There’s an adage that’s being passed around by entrepreneurs that goes something like this: “As soon as you raise this round, it’s time to start worrying about the next round.” I think it’s a wise adage.

It’s similar to my most important principle of fund raising which is “Raise enough money to achieve a set of milestones that will attract a subsequent round of investment from new investors.”

Those two ideas are simple and logical. But what does this mean for the business on a very tactical level? How much revenue? How much dilution should an entrepreneur expect? What should valuations look like over time?

Below, I’ve tried to summarize the way a hypothetical startup might think about the cap table evolution, valuation and revenue growth. First and foremost, a huge caveat: every business is different. Every financing is unique. And this data is based on generalization and medians and averages.

Capitalization Table Evolution

Below is a hypothetical cap table for a startup through four rounds of financing, seed through Series A. The table shows the common shares ownership with time and the typical investment stakes of seed, A, B and C investors. These stakes are highly variable (see caveat).

The most important line for the founding team is the last line called Equivalent Exit Price. This metric tracks the exit price of the business required to generate $30M in net proceeds to the founders with each subsequent round of financing/dilution. Keep in mind, the point of raising money is to create a larger and larger company. As always, it’s important to align VC and founder incentives on exit size.

 

Ownership (in %)	Founding		Seed		Series A		Series B		Series C
Common	100		65		50		39		29
Seed investors			15		10		6		4
A Investors					25		25		25
B Investors							20		20
C Investors									15
Pool			20		15		10		7
Equivalent Exit Price (in $M)	30		46		60		77		103

Valuation Evolution

Below is the evolution of the valuation of our hypothetical startup. Again, this is highly variable. I’m estimating valuation using the forecasted burn for 18 months of runway and dividing that by the share the new investor takes to invest these dollars. It’s an estimate because I don’t take into account the dollars the insiders would contribute as pro-rata but it’s good enough for our purposes.

 

Valuation Evolution
Employees			7		18		45		75
Cost per Employee (in $)			12,000		12,000		12,000		12,000
18 Month Burn (in $M)	0.5		1.5		3.9		9.7		16.2
Implied valuation (est.)			10		16		49		108

 

This last table shows the revenue growth of our hypothetical startup. I calculate revenue by taking the valuation and then using a calendar year valuation to revenue multiple – called CY Revenue Multiple in this chart. That figure is an average of more than 25 SaaS businesses’s financing histories.

Revenue Evolution

 

Revenue Evolution
CY Revenue Multiple		13		11		15
Implied CY Revenue (in $M)		1		4		7

 

My aim with this post is to provide a framework for thinking through the cap table, revenue and valuation evolution of your startup over time. The particular figures will vary depending on market cycles, sectors, teams, ideas and a thousand other variables.

Frameworks, Not Absolutes

But in sharing this framework, I hope it helps those entrepreneurs plan for a successful financing path for this fund raise and every fund raise for their business – a little bit of tactics to promote that great adage above.

 

*Reposted from Tomasz’s personal blog, which you can read here.

This year alone, there is an $11.4 billion mobile advertising opportunity, which means there is tremendous upside for nimble and innovative startups with disruptive mobile-first models. As we saw from Facebook last year, the company was able to turn around and actually make something of its mobile business – a business that didn’t exist at the time of IPO. However, despite the potential of the market, and Facebook’s early success, we’re still a long way from realizing the promise of the mobile medium.

When looking at the opportunity, it’s clear there are a few core challenges that need to be addressed quickly in this nascent market. The startups that address these challenges first will be the companies to watch.

THE PROBLEMS THAT NEED SOLUTIONS

In many ways, we’re at the same juncture with mobile advertising as we were with the desktop web circa 1996-97. At that time we were limited by basic ad-serving capabilities, browser cookies to track visits and boring, static display ads. Search keyword advertising, the most compelling ad format and targeting method the web has seen, was only in its infancy (at Goto.com, which eventually became Overture) at the time.

Right now, the two most obvious hurdles to overcome are what smart companies are focusing on: developing a reliable and privacy-safe method for user targeting across apps, and developing smartphone native ad formats.

Cross-App User Targeting. On the traditional desktop web, browser cookies became a reasonably reliable and standardized method for recognizing and storing attributes of any given user in between visits to a site. Today roughly 80 percent of online ads leverage cookies or some other form of a user-targeting mechanism.

