What is Behavioural Science?<\/strong><\/p>\n

Behavioural science uncovers what people really<\/strong> do, not what they say<\/strong> they’ll do \u2013 and the implications of this on product development are profound:<\/p>\n

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• Enough organisations recognise the importance of consumer insight to product development, but the difference between winning innovation and unsuccessful, backward-facing innovation, lies in the methodologies, frequency, and robustness of this research.<\/li>\n<\/ul>\n

   <\/p>\n

  How do consumers really make decisions?<\/strong><\/p>\n

  In the book Thinking, Fast and Slow, Nobel prize-winning psychologist Daniel Kahneman explains that our brains make decisions in two ways<\/strong>:<\/p>\n

  \n
  • System 1<\/strong>: fast<\/strong>, instinctive, and emotional decisions<\/li>\n
  • System 2<\/strong>: slower<\/strong>, more deliberate and logical decisions<\/li>\n<\/ul>\n

    <\/p>\n

    We may like to think that complex or important decisions are made more rationally by System 2, but if you\u2019ve ever chosen a car based on colour, or recognise that cuddly Meerkat toys help sell insurance, that may not be the case.<\/p>\n

    As an example, in the supermarket we\u2019re typically using System 1,<\/strong> taking us just 3 seconds to buy a product and even less to decide on what to buy.<\/p>\n

    \n
    • It\u2019s a decision largely driven by automatic processes that lie below conscious awareness<\/li>\n<\/ul>\n

      <\/p>\n

      As System 1 is what we use when shopping most of the time, for most things, we need to target System 1 if we want to robustly predict consumer behaviour<\/strong>.<\/p>\n

      Long surveys, leading questions, or biased methods of research don\u2019t target System 1, and lead to a lack of robustness in the data. It\u2019s this robust data that allows companies to act like scientists when going through a development process, strategically and consistently achieving success, instead of like gamblers hoping for \u2018big wins\u2019.<\/p>\n

      The Implications \u2013 why does Behavioural Science, data, and technology matter to NPD?<\/strong><\/p>\n

      There are three important reasons to involve science and technology in the new product development process \u2013 more accuracy, less subjectivity, and more speed.<\/p>\n

      1) Accuracy<\/strong><\/p>\n

      If you\u2019re not incorporating scientific principles<\/strong> into your development process, you may be introducing a lack of accuracy<\/strong> into your NPD cycle.<\/p>\n

      This can sound like…<\/p>\n

      \n
      • \u201cThis concept will perform well as the report we commissioned last year said this is trending with consumers\u201d<\/li>\n
      • \u201cWe asked a focus group whether they liked our concepts \u2013 95% said yes, so this product will do well\u201d<\/li>\n
      • \u201cWe ran research at the start of the process and consumers liked the concept. If we make some tweaks it won\u2019t make a difference as the overall concept is the same\u201d<\/li>\n<\/ul>\n

        <\/p>\n

        Why does this happen?<\/p>\n

        \n
        • Using outdated insight<\/strong> \u2013 consumer opinion is always changing, and so real-time data is important<\/li>\n
        • Using the wrong method of research<\/strong> \u2013 the method of research collection matters \u2013 response bias, aka a \u2018desire to please\u2019 the researcher, may get in the way of honest answers in focus groups<\/li>\n
        • Not testing frequently<\/strong> \u2013 much like a scientist, it is important to test each change as you move along the product development process \u2013 testing every aspect such as packaging, pricing, and key marketing messaging \u2013 else you risk feeding assumptions into your process<\/li>\n<\/ul>\n

           <\/strong><\/p>\n

          2) Subjectivity<\/strong><\/p>\n

          If you\u2019re not incorporating data<\/strong> into your development process, you may be introducing a lot of subjectivity<\/strong> into your cycle.<\/p>\n

