Financial Modeling Where can web startups learn Follow ... mod… · Financial Modeling : Where can web startups learn about financial modeling that accounts for the important metrics

Financial Modeling : Where can web startups learn about financial modeling that accounts for the important metrics and costs?

Matthew Carroll , Building fashion & footwear brands is...288 votes by Sae Min Ahn(안세민), Clement Vouillon, Ian McAllister, (more)

[Alright so here is the deal, below is a fairly detailed & illustrated walkthrough of a financial model for a web-only product startup. There is a ton of info here with screenshots & annotations - but if you want to play with the model yourself, message me with your email and I will forward it over it you. Here’s the only thing I ask → you have to email me back with ideas on how to make it better, comments on things you don't like, clarifications for illustrating data better, etc - that's it. The point is to throw this out to the world & rap with cool people working on interesting things] Introduction This financial model was built to illustrate modeling methodology & logic flows as it relates to a web-only hard goods startup. The format is geared to transition into an operational guide for you to update with data as it becomes available & provide insight into the financial performance of your new firm. A word of caution for non-finance people (& hyper-detailed focused developers specifically) - you can get absorbed (sometimes on the verge of obsessive) into getting every number perfect and conducting a lot of data analysis. My advice - the inputs should be fairly conservative and general to reduce the friction of others (READ Investors). Additionally, a model can become hyper-addictive because you can put ALL the pieces together and clearly understand & see the impacts/results of changes/assumptions over time. You can spend hours breaking out the minutia, which is great for understanding your company (super important), but make sure that there is clear benefit for new insight into the firm by virtue of making these investments *** At the bottom of the answer, you can find image s of each sheet in total OR here is a link to the Google Spreadsheet http://f4il.co/J6t8Nb Important Background Assumptions for this model:

The startup has completed product development at a factory in China1.

The first month of the model is the first selling month - meaning that the purchase order (PO) was placed with the Chinese factory 90 days prior to the start of this model

2.

There are three product categories (Large Luggage, Packs & Bags, and Accessories). Generally these will have broadly similar costs & selling patterns & hence why they will be categorized together

3.

The model takes you through a full build, but these resources will build out your knowledge base for customizing this model to your startup. And with that - Let's do this thing!

Follow Question

FollowMatthew CarrollBuilding fashion & footwear brands is what I live for. Startups are my life - Built 3, crashed 2, currently running 2 - raised ~$7m for fashion startups over the last 18 mos.

Answer Author

E-Commerce : What is the next wave of innovation in e-commerce after flash sales and private sales?

=================================================Her... (continue)

How do startups like Bigdeal.com get into sustaining themselves over time?

This is an incredibly interesting topic that has pushed me on ... (continue)

E-Commerce : What's the average margin a clothing distributor expects to get? What about a retailer? An eCommerce retailer?

[I am going to completely re-work this answer this weekend, it...

(continue)

Related Answers by Matthew

0

Share Answer

Answer Stats

Latest activity 13:6 on Mon May 7 2012.

This answer has been viewed 12019 times.

Matthew has written 32 answers.

Quora connects you to everything you want to know about. Login Sign Up

451

47

43

Like

Page 1 of 19Matthew Carroll's answer to Financial Modeling: Where can web startups learn about financial modeling t...

5/10/2012http://www.quora.com/Financial-Modeling/Where-can-web-startups-learn-about-financial-modeling-that-ac...

Sales Build http://f4il.co/JMqIAb ( Takes you directly to the Sales Build Sheet) The Sales Build tab is a standard tab in nearly every single financial model that you will come across. It is the canvas where you begin to paint the picture as to what you want revenue to look like.

