Performance Firestarters 9: The Power of Feeds


For the ninth in our series of Firestarters events for the Performance Marketing community will be focusing on Feeds and APIs, which are changing the advertising landscape in a unique and potentially powerfully way. As well as talking about how the smartest agencies are using feed data to improve campaign results and bring new levels of contextual relevance to messaging, we'll also thinking about the future and where the application of this kind of data might lead us, including how AI and machine learning might be used to adapt approaches to marketing. So plenty of interesting stuff to talk about, and to help us we have three excellent expert speakers: 

  • Alistair Dent, Head of Product Strategy at iProspect (the UK's largest performance agency)
  • Visar Shabi, CTO at Brainlabs digital, the 'scientific' PPC agency
  • Kris Tait, business director for Croud, one of Google's fastest growing Search agency

The event takes place on September 2nd, 6.00pm at Google Central St Giles, London. I have some free passes to give away to readers of this blog so if you'd like one, message me direct or leave a comment below.

More is Different

"At first, poaching stars from competitors or even teams within the same organization seems like a winning strategy. But once the star comes over the results often fail to materialize...What we fail to grasp is that their performance is part of an ecosystem and removing them from that ecosystem — that is isolating the individual performance — is incredibly hard without properly considering the entire ecosystem."

An excellent post from Shane Parrish on making decisions in complex adaptive systems (like organisations). I like what he says about the perils of extrapolating individual behaviour to understand the likely behaviour of a system, being wary of systems becoming too tightly coupled through lack of individual diversity, and the values of using simulations (or tests and prototypes perhaps) to aid learning. Makes a lot of sense thinking about organisations in this way.

The Modern Blight of Overwork


'...the long hours...may be the byproduct of systems and institutions that have taken on lives of their own and serve no one’s interests. That can happen if some industries have simply become giant make-work projects that trap everyone within them.'

Lots of truth in this New Yorker opinion piece about the modern blight of overwork, and how many industries become victim to 'arms races that create work that is of dubious necessity'. Whilst the promise of technology has for so long been about greater efficiency leading to a surfeit of leisure time for us all, somehow we've ended up with the opposite becoming a reality.

One of the great enigma's of modern working is that despite having more workers and being more productive than ever we are still working longer hours. Rather than focus on workers’ decisions and incentives, Tim Wu is suggesting that we should instead focus on the system - how technology is removing the kind of limitations that created natural boundaries and barriers to excessive working, and how white-collar work in many industries seems to expand infinitely through the creation of 'false necessities' - practices that evolve and develop and become entrenched ways of working yet create little value.

Overburdensome processes that cultivate over time, avoidable meetings, reply all emails, needless reporting, work that feeds systems that have become outmoded. Like Tim, I think there has to be a better way.

What Network Science Says About Career Success

Thanks to Peter for pointing me at this piece on 'The No.1 Predictor Of Career Success According to Network Science'. Like Peter I'm not a fan of the term 'career success' (nor of over-analysing Steve Jobs) since we might define success in so many different ways, but Michael Simmons makes a powerful point about something that intuitively feels right: being part of a small, closed network where you are connected to people who already know each other is distinctly limiting, whereas being part of a large open network, particularly where you are the link between different clusters of people, is empowering, and a good predictor of success.


Research by Professor Ron Burt at the University of Chicago Booth School of Business indicates that no other factor is more important in predicting career success. What the work shows is that simply having a large network of people you know is not enough - but being a 'broker' between different clusters is enormously powerful: 'What a broker does,' says Burt, 'is make a sticky information market more fluid. Great ideas will never move if we wait for them to be spoken in the same language'.

I think this is  a powerful idea for organisations. I've drawn a lot in the past from the book The Power of Pull, which talks about the idea of 'porous enterprise' - how innovation happens at the edges, how valuable connected employees are in bringing fresh thinking into a company, and how businesses need to focus less on protecting existing 'stocks' of knowledge and more on knowledge flow.

It's comfortable and validating for both individuals and companies to stay within the same groups. It's easy for businesses to become extremely inwardly facing and reward managing upwards rather than connecting outwards. But being able to draw information from diverse clusters, make new connections, introduce new information to different audiences or translate and re-apply knowledge has surely never been more valuable. We talk about the need to get out of our comfort zones as individuals, but companies need to do it too.

Pirate Metrics


We're used to looking at financial statements to monitor the progress of established businesses but when you're a startup that may not generate revenue for some time this is less useful. If we consider a startup as essentially (in the words of Steve Blank) 'an organization built to search for a repeatable and scalable business model', then what is most important in the early stages is acquiring learning. So solely using revenue as a measure of success can be distracting and less than helpful. Traditional accounting methodologies can stifle innovation since they are more suited to established products or services - standard accounting practices like cash flow analysis or financial ratios can put early stage products or businesses in an unfairly adverse light.

So we need Innovation Accounting, in which we use metrics that measure the true progress of innovation - things like customer acquisition, retention, user activity and so on. One of my favourite models for doing this is Dave McClure's Pirate Metrics which defines a set of macro metrics that can be used to model the customer lifecycle. Whilst revenue may be one of them, it’s not the only one. 

Pirate Metrics is a 5 metric-model (A-A-R-R-R...geddit?) designed to represent all of the key behaviors of customers - how many users you are acquiring, how many of them are active users, whether they come back and use it again, whether they tell others about it, and how much money you are able to derive from them. 


It’s easy to guess where problems with a new product may lie, or to act on hunches, or to work off flawed assumptions, but analysing and monitoring these 5 metrics can give you a pretty good idea of where you might have potential issues, or where you need to focus improvements, or where the opportunities for optimisation lie.

Revenue is of-course important, but it's not the only thing. These help to define and measure customer value before you actually start capturing some of that value back. In other words they are leading indicators to revenue before actual revenues are realised. And in this sense they can also be used to hold entrepreneurs, and the leaders of innovation projects, accountable. It's a simple model, yet shows the need for flexibility right across an organisation if innovation is to succeed. And that's why I like it.