How well do you know your customers? How long ago did you build your ideal customer profile (ICP) and are you updating it frequently as you learn more about them?
We’ll cover the benefits of building a clear ICP in another article, but safe to say that the better you know your customer, the easier it is to sell to them. Or, put another way, the more relevant the content, the higher the conversion rate.
Structured vs. unstructured data
As a business owner, structured data refers to information that is organized in a specific format, such as in a spreadsheet or database. This type of data is easily searchable and can be easily analyzed to extract insights and make decisions. Examples of structured data include customer contact information, sales figures, and inventory levels.
Unstructured data, on the other hand, is information that is not organized in a specific format. This type of data can include things like customer reviews, social media posts, and email communications. Unstructured data can be more difficult to analyze and extract insights from because it is not organized in a consistent way.
In running a business, it is important to draw insights from a mix of both structured and unstructured data. Structured data can provide a clear and objective view of the business, while unstructured data can provide insights into customer sentiment and feedback. Having both types will help you make more informed decisions.
Analysing unstructured data
Unstructured data, such as customer reviews, social media posts, and email communications, can provide valuable insights into customer sentiment, feedback, and behavior. This type of data can be analyzed to identify patterns, trends, and opinions that can inform business decisions.
There are a number of software tools that can be used to analyze unstructured data, including:
- Natural Language Processing (NLP) tools, which can be used to extract meaning from text data, such as customer reviews. These tools can be used to identify key words, topics, and sentiment (positive, negative or neutral) in the text.
- Sentiment analysis tools, which can be used to determine the overall sentiment (positive, negative, or neutral) of a piece of text.
- Social media listening tools, which can be used to track mentions of a business or brand on social media platforms. These tools can provide insights into customer sentiment, feedback, and behavior.
Practical example use cases
Example business use cases of using unstructured data for decision making include:
- Identifying customer pain points and feedback from customer reviews and social media posts, and using this information to inform product or service improvements.
- Using sentiment analysis on social media posts to gauge customer sentiment towards the business or brand, and making adjustments to marketing campaigns or public relations efforts as needed.
- Analyzing customer email communications to identify common questions or concerns, and using this information to improve customer service or create new FAQs.
- Identifying product trends by analyzing customer reviews and social media posts to identify popular features and functionalities, and using this information to inform product development decisions.
Creating an edge for your business requires you to adapt based on feedback from your customers, whether that be explicit (i.e. structured data like number of orders) or implicit (i.e. the overall sentiment of reviews about your business over time as extracted from unstructured data).
Start collecting high quality and clean data from across your business in a single repository and use it to form a single view of customer. Finally, overlay sentiment and other insights from unstructured data to complete the picture.