In the mobile app world, an analogous, reliable and standardized mechanism has not yet emerged across either iOS or Android, and until it does, relevance-based targeting will be less effective in the mobile environment and remain a giant missed opportunity for advertisers. Currently there isn’t a robust way to track users across applications after Apple deprecated UDID as a targeting mechanism. In order for cross-app user targeting to be fully realized, the tracking of users in a privacy-focused environment must be solved.

Smartphone Native Ad Formats. The first ad formats utilized on smartphones were borrowed from the web. As a result, users are inadvertently clicking on too-small-to-read banner ads, thus ensuring annoyed users. Instead of a fluid and seamless experience, users are pulled out of their task at hand and brought to un-optimized web landing pages in the mobile browser.

The only way mobile ad monetization will flourish is when smartphone native ad formats that enhance the immediate app experience are developed. The good news is that we’re starting to see a few promising native smartphone format candidates with notifications and Facebook’s Sponsored Stories. There is still plenty of room for innovation, as these formats aren’t 100 percent where they need to be. Users and marketers alike can’t wait for some savvy startup to develop innovative and reliable ad formats that fit within the app experience and engage the user without disrupting the task at hand.

THE WINNER’S CIRCLE

Once the dilemmas of cross app user targeting and smartphone native ad formats are solved, there are some very promising areas within the mobile environment that are poised for the taking:

Offline-to-Online Ad Tech Providers. The ad-tech player who can get the ambient context digital wallet and in-app context right for the Walmarts and Coca-Colas of the world will be a really big deal. There will be several winners in this area, each focused on a particular vertical of offline-to-online.

Cost-Per-Lead Advertising. Yes, cost-per-lead advertising. The web performance stepchild to cost-per-click could emerge as a first-call citizen in the smartphone medium. Why? Well, the medium happens to be attached to a phone, and guess what leads perform the best: phone calls. The smartphone promises to connect this intent to buy to a live person more seamlessly than any other medium to date. This will lead to higher conversion rates and thus higher monetization rates. Inadco, a Redpoint portfolio company that started in the web CPL space, is one startup helping these advertisers take advantage of the mobile phone.

Ambient Context and User Analytics Providers. The fundamental problem of user targeting and analytics within the mobile world must be solved. This solution will come from a clever startup, not the underlying platform players Apple and Google. Just as Omniture emerged to be an important platform company in web analytics, there will also be similar companies built within the smartphone medium. Native mobile app analytics companies like Flurry are promising, as are the emerging players in audience targeting like BlueKai (a Redpoint portfolio company).

While we are a far way from identifying the smartphone equivalent of paid search, it will absolutely exist (it has to) and it will leverage ambient targeting, the digital wallet and smartphone native formats that interrupt but don’t disrupt the user from the task at hand.

The market is big and the current players are just starting to crop up, which means the challenge is for the taking. The next two years will undoubtedly be exciting years to see it all unfold – not only to see who the winners will be, but also to see the innovations that make it happen.

 

*This article originally appeared in TechCrunch and can be viewed here.

One of my favorite courses in engineering grad school was Marketing which was taught by a brilliant quirky professor. On the first day of class our professor wrote on the board this equation:

Innovation = Invention + Marketing

Addressing a group of engineers who prided themselves on their technical skills, this professor of marketing tried to instill in us that invention alone isn’t enough to create innovation.

The invention has to be coupled with a way of understanding the customer, speaking to that customer, educating the customer and ultimately convincing the customer to adopt the invention. Only when the customer base has adopted the invention at scale have we truly innovated.

Aside from customer development, the other the most important component of marketing is timing. Sometimes even the best inventions coupled with fantastic marketing still don’t achieve innovation. Because the market simply isn’t ready for them.

It’s not infrequently in the Valley that you might hear, “We built [insert successful company name here] three years before. We were just a little too early.”

Timing the market is one of the most difficult things to do. Sometimes entrepreneurs fall into the right place at the right time with the right idea.

Other times, they might need a few years working within an industry for to understand the long-term trends of a customer or user base and the opportunities the industry affords.

And then there are the exceptions, entrepreneurs clearly have a knack for market timing. Elon Musk, Jack Dorsey, David Sacks are all repeat entrepreneurs who have had success in several industries.

If I were to update the professor’s equation, I would write:

Innovation = Invention + Marketing + Timing

*Reposted from Tomasz’s personal blog, which you can read here.

It’s not news that more and more people are accessing the Web from their mobile devices. Hardware players are winning big with the newest devices, the app market is flourishing with incredible innovation and success stories, and of course, marketers are salivating at the enormous opportunity these markets create.

