Benchmarking your SaaS business

Oracle Social Insight

Pacific Crest and David Skok have released a survey benchmarking SaaS metrics for early and growth stage companies.

The entire report is well worth reading.

Redpoint VC Tomasz Tunguz (@ttunguz) lists his 6 most important benchmarks and observations from the report.

1. Inside Sales Driven Companies Grow Fastest

Inside sales driven distribution companies grow about 40% faster than companies using field sales, web sales or channel, or about 37% revenue growth per year.

2. Price the Product Between $1k to $25k Annually to Optimize Growth

Companies with contract sizes of $1k to $25k grow the fastest, about 26% faster or 35% y/y. There are two reasons to support this pattern. First, purchases under $25k tend to require fewer approvals which decreases sales cycle. Second, these accounts can be closed by inside sales reps which are far less expensive than field sales. On the same sales investment, a startup may be able to hire three or four inside sales reps for each field sales rep.

3. The Cost of Customer Acquisition is About 11 Months’ of Revenue

The median startup spends about 92% of first year average contract value on the sale, implying an 11 month payback period on the CAC. An additional months’ revenue is required to upsell a customer and about the same is required to close a renewal.

4. Upsells are a Secret to Growing the Business Twice as Fast

The top 50% of growers generate more upsell business than their slower growing competitors. The difference in growth rates becomes more pronounced as the business scales into the $15M+ in annual revenue range where upselling companies grow more than twice as fast. In the early days of the business, net new account growth is a priority for most businesses but the growth rate data and CAC data indicate that upselling existing customers is an important and underemphasized key to growth.

5. Sales commission as % of ACV is ~9%

the typical ACV/compensation ratio was about 4:1 but in practice that number is closer to 10:1.

6. Median Monthly Revenue Churn is 0.75%

Churn rates vary dramatically by product category and customer. SMBs churn with greater frequency than enterprises and marketing software has an intrinsically greater churn rate than accounting software, so the median may be misleading for particular categories. This means each year, the median business loses about 10% of its revenue to churning customers.

Creating a new market

HealthKit-HomeKit

 

What lessons for the emerging Internet of Things (IoT) industry can be learned from companies who have successfully created new markets and have become the new market leaders?

The creation of the mobile market provides lessons for companies who aspire to create and lead the IoT market.

Let’s look back…

Apple created a new market by empowering thousands of application developers to define, design and develop solutions for a broad range of consumer needs.   They focused on a developer-centric business model and gave developers the tools and platforms to innovate thousands of applications.

Google created a new market by empowering thousands of device companies to ship millions of Android devices and innovate quickly in the fast growing smartphone industry.  They too provided the platform and tools to make it easy and profitable for entrepreneurial developers to launch their innovations and as a result they created and led a new mobile device market.

Over the past 5 years, the creation of the mobile market provides clear lessons for the emerging market IoT market.

Both Apple and Google created and won the mobile market because they pursued different business models from their competitors at the time – Nokia, Microsoft and Blackberry.   Instead of trying to do everything themselves, Apple and Google focused their business model on creating a network and ecosystem of innovative developers who launched thousands of apps and devices that neither company could ever create on its own.  We’ve seen that this ecosystem-centric business strategy creates new markets that are several times bigger than the closed potential market could ever become.

The same will happen in the creation of the Internet of Things market.  To create and win the IoT market, companies should be driving a strategy focused on creating an ecosystem of developers through developer-centric business models and initiatives.

Look at the IoT strategy Apple announced at their recent developer conference.   Apple didn’t announce new devices or applications.  They announced new IoT related APIs called HealthKit and HomeKit.    These new APIs make it very easy for developers to build IoT applications linked to Apple devices and platforms.  Developers have an easy path to innovation and users gain new connected applications.  Apple continues to build an ecosystem of developers and the opportunity to offer new value to users based on the data generated by HealthKit and HomeKit APIs.

Yet, some of today’s early IoT companies are still focused on solving technical challenges, selling their own devices or developing their own applications.  They are not following the market creation strategies proven so successful in the mobile market.  They are not focused on empowering developers to innovate.  Instead, they are offering closed systems, insufficient APIs, weak tools, multiple platforms that are fragmented and no marketplace (think app store or appexchange).  These strategies are preventing developers from innovating and restraining the IoT market from accelerating.