          Subjectivity sounds like…<\/p>\n

          \n
          • \u201cEveryone in the team preferred concept B, so let\u2019s go with that\u201d<\/li>\n
          • \u201cOur manager said we should go with this concept as she likes it the best\u201d<\/li>\n
          • \u201cThis concept is too risky, so and so said that they\u2019d never buy it, and they often buy in this category themselves\u201d<\/li>\n<\/ul>\n

            <\/p>\n

            Why does this happen?<\/p>\n<\/p>\n

            \n
            • Using a non-representative sample<\/strong> \u2013 your team are often not representative of the population your product launch is targeting \u2013 though validation from coworkers may feel like evidence that others like the concept, this is actually subjectivity, and not science<\/li>\n
            • Listening to the wrong stakeholders<\/strong> \u2013 oftentimes the highest paid person in the room makes the final decision \u2013 but this is based on their subjective opinion, instead of the consumer who actually decides what performs well on shelves when deciding to purchase products, or not<\/li>\n
            • Not being able to provide evidence a concept could perform well<\/strong> \u2013 which means concepts end up being watered down by the opinion of others, that could\u2019ve been winners with the target audience if there was data to prove this<\/li>\n<\/ul>\n

               <\/strong><\/p>\n

              3) Speed<\/strong><\/p>\n

              If you\u2019re not incorporating technology<\/strong> into your development process, you may be introducing a lack of speed<\/strong> into your cycle.<\/p>\n

              A lack of speed looks like…<\/p>\n

              \n
              • Pushing projects back when you need to make a change, in order to re-create concepts, test, and go through a long process again<\/li>\n
              • Waiting for commissioned research or spending time creating a long survey every time you need to make a decision<\/li>\n
              • Spending time on questions popping up that no one can solve, leading to speculation and conflict between members of the team<\/li>\n<\/ul>\n

                <\/p>\n

                Why does this happen?<\/p>\n

                \n
                • Not using an Agile methodology aided by technology<\/strong>, that allows you to make changes and easily test any tweaks, means your project gets pushed back as you spend time tediously going through rigid stages again (aka Waterfall \/ Stage Gate methodologies)<\/li>\n
                • Not adopting technology platforms<\/strong> that allow quick, speedy, and robust consumer research that anyone from your team can run, mean research becomes a lengthy, tiring process, which may even be tempting to avoid<\/li>\n
                • Not recognising the importance of accessible tools<\/strong> that make it easy to distribute robust answers through a team, dissolving any debates on \u2018what consumers would prefer\u2019 by getting answers directly from consumers themselves<\/li>\n<\/ul>\n

                  <\/p>\n

                  All in all, the consequences of not using effective evidence<\/strong> in the form of consumer intelligence<\/strong> in the product development process, means companies keep innovating for a past that has long gone, instead of for the future.<\/p>\n

                  By incorporating data, technology, and Behavioural Science into your NPD process, you can achieve the intelligence needed to make successful products, faster \u2013 and organisations who do not move with the times risk getting left behind.<\/p>\n

                  Want to find out more about the application of Behavioural Science to Product Development<\/strong>? Hear directly from author of The Choice Factory, Richard Shotton, at our upcoming Virtual Conference, Innovate 2.0! Register here: https:\/\/innovate-future.com\/<\/a><\/p>\n

                  <\/a><\/p>\n

                  Want to get to better products, faster?<\/strong><\/p>\n

                  Vypr\u2019s platform is built to tap into System 1. This means you don\u2019t need to understand behavioural science to use Vypr<\/strong> \u2013 we\u2019ve baked it into our platform.<\/p>\n

                  Get in touch with us to find out more:<\/strong> https:\/\/vyprclients.com\/contact-us\/<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

                  What is Behavioural Science? Behavioural science uncovers what people really do, not what they say they’ll do \u2013 and the implications of this on product development are profound: Enough organisations recognise the importance of consumer insight to product development, but the difference between winning innovation and unsuccessful, backward-facing innovation, lies in the methodologies, frequency, and […]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-5088","post","type-post","status-publish","format-standard","hentry","category-blog"],"acf":[],"yoast_head":"\n