To set the context on just how big the mobile market is, according to IDC’s Worldwide Quarterly Mobile Phone Tracker, in 2012 we saw 44.1% more smartphones shipped globally than we did in 2011. What’s more, according to Flurry Analytics, the average American consumer spends 2 hours and 38 minutes of their day “glued” (Flurry’s words) to their smartphones, tablets and the applications therein. Of the 1 billion devices that Flurry tracks, they found that the average U.S. consumer spends 80% of their time within apps, while 20% is spent on the mobile web. However gaming apps takes a rather impressive 32% slice of the app pie.

 

 

All of this incredible growth of both devices in use and time spent on the devices means one thing for the advertising industry: there is a huge opportunity for mobile advertisers and the mobile platforms that move quickly – and intelligently – to support them.  Yet, with all the wide-eyed enthusiasm and early innovation, there’s also tremendous confusion about the mobile advertising opportunity in relation to the confidence analysts have in the overall Web advertising market (which is expected to reach $100 billion this year). The one company that knows this mix of excitement and fear all too well is Facebook.

Facebook’s IPO performance last summer epitomized this mobile monetization anxiety. After a bumpy market entrance where analysts lowered projections citing the faster than anticipated traffic shift to mobile, Facebook shares dropped slightly to $38 per share (vs. the $40-42 per share in private trading pre-IPO), which many felt was too high. Eventually the price settled at the $18-20 range after the market realized that Facebook hadn’t yet figured out how to deal with the shift of time spent to the mobile world. So, instead of the roughly $90 billion valuation that investors had been hoping for, Facebook’s valuation plummeted and media labeled the IPO a failure (basically a $40 billion black eye) thanks largely to the uncertainty of mobile monetization.

Here’s what analysts got wrong and why it matters: they overlooked several important aspects of mobile that make it a fundamentally compelling monetization medium, potentially surpassing the monetization capabilities of the desktop Web.

Like all new media, it takes time for entrepreneurs (and perhaps a few incumbents) to identify the winning elements of a new medium and to develop monetization models that take advantage of them. Case and point: the early days of television. Radio had been around for decades and so the first TV ads were basically filmed radio ads. Years later, advertising executives figured out more compelling formats for the new medium. The same applies for mobile. To date, we’ve largely ported desktop Web ads to the smartphone but I’m certain that very soon we’ll figure out the formats, targeting methods and performance metrics that are native to the mobile platform. One this is solved, the marketing dollars will start to follow.

What the analysts missed about mobile

I strongly suspect that the monetization rates and the winning players in mobile marketing will soon surprise the hand-wringing analysts who have been hesitant to get excited about the mobile ad market. Here’s why: in essence, the smartphone is a Swiss Army Knife for the digital world. Book a table for Saturday night on OpenTable. Check email. Make a bank account deposit. Check the weather. Find your next meeting location on Google Maps. Even for entertainment activities – largely social newsfeeds, games and video – it’s usually a “quick fix” during a few minutes of downtime.

Another important attribute of the smartphone ad opportunity is that users are not stuck with the pre-packaged tools. Rather, they have the freedom to download whatever apps they choose. Given the ease of the iTunes App Store, users experience little friction when purchasing and downloading new apps since their credit card is on file. This is a huge difference from the desktop Web where more barriers exist. This matters because it shows that smartphone users are willing to pay for useful or entertaining apps, and are doing so enthusiastically. According to Bloomberg and App Annie, from June to December in 2012, iPhone users spent $333 million per month on apps and in-store virtual goods. As a result, apps with high user-pay monetization have seen the largest returns in early mobile advertising, even within the currently crude smartphone ad environments.

The Birth of Ambient Context

With the possible exception of our wallets, nothing is with us more during the day than our smartphone. Unlike our wallets, it has the intelligence to understand where we are. This new combination of app data, time and geo-location context – which we call “ambient” context – has the potential to dramatically improve relevance for monetization services in several meaningful ways.

I’d bet Proctor & Gamble or Coco-Cola would be interested in spending premium CPMs to send me a notification or an offer while I’m in the grocery store – particularly if they knew from my virtual Safeway Card on my phone whether or not I was a loyal customer of their brands (or their competitors’). I also bet my fourth favorite take-out restaurant would be interested in moving up to number one by pushing me a notification for a deal on my drive home from work. Both of these are examples of incredibly premium smartphone ad “placements” that leverage the potential of ambient context.

Who will win the mobile ad game first?

