It is fairly simple: your segmentation is not good enough! You’re still doing it by hand, based on your experience as a marketer. But I hate to break it to you; you’re not that good. Artificial Intelligence does it better than you, and companies are starting to take notice.
Advertising is expensive and everyone who has ever engaged in advertising knows that. One of the biggest headaches for advertisers is to show the big boss that it’s worth it and the company is getting its return on investment (ROI). That can turn out to be a merely impossible task and therefore marketers have strived to make their targeting as accurate as possible in order to maximise the effectiveness and acceptance of their message.
That is done by segmentation; the dividing of a broad consumer market, usually consisting of existing and potential customers, into sub-groups of consumers based on some type of shared characteristics. But how do we know if we’re successfully reaching the right group of potential customers? How do we know that we have grouped customers in such a way that every group has something more in common than other groups. All we want is that all customers in a single group are as similar as possible, whatever similar means, and that customers in different groups are as different as possible.
Segmentation done by humans is usually quite simplistic in nature; by age, gender, location, income etc. But what if there are other groups, better groups, that are hidden from the human eye? Those groups might not be obvious at all, but they’re there. If this is the case you could dramatically increase your ROI from your advertising by detecting those hidden groups and make your marketing efforts far more effective.
Until most recently, segmentation has been a form of art. Now it’s science.
Clustering (cluster analysis) is taking the marketing and advertising industry by storm. Companies are now able to significantly increase the effectiveness and acceptance of their marketing message by utilising Clustering in order to create better segments which allow laser-focused marketing messages. Obviously, this leads to higher ROI.
Customer segmentation analysis, usually called clustering or unsupervised learning, is a statistical technique used to group customers into clusters. With the utilisation of machine learning algorithms, we are now able to “group a set of objects (prospective clients) in such a way that objects in the same group are more similar to each other than to those in other groups”. The aim is to form groups where customers in each group are as similar as possible, and also to achieve is that customers in different groups are as different as possible.
This is revolutionary to the marketing & advertising industry and businesses are taking advantage of analytics in order to dramatically increase the effectiveness of their marketing and advertising efforts and increase the return on investment.
This is not just empty words on paper. Personalized marketing has always been one of the most effective marketing strategies and now it’s being taken to higher levels than ever before.