Finance For Startups

Accounting is the language of business.

Warren Buffet

One of the biggest challenges of running a business is the need to understand and leverage accounting as a practice to be able to both run and understand your business. As conveyed by the quote above, it’s indeed a language for businesses and a means to convey the health and aspects of the business through it.

Accrual Accounting

While as an individual, we typically deal only in cash. A business can have revenue, bookings and obligations/costs associated with it which can occur over a long period of time (a few years). Which basically means, the typical means of cash-based accounting of things does not quite reflect the story completely and you need to rely on accrual-based accounting.

Accounting like code(programming) has certain standards like GAAP and FRS but plenty of aspects are open to interpretation and this is where the creative aspect comes in. Due to this, companies often try and present the best picture possible without completely letting in on the risks and assumptions made.

Typically, most startups by nature in early days, are losing money or are still trying to figure out a viable business model, thereby simplifying the accounting side of things. For such a business, there are fewer things to worry earlier on, compared to a Fortune 500, for whom the financial statements are no different than quarterly and annual mark-sheets.

The Three Statements

Because, certain aspects(revenue, expenses) of the business can be interpreted differently and thereby reflected differently, accounting is an art, not a scientific process. There are a set of 3 main financial statements reported by a business. Each one of them tries to capture certain aspect of the business performance and state of affairs.

  • Income Statement (aka Profit/Loss Statement): This is your performance over the recent quarter or the year in case of an annual statement.
    • In brief terms, the goal here is to capture, the incremental performance of the business. Think of this as the change in the state of affairs.
    • One analogy with personal financials could be the combination of your salary and credit card statements.
  • Balance Sheet: Basically reflects the current state of affairs for the company, it’s basically the assets and the liabilities of a company.
    • The analogy of personal finance would be wealth. This is basically a reflection of all assets you own and any debts you owe.
    • Your equity is basically the difference between Assets and Debts (Liabilities). A balance sheet tries to balance the equation Assets = Liabilities + Shareholder’s Equity
  • Cashflow Statement: This is further divided into operating, financial and investing parts.
    • Operational reflects cash generated by the business, financial reflects cash from shares issuance or raising of debt.
    • Investing in cash generated from any investment activities, think interest or bond payments etc.

I need an income statement because it tells me how the company performed in recent times and how well their strategy or execution recently was. Balance Sheet is a reflection of the company’s strength long term state of affairs. Cash flow how well liquidated the company is. Without cash and ability to service obligations like rent, salaries, a company will die and thereby lose on its ability to maximise share holder’s equity.

EBITDA & Gross Margin

From a startup’s standpoint, especially software firms, two of the key metrics are EBITDA and gross margins. EBITDA or Earnings before income tax, depreciation and amortisation reflect operational earnings/income generated by a firm minus the expenses. When we mean before the 3 parts, we mean, we don’t include numbers from those to understand the operational performance of the business.

  • Income Tax: Most startups likely are not profitable earlier on and thereby income tax component is likely to be nothing.
    • It gets important in situations when say, a company gets tax credits as incentives by the government. e.g. Tesla. To evaluate Tesla’s performance in that quarter/annual period, we can need to remove the tax credit’s components.
    • In the case of Amazon, they carry forward their losses from earlier years and can set them off incomes from the current year to reduce the net income or profit.
  • Depreciation: All tangible assets owned by a company, in our context office furniture, laptops, devices and office buildings if owned by the firm etc can be depreciated over a period of time.
    • Unlike individuals, assets are used by companies over a period of time and thereby the drop in the value over a period of time, can be attributed as an expense. e.g.
    • If my office furniture is worth 1000$ and I plan to use for 5 years. I can depreciate the assets over 5 years period as 200$ expense every year. This allows me to lower my net income and taxes but then I need to reduce my asset value by a similar amount every year as well.
  • Amortisation: Very similar to depreciation but for intangible assets. Let’s say, a company has a certain license/patent and company has attributed certain goodwill to the same.
    • The company would like to amortise the value of patent over its entire period until expiry. e.g. A pharmaceutical company amortising its patent value over the remaining patent time.
    • This can also include any kind of debt payments, instead of expensing entire interest payments in chunks, the company will spread the amount similar to an EMI over the repayment period.