As for the possibility of a Web incumbent becoming a dominant player in the mobile monetization space, my money is on (surprise) Facebook.  Facebook will continue to prove those analyst naysayers wrong. They’ve created the first truly native mobile format with Sponsored Stories and coupled it with a marketplace of advertisers.  You can see the potential of this model with the first few quarters of performance in addition to their installed based that have incorporated Facebook Connect to streamline sign-on identity management. With Facebook Connect, the social networking giant has effectively built a proprietary cross-app tracking platform that would enable their monetization platform to understand user behavior across most of the popular apps on phones today, solving the biggest problem in the smartphone medium.

The Facebook stock has returned to the $27 range, and the company is just beginning to exercise their mobile monetization muscles. Mark Zuckerberg is now describing the social networking company as a “mobile company” and announced that its mobile ad business brought in almost $300 million in revenue in Q4 2012 alone, accounting for 23% of total ad revenue. According to Flurry Analytics, of the 80% time spent in apps, a good 18% of that time is spent on Facebook.

However, there is still plenty of room for winners from the more nimble start-up space. With the mobile advertisement market expected to reach $11.4 billion this year, there is most definitely room for innovation, and the players who do it right will make it big. Very big. 

Pricing is one of the most challenging decisions for any startup. One of the simplest ways of discovering customer willingness to pay is simply to ask them.

And while at first blush that might seem a reasonable and effective solution, it is prone to wild inaccuracy. Absolute pricing judgments are hard without reference points. For example:

• How much would you be willing to pay for a new iPhone?

It’s a very challenging question to answer in the abstract. It all depends on what the phone can do and what sacrifices I would have to make to be able to afford that phone. That calculus isn’t any different for smart phones, expense management software, or flash storage. Every pricing conversation is a game of trade-offs.

Instead of asking what a customer might pay for your product, an absolute pricing question, it’s more effective to ask a relative pricing question:

• Would you be willing to pay more for a new iPhone or a new Android HTC One?
• How much would you be willing to pay for a mobile CRM compared to a desktop CRM?
• If flash storage improves performance by 30%, how much more would you be willing to pay than a standard hard disk?

These comparative questions establish a point of reference for the customer and force them to make a relative value judgment by comparing a new product to an existing product where value and price are known. This is much more valuable data because the opinions will reflect more accurately the feedback you will receive in the market.

No decision is ever made in the abstract – there are always trade-offs because every customer’s resources are finite. Purchasing decisions are no exception. The hypothetical “how much would you pay for X?” question will always generate bad data because the decision is made in the abstract.

On the other hand, comparative pricing questions establish relative value between existing products. You will be able to quickly tell which products are more important and valuable. And in talking to your potential customers, you will better understand both the competitive solutions and the complementary solutions for your product.

Most importantly of all you’ll understand the pricing decision process for your customers. You may very well find different segments of customers have radically different decision-making processes and your products features and pricing should reflect those differences.

I use relative pricing questions in researching the market opportunities for startups and on the whole they shed much more insight into the customers’ viewpoint than absolute pricing questions. I hope you can use it in your pricing discovery processes and find it to be as effective as I have.

 

*Reposted from Tomasz’s personal blog, which you can read here.

As you may have heard, Redpoint has invested in Twilio. We have been admirers of the company for some time and are thrilled to welcome them to the portfolio.

By building an incredibly powerful and easy to use communications API platform with a disruptive business model, hundreds of thousands of developers have leveraged Twilio to build powerful cloud communication solutions. It is highly likely that all of you – at some point – have received a text or placed a call powered by Twilio. Twilio’s customers focus on what differentiates their own service, not having to concern themselves with scaling telephony infrastructure, investing in expensive hardware and managing complicated relationships with service providers.

Twilio is also a part of a broader trend towards services and APIs catering directly to developers. At Redpoint, we believe in the power of the developer in both early stage companies and large enterprises. More and more, developers are making critical decisions regarding the nature of the products they are building. Like Redpoint’s earlier investments in Heroku and Stripe, Twilio is at the forefront of this movement, and we can’t wait to watch what they will continue to do.

We are thrilled to welcome Jeff Lawson and the entire Twilio team to the Redpoint family and look forward to working together for years to come.

We all type quite a bit. I’ve never measured how many words each day I type but I imagine it’s probably a few thousand each week between my laptop and my mobile phone and across emails and blog posts. And no one can deny the toll this takes on our wrists.

In the past week, I’ve been suffering from some carpal tunnel pain particularly as I’ve been coding more. Coding often requires all kinds of odd key combinations because of the varying syntaxes of CSS, Ruby, R, MySQL and the English language.

