Early success does not necessarily translate to long-term sustained success
Operators that launch new services may observe early enthusiasm for their offer, but this may not be an indication of future success. In fact, it may signal the contrary – a dismal failure. This is the intriguing suggestion of new research from the renowned Wharton School at the University of Pennsylvania. In a paper with the appealingly gloomy title “Harbingers of Failure”, Anderson et al (2015) suggest that some early adopters of new services may “systematically purchase new products that flop”. This finding, based on a lengthy and detailed study of retail purchases, has significant implications.
Operators need to launch new products and offers to remain relevant. Yet, their track record in doing so, particularly when compared to Internet providers, is patchy at best. In part, the success of a few runaway Internet stars can mask the volume of failures, but this is also instructive, since the Internet world is characterised by a relatively low cost of failure. Many companies fail – some even fail repeatedly – but from the failures, world-conquering success can be found.
In this context, the ability to spot a successful product is clearly important – but if a service does achieve early success, the research points out that this does not necessarily mean it will “cross the chasm” and go on to attain star status. What does this mean for operators? Well, many operators are beginning to invest heavily in big data analysis, with the aim to discover more about their customers, preferences and tastes. They hope to be able to use this data to spot emerging trends and launch more effective, successful offers.
However, it seems that there are some consumers who not only choose products that others do not but do so repeatedly. They are, as Anderson et al put it, harbingers of failure. Such consumers offer valuable lessons. They may, time after time, choose niche or unusual products that are doomed to failure. Worse, it appears that such consumers are characterised by their ability to discover such products before others – in the aggregate, this enthusiasm provides misleading results which are suggestive of future success but in fact turn out to be signs of failure.
Operators that are experimenting with big data analysis need to consider the implications of this research. What if such users could be identified? If that were the case, then providers could sieve data to see if the known harbingers are avoiding a particular product. If they are, then it might be indicative of a slow start but more likely future success. On the other hand, if the harbingers enthusiastically embrace the new product, then it could be a clear sign that something is wrong with it.
Careful use of big data gives operators the potential to do achieve this. If they can succeed in identifying the harbingers, this information can prove crucial – and help operators design more effective trial and release programmes, learning to make changes and adjustments before it’s too late, reducing the cost of failure. Interestingly, harbingers of failure could well be invaluable for increasing the chances of success.