One of the secrets that data analysis helps us uncover is that of consumer behaviour, a key factor in making any business to focus and grow. In a given business there are those pieces of information which we are in the know, but don’t have in-depth knowledge about, the “known-unknown’. In a real-life situation, “Do we know how frequent our customer is to our website or physical store? What is their preferred choice? When was the last they visited us?” In such scenarios, Artificial Intelligence is just the apt tool to unearth a plethora of information from multiple sources such as webpages, customer survey data, CRM databases, and visitors.
As a business owner, you will not only be able to optimize your communication by tweaking your campaigns but also have in-depth insights into customer behaviour. For example: Which url’s or sections are people visiting the most? What content do they like to read? How frequently are they visiting? How long do they stay on the website?
At Infinite Analytics, we identify customer interests, customer preferences, and other characteristics of consumer behaviour for you to direct your business on the right path. For example, there could be a business selling books by way of a subscription model. Users could sign up to receive mystery boxes i.e. packages with pre-selected books to read. When a user visits the website of this business, a simple on-boarding process such as a survey to map out their reading habits better can be designed to get answers relevant for ‘the kind of books to stock’ or ‘the most read genres’ or ‘preferred national and international authors’ among other things. Post this, a specialist can be engaged to help them decode the collected data and apply the results directly to their business model for maximum returns.
As marketers, we use our domain expertise to infer patterns from this data. Even a short questionnaire with 10 questions can generate thousands, if not millions of different combinations of answers. As it is humanly impossible to memorize and identify patterns from data of this kind, AI comes into action again. It becomes a typical case of artificial intelligence to identify how similar or dissimilar are the users’ responses by using the clustering algorithm. The algorithm can spot that there are three or four latent segments of customers based on the type of books they would like to read at leisure or while travelling, or even just to use as a reference while socializing.
In the same example, there could be two categories of people who buy books. One could be the corporate executives who seek knowledge from thought provoking books like “Team of Teams: New Rules of Engagement for a Complex World” and another group could be composed of ‘weekend readers’ for books like “The Blue Umbrella by Ruskin Bond”. As the business uncovers these data insights from the clustering algorithm, one will probably increase the returns on advertising spends to create a lookalike audience on Facebook, Instagram or Google ads. This will help reach out to similar users with awareness campaigns, instead of just relying on the generic ads. While one should adjust existing communication with the current customers, according to their cluster labels, it is also imperative to come up with messaging and imagery tailored to that segment. Thus, providing personalized content without being overbearing helps cut customer acquisition costs.
We hope this detailed post will help you uncover some of the ‘known-unknowns’ in your respective businesses. If you’d like to know more about any particular aspect of AI, tell us in the comments or contact us at firstname.lastname@example.org