There are all kinds of solutions to this problem, ergonomics being the first. But I can’t imagine in 10 years, as the volume of indications continues to increase, that we will all still be typing away on these primeval keyboards.

So, instead I’ve adopted dictation. Initially, I used the built-in Apple dictation feature and then tried using Google’s. More recently I’ve switched entirely to Nuance’s Dragon. This blog post is entirely dictated and all of the posts for the last two weeks also.

I remember using MacSpeak 10 years ago which was Apple’s speech recognition effort. Who could forget the frustration that followed the initial hope of being able to control a computer through voice? Since then, huge leaps have been made. Today, accuracy is close to 99%. A good analogy to demonstrate the progress might be comparing Apple’s Newton and the iPhone.

In five years, I believe voice will be as common a mode of data input as keyboards. It’s more natural to speak to a computer rather than type because the computer can respond at the pace of your thoughts. I spend less time responding to emails because of dictation. It’s also much faster pen these posts because instead of focusing on spelling or typing or corrections, I’m focused on the content and the computer takes care of the rest.

Startups are taking notice and beginning to differentiate through voice. Roobiq is a CRM that solves the data entry problem through voice. Siri and Google Now are the more obvious examples. These will only become more common and particularly on the phone.

At first blush, it might seem that the smart phone ushered out the era of voice in favor of SMS and short form messaging and mobile application use. After all what fraction of time spent on a mobile making telephone calls? But a more accurate refinement of that statement that the mobile phone ushered out the era of synchronous voice.

The mobile phone will be the harbinger of the asynchronous voice-to-text era. And our wrists will be the better for it.

 

*Reposted from Tomasz’s personal blog, which you can read here.

 

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Do you measure your product’s time to utility? If not, you should.

The best products reward users as quickly as possible after installation and account creation. But it’s easy to forget about this and as a result, watch conversion rates from download/install-to-active fall.

CRM products have the longest time to utility of most software products. The end user, a salesperson, logs into a blank Salesforce installation. She must type in a bunch of data about a customer. If the customer account closes, great. But it’s not until twelve or eighteen months later when the customer considers renewal and she has to strategize how to best pitch the customer that this salesperson benefits from any of the data entered into the CRM.

On the other hand, sales managers’ time to utility for CRM products is much faster. As soon as the team enters in current pipeline data, he can see the sales forecast for the current month.

This difference in time to utility is one of the causes of the tension in adopting CRM tools. It’s present in many enterprise tools that generate reports for management. because there’s a time to value mismatch between the roles.

Consumer products tend to offer faster time to utility. Google search, Facebook news feed, Twitter feed. Immediately after searching or logging in, the user receives some value: the right results or some relevant updates.

But if you think about the most frustrating software to use, by and large, the time to utility will be long and the magnitude of that utility will be small.

Measure your time to utility for all your product’s segments and try to minimize it. You’ll see the impact at every step of the conversion funnel.

 

*Reposted from Tomasz’s personal blog, which you can read here.

I’m excited to announce Redpoint’s investment in Scripted, a human capital marketplace startup with a novel twist that is fueling the next wave of online marketing.

The Opportunity

Over the last few years, the rules of online brand marketing have quietly changed in a fundamental way, thanks to the spread of social media and the accompanying proliferation of publishing tools and platforms. As a digital marketer, it’s no longer sufficient to litter the Web with banner ads and pre-roll videos to get your message out there. Consumers have increasingly become blind to these “ads,” and are instead busy consuming and engaging with content. Be it blog posts, Facebook posts, Twitter posts, articles, reviews, or tips (or white papers for the B2B crowd) – the content types and platforms continues to grow. Consumers are now demanding more from marketers than catchy ads; they expect a conversation. And marketers don’t have a choice – they must publish good content regularly across all relevant platforms, or risk losing ground to their more social and content savvy competitors.

Trouble is, publishing good content regularly is hard for most online marketing departments. Most don’t have the time (or, let’s face it, the capabilities) to come up with the ideas and the words a week’s worth of content. What they need is a virtual content creation department – an on-demand, domain expert network of skilled content creators that can help with both what to say, and how to say it.

