Traditional marketing can refer to the channel that is taken, or it can refer to the technique that is used to determine what to market to who. While the channel of marketing has been an obvious transition from postal to online, what hasn’t been so obvious is the rise of utilising digital, rather than traditional demographic, data to make marketing decisions. More than a third of marketers are looking to shift spend from traditional mass advertising to more tailored advertising on digital channels (Salesforce, 2015.)
Firstly, it is important to stress that traditional demographic data will always be necessary. Certain services and products have a target audience limited by age, gender or location, for example over-50s insurance, gender-specific products, or location-dependent offers such as a restaurant chain with multiple locations.
With marketers reporting that customer satisfaction and customer retention rates are both key digital marketing metrics for success (Salesforce, 2015), it is even more important to keep up with the ever-growing demand for a personalised user experience. 70% of consumers want a more personalised shopping experience, and 60% of consumers are comfortable with their digital data, such as their interests, being used by retailers so that they can receive more relevant offers throughout the year.
While traditional data has its place in a modern marketing world, this alone is not sufficient to provide true personalisation to your consumer base, and it often fails, resulting in drop-offs during the buying process, and a reduced sense of brand loyalty stemming from feeling unvalued as an individual. Assuming that an entire demographic group all hold the same interests is a huge mistake that can cost you thousands of customers- not every Millennial likes coffee cups with their name on, not every female loves pink, and not everyone living in London wants to see a West End musical. Offers based on demographic data like age, location or gender can result in communications being impersonal and consumers feeling frustrated. Research has found that targeting more specific emails to smaller groups of consumers results in higher open and click rates (Informz, 2014.)
A way that businesses can get around these restrictions is by utilising big data analytics. Big data is a term which refers to a large set of unstructured data that requires advanced analytic techniques to derive meaning. One way to put it would be considering big data as a goldmine – there is a lot of value there but it is useless without the correct tools to extract it. Big data analytics is the process of getting gold bullion from this gold mine – where the gold bullion is the meaningful and actionable insight. Big data is by no means a new term utilised by businesses, and it has been discussed, and even invested in for a long time. What businesses seem to be missing, however, is the right tools to extract meaning from it. As mentioned earlier, consumers are increasingly becoming comfortable with having their online data utilised in return for a more personalised user experience. When comparing the depth of consumer insight that can be derived from a consumer digital footprint to the amount that is utilised in traditional marketing techniques (which is usually limited to sociodemographic data), there is no question that it would enable more effective personalisation. With the right analysis, businesses can gain real-time insight into consumer personality, their hobbies and interests, their life events, and more, all on top of the traditional sociodemographic data, and this is what is required to make the consumer experience truly personalised.
It is unlikely to be the case that traditional data in marketing will become obsolete to businesses, and this data can be used in conjunction with more advanced data mining techniques to enable more personalised targeted marketing based on deeper consumer insights.
On top of personalised marketing, this insight can be used to pre-fill application forms, detect and reduce fraudulent transactions, asses credit risk and boost financial inclusion, and personalise products based on customer interests, saving time for customers and increasing the chances of them completing an application or buying an item.
It’s important to remember that the acquisition process and using targeted marketing is only the start. Following through the consumer journey can go a long way to building customer loyalty. Understanding consumer behaviour based on personality, interests, and life events provides key indicators of what products and services they might be interested in. For example, if a TV and internet provider has real-time insight into its customers’ life events, it could identify which customers are going to university and market their services as a student bundle, ideal for multiple users streaming at once. Likewise, a coffee shop could identify which of its customers have upcoming exams and offer them a revision such as ‘skip the library: get your 2nd coffee free for a stress-free revision session.’ This is just one of an endless list of examples of how businesses can leverage big data insights to create a personalised user experience.
By harnessing the power of big data businesses can personalise the user journey from sign-up, throughout the entire relationship and adapt alongside their consumers’ ever-changing needs. Real and effective personalisation isn’t just offering a football fan football tickets, it’s about offering a football fan tickets to their favourite team on their birthday.
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