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How to Collect Valuable Customer Data and Transform It Into Cash Flow

How to Collect Valuable Customer Data and Transform It Into Cash Flow

Customer data is one of the most valuable assets when creating marketing strategies, scaling up, or optimizing current processes. You can use it to obtain valuable insights or uncover specific patterns that can help you drive decisions or adjust current practices to reach peak performance.

Try this AI-powered business tool:

  • Airgram is an AI-tool that records, transcribes, summarizes, and shares meeting conversations. It transcribes speech into searchable text and creates sharable video clips.

Furthermore, it would help if you had a proper way to collect this data as well as reliable strategies to leverage it to understand your customers to reap the full benefits. When you truly understand your customers, you can create personalized experiences for them and skyrocket your company’s relevancy.

In addition, a successful personalization strategy needs a lot of customer data coupled with creativity to create those special, hyper-personalized experiences.

For example, you can send unique handwritten notes to your customers, but without relevant customer data, you won’t be able to tailor them to each one individually.

Now, let’s evaluate the best ways to collect valuable customer data, and transform it into cash flow.

Types of customer data

First and foremost, let’s explore the kind of data valuable to companies. This categorization corresponds with the actual value customer data can provide, and the main categories are:

  1. Personal (basic) data – This includes personal data like customers’ names, email addresses, location, job titles, etc. Personal data can also include non personally identifiable information such as IP addresses, device IDs, device types, etc.
  2. Behavioral data – This data consists of customers’ purchase histories, usage information (when using the company’s products or services), as well as the information about how customers scroll, click and even move their mouse.
  3. Engagement data – This category encompasses data that is generated through customers’ interactions with a particular company. Precisely, engagement data can include the way customers interact with websites, social media ads, apps, customer service, etc.
  4. Attitudinal data – This data is connected with various metrics that show customers’ satisfaction, purchase preferences, brand desirability, perceived value, etc.

There are many sources companies can use to collect valuable customer data, ranging from email campaigns to social media ads to websites. Basically, almost any touchpoint companies have with their customers can be turned into a source for valuable data collection.

An excellent example of collecting customer data through social media ads is LinkedIn advertising – a great source abounding with rich and relevant customer data. 


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The important objective of your data-collection task is defining what you need customer data for. Start by defining your end-goal and determine if you want to:

This step is vital because the methods you are going to use for effective data analysis depend directly on your data-analysis objectives.

How to collect valuable customer data

When collecting customer data, it is essential to pay attention to privacy standards and the security of data your company will collect and process. These are the three most common ways to collect customer data:

  1. Asking your customers
  2. Buying data
  3. Tracking your customers

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Asking your customers for data mainly means asking them for their feedback. You can do this by having them complete surveys, questionnaires, contests, etc. You can also collect customer data when they reach out to your customer service, obtain their phone number, purchase history information, gauge their satisfaction, and other relevant information you are after.

A good idea is to include a quick satisfaction survey at the end of a customer service call & chat and add fields to collect relevant data.

Buying data primarily means using data brokerage services used to outsource all the work for you. Data brokerage companies specialize in collecting customer data from social media, public records, online behavior, etc. Afterward, they use machine-learning algorithms to segment customers into specific groups based on their similarities.

Tracking your customers revolves around leveraging intelligent metrics and AI that can effectively collect and extract data. Virtually, any interaction with your customers can be quantified, measured, and then analyzed.

After successfully collecting loads of data, you need to analyze it carefully and effectively. For this, you’ll need a reliable way to present and structure your data clearly and concisely.

A great approach is to go with visualization, and one of the best visualization methods out there is the Kano model. This model can help you discover your customer satisfaction based on behavioral data from your website.


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Transforming insights into cash flow

Finally, here is the essential part of your data-collecting endeavor. There is a myriad of ways you can transform customer data (and extracted insights) into cash flow. You can:

  • Optimize your marketing and advertising strategy
  • Build top-notch customer experiences – Powerful insights will help you create a hyper-personalized experience and provide your customers with rich experiences they’ll remember. It can improve your brand reputation, relevancy and boost customer loyalty. With a strong and consistent customer pool that’s constantly expanding, your ROI can explode as well.
  • Data brokerage – Given the moral standards and privacy regulations, this option is not suitable for every company. However, the demand for buying data is rising and companies can specialize in data-brokerage to create a constant cash flow.
  • Create new business models – Insights from valuable customer data can open new opportunities to create thriving businesses.
  • Optimize your business processes — In using the abundant customer data intelligently, companies can enhance and improve their processes using relevant, up-to-date data.  For example, insurance companies can collect real-time location data to assess the driving behavior of their clients and define the risks and pricing for each.

Final words

Collecting valuable customer data is the first step of a successful data strategy. There are many ways and strategies to collect it.

However, the most crucial step is how to go about analyzing this data to transform it into cash flow.

To succeed in this, you should use proven tools and best practices that will enable you to create profound insights on your customers.

Guest author: David Wachs – A serial entrepreneur, David’s latest venture, Handwrytten, is bringing back the lost art of letter writing through scalable, robot-based solutions that write your notes in pen. Developed as a platform, Handwrytten lets you send notes from your CRM system, such as Salesforce, the website, apps, or through custom integration. Used by major meal boxes, eCommerce giants, nonprofits and professionals, Handwrytten is changing the way brands and people connect.

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