Media Spend by Product Lifecycle, Part 1: Launch/Pre-Launch Spending on Social Media

June 25th, 2008

In the face of uncertainty in new media spending – What’s the ROI for blog outreach? Do widgets produce measurable returns? Is spending on word of mouth scalable? – it’s tempting to retreat to the familiar.

One rough rule-of-thumb for media/ad spend is the 70/20/10 rule (see What Sticks by Rex Briggs and Greg Stuart).  The rule suggests something along these lines: spend 70% of time/resources on proven techniques and media, 20% of time/resources on slight variants of proven techniques and media; and 10% on tests of brand new media and techniques.

In the aggregate, this model might make sense.  But, as always, the devil is in details: what’s proven media and technique for one product stage may in fact be unproven at another product stage; high-ROI media for one product stage may be low-ROI when deployed at a different product evolution stage.

By way of comparison, let’s consider how money is allocated in an industry that’s studied allocation extensively: financial portfolios. There are very different recommendations for portfolio allocation, often based on life stage.  Younger people typically should allocate the majority of their funds to less proven, higher-return, higher-risk investments (e.g. stocks) whereas older people typically should allocate the majority of their funds to proven, lower-risk, lower-return investments (e.g. bonds or annuities).

It would seem logical to explore a similar model for media spending that’s based on product stage.

Thanks to innovative research by Geoffrey Moore, Seth Godin and others, we now have good models for new product adoption and growth stages – Moore’s well known model segments consumers, discusses early target segments and reviews challenges related to crossing the “chasm” between enthusiasts/early adopters and mainstream consumers.

Early on, driving usage and positive word of mouth from early adopters and enthusiasts is critical. Consequently, it makes sense to allocate early marketing spend much more heavily on the new, evolving media – social networks, blogs, widgets and so on – that early adopters use.

In fact, it’s not crazy to imagine that – early in the lifecycle, i.e. pre-launch/launch – 70% or more of the media and resource spend should be focused on these new, more experimental media channels, and 30% or less on channels that are considered more proven , e.g. ads.

Here are the specific benefits of spending early on social media:

  • determine how consumers are actually perceiving your brand – what’s their motivation to buy? what’s the specific discourse around your new concept?  is it around price? status? design? (as Briggs and Stuart emphasize, over $50 billion of marketing spend is wasted due to inaccuracy in understanding consumer purchase motivation)
  • start engaging and generating excitement among the critical early adopter group

If you’ve implemented a well thought out social media initiative, you’ll have a strong early adopter evangelist group and much better insights to use in successfully scaling up traditional media spend.

Image reprinted by permission from Geoffrey Moore.

2 Responses to “Media Spend by Product Lifecycle, Part 1: Launch/Pre-Launch Spending on Social Media”

  1. [...] Image 3: http://www.irfankamal.com/social-media/spend-more-on-new-media-early-in-a-new-campaign/4 [...]

  2. Annaon 20 Apr 2011 at 6:38 pm

    There seems to be widespread confusion regarding Moore’s model of Market Evolution throughout the lifecycle of a new technology.

    The y-axis on your normal distribution should read “rate of market uptake”: a percentage of your total market uptake per unit time. You would then integrate this curve to reveal the percentages of customers which fall under each segmented category.

    The relative percentage of customers which are Early Majority Pragmatists, for example, should be the area under the third segment, representing roughly 34% of your total market. By integrating the “rate of market uptake” across the whole lifecycle with respect to time, you should yield 100% of your total market (1, the area under a normal distribution).

    I’ve seen this error on many sites. I wonder why nobody else has realised that the graph in its current form cannot make sense.

    Regards

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