Given the accounting complications behind the income tax, depreciation and amortisation. EBITDA is the most relevant and accurate measure of a company’s operational performance and one widely used for startups. EBITDA reflects if the company made more money than the cost of goods, which in case of software is very small. The Software can be replicated almost for free of cost. Costs associated are things like recurring server costs etc.

EBITDA = Revenue – Cost of Goods

Just to be clear, EBITDA expenses does not include fixed costs like salaries of developers, office rents but rather operational expenses needed, like any other software subscriptions, support salaries etc. Because aspects like salaries, rents etc are not measured. An EBITDA positive firm can still be losing cash due to fixed expenses.

Gross Margin is basically taking EBITDA and dividing it over the revenue. This gives a sense of the pricing power or how strong the business moat is. An increasing margin over a period of time is great and the other way around is not good. A light touch sales process would result in high gross margins and with sufficient volume of sales, the entire business might become profitable as well.

Besides the above, as the business scales and especially for firms with operational aspects like Amazon, Flipkart etc. The accounting gets more complicated and aspects like operational expenses vs capital expenditure have an impact on how these numbers treat the EBITDA calculation. Operational expenses are one time and CAPEX is spread across a period. This might help understand Flipkart/Amazon vs Income Tax Department

Finance For Startups (Coursera)

Startup Sales and Marketing Stack (Tech)

“CEOs that build their organisation’s processes, technology and culture around the experience buyers want and value outperform their peers. That starts by aligning sales and marketing, not by resolving differences between them, but by resolving differences between them and the buyer.”

Christine Crandell

One of the most underrated functions but probably the most important one is, sales and marketing. Something, which I was exposed to as an intern with the Xbox team at Microsoft but didn’t quite understand for quite some time since I started working in startups.

The typical tech/research background founders completely discount this aspect of the business, so much so that, plenty of them happen to get the market wrong or fail to build a sustainable distribution for the business to allow it to take off.

Every business is essentially a product and distribution game. Building the product which is basically engineering, research, product management and getting it to consumers or businesses which is basically a sales and marketing combo. The latter is as important if not more because without a viable strategy and execution, it’s like having a car with no wheels, you are not getting anywhere.

Sales Vs Marketing

For the absolute noobs, sales and marketing are similar, when in reality, they are both supposed to serve different purposes. In layman terms, marketing pertains to brand, positioning, pricing and channels. It’s basically inbound in the sense it pertains to getting leads or potential customers reach out to the business to query about the product/service.

Sales is more outbound oriented. In some cases, you might be calling up and trying to convince customers to purchase something. It is also the process of getting these leads/prospects to getting final conversions or deals. Any visiting your site can be a potential lead and the process of getting these people to commit and buy something is basically sales.

Why the need for a Stack ?

The engineering or development cycle is now fairly matured and has plenty of tools to both aid and track efficiency of the process of building products, maintaining them etc. Tools like Version Control (Github), project management (Trello/Asana/Jira), IDE are ubiquitous across engineering teams.

Besides these, you have the actual stack in terms of databases, backend language/framework, frontend framework and machine learning libraries. Similarly, designers rely on Figma and other design tool. Product managers might be using wire-framing tools like Balsamiq over above the others mentioned above.

Similarly, sales and marketing are supposed to have a stack to help organise and streamline their operations. While, excel used to the de-facto tool for all business functions, the increasing complexity of marketing operations and sales funnels has resulted in the need for a more well thought through approach.