Steps for the Traffic Build



Traffic Build *** Traffic Build is the first section on the Sales Build Sheet - http://f4il.co/JMqIAb *** Sales for any website (or company for that matter) originates from the # of visitors that you have coming to your site. In order to calculate the Sales per Visitors (e.g. your conversion rate), you need to start with the # of total people (unique visitors) that came to your website and divide that by the # of orders that we completed on your site over a specific Organic Traffic: 1. Organic Growth Rate: This is % change from one month to the next that you are forecasting to grow based upon your company organically growing from people randomly searching for something related to your product on Google (this is why SEO is important), users talking about your company with their friends, or stumbling across previous marketing campaigns. This is a variable figure that you can toggle in this model based on what you see fit. 2. Unique Visitors / Mo: You need to start somewhere and this row calculates the compounded impacts of the previous month’s unique visitors * (1 + Organic Growth Rate). In the example template, the baseline figure is 2,000 unique visitors (a figure that I pulled from one of my old companies VÆL Project - a men’s footwear line). Therefore in Mo-2, we had 2,000 unique visitors from last month and we grew 5% organically - so 2,000 * (1 + 5%) = 2,100 forecasted unique visitors. Marketing & Promotion: Businesses need to market their products in order to let potential customers know that they exist and how their product/service solves a problem or a want. Therefore, when a marketing piece is published (i.e. a Thrillist email about your cool product or TechCrunch posts a review of your service) people who see this piece of marketing will come to your site. As you run your company, you will see that there are 3 generic profiles that construct the traffic being driven to your site. Don’t waste your time in getting super analytical about this metric - after 10 marketing pieces are posted about your site take a look at when the marketing piece was posted & annotate your Google Analytics with the event. You will notice a general trend in # of visitors to your site. For the purposes of this financial model, I averaged three traffic categories (Premium, Moderate, Niche) from 4 fashion brands for whom I had access to their Google Analytics data. Qualifying the three categories: Premium: These are the marketing pieces that have the highest viewership bases of the source breakdown. They are compromised of highly engaged readers who admire / respect the content creator. Moderate: This source is a 2nd tier distribution vehicle or ad hoc company references (i.e. when a blogger writes an article and references/links to your company in the main article - but the reference is not the focus of the piece). Niche: This is a 3rd tier source that will drive a little traffic - maybe a design blog.



Conversion Rates *** This section can be found by going to: http://f4il.co/JMqIAb *** A conversion is a customer that “purchases” from the site or, in other words, “converts” from a visitor into a customer. We want to break out the conversions by source because each source has unique behavior and converts at different rates.

One of the most important things to know about building a financial model - is that you don't want to look like an ass - so saying that you have a 15% conversion rate is cause for someone to completely discredit your model. I ran into this problem when I was at a Bulge iBank training for new bankers - basically serving as the entrepreneur for the youngsters to argue against. In the Saturday session, I used Salesforce as a comp & fucked up the EV calculation because of the shares outstanding calc from that super complex convertible note that they brilliantly issued in Jan '10. Basically, the rest of the session the banker (smartly and to my dismay/irritation) a comment about the mistake to drastically reduce any clout in the argument that I was making. So the most important thing is to present yourself and your calculations as reasonable, logical, and prudent. To do that, you are going to need some comparable statistics to demonstrate that you know what you are talking about & that your build is sound.

Sales Mix & Pricing Sales Mix is the weighting average order value for your company's sales. A simple average is misleading because smaller $ value items will compromise a higher



proportion of sales #s than the larger ticket items (most likely).

Just like in the conversion rates, I wanted to give you folks some comparable figures to provide a basis for when you estimates are just crazy. Company, Avg Order Value: LL Bean, $139 Gap, $110 Saks Fifth Avenue, $400 Neiman Marcus , $410 Urban Outfitters , $130 Gilt Groupe , $360 Abercrombie & Fitch , $125 American Eagle , $145 Blue Nile , $1,669 Net-A-Porter , $190 Eastern Mountain Sports, $100 ModCloth (Adil Wali ) $95 Karmaloop , $100 Sorry for the formatting - Quora doesn't allow you to tab. Shipping Analysis

Purchases by Segment

Revenue Build

Long Term Value per Customer *** This gets a little confusing, but check out the actual sheeet at



http://f4il.co/JMqIAb *** Some of you have noted in messages that there is this huge portion of the Sales Build that I omitted from explaining in the Long Term Value per Customer. It is a contentious issue that is very difficult to quantify, but I will explain it in more detail here. Logic - Building brands is an intensely emotional process of connecting with your customers and creating an ongoing dialogue that makes your customers feel like you are really friends IRL. - Customers want to feel like they are close to small brands almost to the point where they can say "Oh this shirt? It's my buddy's brand.." For small brands, the first customers are going to be ideologically similar to the founders and the branding/external communication will support this. In fact, some people who I would qualify as good friends began as customers of one of my old brands, VÆL Project. - As such, there are a certain portion of customers that will love the product so much that they will look to purchase additional products from you to fill out their collections / purchase complementary goods (Dopp Kit with Overnight or Category C when the original purchase was Category A). Long Term Revenue is reflective of two main segments - Secondary / Complimentary purchases & Replacement Purchases.

