Flying Blind in a Time of Crisis:
How Analytics Can Help Us Thrive
The future is uncertain. You will not be able to survive forever on cost restructuring and balance sheet transformation. You will need to evaluate how your customers’ needs may have changed as a result of disrupted supply chains and perhaps permanent shifts in demand for how your product or services are delivered. You will need to change how you work, as you won’t have the resources or the time to spend on initiatives that don’t contribute to your bottom line. An effective and ongoing analytics practice will not only help you survive these times, but also give you the tools to ultimately thrive. Michael Festa's article: "Business Survival Guide - Creating 'Survival Time'" lays out the steps needed to extend your company's survival time.
What information do you have about your customers? Which of them generate your greatest revenue or profitability? Do you know how to retain your best customers? When they leave, do you know why? These questions and more can be answered by leveraging the data and information you already have about your customers with sound analytics.
Analytics means different things to different people. Some think of it as a department that helps inform marketing with A/B testing (test and control set up and evaluation), targeting and measurement. Others see it as a practice that falls within IT to produce reports and dashboards. The fact is, it is both and so much more. The dictionary defines analytics as “the discovery, interpretation, and communication of meaningful patterns in data.” This definition only identifies the computational part of the practice. To be leveraged successfully, analytics needs to be more than just the math and statistics. The analysis must combine judgement, common sense and business understanding in order to gain real meaning from data and truly inform the business.
Retaining Your Most Valuable Customers
One of the most important things to understand in any business is who your most valuable customers are. They have always been a company’s greatest asset, and now as we emerge from this pandemic it is even more critical to retain and reward these customers. You may have heard of the Pareto principle (also known as the 80/20 rule), where 80% of the result (in this case, sales) typically comes from 20% of the causes (in this example, a company’s customers). It is amazing how this principle holds true for so many companies and industries (illustrative example below).
Given this universal truth, it is incredibly important that companies do two things:
Identify who these critical customers are today, as they have likely changed in recent months.
Develop the proper controls to retain and reward those customers who have stayed with them through the crisis.
As David Ogilvy said, “Don’t count the people you reach, reach the people who count.”
Loyalty programs have never been more important as these customers are critical to your ability to survive and later thrive. A solid loyalty program will not only help retain and grow existing customers, it will ensure you have what is needed to appropriately encourage and nurture new customers to buy again.
Think of customer acquisition as a leaky bucket. While you’re acquiring new customers, you continue to lose existing ones. A solid loyalty program can plug some holes in your bucket, allowing you to keep your existing customers happy.
It costs so much more money and effort to acquire new customers to replace those you have lost. Your marketing, customer service, and operations budgets will go much further if you keep your high valued loyal customers happy before focusing on acquisitions. Otherwise you waste time and resources trying to fill up that leaky bucket. Rob Tedesco's article: “Hastening the Inevitable: How the Crisis Moves Retail Toward Digital” explains the importance of having these strategies in place along with segmentation, personalization and eCRM to incentivize frequency and steal visitation.
How Predictive Models Identify Where Your Bucket Leaks
Businesses will always have theories about why customers behave in certain ways—like understanding why customers stop purchasing from them. It is natural for most to think that there is only one reason a customer left, when in reality it is likely a combination of several. It is also common and, unfortunately, very unproductive to have a hunch about why customers are leaving, and then ask analysts to perform data mining tasks until the information needed to support the theory is uncovered. This scenario is known as a “fishing expedition.”
It is a challenge to identify all of the reasons why a customer stops purchasing, especially with one-off bivariate analyses. Predictive models can help in these situations as they are meant to:
Identify drivers of a specific customer behavior
Predict future customer behavior
Monitor customer performance
EXAMPLE: A former client believed that price was the main reason their customers stopped purchasing a certain product. So, they hired a pricing expert to test various pricing scenarios and recommend which would retain their customers while maintaining revenue and profits. Unfortunately, the analysis and testing were inconclusive. As they continued to see their customers leave, this client became desperate for answers. They engaged an experienced Analytics professional who developed a predictive model on all available data sources. This model uncovered multiple reasons why customers were leaving, none of which had anything to do with price. Some of the reasons included solicitation channel and payment method, things the client could quickly change and correct. The client was able to immediately adjust their solicitation channels to those that acquired customers preferred and encouraged payment methods that made it easy for customers to renew their orders. The model was also used to predict when a customer was likely to stop purchasing, so corrective action could be taken before the customer left. These improvements quickly and significantly increased customer retention rates.
Leveraging analytics to retain your customers is just one of many use cases that can help a company thrive. Other pertinent topics to come include but are not limited to:
Leveraging models to prioritize and invest in the right strategic initiatives.
Why and how you measure matters—defining KPIs that accurately measure company performance.
Calculating and predicting customer lifetime value post-COVID as inputs have changed.
Understanding and leveraging behavioral and attitudinal segmentation.
Integrating new sources digital data sources to improve personalization.
Whatever your questions are, they can be answered with the data you have and some analysis.