AI Your Future Today

Think Small

Think Small was one of the most famous ad campaigns for the Volkswagen Beetle. Now, we’re giving you that same advice when it comes to maximizing results for your business.

Your organization may still be recovering from – and paying for – the last major digital transformation project to be able to deliver information from your legacy systems to web, cloud, and mobile app requirements.

Meanwhile, your digital innovation team continues to explore how to use the latest technologies to transform major parts of your business to meet the demands of today’s consumers.

Now, we’re suggesting you should think small. We’re not saying that you should stop your path to technological enlightenment or cancel the technology projects that have already started delivering returns.

What we are saying is that it is time to take a step back from the project management perspective and return to the overall strategic view of why you began all of these initiatives to begin with.

Sometimes tweaks can have a higher ROI than transformations. It’s time to examine your overall operations to find the smallest, most incremental steps that will allow you to leverage the systems already in place while strengthening your bottom line.

Let’s go to the cliché. It’s cheaper to retain a customer than to recruit new ones, especially when you consider the lifetime value of a customer. Those digital transformation projects were implemented to strengthen those retention rates, but the ROI takes quite some time to realize.

The critical goal of “thinking small” is to strengthen and maintain your existing customer base without yet another digital transformation project.

Now it’s time to think small – very small.

One single number can have a major impact on increasing the ability to maintaining and strengthen the customer relationship – customer churn. Analyzing and predicting customer churn immediately identifies a specific group of customers that require immediate intervention.

From a “digital transformation” perspective, getting the data together to create this model is generally pretty simple; it requires the customers’ transaction behavior for a previously determined time period – generally one to 2 years, with a focus on the latest (two to three months) before the churn.

To create the model, the analysis is to create “churn” and “no churn” groups. The model can then be applied predictively to other customers.

Once the potential churn group is discovered, the first item for analysis is pretty simple. Based on their previous activities, the enterprise needs to determine if it wants to keep the customers most likely to churn in the next three months. If the answer is no, the business can instantly reduce costs by eliminating special offers to this particular group.

If the answer is yes, the organization can immediately pass the list of clients to the customer success team, who can quickly begin A/B testing regarding retention campaigns to prevent churn, such as loyalty campaigns, rewards cards, upsell, a discount and refer-a-friend programs.

No digital transformation. No advanced Data Science. No machine learning experiences. No major investment in IT. Just simple, laser-like analysis of customer behavior – think small, and profit big.