Customer needs are constantly undergoing change; oftentimes, this is the result of new technology, major global events, or simply a shift in people’s priorities and knowledge. For your business, being aware of this change and making efforts to be proactive are vital towards the growth of your company.
The first step you can take to do so is to gain a comprehensive understanding of your customer’s journey, or in other words, how they arrive at your services. By breaking down this journey, your company will be able to market your brand more effectively, install features to retain clients for longer periods of time, and create memorable experiences that will help to boost your company’s reputation.
One of the best ways in which to approach this task is through data analytics, which in recent times, has taken the business world by storm through the advantages and insights it can provide. In this blog, we will discuss how data analytics plays a role in the customer's journey, why data is necessary in this process, and how the rise of augmented features has improved the way in which we analyse data.
Data Analytics
Data is the fundamental requirement to accurately mapping out your customers’ journey. Without access to data, the most your company could do would be to make unsound speculations about your customer’ journeys, as with no hard evidence, accuracy would be compromised. However, having a solid foundation of data helps you to precisely determine the path your customers take to reach your services, and allows you to learn about their basic needs, tendencies, interests, and more.
Through data analytics, your business will be able to glean useful insights and use this information towards improving marketing campaigns, launching new products, or detecting issues in your company. For instance, if your company sells a series of hair products, and you notice that many of your customers spend an extended period of time scrolling between various products without actually purchasing any, this could indicate that you simply have too many products offered. If so, implementing a change would be easy, and again through the power of data analytics, you would be able to see how this change would affect your company in real-time.
The beauty of the process is that if it did negatively impact your company, you could revert the change and minimal harm would be done. But where exactly can you collect and harness data to use towards your company? Below, we have listed three of the major sources where you can get the data you need to map your customer’s journey:
- Web traffic data:
Arguably one of the most practical and widely used sources of data. On the internet, clients leave behind a detailed record of the websites, links, and applications they have clicked on. By collecting this data, you can create profiles of individual clients, as well as examine trends of data from multiple clients to help gain a clearer picture of your audience.
- Advertising platform data:
By collecting data from advertising platforms that you use, you will be able to gain information about the effectiveness of your marketing strategies, specifically in their ability to attract new clients to your services.
- Sales data:
Data on product sales is one of the most straightforward forms of information that can help you make business decisions. It directly notifies you of what products are selling, what aren’t, and helps you make changes to improve your overall services.
Augmented Features
One of the risks of data analytics is the risk of misinterpretation, typically due to the fact that tasks are performed manually and thus, are prone to human error. One of the recent solutions that have been developed to address this is known as augmented features. Business users who utilise this form of data analytics are often referred to as augmented consumers. Augmented consumers differ from their counterparts in that they do not strictly rely on traditional dashboards to graphically analyse their data. Instead, augmented consumers utilise advanced features such as augmented dashboards, natural language processing, and more when examining data. One of the advanced features of augmented analytics is known as automated business monitoring (ABM). ABM, as the name suggests, uses algorithms to give your analytics platform the ability to automatically detect and deliver important data insights in real-time to your employees, removing the need for error-prone manual exploration. Through ABM, your company will be able to respond to changes or events at a much quicker and more convenient pace.
Conclusion
To conclude, data analytics is the new norm for companies far and wide who seek to make use of customer data for their benefit. But for companies who wish to go the extra mile in order to ensure their success over competitors, the implementation of augmented analytics features such as ABM is highly suggested. By reducing error, increasing convenience, and boosting efficiency, the benefits are surely worth the effort.
About the author: Mark Roychowdhury is a Copywriter Intern at ei² niche consulting for #data #insights #performance www.eisquare.co.uk
Editor: Aleksandra Pavlovic