The Churchill Club recently had their annual Top 10 Tech Trends event in Silicon Valley. This was the 17th time that they had their event. It’s a great bit of content to have on in the background.
One thing that immediately struck me when listening to the venture capitalist panel discuss tech trends was how every idea was put through a ‘consumer behaviour’ filter in order to consider the merits of a given trend.
A classic example was some of the very smart things said about wearables and health monitoring in the session. There was skepticism expressed for some very valid social behavioural reasons – if one looks at Facebook, consumers generally share only the good things in their lives, with the notable exception of life events, such as the death of a family pet. Stephen Waddington even describes his behaviour on Facebook as ‘cognitive behavioural therapy’.
So people really into fitness are far more likely to employ self tracking than couch-dwellers. Self tracking was described as a ‘Quicken Problem’. Quicken allows US consumers to easily complete their tax returns – a universal problem, yet is only used by five per cent of the population for various reasons.
All of this is very valid stuff of its self, but what happens if it isn’t only consumers making the decision?
My reservations about self tracking technologies are well recorded, to quote myself from Stephen Waddington’s Brand Vandals
Self-tracking adds massive amounts of data to your personal data pool and social graph and raises huge privacy concerns that users need to be cognisant of
A number of the key points that I made in my conversation with Stephen was not about consumers using their self-tracking data but how the data could be used to recalibrate car insurance, home insurance (based on absence from home) and health insurance based on activity and risky behaviours.
Let’s look at a specific type of self tracking, the car insurance black box. Aviva (Norwich Union) trialled the use of telematics to set car insurance premiums on a monthly basis as a type of continuous assessment. It looked at factors such as:
- When the car was used, nighttime driving was considered to be risky behaviour
- What distance was covered, charges were on a per mile basis
- Breaking data
In IBM Research’s case study, Norwich Union envisaged that black boxes would allow it to sell insurance to consumers that drive less often. Norwich Union dropped the pilot in 2008, apparently due to a lack of consumer interest, but resurrected the car insurance black box when the European Union ruled that charging for car insurance on the basis of gender was illegal. Presumably the needed some other form of actuarial data instead of whether the driver was a female or not. This is just one example where consumer behaviour didn’t drive product innovation that wouldn’t be accounted for in the tech trends discussion.
Credit ratings were driven by the need for businesses to mitigate risks, direct (rather than operator) dialling on a telephone was developed to help reduce the manpower required to run telecoms networks. Night safes and ATMs (automatic teller machines) were about providing services without staff. The US airline tradition of baggage charges came from shareholder pressure not consumer demand yet is worth hundreds of millions of dollars a year.
The point at the end of the day is that opportunities for venture capitalists are broader than meeting consumer needs and wants.
Brand Vandals by Stephen Waddington & Steve Earl
AA launches black box car insurance | Guardian
Norwich Union heralds new Pay As You Drive insurance – Aviva Media Room Archive
Norwich Union Insurance Telematics Pilot – Pay As You Drive Telematics trial of usage based motor insurance by Volker Fricker of IBM Research – (PDF)
Aviva Telematics Insurance Review | Telematics.com – Norwich Union (now Aviva) abandoned telematics insurance a number of years ago and is now reinstating it