29/05/2014

By Dave Peters, CEO and Founder, Emagine International

Relationships are generally understood to be personal things, driven by a mutual understanding and recognition. In the past, this has been difficult for marketers to achieve, with customer communication based largely on guesswork, trial and error or segmented targeting. In today’s information overload society though, personalisation and value in customer relationship management is absolutely key. In a crowded marketplace, marketers must find new ways to keep existing customers happy, stop them from transferring their business to a competitor, and increase their revenue.

The effective collection, analysis and application of customer data is the key to this activity, and can be used to totally transform CRM and wider marketing strategies as we know them. Admittedly, brands have long had information on their customers. But in recent years the amount of data available from the diverse sources such as the internet, social media, mobile, credit cards, transport and even building infrastructure has become so huge that we can really only make sense of it with the help of automation and machines. Welcome the era of big data!

Technology is now at the point where big data analysis and machine learning platforms can process hundreds of millions of records every day, applying algorithms that can be used to solve a problem or find a link a thousand times faster than conventional computing methods. This means that marketers can finally harness the full power of these new data streams, creating not only a far more complete profile of the individual, but also analysing this profile in real time to optimise marketing offer allocation and interaction with customers.

As a result, marketing can finally live up to the promise of one to one marketing made back in the 1980s, moving beyond the segment to the individual and creating truly personalised marketing. This also represents greater freedom for marketers: negating the need for lengthy test and learn marketing cycles, reducing the level of engagement required and making choices more accurate. Finally they are able to concentrate time and effort on the creative elements involved in generating the right offers and therefore giving the machine more to work with.

If we look at a mobile operator as an example, this might mean offering one roaming customer a roaming bundle via SMS. For another customer running out of data, this might mean a notification and upsell message for more data. For another it may simply be a reminder to top up before their credit expires.

In this way, big data and machine learning enable true Customer Value Management, enabling marketers to understand and maximise the value of each individual customer through ongoing, tailored interactions. Customer interactions are relevant and valuable and customer experience can be easily tracked and improved, providing marketers with the opportunity to create rich records of what a consumer wants while creating greater “stickiness” with the brand – making a far more powerful CRM proposition than has been possible before.

While this clearly has impact on decreasing the likelihood of customers churning to a competitor, it can also directly impact the bottom line by delivering a greater return on investment. Our customers typically experience incremental revenue increases of 3-5% across the entire base.

Big data and machine learning are certainly the ‘next big thing’ in the evolution of CRM and customer marketing; extracting more value from data and enabling faster, more intelligent customer interactions that are based on relevance, value and personalisation, and living up to the promise of one to one marketing. Brands must now learn how to effectively harness this new world of big data to be able to claim the welcome rewards.