Aspiring leaders of the emerging IoT market should follow the market creation strategies that were so successful in accelerating the creation of the mobile market.   They should focus on linking their products and platforms with the innovation and market demand created by developers through open APIs, powerful tools, developer friendly policies and a marketplace to monetize their innovations.

Otherwise, early IoT companies risk becoming a commodity in an IoT market dominated by someone else’s ecosystem.

 

Apple Silently Becomes One Of The Most Influential Companies In The Smartwatch Industry

Originally posted on TechCrunch:

Somehow, despite the fact that Apple hasn’t even announced a smartwatch product, the company is still the second-most influential corporate entity in the smartwatch industry, just behind Samsung.

Samsung has already released a handful of different Smart Watch offerings, and Google, ranking third on Appinions Smart Watch Influencer report, has also shipped various hardware products. Still, the market waits with bated breath for what Apple might do. Despite silence. Remember, all Apple has said about smartwatches is “no comment.”

Behind Samsung, Apple, and Google, other smartwatch companies such as Motorola, LG, Acer, Pebble, Sony, Intel, and Microsoft close out the top ten.

Early entrants like Pebble are reportedly dropping off in terms of influence.

Perhaps more interesting, Tim Cook ranks third among influential executives in the smartwatch space, behind Nike CEO Mike Parker and Misfit Wearables CEO Sonny Vu, respectively.

As we’ve already discussed, Apple has yet to release a…

View original 96 more words

IoT – Everything to Everything Communication

 

The-Internet-of-Things

Xively is a leader in the evolution of the Internet of Things and provides free, open and supported libraries and certified Xively Enabled™ hardware platforms to make connecting to the Internet of Things simple, intuitive and fast.

In this infographic, Xively outlines how the Internet of Things is rapidly transitioning from “What” and “Why” to “When” and “How.”

The Future of the Internet of Things

Product Strategy Lessons

Product Strategy

The following product strategy lessons were pulled from Paul Adam’s post “Product Lessons We Can Learn from Google+“.

The reshuffles in management in Google+ recently attracted a lot of press comment and speculation. I thought it an appropriate time to look back on the last couple of years and see what broader product lessons we can learn from the inception, launch and evolution of Google+.

1. Build around people problems, not company problems

2. Perceived benefits need to be greater than perceived effort

3. Ruthlessly focus and descope, be patient, the internet is young

4. Embrace the idea that life is messy

5. A fast follow product strategy doesn’t work when you have network effects

6. Google+ suffered shiny object syndrome

7. People need clear conceptual models that exist in real life

8. Distribution often trumps product

So what to do next

Remember that product strategy means saying no. To understand what people problems Google+ might solve, focus on a tiny number of these, possibly even just one, and make this simple to understand, just as Instagram, Snapchat, WhatsApp, Secret have done.

Google+ is incredibly complex and hard to understand. Simplify the product offering by killing features, and lowering the effort required to get value out of it by killing many of the choices in the UI.

Finally, and most importantly, it needs to build upon established real world social norms and conceptual models. We’re still only getting started with social software.

Whilst social science patterns are very well established, there are no established ways to build social products. Copying competitors is unnecessary. There are so many things we can make better for people if we carefully and deliberately observe and understand their world.

image source – Intercom – Product Strategy in 7 minutes

Data from Everywhere, Personalize Anywhere

Personalized Experiences

This week Facebook unveiled a new mobile ad network at its F8 conference. The purpose of the network is for Facebook to sell ads outside of Facebook.com and outside the Facebook mobile app.

If Facebook’s direction or strategy isn’t clear, let me spell it out: Harvest personal data from multiple apps, then sell personalized advertising in multiple locations.

This is an important evolution in the social / mobile advertising business model with implications for the growth of real-time, context-aware personalized experiences for consumer and business users.

The old social advertising model was simple: get everybody to gather at a single location like Facebook and Twitter, harvest social signals at that location, and sell ads that would be displayed at that location. Everyone and everything in one place.

