One-to-one marketing, where sellers know that what they are offering to a customer is both timely and truly relevant to them is the holy grail of marketers. To achieve this, you need reliable information; and that means knowing your customer well. This has always been the secret to successful selling. Back in the day when sales revolved around personal interactions over a shop counter, simply chatting, asking the right questions and having a good memory meant the sales assistant could learn their customers’ preferences and buying behaviour. But things have changed. The advent of mail order and then click-to-buy has meant that sellers no longer have as much, if any, personal contact with their customers. They do still have customer data however, gathered not through personal communication but through digital interaction with the internet, social media, mobile devices, credit cards, transport and building infrastructure, to name but a few.
Today, the amount of data has grown so large it is known as Big Data, and clever machine learning technology can apply the results of analysis so that marketing can optimise offer allocation and customer interaction. The tools may have changed, but the age-old strategy of ‘know your customer’ is the same.
Of course, the proliferation of customer data, largely as a result of the internet, has been matched by the availability of choice for the consumer when it comes to suppliers and services. This makes it doubly important for brands to be able respond to a saturated and fragmented marketplace to keep existing customers happy, stop them turning to a competitor and, in an ideal world, increase the amount of money they spend. To achieve this, brands need to interact better with their customers in order to protect the relationship and encourage spend in ways in which they may not previously have been able to. The challenge is that subscribers’ lives are constantly shifting. So how can brands not only reach particular customers, but also respond to changing environmental factors to treat each one as an individual with tailored marketing?
The answer is adaptive contextual marketing, based on the effective collection, analysis and application of customer big data. It is the next step in the evolution of customer marketing – extracting more value from data and enabling faster, more intelligent customer interactions. In adaptive contextual marketing, context is everything. It is about adapting every part of the marketing mix to connect customers with the brand. In this way, the ‘know your customer’ rule comes full circle as profitability is once again driven by tailoring the products and services offered to customers to meet their individual profile and needs.
Now the algorithms behind big data analysis and machine learning are capable of finding relevant links faster than ever before, marketers can map what we call customers’ ‘Behavioural DNA’. This kind of deep data analysis provides a far more complete profile of each customer than was possible before, making market segmentation a thing of the past by enabling truly personalised marketing.
With modern computing power taking care of the customer profiling, marketers are released from time consuming test and learn marketing cycles. Instead they can put their time and effort into the areas that need human creative input and hands on experience such as developing the offers with the best impact. This might be a real-time offer in response to particular customer behaviour or spending pattern, acknowledgement of a service-related issue with an apology and ‘sweetener’ offer or a loyalty reward programme.
It is more than clever marketing, it is about understanding how to maximise the value of each individual customer, or customer value management, and it is the ongoing practice of building and nurturing powerful and effective customer interactions, even around a simple educational message. The customer experience can be easily tracked and improved, which means marketers have the opportunity to create rich records of what a consumer wants and so create greater “stickiness” with the brand.
We know from experience that tailoring offers to this degree has a definite influence on whether a customer will churn to a competitor or not and we also know that it can deliver an increased return on investment. Our customers typically experience incremental increases of 3-5%.
Leveraging big data and machine learning in an adaptive contextual marketing approach represents the next step in establishing a valuable relationship with the customer. As always, it is about the quality of the customer experience which leads to brand popularity and profitability. But as yet a large proportion of brands are not leveraging the full data set that they have access to when it comes to their customer. What an enormous and untapped opportunity for marketers everywhere!