The Critical Role of Customer Data in Creating Personalized Product Experiences

In as little as the past decade, the importance of customer data has grown and changed in immeasurable ways. Even ten years ago, the customer data available to organizations was more sparse, hard to monitor, and challenging to pull significant insights from. Today, things could not be more different; data availability is easier than ever, and customers expect that the way companies target them revolves around that data.

Product Personalization

Product personalization is just one example. According to Zendesk, 76% of customers expect personalization when engaging with goods, services, and companies. In large retail companies, the healthcare industry, and even the hospitality industry, developing products and services that keep customers returning is the continuous challenge businesses face. Product management and customer data are inextricably linked regardless of the business setting itself. It’s more than focus groups and surveys nowadays; it understands what a specific customer is searching for, frustrated with, buying, and more. These small pieces of information come together to paint a picture that benefits both the customer and the business, making this data invaluable.

Major retailers like Amazon or Walmart and other global companies focus on projects for international markets like Canada, Chile, India, China, South Africa, and many other countries around the globe. These projects pair customer data with business data sets to draw insights and inform decisions. While it may seem like customer data exists in a silo, it has a proven track record of leading to business success when pulled together in suitable ways. Algorithms are built to read and monitor the data, ensure validity, and integrate customer profile elements worldwide. These tools enable targeted marketing, personalized communication, and a seamless customer experience.

With this data, businesses can do much more than incorporate customer insights into product roadmaps and can also anticipate supply chain issues, track repeat returns from customers that may be abusing the return policy, and avoid time loss within the production process. Although most organizations only analyze 37-40% of their available data, major global retailers exemplify what strong data capabilities can enable. On an annual basis, the incremental revenue from customer data insights is in millions of business value.

How Data Influences Product Roadmaps

Product experts rely on this data type to vet product ideas, implement new product features, and enhance existing products. If one product is getting returned at a high rate, they can dive into complaints or possible defects that might be happening, work to resolve the issue, and get a better product back on the shelf. Similarly, with new products, product teams examine customer requests and complaints to help with the product design process, ensuring that the “voice of the customer” is always part of the equation without having to reach out to the customer through manual channels.

If organizational leaders are not well-trained in analyzing and interpreting data, they will not be able to make data-driven decisions or notice trends within their departments. Data literacy is critical for many different individuals within an organization; just like customer data provides context for product enhancements or new releases, that same customer data can help customer service teams determine where gaps in their customer management might be. Data is the most powerful currency in business, though only some truly understand that reality.

Healthcare Data

For many, understanding the importance of clean, actionable data sets for retail giants like Walmart is easy, but in reality, every business in today’s world requires strong expertise surrounding data and its capabilities. Inovalon, the healthcare industry partner, as an example, is a data aggregator for large healthcare providers in the US. The organization relies on patient data to help medical providers predict the risk of specific patient categories and even determine reimbursement rates. Though the data used by Inovalon’s clients differs from that used by Walmart, it still plays a critical role in helping its clients serve their patients and provide proper treatment plans.

Travel Industry Data

In the travel industry, using Expedia as an example, data is one of the significant benefits of the platform and a big reason why travel partners such as airlines and hotels offer their services on the site. Expedia Partner Solutions (EPS) is a division dedicated to providing tools and technologies to enhance marketing efforts, offer data-based insights and make managing guest communications easier for travel partners. With a significant value proposition devoted to data, Expedia illustrates the importance of customer data in yet another industry.

Final Thoughts

Each time a person interacts with a business, whether to purchase a product or browse a website, small actionable bits of data, including events and profile-based elements, are collected to make the next time that person interacts with the business even better. As data becomes a focal point for industries all over the globe, people will see refined advertisements, personalized experiences, and even tailored products show up in their lives more frequently – all thanks to data collection and analytics. Product creation – and business in general – is facing a revolution that centers the business experience around the people it serves.

The great thing about data is that it offers value to every entity involved; when the impact of data is examined from different angles, such as the data’s impact on the customer, the business, or even the internal employees, it’s powerful. More effective solutions will become the norm as more companies across industries learn how to capture and utilize valuable data, and customers will feel seen in new ways. With 97.2% of businesses investing in data and AI, one thing is clear: data isn’t a “nice to have” anymore; it’s a necessity.

The lead image for this article was generated by HackerNoon's AI Image Generator via the prompt "(customers:3) in a (store:2)".