Secondary Purchases are purchases based on super satisfied customers & those strongly connected to the brand. Most likely they are purchasing down-stream so if they purchased the big bag (Cat. A) then they would purchase a Dopp Kit for the overnight bag. Most likely, this purchase will take place after the initial purchase because they will have the opportunity to feel & use the product & have a time to experience it (like a trip). So to calculate the Secondary Purchases, we need: Repurchase Rate: The % of customers in each cohort that will purchase another item. I set this rate at 10% because that is a good baseline forecast. For apparel companies this is way different, but for a leather goods company like the one I built in the model - it's kinda all that we have. Secondary Purchase Value : This is a modifier from the AVG Order Value that will be used to calculate LTV rev. Above I mentioned that customers will most likely be purchasing complimentary goods, so category C is a safe bet as to what they will be buying next. OR if they are a Category B who purchased the backpack, they most likely will purchase the messenger for different occasions. Either way a forecasted secondary purchase value of $220 (or 75% of Avg order value for the monthly of the cohort) is pretty safe to assume Secondary Purchase Timeframe: The timeline when the vast majority of purchases will be taking place. This is an arbitrary # based on experience, but I think that 6-months is going to cover the vast majority of the cases. Since we can't really forecast a distribution - we should assume that the secondary purchases are evenly distributed throughout this 6-month window. For example.

Now we know that the timeframe is 6-months. In this simple example, the incremental monthly from Cohort 1 is $220/mo for periods (mo-2 through Mo - 7)



Now that we have the 2ndary purchases calculated, there is going to be a lifetime customer. The is essentially the same calculation as a secondary purchase just the logic is different. Replacement Timeframe: The date at which the product will most likely want to be replaced. I arbitrarily set this as 18-months so that it fits on my 24-month forecast. But this is the time when you start to see people returning to the site to pick up the same good or more. Replacement %: This is the # of customers that were stoked on the product that want to get another. This # is going to be different than the secondary purchase rate so it has it's own toggle.

[NOTE: There was an incredible infographic out of KISSmetrics (Hiten Shah - Damn you guys are good - always inspiring me to contribute more to Quora - Wish I could keep up with the incredible contributions you guys make) - I didn't want to lose it, so here is the link: http://www.fastcodesign.com/1664... Sales Build Overview This is how it all fit together

Email Build *** Email Build can be directly accessed by going to http://f4il.co/JahX5K *** One of the most important things to do as a young startup is to communicate &



engage with your consumer. At least today, the primary & most valuable way of doing this is through email. The goal is to build a direct & engaging dialogue between you and your fans in a private format with the visual and content freedom (READ branding) that most effectively communicates your story & builds the relationship. This section is where you work to systemically build out how this list will generate revenue for your startup.

Newsletter Reach is the total # of people that are subscribed to your email list. If you previously worked at a brand, have a personal blog/email list, or had a bad ass pre-launch strategy that got a ton of emails (a la hipster.com ) - 4,500 is a decent # to start. As we go down this build there will be additions & subtractions to this # reflected in the changes shown for the following month. Campaigns are the # of emails that you are sending to each member of the newsletter. This number grows fairly slowly (1 → 1.3 → 1.5) due to the fact that you are going to invest more time, cash, and energy on capitalizing on this opportunity as it becomes a more substantive revenue source. In addition, over the course of two years you will learn what your subscribers want to read and customize the content & message to deliver on their expectations Segments are the qualitative differentiating factors that compromise your subscriber list. All customers fall into broad customer segments that you will learn more and more about as you gain experiential knowledge from working with them. For purposes of this model, I arbitrarily put the numbers to 1, 2, 3, 4. You can get as complex as you want, but keep in mind that this takes a lot of time building custom content in a way that delivers positive ROI for the time invested - don’t go nuts here. Click Through Rate (Engagement) Click Throughs are newsletter recipients that opened the email & clicked on something within the link (performed an action), thereby placing them within the medium to purchase something from your site. If you create more engaging emails & more clear about what actions you want the recipient to take, then you will have more people clicking & coming to your site. To get better at something relies on experience, knowledge, and trial & error - hence why in the 6th month, the model adds a second customer segment (meaning you have learned what you did well & poorly over the last 5 months and are positioned to capitalize on those mistakes in month 6)

