October 13, 2010

63) Netflix

危 wēi  danger

Great businesses continually improve, prototyping new offers and services before rolling them out to the relevant customer base.  But, success criteria for innovations are often vague and ‘success’ is therefore highly subjective, particularly when innovation teams only prototype to small groups of customers.  The alternative, rolling out to large numbers of customers immediately is too risky though?  And anyway, given how quickly markets change how could the team say with confidence that any change in performance was attributable to the change in strategy?

机 jī opportunity

In my previous post about Netflix I sang the praises of the company placing a top-level strategy summary in the public domain – you can see it here.  Slide 20 particularly caught my eye, a brief slide on customer satisfaction:

I love the idea of breaking customer bases into equal sized groups, allocating each to different employees or teams and then giving them free reign to attempt to improve their group’s experience.  I imagine that this enables more offers to be prototyped and creates a competition internally to deliver quantifiable results.  I also admire the size of these groups in this case – many companies would be tempted to limit the trial to a handful of customers at most, going with groups of 10,000 enables Netflix to really quantify the benefit and assess relative performance.

The approach establishes what would be called a ‘control set’ in a science experiment and encourages agreement in terms of what success metrics might be in advance.  In fact, my colleague Elizabeth said in a talk recently that she likes to approach piloting using the scientific method:

set a hypothesis -> agree variables -> agree metrics -> agree duration -> feedback and conclusions

That makes sense, and contrary to many people’s perceptions it doesn’t need to stifle creativity. After all, the development of new approaches to pilot and the spotting of interesting new patterns in any results depend on creativity.

How About…

  • Taking a scientific approach to piloting new offers?
  • Thinking how you might divide your business into comparable units for benchmarking?
  • Tasking teams with innovating the offer to different units, then rolling out the most effective new approaches?

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October 4, 2010

61) Amazon Prime

危 wēi  danger

Retailer loyalty programmes fall in and out of fashion.  Their supporters describe increased customer stickiness (particularly for retailers that become known for value in price-sensitive markets), increased average spend per customer and valuable data aggregation for market research on shopping habits.  Tesco clearly believes in these benefits as it relaunched its Clubcard last summer, leading to an increase in scheme members to 15 million.  However, the schemes are expensive to launch and run: Clubcard’s relaunch cost c£150m.  In addition, as referenced in this Marketing Magazine blog, Tesco is quite unique: it sees data frequently and across many items, is able to change its offer using that data and can sell the data to its suppliers, turning a cost-centre to a revenue centre.  Given the high costs and uncertainty of benefits Amazon would surely be crazy to launch a loyalty programme open to everyone in a similar way?

机 jī opportunity

Maybe not.  Keith Melker, my friend from HBS, recently brought to my attention a slightly counter-intuitive trend in the introduction of ‘paid’ loyalty programmes in the US, and helped me understand why they’re often smarter than they appear.

Amazon Prime, launched in 2005 is one such example in which members enjoy unlimited free shipping with no minimum purchase amount.  But, instead of giving membership away free Amazon charges $79 per year.

Superficially you might expect this to be taken up solely by Amazon’s most frequent customers and that the programme would be loss-making because those customers place frequent orders (which Amazon would have to foot the shipping bill for).  But that assumes that customers don’t change their behaviour as a result of being a Prime member and a quick scan of various blog posts suggests that they do.  In fact anecdotal evidence suggests that Amazon’s customers go from about $160/yr to $600/yr after they buy Prime.  It appears that once customers pay for Prime they begin to order more (perhaps because they feel that they’re beating the system).  So, assuming the combination of the Prime charge and the increase in margin per member is greater than the value lost through free shipping it’s a business masterstroke.  Had Amazon given it away free the uptake might have been greater and the behaviour change might not have been as dramatic: that could have been hugely expensive.

How About…

  • Re-examining loyalty programmes – perhaps deliberately offering it to a select group (rather than everyone)?
  • Or even charging for it if it might drive positive behaviour change?

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August 2, 2010

Why I think OpenIDEO is important

This is a break from my usual blog post format but today is a special day: we’re launching OpenIDEO – a platform designed to bring people together to solve problems for social good. Here’s a quick intro video (those of you that know me may recognise the voice):

I’ve been thinking about and developing this opportunity for a few years and thought I’d jot down a quick personal perspective on why I think it’s important.

Collaboration works. Cities have always been hotbeds of innovation.  Why?  Because high population densities bring together minds and enable collaboration.  Solitary inventors deliver, but the world is getting too complex for individuals to make breakthroughs at the societal level as frequently.

vs  

Take helicopter design: although Leonardo Da Vinci had a good go at designing a whole ‘helicopter’ in the 1480s no individual on the planet would be able to design and build a groundbreaking one today from scratch.  I don’t imagine there’s even an individual that could design and build all of the electronic systems. Today, most breakthroughs require collaboration.

Collaboration works between similar individuals: 1+1 = 2.5. But we have learnt through our work that collaboration works even better between diverse individuals (whether the differences stem from culture, experience, knowledge, approach or all of the above): 1+1 = 3. Diversity of perspectives drives better results.

And it doesn’t need to be ‘physical’ anymore. In the past collaboration has generally required physical meetings, it’s still arguably the most effective approach.  But technology is providing new means to meet and collaborate virtually, for example social networks (including Twitter, Facebook and LinkedIn) provide us all with new tools for collaboration.  Harnessing technology will be essential for impactful collaborations in the future, particularly since we know that diversity is important.

When companies choose to prevent employees from using social networks (usually to keep them focused) I wonder if they’ve thought through downsides – not least that they may be preventing their employees from developing these new collaboration muscles.

And we care. Although voter numbers are dwindling, consumer and citizen engagement around brands and local politics is increasing – partly because these are the areas where we believe we can have impact. This is likely to increase – particularly after a period where we have all been forced to reassess our values (the economic meltdown) and because technology is offering us all greater power to affect that change.

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So, with these big trends in mind, we built a technology platform to enable diverse people to collaborate in solving problems for social good.  We hope that it makes a difference.

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