemax might be able to charge a premium while the SMB focussed mHelpdesk might not be able to charge that premium. Same goes for the other software categories as well. In the CRM space, a Salesforce commands a premium which a Zoho or a Nimble will not be able to get.

The message should be clear across all touchpoints – website, collateral, ads, PR, Sales pitch and every other channel the brand gets visibility. The pricing strategy reinforces the brand positioning be it Premium, Mid-market or low cost alternative.

Sales Team Structure:

Pricing defines the structure of the Sales team. Higher price points are very attractive from a revenue perspective but they also require a larger sales cycle, a much more sophisticated sales rep, increased chances of opportunities lost and volatility.

Nimble CRM for eg. has a pricing of $15/user/month and mostly sells into the SMB market. With a deal size of $3k-$5k, typically an inside sales person should be able to close 3-5 accounts a month. This is a much predictable model with a steady revenue coming in every month through these closures. However, for, a higher priced product like a Siebel CRM system, an inside Sales team will not be the right fit. They would be multi-million dollar contracts and would require specialised field sales person who would charge anywhere from $250k or above.

The Market at Large for your product:

It’s important for organizations to scope the market at large for them. The value of any organization is broadly the NPV of its earning (profits) for the next 5 years. Reducing price points might enable you to sell more, increase the closure rate, however in the longer run you need your product to be profitable as well. Any product will have churn, so the net revenue that you make out of a customer should be at bare minimum equal to the cost of acquisition. Also, the market size for your product is the price point multiplied by the number of potential customers. If the no. of potential customers is not a very big number and your product’s price point is relatively low, then the max market you can address might be very less for investors to have any interest in your company.

Pricing Model:

Pricing models can be different for different organizations. One could have a one-time license based pricing structure to subscription based pricing. Even with subscription based pricing – you could have a monthly or quarterly, bi-annual or an annual plan. For subscription based pricing model, I had in my previous post discussed the benefits of having an annual subscription model not just from a cash flow perspective, but also from a revenue predictability perspective and in reducing the overall churn numbers.

Like any function in a startup, pricing is also a constantly evolving function that changes with time. The best way for any startup is to broadly identify each of the parameters discussed above and create a framework which they can rely upon in revisiting pricing few times a year.