The Solution

That’s where Scripted comes in. Scripted has attracted 10,000’s of freelance writers with the promise of supplemental work. Unlike most other freelancer marketplaces, Scripted takes responsibility for quality of the work product delivered and, therefore, for the satisfaction of the marketers demanding the content. Using the Scripted platform, content marketers specify the basics of piece(s) of content they’d like to “buy,” and Scripted handles the rest. To insure quality and performance, Scripted employs several techniques, including a Wikipedia-like peer review system, a customer feedback loop on every job, and a programmatic cataloguing of freelancer domain expertise through the crawling of every piece of content produced on the platform. By leveraging the Scripted platform, the content marketer gets the content producer that is best-suited for the specific content job, and the best content producers get the most relevant work.

One thing from our investment diligence that got us really excited about Scripted was that both the demand-side and supply-side found the experience on the platform superior to the other approaches that they’ve tried. On the demand side, content marketers just want high quality content, period. They don’t want to waste time and effort sifting through 100’s of freelancer bios, haggling over compensation and then hounding the freelancer to get it done on time. On the supply side, freelancers want to let their work speak for itself, and to get as much work as they want within their areas of interest and expertise. The Scripted model delivers both.

Attractiveness of Marketplaces

At Redpoint, we like marketplace models a lot. If done right, there are natural network effects to marketplaces which provide barriers to entry, sustainable competitive advantage and, with a little luck, winner-take-most dynamics in terms of market share (and ultimately, company value). We’ve seen it in the vacation rental market with our investment in HomeAway, and in the online ad space with our investment in Right Media, and we’re seeing it in other markets at Adap.tv, Just Eat, Axial Market, and BlueKai. The growing organic demand and high customer satisfaction levels that Scripted is enjoying gives us encouragement that we will see it in the content creation market as well. We’re thrilled to be in business with the Scripted co-founders Sunil Rajaraman and Ryan Buckley, and look forward to working together to scale the Scripted platform for content creation.

 

You have just launched your new software start up. The last webpage to go up on the website is the pricing page. Like many other SaaS startups, you decide to employ some version the three pane pricing plan: first the free version, second a paid upgrade costing between $5-$40 per month, and third an enterprise tier with a “Call for Quote” in place of the price.

A few days after you launch, an enterprise customer contacts you asking for a quote. You respond with an offer that significantly higher per seat than the paid plan. Let’s test the waters, you think. And having seen your pricing page, the enterprise customer asks why the enterprise tier is so much more expensive than the paid tier. After all, the cost to deliver the service for each kind of user, whether individual or enterprise, is the same.

Serving Two Customers at the Same Time

This dilemma is called channel conflict. The pricing page is trying to serve two contrasting customer segments: the individual who wants to upgrade and the enterprise looking for a companywide or team-wide plan.

Each of these customers perceive the value of your service differently and each has a wildly varying willingness to pay.

Typically, the individual user is on a budget. They might be paying for the service out of pocket and are generally price sensitive. As the founder, your strategy might be to maximize the number of individuals on the service in order to drive bottoms up adoption. So instead of maximizing revenue from this segment you price the paid tier to generate profit based on the cost to acquire the customer and cost to serve the customer. This is cost-based pricing – charging the customer the your cost to deliver the service plus some mark-up.

On the other hand, the enterprise customer will derive significantly more value from the use of your service than the individual [1]. Additionally, this customer segment has the capacity to pay orders of magnitude more than an individual who upgrades to a paid tier. So quite naturally you want to capture some fraction of that value. This is called value-based pricing.

Rationalizing Channel Price

It’s hard to convince one customer segments to pay based on cost-based pricing and another to pay on value-based pricing on the same page for nearly the same service. So, you have two choices.

First you can distinguish the paid and enterprise products by offering enterprise-level support, service-level agreements, and IT management features that aren’t available in the paid-tier in order to justify the value based pricing to the enterprise customer. Many startups pursue this route like Yammer.

Second, you can create different websites or even brands for different segments. Within each website, one segment is prioritized and the marketing copy, pricing page, and other content all serves that particular segment. In retail, brand name drugs and generics serve different customer segments the same products at different prices (value vs cost-based pricing). This strategy can be harder for start ups because of the complexities managing two or more friends at the same time.

Whichever route you decide for your startup, the most important thing is to clearly determine which customer segments you’ll be charging on a cost basis and which you’ll be charging on a value basis. Clearly separating the value proposition either with feature disparity or by creating different brands will be critical to supporting the pricing differences between the two segments.

Do you have other strategies for mitigating channel conflict? Let me know on this Branch.

Footnotes: [1]: According the US Census, a 5k person organization pays more than 50% more in payroll than a 10 person company. So at the very least, in larger organizations, an employees time is worth 50% more to an employer.

 

*Reposted from Tomasz’s personal blog, which you can read here.