According to the IT Services Marketing Association, marketing budgets as a percentage of revenues are at an all time low. Marketers will continue to face budget challenges until we can demonstrate the value of our marketing programs and they contribute to the business.

According to a spring 2010 study by Econsultancy and analytics firm Lynchpin, over half of the responding companies indicated that the biggest barrier to an effective measurement strategy is a lack of budget and resources and less than one-third selected any other issue. Unfortunately, we’re in a Catch-22. Being able to measure and improve performance in order to secure program budget takes investment; investments we can’t secure funding for until we can demonstrate value.

How can we break the cycle and secure the funding needed to improve our effectiveness and accountability? The first step is to synchronize marketing activities and costs with business outcomes. This alignment effort should be incorporated into the marketing planning and budgeting process. The second is step is to make sure we have the right skills, infrastructure and performance management systems in place. Escape the Catch-22 by investing in three key areas: training, infrastructure, and benchmarking.

Invest in Your People

A recent study by Omniture confirmed the findings in our annual MPM study, that while marketers said it is important to measure marketing costs, orders, average order size and conversion rates, they tend to track metrics they have the greatest ability to measure. According to their study, the biggest reason marketers struggle to move from measuring metrics to measuring performance is talent.

Over half of the respondents in the Omniture study indicated that they don’t have the training and support need to develop the analytical skills within their ranks in order to glean the valuable insights needed from the data available. What’s holding these organizations back? You guessed it. Budget was the number one reason cited for the lack the talent. And of course, until we have these capabilities it will remain difficult to leverage analytics and data.

Invest in Your Infrastructure

Let’s say we have the analytical talent. The next potential hurdle is being able to translate insights from analytical systems immediately into marketing decisions and then use operational systems to execute on these decisions. The challenge is that often these insights are derived from various disparate data sources that house various types of customer data — such as customer profile information and segment data, customer transaction history, and communication history along with lead scoring models. Top that off with the need to append external data related to the market and competitors.

And all this data probably requires systems that can recognize the same customer/prospect across different channels and the ability to access and update information in real time. Real-time and near real-time updates alone require fundamental changes in how marketing databases are designed, managed and analyzed. Organizations often need to be able to revise business rules and execute analytics and update models as quickly as new data becomes available.

All of this explains why the entire marketing infrastructure is increasing in complexity at the same time that speed has become a dominant requirement. As a result marketing systems and processes need capabilities an order of magnitude better those most marketing organizations are using today. So improving marketing effectiveness will take revisiting and investing in the marketing infrastructure.

Invest in Benchmarking

A benchmark is defined as the standard by which all items of similar nature can be compared or assessed. Benchmarking is a self-improvement tool. It allows you to compare yourself with others, to identify areas of comparative strengths and weaknesses and learn how to improve. Robert Camp who published the first book on benchmarking suggests that by using benchmarking to identify and replicate “best practices,” a company can enhance its business performance.
We need benchmarks to know what and by how much we need to improve yet, according to our annual MPM study, only a third of the 400+ respondents indicated they were satisfied with the marketing performance skills. Sixty percent of the respondents don’t do any kind of auditing when it comes to data, analytics, performance target setting, systems, processes, measurement, and reporting. If improving your marketing performance is important to your organization, then it’s time to invest in benchmarking.

In a matter of months many marketing organizations will begin to work on their next fiscal year plan and budget. Now is the time to take stock of your talent, infrastructure and how you stack up against peers and best-in-class performers so you can request the funds needed to improve your marketing organization on all fronts.

We all understand the need for Marketing to positively and directly impact the sales cycle and win ratio. This is still an area of challenge for many marketers.Two studies this past spring, the CSO Insights 16th annual sales performance study of 2,800 companies and an Aberdeen study conducted with 472 participants, brought to the light the need for marketing to do a better job when it comes to both quality and quantity of leads.

When these are out of kilter, sales cycle increase and the lead-to-conversion ratio declines. Both of these are critical metrics for marketing to monitor, measure and manage. Our ability to affect these metrics is indicative of how well Marketing is affecting business results.

Sixty-three percent of the respondents in the CSO Insights study reported that the quality and quantity of leads generated by marketing need improvement. The Aberdeen study found that 59% of the respondents don’t convert enough leads to sales.

The Aberdeen study revealed that Best-In-Class companies convert 44% of the leads to sales compared to an industry average of 26% and have experienced 8.4% year-over-year reduction in the sales cycle time compared to a 1.3% reduction by the industry average.

What do the Best-in-Class do differently?
Best-in-Class Marketing organizations embrace performance analytics, invest in training and technology, and streamline their processes in order to shrink lead turn-around time and response to customers. And they improve their understanding of the customer buying process and organize their marketing and sales processes around the way customers’ buy.

