The Roles of Analytics in Data-Driven Product Design

Data can be very useful if it is correctly collected, organized, and interpreted. Data can provide useful information on what best fits customers. Hence, businesses are prioritizing data-driven product designs.

A business must employ a data analyst or data analytics tool to ensure that data is not just a pile of facts and figures. The business can vet the authenticity of the available data and its interpretation through data analytics or scientists. In addition, data scientists helps to extract information that is close to end users’ experience.

The most appealing products on the market are designed in a proportionate mixture of form and function. Hence, you need data to know the needs of the end users – function. Also, the design must be aesthetically appealing to the target audience of the product – form.

Hence, this article will show you some of the roles that data engineers need to champion in your company. These roles are specifically picked to address the need for a product design that will be functional and compelling for users.

Role 1: Research and Product Development Department

After the ideation process, top-notch market research is required to know the needs of end users. Check these roles of market research in product development.

The role responsible for this task is under the R&D department. The data engineer collects the raw data needed to process the information that the business should work with.

They conduct market research through online surveys, questionnaires, polls, interviews, etc. In addition, they study competitors and their products. The analyst provides the market study that the data should represent.

It might not truly represent the end users’ needs if the data is not well collated. Hence, analysts provide the research department with the type of data to collect. They can request a quantitative or qualitative survey.

The result of thorough research and accurate analytics can take time. Hence, it depends on the cooperation of other roles identified in this article. Introducing the collation early helps other roles to function well with the available data.

Role 2: Data-Driven Product Manager

The role of the manager entails having informed control over the product production process, especially design. However, it will be easy to determine the product viability before design with a data-driven product manager.

The manager needs to decide on what the ideation and research teams provide. The PM needs to be data-driven since the most influential decisions about the product design lies with the individual. You can learn more about decision-making for PM here.

The product concept can be verified for viability to make necessary inclusions for product design. In addition, the objective analytics of a PM should override the intuition based on the expertise of the PM.

Hence, the PM can determine which team is working and which one needs to improve. Data enginerering for data-driven product managers also helps in easing workflow backlog. Therefore, it can be used to create a product design roadmap for when it should be ready.

Role 3: Data-Driven Product UX Designer

The UX designer has more say than the PM when considering detailed decisions about product design. Working together with the analytics will make it easy to create an impeccable user experience. Learn here how to develop a data-driven UX.

A lot of features can appear confusing for end users. However, it is the role of a data scientist to help UX designers identify such features. In this case, objective functions and forms must be prioritized over design know-how.

Role 4: Data-Driven Product Developer

Product design involves a developer because the backend features of the product are equally important. Developers can innovate when creating the product for the data-driven design through analytics. New product development can be challenging, but the thorough sorting of data will help ease the burden on developers.

Role 5: Data-Driven Product Marketers

At the end of production, data drive product design remains relevant because it shapes how a product will be marketed. Analytics helps the marketing team sell directly to their target audience.

They can capitalize on information like medium, location, size, color, and much more when reaching out to their audience. Check out our article on how to leverage user-centered design.

Top 5 Questions on the Roles of Analytics in Data-Driven Product Design

These are some more questions you can have about data-driven product designs.