Leveraging Customer Analytics
It is important to understand that customer analytics alone cannot achieve the intended benefits. Specifically, data cannot take action; rather, insights from it empower leadership teams to make better business decisions. Additionally, the data that is available and accessible for analysis depends on the industry, type of business model, and varied customer interactions.
An appropriate customer analytics strategy should support business leaders in developing well-informed plans with minimal risk that drive profitability through customer spend. From the capability perspective, a deep expertise in algorithms will not be sufficient; a true understanding of human decision-making processes and their associated behaviors will provide the ability to capture complex phenomena that is critical to start a meaningful conversation with the data.
A true understanding of human decision-making and purchasing behaviors provides the basis for a customer-centric approach to Analytics.
A Focus On The Customer
For years, companies have gone about analytics from a business-process standpoint. Using the example of a consumer mobile phone service, providers have traditionally viewed the customer lifecycle as follows:
How do i identify prospects that are:
My best targets?
Most likely to respond to my offer?
In the market for my products/services?
Most likely ot actively use my products services?
How do I prioritize and manage the leads to focus on the best ones?
How do I optimize my offers based on the needs of the prospect?
How do I optimize the offer and product mix based on the profile and needs of the customer while I have his/her attention?
How do I assess payment risk of the customer?
How do I improve my fraud detection and investigation processes?
How do I price the service appropriately?
How do I improve the customer experience at the POS?
How do I continue to optimize the offer product mix for the evolving behavior and needs of the customer?
How do I identify and mitigate risk (payment, fraud) more effectively?
How do I retain my customers?
How do I cross-self other products within my organization?
How do I manage customer care effectively?
How do I improve the customer experience?
How do I collect recover more efficiently and effectively?
How do I win back ex-customers more effectively?
Viewing The Customer Lifecycle From The Customer's Perspective
However, the customer’s view of his or her own lifecycle is a very different one—much more complex, non-linear, and multi-dimensional.
If the goal of customer analytics is to better understand human behavior, leaders must make decisions based on how customers think, and not within the context of how business processes and functions are built.
As a customer moves through the process from awareness to purchase, she is considering whether a specific product - or any product - will meet her needs. At any time, she can spin off to explore
Tearing Down Silos And Moving The Business Forward
To get the most out of the available analytics, businesses must measure many different behavior dimensions. The views of a single customer can show loyalty, consumption propensity, risk, influence, and more, and business teams must shift from focusing on a single distinct part to looking at the customer as a whole. Silos within the organization can be the worst enemy of effective customer analytics. The impact of customer analytics can reach beyond simply responding to customer needs as they arise. Ultimately, businesses must be in tune with what customers are thinking and experiencing today to proactively predict their behaviors of tomorrow.