These six steps will help you engineer your pipeline around the customer buying process:
1. Create a detailed list of your customer’s entire buying process. (customers in different industries or different sizes may have different processes, so one process may not “fit all.”)
2. Organize the list in the order you think they occur.
3. Validate the process with your customer advisory council or board or other “friendly” customer.
4. Reconfigure your opportunity pipeline stages using the customer buying process so that your stages are linked to specific observable incremental customer buying behaviors.
5. Revise your lead scoring methodology to match the customer process to improve the handoff between sales and marketing, reduce leakage, and improve the conversation rate.
6. Synchronize your marketing and sales activities with the customer process.

The Value of Pipeline Engineering
Pipeline engineering helps identify where bottlenecks or gaps exist. For example, maybe there are too many contacts and the organization cannot process them quickly enough. Or there is a dearth of qualified leads indicating that the sales team won’t be able to produce the needed number of deals. We can also use the pipeline to compare a program’s performance to industry standards. Pipeline engineering allows you to calibrate your marketing and synchronize marketing and sales efforts. It truly is the first step in marketing and sales alignment.
This methodology also allows you to take a more scientific approach to opportunity and customer development enabling you to understand what is happening in the buying process and where to make adjustments. Pipeline engineering enables you to manage opportunities and improve the lead-to-win ratio.

See original post at cdixon.org – chris dixon’s blog:

Google recently added a caustic warning message when users attempt to export their Google Contacts to Facebook:

Hold on a second. Are you super sure you want to import your contact information for your friends into a service that won’t let you get it out?

Facebook allows users to download their personal information (photos, profile info, etc) but has been fiercely protective of the social graph (you can’t download friends, etc). The downloaded data arrives in a .zip file – hardly a serious attempt to interoperate using modern APIs (update: Facebook employee corrects me/clarifies in comments here). In contrast, Google has taken an aggressively open posture with respect to the social graph, calling Facebook’s policy “data protectionism.”

The economic logic behind these positions is a straightforward application of Metcalf’s law, which states that the value of a network is the square of the number of nodes in the network*.  A corollary to Metcalf’s law is that when two networks connect or interoperate the smaller network benefits more than the larger network does. If network A has 10 users then according to Metcalf’s law its “value” is 100 (10*10).   If network B has 20 users than it’s value is 400 (20*20). If they interoperate, network A gains 400 in value but network B only gains 100 in value. Interoperating is generally good for end users, but assuming the two networks are directly competitive – one’s gain is the other’s loss – the larger network loses.

A similar network interoperability battle happened last decade among Instant Messaging networks. AIM was the dominant network for many years and refused to interoperate with other networks. Google Chat adopted open standards (Jabber) and MSN and Yahoo were much more open to interoperating. Eventually this battle ended in a whimper — AIM never generated much revenue, and capitulated to aggregators and openness.  (Capitulating was probably a big mistake – they had the opportunity to be as financially successful as Skype or Tencent).

Google might very well genuinely believe in openness. But it is also strategically wise for them to be open in layers that are not strategic (mobile OS, social graph, Google docs) while remaining closed in layers that are strategic (search ranking algorithm, virtually all of their advertising services).

When Google releases their long-awaited new social network, Google Me, expect an emphasis on openness. This could create a rich ecosystem around their social platform that could put pressure on Facebook to interoperate. True interoperability would be great for startups, innovation, and – most importantly – end users.

* Metcalf’s law assumes that every node is connected to every node and each connection is equally valuable. Real world networks are normally not like this. In particular, social networks are much more clustered and therefore have somewhere between linear and exponential utility growth with each additional user.

I never had the opportunity to invest in YouTube but I have to admit that if I did I probably would have passed (which of course would have been a huge mistake). I’d been around the web long enough to remember the dozens of companies before YouTube that tried to create crowdsourced video sites and failed. Based on “pattern recognition” (a dangerous thing to rely on), I was deeply skeptical of the space.

What I failed to appreciate was that the prior crowdsourced video sites were ahead of their time. YouTube built a great product, but, more importantly, got the market timing just right. By 2005, all the pieces were in place to enable crowdsourced video – the proliferation of home broadband, digital camcorders, a version of Flash where videos “just worked,” copyrighted web content that could be exported to YouTube, and blogs that wanted to embed videos.

Almost anything you build on the web has already been tried in one form or another. This should not deter you. Antecedents existed for Google, Facebook, Groupon, and almost every other tech startup that has succeeded since the dot-com bubble.

Entrepreneurs should always ask themselves “why will I succeed where others failed?” If the answer is simply “I’m doing it right” or “I’m smarter,” you are probably underestimating your antecedents, which were probably run by competent or even great entrepreneurs who did everything possible to succeed. Instead your answer should include an explanation about why the timing is right – about some fundamental changes in the world that enable the idea you are pursuing to finally succeed. If the necessary conditions were in place, say, a year ago, that might still be ok – YouTube happened to nail their product out of the gate, but if they hadn’t a company started later might have succeeded in their place.