1. Optimization Gains from Segmentation CTR Optimization Gains (2.5%) X # of Monthly Segments (Segments = Optimizing Emails)



Total Optimization Gain (2.5% * 2 Segments = 5.00%) 2. Total Click Through Rate Base Rate (15.00%) + Optimization Gains (5.00% = 2.5% * 2 Segments) Monthly CTR Rate ( Mo-6 = 20.00% = Base Rate 15.00% + 5.00% Optimization Gains Forward Rate This is an area that I was hesitate to initially build into the model, but it was something that I saw very often in myself and a behavior that is systemically different from the open & engagement rates of other asks of the forecast. The logic is that the email marketing will excite to a certain % of your subscribers that they will want to forward the message onto to their friends - something maybe more applicable to someone else or simply to show off something cool. Think of it like sharing on Facebook & tagging a friend in the post. Forward Rate: The % of readers that will forward the campaign to someone else (they could be a subscriber but most likely not). Based on the campaigns that I have run & the campaigns of companies that I work with, I set this # at 4.5% - this # could trend up over time, but for illustrative purposes let’s keep this constant since it’s a more difficult variable to conceptually quantify. Forward Rate is based on “Open Rate” because conceptually the original recipicient may see it and think “Wow, this is perfect for John” and subsequently forward the email to John. It doesn’t necessarily rely on that recipient engaging with the email or clicking through him/herself - only that they saw it. Forward Click Through Rate ( FWD CTR): The % of users that will click on the email and go to your site. In the model, the CTR rate is 75% - this may appear high, but odds are that this person is close friends with the recipient as implicitly the sender has some understanding of the forwarded person’s personality that this email will appeal to them. Hence why they will open it. Email Traffic to Site (Calculated Summary) This is a calculation summary section to provide explicit #s of visitors going to your site.

Net Additions to Email List (Newsletter Reach Growt h)The goal is obviously to build your email marketing channel and more effectively generate revenue from your customers → serve as a controlled demand source for your business. Site Signups: When a visitor comes to your site and enters her email into the “Newsletter Signup” box & successfully signs up for your list. Signup Optimization Rate: A toggle metric that reflects that you will get better at signing up visitors to your site as you gain more experience & deeper understanding of what they are doing & how you can effectively capture their email. Signup Rate: The conversion rate of visitors to your site that signup for the newsletter. This number can be found in your KissMetrics or setup as a Goal in Google Analytics.



Purchase Signups: Think about when you enter your billing information on a standard shopping cart, there is generally a check box selected by default to sign up for the site’s newsletter list. Since this enabled by default, there is a strong possibility (i.e. 75% of the time, which is what I have in the model & my average experience of successful cart goal completions in my analytics for Purchase Conversions + Email Signup) → This becomes important for Long Term Value per customer.

Unsubscribes: As easily as users signup to follow your company - they can likewise unsubscribe. One guiding principle to govern your strategic decisions about your email marketing initiatives - every email is a touch point with your consumer that you give them the power to say “do I really like this? Do these guys “get” me? Do I really care about receiving these emails?” This is why I add the segmentation & the campaigns to the main section to reflect that you will learn how to better target your customer. However, prudence is your friend - often times it is better to not say anything at all, if you aren’t sure that you will say the right thing to grab the email subscribers attention & bring them closer to the brand. Saturation Rate: As you send more emails, you are increasing the natural churn rate in email subscribers. This # increases based on the fact that a certain % of users will simply just “get tired” of getting your emails. This is okay - don’t be upset, it’s normal. But it’s your job to learn from this to understand why and how to better tailor your emails to reduce this risk Unsubscribe Rate: The % of the your email list that unsubscribe on a monthly basis. The number that I used here .25% begins low because you are a small brand (read: cool, new, you are cool because you are new). So you have a low # in the beginning - this sample variable is the average from 4 companies in fashion that I have run or been a part of for the last 5 years.

Page 10 of 19Matthew Carroll's answer to Financial Modeling: Where can web startups learn about financial modelin...