Tool Kit

  • Ad Networks: Google Ads, FB Ads and so on.
  • Tracking Tools: Google Analytics, Hotjar
  • Email Marketing Automation: Mailchimp
  • Specialised Products: Re-Targeting Softwares(Perfect Audience), Referral Management
  • CRMs: Hubspot, Zoho

The modern day, marketing function is more science and analytical oriented than the Mad Men days of creative driven operations. While, lots of traditional brick and mortar businesses still operate with traditional paradigms of brand building etc. SAAS and cloud based startup products have their distribution on the web and need a more numbers driven approach. At least in the early days, your marketing priority needs to be numbers driven to get a sense of CAC which is one of the most important SAAS metric.

To be able to compute this number accurately and further optimise it going forward, not only will we need to track everything accurately but also attribute results aka sales accurately to leads and leads to marketing campaigns.

Why a CRM ?

A small startup might just have one person doing the entire lifecycle of marketing from lead gens to maintaining different accounts and finally building and optimising sales funnel. All of this is not possible without centralising the operations through a CRM by tracking and keeping all data there and using other tools as satellite around it. Even with multiple team members, centralised data has its own need. CRM is basically a database for sales and marketing folks with a UI/UX layer.

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As a data scientist, I cannot emphasise the need for centralised data lake and maintaining its quality. This is paramount for getting engineering right and there is no need why sales and marketing has to be any different, which as far as I believe is slowly becoming part of engineering division.

CRM Overview

I will be using Hubspot to give a walkthrough but this is largely true for any CRM. The relative difference between them and pro cons is a lot more nuanced decision which need size of startup, domain etc to be able to make a more deliberated decision.


This is the central operations and is basically repository of all your customers and gives you an ability to track, manage them. Add and edit the basic details and can be thought of as the key to your dictionary.

Marketing Automation

You can also your system to Google Ads and other networks. This is key to be able to organise your campaigns by tracking the users you are hitting. Apparently, ad networks are not that straight forward and you need to track and re-target engaged users to be able to finally convert them.

The ability to run, email campaigns from CRM itself allows you do not maintain separate accounts like Mailchimp which unfortunately are quite limited in functionality.

Notes & Documentation

The other major learning about sales, has been how it’s a series of engagements and not a one meeting event. This requires the need to keep track of different leads, their objections or concerns and how they are being addressed and tracked as we go.

I haven’t set it up in my case but for a B2B oriented firm, this is absolutely necessary and the ability to track conversations and pick up context from last meetings is pivotal. A good documentation culture goes a long way in preventing re-work and channelising efforts better. This saves time and brings effectiveness.

Having this centralised data, allows you to constantly monitor and track data better. The bird’s eye view is necessary to keep the marketing humming. Needless to say, a good CRM gives access to lots of data and this can be used to build automation workflows to speed things up.


There are bunch of other videos and content emphasising this need and I found the following really useful. More so, the post was inspired by the webinar from Hubspot.

Startups : Google Analytics Metrics To Track

In God, we trust. All others must bring data

W Deming

Google Analytics is one of the most popular website tracking tools and especially important for early-stage companies aka startups which are still in the experimentation phase and setting up their direction. Despite its popularity, GA is fairly under-utilised and typically not set up properly.

The goal behind this blog is to quickly identify the key metrics to track and how to measure those using GA. Some of the metrics are fairly well known and pretty straightforward while others can be a bit more nuanced and might help reach the right conclusion.

A lot of these metrics are useful for all firms except those in Professional services or those dealing with very large enterprise clients. Anywhere, the sales process or the distribution for the product happens completely or largely online will find these relevant.

The below metrics have been arrived at from the overview section under the audience

User Growth

  • The simplest metric to measure and understand is the growth in user base. You ideally want to see a growing active user base.
  • Assuming you got the market right, the goal should be an increasing user base. The count while volatile over a short period, should show a trend over a long period of time, say a few months.
  • This basically is an indicator of whether your marketing channels or distribution is working. This does not tell you whether your website is doing fine or not or if it is relevant to the audience well or not.
  • In this case, the graphs show specific spikes and it will be interesting to know what prompted those.

