In the absence of marketing, information about products and their benefits spreads at the speed of social contact. Imagine a new sector being opened up simultaneously by a group of competing manufacturers (as, say, the alcopops market was, a few years ago here in the UK). Assuming that the objective benefits of the products are all similar, then in the absence of branding and marketing effort, you could expect that for n products in the sector — in a free market, and assuming that all have equal access to distribution etc. — each would end up with around 1/n of the market. However, the world tends to power-law distributions — it doesn’t take long before the unpredictable unevenness of things means that after an initial period of chaos, one of the n would reach a tipping point and become a clear market leader [is this substantiable?] through network effects, after which power law dynamics would tend to keep it in that position. (Incidentally, this thought suggests, as corollory, that market leadership in a sector where all competitors are equally ineffective at engaging the target market may be solely due to network effects, rather than marketing effectiveness — is Red Bull the market leader in its sector due to great advertising, or a singular failure of all brands in the sector to communicate effectively with young club-goers?)

In the real world, of course, marketing seeks to skew matters in favour of a particular product or brand.

I’m wondering whether there’s a way to use social network analysis to quantify the effect of marketing on the diffusion of brand awareness through social networks (and thus serve as a metric of marketing effectiveness). Taking ‘no branding/no marketing’ and ’100%-effective saturation marketing’ scenarios as limiting cases, it should be possible to apply geometric models to the spread of ‘awareness’ and ‘preference’ (as determined by regional or social demographically-segmented sampling), over time (or geographically) — and those models should look substantially different for the two cases. Growth of awareness through social networks alone would show a characteristic diffusion pattern, radically different from awareness due to effective marketing. I would expect that the real world situation in any instance would be some (possibly linear) combination of both models — the extent to which a real-world case study veers towards either would make a simple measure of the effectiveness of the marketing being conducted on the behalf of that product/brand. The difference in diffusion geometries would also expose highly useful information about the effectiveness (or indeed, in an epidemological view of this, infectiveness) of a given campaign, across space, time and markets. Current sampling techniques seek to identify the percentage of target markets who are aware of — or think favourably about — a brand. This proposal is really about geometric analysis of the higher-order derivatives, over space and time, of such information, and more particularly, to geometric modelling of such metrics.

Such a technique would constitute a more objective basis for measuring both effectiveness (and the nature of effectiveness) than simple examination of temporal correlations between the launch of marketing campaigns and consumer spend on the product, and it would be, I think, relatively immune to external effects (macroeonomic conditions, individual sector characteristics etc). Lots of research needed. I will update this when I’ve talked to people who understand the marketing side of this, and see if I can find anyone to tackle the geometry.