Optimizing “Freemium”

Making Freemium Model Work

From Ava Seave at Forbes:

Professors Vineet Kumar, Clarence Lee and Sunil Gupta have been working on understanding the economic dynamics of freemium pricing by looking at customer behavior; their co-authored paper and an article by Kumar in the Harvard Business Review shed light on how companies can maximize profit, get upgrades and encourage referrals.

In a recent interview, Kumar says he has found “patterns,” in the data, although he is reluctant to say they can draw actual conclusions. “The shape of the pattern may change a little based on the setting,” says Kumar. “But what I tried to draw is generalizable and applies to most freemium companies.”

As companies make decisions about how their freemium products are designed and priced, they should consider the following:

  • When your product is not attracting enough new users, it means “your free offers are not compelling enough and you need to provide more or better features free.”
  • When your product generates lots of sign-ups, but few decide to pay, it means “your free offerings are too rich and it’s time to cut back.”
  • When customers don’t understand why they should upgrade, it’s going to be tougher to move people to the paid product. What to do? Kumar gives the example of LinkedIn LNKD -0.57%, where he says “the advantages of upgrading are murkier” than they should be. He believes the company could monetize more users if this was corrected.
  • When your conversion rate is too high, you may not be attracting enough trials because “your free product is not very compelling, which will limit your potential acquisitions.”
  • Early adapters are less price sensitive than later adapters. Rates of conversion from free to paid users vary over the life cycle of the product, with early adapters to the product probably converting at a much higher rate than later adapters.
  • Companies will notice the pattern of a declining conversion rate — initially.  When you have “an introduction of new features, the conversion rate starts picking up.” Kumar gives an example using Hulu. They probably see conversion rates increasing when they’ve “introduced a new show, or new episodes of a show that are in the premium version, not in the free. It’s not surprising when you have more of a value proposition from a consumer’s perspective it increases your upgrade probability.”
  • Referral bonus programs – where current customers are rewarded for referring new customers– are effective, but if they are too generous, the program won’t encourage multiple referrals.

Creating a Market with Dynamic Pricing

Uber Car

From James Surowiecki article titled – “In Praise of Efficient Price Gouging

“In the four years since the car service Uber launched, it has been beset by criticism from myriad groups, including city officials annoyed by its sometimes cavalier attitude toward regulation and taxi companies annoyed by increased competition. Some of the harshest criticism, though, has come from an unlikely place: Uber’s own customers. Thanks to its reliance on what it calls “surge pricing”— meaning that during times of high demand, Uber raises its prices, often sharply—the company has been accused of profiteering and exploiting its customers. When Uber jacked up prices during a snowstorm in New York last December, for instance, there was an eruption of complaints, the general mood being summed up by a tweet calling Uber “price-gouging assholes.”

Uber’s algorithm (which it has been refining since 2011) is the company’s greatest asset and most significant innovation, allowing it to find the price that will attract drivers—whom, as independent contractors, it can’t order onto the road—without alienating customers.

The basic reality of Uber’s business model is that when people want a ride the most, it’s likely to be the most expensive. This will always be irritating, just as exorbitant prices for last-minute airline tickets are irritating. But over time, surge pricing will also become more familiar and less surprising.

Utilities are now starting to use dynamic pricing for electric power, which can help prevent blackouts at times of high demand and promote energy conservation more generally. A new startup called Boomerang Commerce, which is led by former Amazon engineers, has been helping online retailers set prices dynamically. Dynamic pricing is the future, even if the road to get there will be bumpy.”

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…

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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