Data Science

Using Data to Prosper in Tough Times

As processes gain greater quantities of data, businesses can leverage data's power to become leaner and more profitable.

Become leaner, more efficient and smarter

There is no doubt that the coronavirus pandemic has taken a significant toll on human life, social structures, and the global economy.

This article outlines how the intelligent use of data can help organizations through these tough economic times and potentially thrust them into a further competitive advantage in the future.

Customer Relationships

Keeping existing customers happy

It is far more expensive to acquire new customers than to retain new ones. In tough times, customers are forced to make hard choices with limited resources leading to a change in their behaviour.

“It is six to seven times more expensive to attract a new customer than it is to retain an existing one”  —  ThinkJar

Predicting which customers are about to churn could help you take preventative action by offering rewards or simply reaching out to your customers and listening to their problems.

Acquiring new customers

Marketing budgets are among the first items to be cut in times of hardship. Your existing budget can likely be optimized and used in the most efficient way possible by focusing on higher-quality customers.

Quantity versus quality: Ever heard of the 80/20 rule?

The theory goes that 20% of your customers will give you 80% of profits. Through intelligent customer segmentation, you can identify common characteristics of your most profitable customer segments and correspondingly spend more of your marketing budget on targeting more of those customers. This leads to lower customer acquisition costs for the highest value customers.

Process Optimization

You could optimize processes at your company to allow for the business to be run more efficiently and to free staff to work on higher-value tasks. You could either do this through automation or enhancing human tasks by taking advantage of the relative advantages of humans and computers.

Some examples:

1. Call Centre Optimization

You might be running your call centre with skeleton staff due to financial and logistical constraints. Many call centres contact all leads indiscriminately. However, by prioritizing the most important leads that are most likely to convert, call centres can save hours for their call centre agents and increase profits.

2. Quality Control

Using a camera and other sensors, one could leverage the power of Artificial Intelligence (AI) to identify items that may be lacking in quality. This has become far more effective in recent years due to advances in AI and cloud computing. An employee will verify that the system has correctly assessed that a product is faulty. These systems allow you to improve the quality of your products without having an army of employees assessing product quality.

3. Automated Personalized Newsletters

I have received many emails during the coronavirus lockdown from retailers whose wares I often buy. However, most of these offers are completely irrelevant to me. How can this happen when I have bought products from these retailers before and they have data about me?

Product recommendation algorithms combined with automated personalized emails designed to maximize sales would allow retailers to target customers with what is most relevant to them. This leads to increased engagement and more sales.

35 percent of what consumers purchase on Amazon and 75 percent of what they watch on Netflix come from product recommendations” — Mckinsey

Decision Making

Decision making is a tough science. However, it can be made easier by making the right information available at the right time to the right person.

It falls into two broad (often overlapping) categories:

1. Decisions made by humans using timely information

2. Decisions made (mostly) by computers

Decisions made by humans using timely information

Excel to Dashboards

Real-time analytics are essential for a modern company wanting to stay competitive. Highly visual dashboards allow executives to understand the organizations at a glance and make decisions on the fly. Furthermore, they can be customized to each user — for example, the sales exec has a different need to the accountant. Dashboards can be made available on desktop, mobile, and even chatbots (imagine talking to your chatbot to ask for sales figures for last quarter and getting an instant response).

Present Versus Future

Most dashboards are configured to tell you what has happened in the past, e.g. how many sales did you make yesterday? However, when making decisions, you don’t only want to know about yesterday; you also want to predict what will happen tomorrow and make the future more certain. Incorporating predictive analytics into dashboards by predicting relevant items such as sales, and customer and employee churn gives you the power to anticipate the future and make better decisions in the present.

Decisions made (mostly) by computers

Data is growing at an increasing rate and at a certain point, it becomes impossible for humans to make optimal decisions by themselves. AI works in the exact opposite way: the more data, the better the decisions. Moreover, some business environments need to make thousands of decisions on an automated real-time basis.

For example, sending hyper-personalized messages to millions of customers or making extremely fast credit decisions.

Where to from here?

I hope that I have managed to convince you that using your data better will enable you to become more efficient, lean, and profitable during the pandemic and beyond.

Reach out to us [] for a free consultation to discuss your unique data strategy.

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