Social Build This is fairly rudimentary approach to calculating the impact of social virality as a traffic source. The foundation is approach this: 1. An article is written about your company ( # of articles from the Marketing & Promotions section from the Sales Build Sheet) 2. The assumption is that of those who click through (i.e. Premium: 1,500) to your site a certain % will share it on Facebook or Twitter (illustrated below by Rebroadcast rate by Source) 3. Do a Twitter search / SocialMention.com / Klout search for a good idea for the distribution of average # of followers. 4. Take the sumproduct to establish the total potential # of people that could become aware of your company by virtue of their followers 5. There is a fairly low engagement rate these days from social sources. Hence the 0.5% traffic inbound to your site. Rebroadcast Build A rebroadcast is essentially a "Tweet" based on the original content marketing piece that references your company. Considering the tech-focused community on Quora, I will use a TechCrunch example: 1. TechCrunch posts an article about your company. 2. 000,000s of people see this article and think it's cool, so they Tweet a link to the article - this is what I refer to as the "Rebroadcast Rate", meaning that readers of the article promote the content piece to their followers. 3. Followers of the "Rebroadcaster" (readers of the TechCrunch article who tweeted/shared on Facebook) - then come to the site. 4. In order to get a proxy for how many users could, we have to calculate the average # of followers by source. Obviously, the premium source (TechCrunch) has techie users who are more inclined to have lots of followers. [Note: Don't get bogged down in a super detailed data analysis of average twitter followers by source - just look at like 20 or 30 profiles (this will take all of 5 mins I know) and get a general picture - then use that #. This number changes over time & as the more followers build on Twitter or Facebook, hence why this Figure reoccurs monthly] 5. We calculate Rebroadcast rate by the following: TC Reader Tweets, then one of the followers of the Rebroadcaster clicks on the shared link & goes to TechCrunch. In turn a certain % (in this cast we forecast it at 0.50%) will click through from the TC article to your site. I know this is a little confusing but it's important to begin to format the framework for understanding how traffic & subsequently sales will grow as references diffuse through the social-sphere.

Sphere of Influence Build In the same way that we built the newsletter reach, we are going to quantify the net gains of Facebook/Twitter followers of your site. We start at the Organic Follow-Rate - or users who just came to your site & started following you. This rate is generally very low because although their are 100m Twitter users only a small % of those users are "active" - hence social is not within their workflows.



We can see that a connecting with brands & companies via social is "catching on" so let's take a look at some research that was just research about demographics of users that are following brands.

Paid

Production & Expense Build The Production & Expense Build is where the we breakdown the demand estimates (from the Sales Build) into their cost pieces and forecast how these expenses will connect with pricing & margins. The main aspect of this model is that all goods are purchased FOB Hong Kong. This means that the factory assumes all aspects of the production process (sourcing materials, labor, cartonizing, containerizing, and transport to Hong Kong as the port of export).



Shipping & Landing Expense



========================================================== DOES IT CHECK ========================================================= Let's take Bonobos (company) for a comparison. Some background stats; Rev: '08: $1.8m (http://www.businessweek.com/smal... ) - 8 EEs '09: $4.9m (Ibid) - 20,000 Customers for Bonobos (company) '10: Est. $15m - Sept '10: $830k/mo - Nov '10: $1.3m So how does this model compare? Well by end year 2, we are forecasting: - 7.782 paying customers - 12,967 email subscribers - 4,428 Social Influence - 9 Forecasted EEs for FY2 So a focused product selection after two years looks moderately comparable to Bonobos (company) Not half bad, when you think about it? eh Andrew Weber, Andy Dunn, D. Craig Elbert - Please feel free to add any insight for the comps to Bonobos In addition to the Sales Build Comps, I figured that I should wrap this piece of with some additional supporting info to support the validation of this framework for all of you startuppers!!! +++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Additional Background Piece Data Sources After building models for several of my companies, refining them over the years, and working with dozens of product startups to help them understand their financial picture, the following model’s inputs are filled with general variable toggles. They may not necessarily be perfect for your startup, but they should give you a good starting point. This is a short list of where you can find the data to tailor the model to your company:

Google Analytics - Visitor Data, Traffic Source (Performable will make your life much easier, but more on that later. You will need to export the data & break out product traffic by how you segment your categories (best done in Excel)

1.

MailChimp - Email Newsletter campaign performance2.

Magento - Shopping Cart & Sales by Category3.

