How to Use Data to Make Your Business More Profitable

Your company probably owns mountains of data, we should simplify things by defining four key sources of data:

1. CRM and web-generated marketing data: serves as the customer’s voice;
2. Transactional data from the ERP: offers rich insights about the client;
3. Financial data: translates transactional data into monetary figures;
4. Data from third parties: brings additional context to the data.

Data science can be applied to find and refine a target customer base to generate more revenue. In sales, specifically lead management, models can analyze your past customers and score leads resulting in greater sales efficiency. Not only past in-house customer data is used but also social media interaction for scoring. If you did apply artificial intelligence lead scoring you will see an increase of 50% more appointments and a 60% reduction in call time. And as you may well know, better leads will get the sales deal done faster and thus resulting in more revenue.

On the marketing side, data science improves marketing campaigns by enhancing customer profiling.

“Studies have shown that correctly targeted emails lead customers to spend 38% more, and retargeted customers convert 70% of time.”

Big data is providing insights into which content is the most effective at each stage of a sales cycle, how investments in CRM-systems can be improved, in addition to strategies for increasing conversion rates, prospect engagement, conversion rates, revenue, and customer lifetime value. For cloud-based enterprise software companies, big data provides insights into how to lower the customer acquisition cost (CAC), customer lifetime value (CLTV), and manage many other customer-driven metrics essential to running a cloud-based business.

Typically, marketers are interested in three types of big data: customer, financial, and operational. Each type of data is ideally obtained from different sources and stored in different locations.

• Customer data helps marketers understand their target audience. Data of this type are facts like names, email addresses, purchase histories, and web searches. Just as important are the indications of your audience’s attitudes that may be gathered from social media activity, surveys, and online communities, etc.
• Financial data helps you measure performance and operate more efficiently. Your organization’s sales and marketing statistics, costs, and margins fall into this category. Competitors’ financial data such as pricing can also be included in this category.
• Operational data relates to business processes. It may relate to shipping and logistics, customer relationship management systems, or feedback from hardware sensors and other sources. Analysis of this data can lead to improved performance and reduced costs.

Companies now need to apply data science as a part of their business and culture. Not doing so leaves too much money on the table. Data alone does not provide actionable insight. Data science unlocks its value. Marketers should work closely with data scientists in order to gather valuable insights across departments. If you are still struggling to understand how to increase data profitability make sure to reach out to 4P square’s experts. We are happy to provide the extra hands needed!

This article was written by Alexander Adams, a marketing consultant at 4P Square. He has a particular interest in (digital) branding, and he brings expertise to the overall product marketing strategy.  He’s been active in various industries, ranging from tech to automotive, where he connected dots between digital marketing & sales. You can find him on LinkedIn or reach out to him directly via the 4P Square contact form.