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Marketing is an intrinsically complex job. The roles a marketer undertakes are varied and understanding which objective requires focus can be a time-consuming task.
Three marketers at rival firms might share the job title Brand Manager, yet their responsibilities may differ wildly.
One is measured on generating brand awareness. Another is constantly working on differentiating from competitors, while the final brand manager’s sole objective may be to supply a healthy pipeline of leads.
Ultimately, marketers rarely share their priorities. Their roles are shaped to meet the needs of their organization. This distinguishes this role from many other jobs.
Salespeople, for example, seldom change their sole priority – to close sales – only their sub-priorities, like the length of contract and the type of customer.
Hampered by this complexity, marketers look to educational material in an attempt to clear the fog and hone focus. However, much of the marketing literature available emulates the complex job, by offering advice that varies wildly.
Look at most university marketing courses and you will almost certainly find a module that promotes differentiation.
However, open Byron Sharp’s How Brands Grow and marketers will find research that disproves the effectiveness of differentiation. Instead, it suggests that distinction, not differentiation, requires focus and attention.
This ambiguity has become increasingly apparent as the speed of change increases. For instance, we spent months working on our Google+ page, publishing hourly updates and even creating bespoke content, only to find the site all but shut down in May last year.
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Attributes we see in successful product launches
Marketers have few solid and reliable laws to follow before making a decision.
But this shouldn’t be the case. There are basic proven guidelines that can be used to guide decisions.
Everett Rogers created the diffusion of innovations theory, which seeks to explain how and why new technology spreads.
This bell curve is often used in marketing and most know it well. However, what is less well-known is why some products successfully diffuse through an industry and why others don’t.
Rogers had an answer for this. He reviewed hundreds of product diffusion studies and identified five attributes that influence rates of adoption:
|Attribute of innovation|
|Relative advantage||The innovation is technically superior (in terms of cost, functionality, “image” etc.) than the technology it supersedes|
|Compatibility||The innovation is compatible with existing values, skills and work practices of potential adopters|
|Complexity||The innovation is relatively easy to understand and use|
|Trialability||The innovation can be experimented with on a trial basis without undue effort and expense; it can be implemented incrementally and still provide a net positive benefit|
|Observability||The results and benefits of the innovation can be easily observed and communicated to others|
Although theoretical, these attributes can be seen in almost every successful launch.
Take the iPhone, cited by most as the classic example of innovation. Was there a relative advantage? Yes, with its responsive touchscreen, internet compatibility, and streamlined software, the smartphone was technically superior.
Was it compatible? Yes, potential adopters were pros at web surfing on laptops and desktops, the iPhone synced this perfectly on mobile.
How about complexity? Well, as with all Apple products, the clean design, intuitive software and straightforward touch screen made it simple to understand. Also, observability was easily dealt with through an intensive burst advertising campaign.
To tackle trialability, Apple encouraged potential customers to test the product by placing dozens of ready-to-use iPhones in their stores. Customers who queued up and used the product immediately recognized the relative advantage over other products, the compatibility with their own desires, and the innate simplicity, despite its powerful technology.
Although this reexamination of Apple’s success is enlightening, Rogers’ attributes of innovation don’t have to be conducted retrospectively.
They can and should be applied before designing a product, building an advertising campaign or even writing a blog. All that’s required is a change in mindset.
Continuously checking work against these attributes will guide your decisions and help you create something that gets adopted by every potential user.
However, the problem of measurement arises. How can you be sure your work is emulating each attribute?
In reality, it’s impossible to know completely, but there are indicators that will detect if you’re obviously failing in one area.
Traditional methods are obvious and trusted ways of measuring consumer behaviour. Observability can be calculated through recall and recognition tests and complexity can be checked in focus groups or surveys. These methods are still extremely useful and should not be dismissed, but they are not flawless.
Each measurement is costly, time-consuming and usually limited to a small sample size. In fact, working within a fast-paced industry provides almost no time to conduct reliable research into even the most important business decisions. That’s why brands regularly rely on social listening platforms to gauge real-time consumer preferences immediately.
Social networks, forums, review sites, news platforms and more, can all be holistically analyzed to reveal clear indicators about potential diffusion. After all, it’s the “largest searchable archive of human thought“.
The real-time analysis allows brands to conduct quick-fire acid tests on each of the five attributes. Large scale decisions like product development can receive constant guidance through monitoring, while small everyday decisions can be backed up by tangible and valuable consumer data.
Marketers are dropped into an industry where results are expected immediately, yet, they are often prepared, academically or not, with insufficient, contrasting ideas, which cloud judgment and produce varied results.
Guidelines, like Rogers’ attributes of innovation, can be used regularly with real-time social analytics and long-term traditional methods.
Doing so can enlighten your organization with high-leverage intelligence to simplify even the most complex decisions.
Bring the power of social data into your decision making.
Bring the power of social data into your decision making.Find out more