What are customer insights? A standard definition defines customer insights – or customer intelligence – as an interpretation of trends in human behavior to increase the effectiveness of a product or service for a customer and to increase sales. According to a survey from McKinsey, having a deep understanding of customers, which is often referred to as a 360° customer view, is essential for developing strategies for sustainable growth, creating a superior customer experience (CX) and driving innovation. The research revealed that organizations that leverage customer insights outperform peers by 85 percent in sales growth, which is why more than 200 customer insight professionals in the survey said that customer insights is a key source for competitive differentiation.
What is a 360° Customer View?
Digging deeper into what constitutes or defines true customer insights reveals that a company may have some knowledge – or even a wealth of knowledge – about a customer and still lack true customer data insights needed to provide competitive differentiation.
A company may, for example, have a record of every customer transaction dating back years, from multiple in-store and ecommerce POS systems. Or, a company may have customer data from multiple channels; a customer’s call center activity, social media and ATM activity, to name a few. Unless the data is fully integrated, breaking down every channel or data siloes, the company will not have a single view of the customer. A true unified customer profile factors the interplay between every piece of customer data; how activity on one channel affects another, or how an in-store transaction might influence online behavior.
This is what is meant by a 360° customer view; a unified customer profile that tells a marketer everything there is to know about a customer. A 360° customer view enables true marketing insights, empowering marketers to analyze how one customer data set relates to the complete view, make prioritizations according to recency, business goals or what will create the optimal customer experience at a precise moment of a customer journey.
A single view of the customer that is updated dynamically in real time is known as the Golden Record, the foundation for marketers to proactively engage with customers across an omnichannel customer journey, providing a next-best action that is consistently in cadence of each unique journey.
How Does a 360° Customer View Work?
To use customer data insights provided by a 360° customer view preclude data or channel siloes. If, for example, a company is using customer lifetime value (CLV) as a metric for an email retention campaign, but bases CLV solely on transactions, transaction frequency and average spend, it misses an opportunity to capture other signals that may drastically alter the calculation. A customer may log a call center complaint, or post a negative social media post. If unstructured data is not persistently updated into a single view of the customer, the company runs the very real risk of introducing friction into the customer experience – especially if the email is locked and loaded and unable to account for dynamic, real-time updates.
A single customer view that is updated in real time, with customer data from every conceivable source, is an essential capability to accurately predict probabilities of retention, churn, acquisition or any key indicator tied to a busines outcome. Any customer interaction or engagement at any time or on any channel can change a calculation, which is why data or channel siloes or latency between when the customer data is compiled and it is matched, cleansed and made ready for actionable customer data insights tie the hands of marketers in providing a superior customer experience.
Innovative Use Cases for Customer Data Insights
A call center complaint and negative social media post just scratch the surface of the endless possibilities for what constitutes true customer intelligence, and how data-driven marketers can use a unified customer profile – the 360° customer view – to drive competitive differentiation with ambitious, innovative use cases.
In retail, for example, location-based marketing is becoming a popular way to use customer intelligence to create a unique, personalized CX. When geo-fencing insights are incorporated into a 360° customer view and made instantly accessible for a marketer, a retailer knows whether a customer is nearing a location, a competitor’s location or even a specific location inside a store. This knowledge becomes even more valuable when it is combined with other customer insight. Consider a curbside pickup scenario, where a customer has purchased a product online and has arranged a same-day curbside pickup. A geo-fencing capability may let a retailer know to send an SMS alerting the customer of the closest available parking spot, and send an associate out to be ready with the product upon the customer’s arrival. But what if there’s a rainstorm, or heavy traffic at the designated pick-up time? A unified customer profile that includes local weather and traffic conditions may change how that retailer engages with the customer. A personalized CX may account for inclement weather by securing the product in a waterproof container, directing the customer to a covered parking spot, or providing a one-time offer for 10 percent off rain gear, etc. Gridlock near the store may warrant an SMS to let the customer know when a more favorable drive time is expected.
Because curbside is an increasingly popular option, which some have called a “must-have service” that aligns with customer expectations for an increasingly digital and touchless experience, the above scenario illustrates the importance of combining multiple facets of customer data insights to create innovative customer experiences. Behaviors, transactions, preferences – even a customer’s surrounding environment – all contribute to a marketer’s full and complete understanding of a customer, and how that understanding helps to optimize a customer journey.
Data Aggregation, Machine Learning and Customer Data Insights
Customer data insights can also be mined from large segments of customers; audience cluster behavior analysis is a useful tool to predict what one customer may do based on trends in a larger data set. A bank customer who posts a social media screed complaining about checking fees may be a key churn indicator. By analyzing the aggregate behavior of thousands of customers who already did churn, a bank might extrapolate more meaning from the single customer’s social post. Perhaps customers who go negative on social are less likely to churn than those who place a call, and are more incentivized to stay with an extra book of checks than a reduced rate.
Cluster analysis for the purpose of deriving audience intelligence is made possible by automated machine learning. Predictive hyper-dimensional model clustering, with algorithms tuned to optimize and adapt for a specific metric can find nuanced pairings that truly predict a behavior, interest or outcome beyond a shared characteristic such as age, gender, income or geography.
Analyzing and understanding macro trends is a beneficial exercise to predicting the behavior of a single customer based on patterns of large segments. Automated machine learning predictions far exceed the capabilities of human in terms of scale and accuracy, providing meaningful customer insights that can be used to deliver a personalized CX across an omnichannel journey.
Customer Insights, One Platform & a Single View
For data-driven marketers who understand that true customer insights are a foundation for providing a differentiated customer experience, the days of using intuition or hazarding a guess as to how a customer might behave – or to think a trend applies equally to all customers – are long gone. In Addressing the Gaps in Customer Experience, a Harris Poll sponsored by Redpoint, customers were asked to define what a personalized customer experience means for them and 43 percent said that when it was a company or brand knows they’re the same customer across all touchpoints. That capability comes from having true customer insights, unfettered by data or channel siloes that cloud a single customer view.
With actionable customer insights derived from a 360° customer view, brands understand what makes a customer tick – motivations, desires, wants and needs. This is the premise behind the Redpoint rg1 digital experience platform, which applies real-time decisioning to the Golden Record to intelligently orchestrate a customer journey in the cadence of the customer. Delivering a superior customer experience depends on knowing everything there is to know about a customer. rg1 generates meaningful customer insights, and then turns them into differentiated customer experiences that drive revenue.