How augmented analytics can help you improve customer focus
The pioneering retailers Harry Gordon Selfridge, John Wanamaker and Marshall Field coined a motto that was popularized in the 1800s: “The customer is always right”. While it’s still largely true, it’s also vital for businesses to make sure they attract the ‘right customers’ for them, and that they get to know them well.
Augmented analytics was not available to the likes of Selfridge, but it can provide today’s businesses with accurate and detailed information about their customers, insights they might have not been able to obtain through other analytics techniques. And since marketing is all about people, the greater insights you can glean, and the more you can understand the desires, activities and behavior of prospective customers, the more successful your marketing efforts will be.
Advanced analytics techniques enable companies to improve the customer experience, by developing a deep understanding of how customers interact with their brand through multiple channels. And, by unifying a diverse range of datasets, including website, CRM, demographic, psychographic and product usage data, it can provide marketing teams the detailed information they need to maximize customer value.
With this in mind, here are a few of ways on how advanced analytics can help you to improve your customer focus.
Make a step forward in understanding customers
Analytics based on machine learning can be used to assist with sophisticated marketing practices, such as modeling and predicting customer behavior and calculating customer lifetime value. It achieves this by exploring large volumes of different types of information and running algorithms on multiple customer micro-segments to discover trends and patterns.
Customer micro-segmentation identifies the interests of specific groups by applying analytics techniques to customer information. It helps marketers to send targeted messaging and offers to these, now more precisely defined customer groups. By sending the right message at the right time to the right person(s), marketers significantly reduce the cost of customer acquisition, but also increase customer satisfaction, as they are no longer bombarded by irrelevant messages at inconvenient times.
You can establish micro-segments on a range of criteria, including geography, demographics (such as age, education and family unit), psychographic (personality type, lifestyle and values), and behavior (loyalty, buying patterns and price sensitivity). And by developing hundreds – or even thousands – of micro-segments, you can more accurately target your customers with the right mix of products, services and price points.
Banks identified new customer segments by using augmented analytics
Industry research done by Gartner has shown that banks were traditionally targeting older customers for wealth management services, under the assumption that this age group would be the most interested. Using augmented analytics, banks found out that clients aged 20 to 35 are actually more likely to transition into wealth management.
Improve customer retention and reduce churn
Marketing professionals can also use advanced analytics technology to improve customer retention and drive down churn. Tools based on artificial intelligence can be used to work out which customers are most likely to leave, for particular product or service combinations, in which specific segment, and at what point in the customer journey or lifetime.
This information can be used to trigger specific marketing interventions, for example, tailoring special offers or bundles to individuals to prevent churn, or winning back customers through appropriate messaging. Augmented analytics can advise you on the right marketing mix and tell you the best channel to reach targeted customers, whether that’s social media, email, SEM, TV, OOH or even a traditional mail campaign.
Companies in the telecommunications industry are known to be among the most advanced in handling vast amounts of data they have on their customers. By applying advanced analytics methodologies to this data and using specialized tools in analytics platforms such as Adverity, telcos are able to deliver highly customized and targeted information to perspective and existing customers, displaying the right offer to the right segment of customers.
Recommend the right products to the right customers
Another great use of advanced analytics based on AI is product recommendation, which can also increase conversion rates and drive down customer churn. A product recommendation engine is a predictive analytics algorithm that digests all the available data on a customer prospect, and predicts which product, service or package they are likely to buy.
This may sound like science fiction, or something you don’t think is possible, but we have seen it in action, and it works. The algorithm carries out statistical analysis on as many data points as possible, on such things as customer demographics and psychographics, to get the most precise recommendation. You can combine this information with data from search queries and browsing habits to gain a more accurate picture of the prospect.
Then, based on a range of tested and proven product and service packages, and their adoption and churn rates for the prospect’s sub-category, the recommendation engine can suggest the best fit for each individual customer, optimizing cross-sell and upsell opportunities.