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Influence marketing - tapping into the herd instinct

According to Wikipedia, herd behaviour describes how individuals in a group can act collectively without centralised direction. The term can refer to the behaviour of animals in herds, packs, bird flocks, fish schools and so on, as well as the behaviour of humans in demonstrations, sporting events, religious gatherings, episodes of mob violence and everyday decision-making, judgement and opinion-forming.
Image credit: WildVeganGarden via Pixabay.

Anybody who has watched flocks of birds, antelope or other forms of herds, will have noticed that they can be peacefully stable, but the slightest disturbance results in the agitated behaviour.

There are two dimensions of the herd instinct – the transmission of a message from an individual to the herd and the subsequent behaviour of the herd.

While influence marketing (IM) is made out to be the latest, great marketing and media innovation – there has been serious discussion since around 1940 when a study on social influence found that ‘the majority of people receive much of their information and are influenced by the media second-hand, through the personal influence of opinion leaders.’ This became known as Word of Mouth (WOM) concept that you’ll find in most marking textbooks. In essence, omitting the ‘personal’ in the quoted sentence would leave you with a good description of IM.

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Taking this approach, we examine the two dimensions and apply it to IM to gain insight on how IM can be harnessed.

Transmission of a message

The impetus for the metamorphosis of WOM into IM has been the dramatic transformation of society by the impact of technology; especially the inventions of the internet and mobile devices. This has vastly magnified the transmission of an individual’s effect on a greater population (such as a herd, or subset of a population).

While WOM has not been taken seriously by marketers, it’s importance was recognised over 20 years ago by Marketing Science when WOM was incorporated into the New Product Radar mathematical sales forecasting model, which resulted in the improved prediction of new product launch success.

Turning to the actors in originating and/or transmitting a message, Malcolm Gladwell suggested three types of influencers (The Tipping Point: How Little Things Can Make A Big Difference – Little Brown, 2000):

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  • Connectors: Individuals (or groups) with large and active networks. 
  • Mavens: These are individuals (or groups) who have a high level of recognised expertise. For example, millennials in relation to digital devices; art critics about art; wine writers about wine, etc. Mavens are intimately attached to the particular category.
  • Salespeople: Gladwell calls these ‘charismatic persuaders’ who function both at an overt (testimonial) and covert (emulation) level.

In evaluating each of these categorisations, a search of the literature revealed 5 factors that define each of these categories’ relative effectiveness for a particular IM deployment:

  • Different categories will have different reach. For writers, commentators, thought leaders, their reach may be restricted to the publications they are attached to. However, the measure needs to factor in activity in social media, but care has to be taken to de-duplicate the audience measures.
  • The extent to which a person is a maven would carry greater authority.
  • Frequency will vary across the different categories. So, the influence of, for example, a TV chef will be directly related to the frequency with which they may publish and support their TV shows.
  • If the risk of making a bad choice is high, so the effectiveness of influencers in each of the categories would be high. 
  • Blatant overt selling can have a negative effect, so the extent to which a maven would be effective may be reduced by the extent of his personal gain from resultant transactions. This is closely related to integrity

The measurement of all these in the application of a particular IM deployment is a fairly straightforward exercise in applying trade-off technology – readily applicable to mobile devices. In fact, if a company sets up category-distinct consumer panels, the category classification of each panellist will be relatively stable over time and knowing each person’s category, together with their value to the company will support the decision process of any IM deployment.

Subsequent behaviour

Other than the reference earlier to New Product Radar, there is no evidence that IM works in generating sales. Yes, you get a lot of measures such as likes, and clicks, but nothing that the accountants will be able to use to calculate a ROI for a particular IM campaign.

Of course, this is largely true of all forms of marketing and there are ways that both can be done.

Achieving better measures of ROI on marketing spend is a huge unsolved 100-year-old problem that is closer than ever to a solution.

Just as technology has spawned the internet and mobile devices, so too has it delivered astonishing knowledge management tools and capabilities. Think of Google – who can live without it now, but at the turn of the millennium, it was a mere blip on the radar.

Then think of your company’s reporting processes. Do they run like the spaceship in Star Wars? Everything you need to know when you want it?

The problem lies in the information structures, their complexities, access and ability to be integrated with one another. On the one hand, most large companies have data warehouses which have, as their fundamental data structure the accounting systems, balancing income and expenditure to the last cent. So, your balance sheet should, well … balance. This is a closed information regime that is fully controllable by the business. It operates, not in a vacuum, but in a social, political and economic environment that is not controllable. All uncontrolled influences are not necessarily well behaved – they involve people, relationships, dynamic interactions and dependencies which all have to be taken into consideration.

So, really the challenge of measuring ROI is to build a system that delivers all the data a decision maker would need when they need it. It is not a trivial issue because of four main factors:

  • Measurement
… its validity
… its availability
… its timing
  • Scope, comparability and context
  • Cost
  • Other stuff (the demons)

The proposition that we put to our readers is that all except the last are pretty much resolved. The ‘other stuff’ relates to the wetware (aka the soft material between the ears).
Decision makers have to go to:
  • Nielsen presentation to find out about brand share, competitor activity 
  • Research presentations to find out which packs concepts, etc, are better
  • Planning meetings to resolve the politics
  • Sales meetings to motivate the team
  • Ad agency meetings to the meaning of communication
  • Conferences
Now, we’ve all heard about big data, but there’s another important aspect that needs to be discussed further…….

The next article will address the interlinking of data from different sources and topics and visualising the interactions and trends. It starts with well-run panels and sophisticated automatic sleeper surveys that populate cloud-based data of information, which draw from other clouds comprising social, political and economic trends. The goal is to build reliability into the business processes and systems, ultimately making the idea of customer satisfaction redundant, as it is in the herd. There is little delight and little dissatisfaction among members of the herd. There is, instead, optimal survival.

Interlinking is only useful if it can be accessed in context. The use of smart and easy to use online dissemination, in the form of Infotools Harmoni, provides a contextual view of the competitive environment. This being the source data as well as overriding touch points that make the trended panellist information come to life. This is done by way of multiple data source access and contextual media and behavioural data being housed in one online knowledge portal platform. Users of the platform get to “see” the clear picture of the consumer behaviour by cross-referencing the various data and resources to extract deep dive insights from which marketing strategies are born.

About mike broom

I have been involved in marketing research for over 40 years, across all spheres. I started Marketing Science in 1992, Infosense (aka Infotools) in 1995 and Panel Services Africa in 2005. For more information on Ad-Audit, please contact me at infoQuest (formerly PSA) on 083 255 2668 or click here to send an email.
Mark Sindone
Hey, you'd be very surprised what kind of traffic influencers can bring to you when they help you to advertise your merchandise! The facilities that you have, you've got to use them, and most of the time with these people, you just need to give them a unit of your product and let them take it from there! Low cost, pretty high returns!
Posted on 21 Dec 2018 05:05
Stephen Giderson
It is actually fascinating to see an entire group, be it animals or humans, acting together in a similar fashion though no prior instructions were given. It is as though they had already communicated prior to being at that very location to act as a single unit upon seeing a certain movement or hearing a certain sound.
Posted on 11 Jan 2019 06:40



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