Additional Resources: The reason that I wrote this is that there isn't very much written / explained about the full build from Mo-1. 1. Read Featured Essays by the metrics god himself, Andrew Chen - http://andrewchenblog.com/list-o... Pay Attention to: http://andrewchenblog.com/2009/0... 2. Mark Suster had a great TWIVC talking about Cap Tables & models - I can't find the link now. But it's somewhere around TWIVC #15 -



3. Mark MacLeod's startupCFO's archives has loads of resources & Fred Wilson's MBA Mondays give you a lot of the background details. All Screenshots





16+ Comments • Post (9) • 5:14 on Mon Jun 13 2011

Cannot add comment if you are logged out.

Upvote • Post • 5:11 on Thu Mar 1 2012

Jawwad Farid

Matthew - Thank you so much for sharing this. I have never seen this level of detail on any Forum before. Most appreciated.

Upvote • Post • 22:8 on Tue Jun 14 2011

Carlos Leiva Burotto

wow! ;)

Matthew Carroll : “I take it that it meets with the laud...”

Upvote • Post • 13:51 on Tue Oct 25 2011

Michael Imstepf

good stuff

Upvote • Post • 21:16 on Sun Dec 18 2011

Antoine Carriere

That is a detailed and brilliant answer. I am lookig forward to playing with your model

Andrew Jude Rajanathan



Upvote • Post • 7:22 on Tue Oct 11 2011

Brilliant, thank you!

Upvote • Post • 23:52 on Tue Mar 27 2012

Rod Ruhl

Matthew, when trying to access your model on Google Docs the access is denied. Is it not publicly available? I asked for access. Lock out for [email protected]

Upvote • Post • 23:53 on Tue Mar 27 2012

Rod Ruhl

BTW, excellent post!

Upvote • Post • 0:5 on Sat Apr 7 2012

Crystal Campbell

Hi Matthew, thanks for this, it's fantastically helpful. I tried, and you'll get a request from my email campbell.crystal... to access your model on Google Docs. I'll be more than happy to send feedback in response if it's still available. Many thanks.

Matthew Carroll : “Wow! Thank you! It's an hon...” and 1 other

Upvote • Post • 5:31 on Sun Feb 26 2012

Daniil Sokolov

Perfect! Thank you!

Upvote • Post • 19:16 on Mon Apr 23 2012

Dave Sandrowitz

Just found this and I am amazed at the effort and detail here. If only more people shared in this way...our companies, projects, and ideas would all be better for it. My only question is whether anyone has applied this to a non-hard goods business? I'm looking for lightweight models for SaaS-based businesses and am not sure that this will fit well enough. Still very interested in seeing the spreadsheets "in the flesh" though.

Upvote • Post • 23:54 on Sun Apr 15 2012

Rajarshi Chatterjee

In the same boat requesting for access to the spreadsheets - [email protected]

Upvote • Post • 23:37 on Fri Apr 20 2012

Beau Roberts

Thank you. This is great. I'd love to play with this and give you my feedback. Could you provide me with access to the Google doc version?

Upvote • Post • 16:31 on Wed Feb 1 2012

Chérif Zouein

This is hugely helpful, thank you!

Matthew Carroll : “Honored that you found it interesting...”

Upvote • Post • 10:32 on Sun Apr 8 2012

Ricky Sperber

Excellent post Matthew... Can you please send me the model to [email protected] . I am building an e-commerce company in Brasil, we will sell high end furniture and decor, all on demand (meaning the pieces are produced only after they are sold on the website, as holding inventory in Brazil is just too costly). The site is www.dob.com.br (official launch is in May). As I am building my model to present to potential investors, I am trying to figure out what exactly should be included in COGS in my model. If you have any thoughts on that would be great. Thanks.

Upvote • Post • 6:54 on Fri Apr 13 2012

Guillaume Jaillet

Extremely interesting and relevant! Great work!

Upvote • Post • 6:28 on Mon May 7 2012

Yasar Oz

You should write a book!



View All 12 Answers • View Answer Change Log

About Jobs Privacy Terms • Help • Login Sign Up Mobile SiteiPhone App

Matthew Carroll : “Maybe - but then all this really cool...”



Documents

Financial Modeling Where can web startups learn Follow ... mod… · Financial Modeling : Where can web startups learn about financial modeling that accounts for the important metrics