Often the necessary conditions are only beginning to emerge and knowing when they will do so sufficiently is very hard to predict. We all know the internet will become fully social, personalized, mobile, location-based, interactive, etc. and lots of new, successful startups will be built as a result. What is very hard to know is when these things will happen at scale.

One way to mitigate timing risk is to manage your cash accordingly. If you are trying to ride existing trends you should ramp up aggressively. If you are betting on emerging trends it is better to keep your burn low and runway long.  This takes discipline and patience but is also the way you hit it really big.

The weather just keeps getting better and better to share some pizza and beer at a nice indoor bar while talking with Eastside tech entrepreneurs. Come join the fun, no experience necessary.  This month’s next TechFoams will be November 17th, at the usual time and place.  Thanks again to nPost for buying the first two pitchers at each event.

A few months ago I created a fun device at WPEngine to focus everyone’s attention the most important thing.

If nothing changes, when will you run out of money?

Sometimes fear is a good motivator. In this case, fear takes the form of a tiny spreadsheet:

I know it’s looks silly to name the very day that we run out of money — why not include the hour and minute too? Clearly it’d be more accurate to say “sometime in Q1 2011.”

But the goal here isn’t accuracy, it’s motivation and focus. Nothing drives correct thinking about getting to profitability like facing your own demise. No hedging, no estimating, no complex Profit & Loss projections, just a date.

Confronted by an ultimatum, your thoughts crystalize. Maybe some of those things on your to-do list for this week aren’t as important as you thought. Maybe you could get v1.0 out the door faster. Maybe you should be spending your time getting revenue instead of ruminating on the philosophy of startups with strangers in the comment section of some blog. (Err, except for this blog of course!)

[UPDATE: @rjrodger created an awesome, easy tool for this at http://startupdeathclock.com/]

So did it work?

Four minutes after emailing this internally someone responded with a way for us to launch a week earlier than planned. Three minutes after that another email appeared with a focused list of “must-haves” before release (with a few items omitted from the previous “must-have” list).

Yeah, it works.  Try it!

Tracking Progress

Of course as you improve your profitability — hopefully through more revenue but possibly through lower expenses — this date will change. Tracking that change over time is an easily-digestible demonstration of progress, and/or acceleration of progress.

Here’s our actual data:

It’s easy to see that we’re replacing our burn to some extent, with a notable down-spike when we make a new investment that eats cash. It’s a particularly nice way to visualize just how big of an investment we made, and how subsequent income replaces it (or doesn’t).

Even better: Tracking your break-even date

Tracking “death” is good motivation, but it’s so negative! If you actually have revenue — and it’s growing, and growing faster than expenses — there’s another more positive and more useful way to plot your progress: Your anticipated break-even date.

Here’s how we generate this date for WPEngine. First we track our expenses measured daily as “monthly accural revenue for past 30 days.” Put another way, if 100% of our expenses for this month (salaries, servers, bandwidth, credit cards) were paid on a single day, how much would it be?

Second we track the same concept but with revenue. Our customers pay us monthly, but everyone is on a different day of the month (specifically, 15 days after they signed up, when their trial expired).

The result looks like this (dollars intentionally omitted… there’s a limit to transparency!):

We can see that revenue is catching up with expenses, so how do we project when that date will be?

The idea is to approximate both of these curves with straight lines and see where they’d intersect. The simplest linear estimation is to just draw a line between the first and last point in the window and project from there, but this products erratic results due to the normal bumps and dips in the graphs. So it turns out you need to use least-squares regression to generate approximation lines that are relatively immune to minor undulations. Determining the x-value for where the two lines intersect is as easy as setting the linear equations equal and solving for x.

(For those of you actually following along with the math, remember that what you’ve just computed is the number of days from the beginning of the data window that the two lines intersect. I also convert that into an actual date, e.g. March 14th, 2011, not a relative date, e.g. 127 days from “now.”)

The result is worth the effort; here’s our projected break-even date over time:

When the date is moving out it means we’re being less efficient (either at expenses or revenues or both), and the same in reverse. Recently it’s stabilized which is a good sign that we’re starting to lock in our process, and with the break-even date much closer than our running-out-of-money date, we’re confident we won’t run out of money.

And perhaps most importantly of all, as soon as anything changes for the worse, we see it. No surprises three months later when suddenly we realize we don’t have enough money to keep going.

It ends

As you approach cash-flow break-even, your “run out of money” date accelerates into the future. As you blow past that magical moment, your business can sustain itself indefinitely without further cash investment, and the date becomes infinite.

That’s the end of the chart. Congratulations, now there’s only 47 other metrics you need to be tracking.

Oh well, we should all be so lucky.

Let’s compare notes

What other simple, motivating metrics can you use early on in your startup? What’s your death-day? Join the conversation in the comment section.