How to Unleash the Power of Insights and Data Science Teams

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    Insights and data science teams play a key role in gathering crucial research that empowers objective, strategic decision-making. Unfortunately, insights professionals and data scientists often sit on separate teams and report to different leaders, which can potentially cause breakdowns in communication, missed opportunities to collaborate, and unnecessarily duplicated work.

    Because their strengths lie in complementary areas, increasing alignment between insights and data science teams can have a drastic impact.

    Insights teams are experts in conducting qualitative and quantitative research to answer strategic business questions. For example, they may interview customers or conduct surveys to understand:

    • The reasoning behind their shopping behavior
    • How they experience the customer lifecycle
    • How your products or services fit into their day-to-day lives

    New technologies are making it possible for insights teams to collect a vast amount of data from their research. And that’s where data science comes into play.

    Data science teams are skilled at analyzing large amounts of raw data and extrapolating trends. They typically use data modeling, machine learning, and algorithms to investigate structured, unstructured, and semi-structured data .

    When they work together, insights and data science teams can help you get a complete picture of what your customers want and how they behave, allowing you to develop a uniquely engaging customer experience.

    And considering that organizations spend more than $16 billion on research each year, it’s worth the effort to align both teams and maximize the value of their research.

    So, how can you combine the power of these traditionally separate teams?

    Below, we’ll cover three tips you can use to get your insights and data science teams on the same page.

    Discuss Priorities

    Because of their different skills and experiences, your insights and data science teams likely have different ideas on what new research and data would be most impactful.

    Facilitate conversations where both teams discuss their current priorities and weigh the pros and cons of each. By creating alignment around your company’s most pressing needs, both teams can put their focus on fast-tracking the most important initiatives.

    As a bonus, these discussions often expose both teams to new ideas they wouldn’t have considered on their own, leading to entirely new priorities that bring significant value.

    Aligning insights and data science teams around the same priorities can also reduce the time it takes to complete research. For example, if a project starts with your insights team conducting interviews and journey-mapping projects, the data science team can immediately begin setting up the data pipelines needed to validate their findings.

    Review Research Methods

    If insights and data science teams don’t understand how the other team conducts their research, there’s little hope of alignment.

    Make sure both teams review the research methodology the other team employs.

    Not only will this help both teams understand how the other works, it will also give them the opportunity to offer suggestions that can improve your current research processes.

    For example, your insights team might notice that certain data collected around product use that isn’t currently analyzed could provide valuable knowledge. Conversely, your data science team may notice your insights team should focus more on interviews with a certain persona to help gather specific data.

    Allowing each team to better understand the other’s research methods can also help them develop consistent terminology they can use when discussing research. This will improve communication and understanding, allowing for more accurate analyses.

    Share Findings

    To get the most value out of their research, your insights and data science teams must share their findings with each other. Then, they can conduct supplementary research to validate and expand on each other’s findings.

    But it shouldn’t end there. They should also distribute the results of their research to the entire company, so every department can use it to make improvements.

    If you can create a culture of knowledge sharing, your insights and data science research can impact many different areas of the business. For example, your research can help:

    • Customer success and support teams offer better service
    • The product team improve your offerings
    • Marketing and sales accurately convey the benefits of purchasing from your company

    But many organizations lack the resources to ensure research makes it into the hands of everyone who would benefit from it. According to a Deloitte study, an inability to share customer data and knowledge across departments is the number one reason organizations are unable to create a customer-centric culture.

    That doesn’t have to be the case at your company.

    To ensure your insights and data science teams can share the results of their research across your entire company, consider investing in a knowledge sharing platform.

    This will empower your insights and data science teams to easily store, organize, and share their research. And it will give other departments the ability to search for the information they need, when they need it.

    With the information available to all departments, your organization can truly unleash the combined power of your insights and data science teams.

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