Facebook used F8 to describe their evolution to a new model for real-time, context-aware personalized experiences, advertising and apps.  Twitter, Facebook, Google, Foursquare are all managing their portfolio of social apps as stand alone offers that enable the harvest of social activities to drive personalized, contextual experiences across other social apps.

The new model is to harvest social signals from wherever and sell personalized ads wherever.

Of course, none of the social networks are going anywhere. They’re still important both to their companies and to their users, and they still play an essential role in user identity and data harvesting and, for Twitter and Facebook at least, as places to display advertising.

What’s important for these companies from a future-facing business perspective is to have multiple mobile apps that harvest multiple dimensions of personal data that can be applied to highly customized and personalized mobile experiences and advertising at multiple locations.

This new model of harvesting data from everywhere to personalize the experience anywhere requires a database that lets you:

  • collect big data in real-time
  • map IDs across Web, mobile, search, video and other channels
  • combine real-time data with insights from big data analytics
  • look up as much data as you can, as fast as you can, in order to put precisely the right message in front of the right person at the right time

To be successful in this new model, every player, not just ad-tech companies and social networks but every enterprise, must build some form of a universal context store.

That’s why Oracle recently acquired BlueKai, a Data Management Platform (DMP) powered by Aerospike, at the core of the modern enterprise.

Oracle Marketing Cloud

Aerospike’s database powers the “universal context store” for major players in the real-time bidding ecosystem. This ranges from ad exchanges like AppNexus, to demand-side platforms (DSPs) like The Trade Desk, supply-side platforms (SSPs) like Pubmatic, data management platform (DMP) providers like eXelate, and companies in mobile, search, gaming, video and more.

It is Aerospike’s realtime universal context store that powers today’s leading personalized experiences at scale.

With Apple and Amazon setting the standard for personalized experiences, consumer and business uers expect instant and intuitive services no matter what device or channel they use.    Enterprises must deliver on these expectations by sensing and analyzing user context and interaction data from web, mobile, offline and online channels to gain immediate insights, context and relevance to respond with just the right content, on the right channel, in real-time.

 

 

Sources:

“Why the Social Networks Are Falling Apart,” Mike Elgan, @MikeElgan, Computerworld.com

“BlueKai Achieves Speed at Scale…”, Aerospike, http://www.aerospike.com/blog/bluekai-speed-scale-simplicity/

“From Everywhere to Anywhere…”, Aerospkie, http://www.aerospike.com/blog/everywhere-anywhere-universal-context-store/

Image – http://www.certain.com/index.php/resources/webinars/

The Personal Data Economy

 

Your Data for Sale

 

Anya Skatova is a research fellow at the Horizon Digital Economy Research Hub, based at the University of Nottingham and funded through RCUK’s Digital Economy theme.

In her research, Anya asked a group of participants to think about different types of data, including physical location GPS, electricity bills, broadband usage, mobile phone bills, loyalty cards, internet browsing, demographics, social networking and bank statements. She wanted to find out whether people see these different types of data differently and how concerned they were about their information being protected.

When asked about comparing their security concerns vs. the benefits of certain types of personal data, users felt security was important when talking about their physical location, mobile phone bills, social networking or bank statement data. They felt that this type of data was personal and should only be shared when it is necessary to do so. When considering loyalty card data, users felt the benefits far outweigh security concerns saying that the information contained on loyalty cards “can’t harm me or anyone”.

Security vs Benefit of Personal Data

 

In a different study, Anya found that people value different data differently. People were willing to pay the highest amount to protect bank statement data, social network profiles and history and physical location data. People care a little bit less about broadband bills, mobile phone bills, loyalty cards, internet browsing history, demographic information, but they will still pay something to protect it.

How much to secure your personal data

Increasingly, we will see the emergence of personal clouds, data exchanges and data currencies that allow people to determine how valuable and shareable different types of personal data is to them.

A recent report from the World Economic Forum, prepared in collaboration with the Boston Consulting Group, explores new approaches for managing and sharing personal data, and suggests that we need to find innovative ways of using, rather than trying to safeguard, data. To read the report, please visit: www.weforum.org/issues/rethinking-personal-data.

Finally, the team at Vibrant Data developed the following video to summarize the challenges of growing the Personal Data Economy and identified 4 grand challenges including (1) access, (2) trust (3) data literacy and (4) openness.