Returning Users (%)

  • Another metric to track along with user growth is to returning user percentage.
  • This is proxy measure of product/blog stickiness. An increasing percentage is an indicator of product stickiness growing.
  • A small number is an indication of wrong fit or the product not working out for the respective audience.
  • I personally believe, this number is an indicator for product market fit. A number larger than 40% similar should be a pretty strong indicator of market fit.
  • Here in this case, the orange line has not really taken off and that’s a sign of worry. It also explains why the blue line has not taken off because an increasing percentage of returning users means, a growing audience. This is needed for the overall user base to grow.

Cohort Analysis

  • This is a bit similar to the returning user metric and also is an indicator of product stickiness. Both are similar metrics but this one is a lot more insightful.
  • The curve is basically a tracker of percentage of users returning to the site from the overall set of users/cohort who came to the site for the first time on that specific day.
  • We basically, track the returning user base over a period of time, say over a monthly. Ideally, a product which has achieved product market fit will have a fall in returning user base which eventually saturates or flattens.
  • A leaky bucket or no-product market fit will have a situation where this metric simply crashes to zero over a period of time.
  • The blue line is our cohort/retention curve. It simply crashes to zero here, a product market fit situation will have resulted in something like the green line. The percentage though could vary.

The above metrics are more of KPIs or measurements of whether we are doing good or not and in most cases, it’s not going to be good. The second question or the key step would be to know why and how we can improve. The second set of metrics help us diagnose the problem and thereby take the necessary action on the basis of it.

These metric can be setup from the conversions panel and the behaviour panel above it.


  • This is a metric which needs to be setup and not directly available since the end goal/objective for the site needs to be defined.
  • In case of a consumer startup where the user base is the product, time spend on the website could be a goal. In case of an e-commerce website, the end goal would be sales.
  • Setting up a customised goals helps in tracking it and knowing much percentage of user base end up meeting the objectives.
  • This number can be an indicator of the website design’s quality. This helps measure the design aka UI/UX for the website.
  • This number is especially useful if we have achieved some indication of product market fit. A growing goal conversion rate basically indicates improving website design.

An increasing number here can be the north star for the product design team. How to build the user flow better, so as to guide the users to desired objective/goals.

Behaviour Flow

  • This is the diagnostic part of the metrics and is quite useful to understand user behaviour on site.
  • By giving the popular user flows and the drop off rates, we can clearly identify the bottle necks in the website design.
  • This can also give useful indications for possible poor retention rates etc as it can clearly identify areas where users lose interest.
  • Improving user flows by reducing drop-offs can be useful to achieving goals mentioned above.

Besides fixing and iterating over the overall user base and figure out how the site is doing as a whole, the next plan of action could to be figure out the segment or user base for which the fits seems to be the best. The idea being to be able to narrow down the user-base which is most engaged with our offering.


  • These are a collection of different metrics/sections available under the audience section.
  • Once, a decent amount of traffic has arrived on the site, it might be a good idea to check for metrics and how they compare against different segments.
  • Demographics aka age might be an influence, a certain age group might resonate better.
  • Similarly, the audience and the corresponding metrics can also be compared against geography and interests. Devices can also be a good metric because, the website might be broken for a specific set.
  • It can also be an indicator for what kind of section of society engages better, iPhone vs Android and so on. Especially, places like sub-continent where iPhone is still fairly rare and reflects a certain segment of the user-base.

Google Analytics is an incredibly rich tool which collates and puts together business and operational data for websites, which are typically used by big mainstream corporations for decision making. Often such reports are generated post consulting engagements worth several thousand and sometimes millions. The fact that online businesses can avail all this for free of cost itself is a huge indicator of edge over traditional brick and mortar setups. Often, small entities cannot be so accurate about their numbers and might be running a very inefficient setup and not know, what to do about it.

Lean Analytics: Use Data to Build a Better Startup Faster

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