Meet Dr. Felipe Maldonado:

Felipe Maldonado is a Postdoctoral Researcher in the areas of Artificial Intelligence, Game Theory, Applied Mathematics, and Market Design. In his latest research, he covers the scientific approach to determine how social influence can impact demand and demand predictions. Felipe also provides his insight on how social influence can impact new product innovation and launch a new product into the market.

Can previous consumers and their star rating/feedback really influence our buying decision? Find out the truth.

What you will learn from this podcast:
• Decision science in retail. Felipe investigates how consumers make choices in online marketplaces (i.e Amazon)and the key features (e.g. product display, order, and ranking).

• The effects of online social influencer signals and how previous buyers, their star rating and comments influence buying decisions.

• Demand predictions and how it impacts decisions on what to put in stores (regardless online or offline).

• This opens up the question: can social influencers (i.e rating and feedback) be a more effective demand signal (hence, demand prediction tool) than traditional demand signals like seasonality? How can brand managers and category management professionals leverage this model to impact the likelihood of success of new product releases? What strategies can product brand managers and category management professionals leverage when their new products have no social proofing yet? Should product brands and marketers invest more of their funds into contacting external social influencers and get them to review a new product, seed ratings, and influence future online shoppers?

• You can download and read Felipe's research "Modelling consumer behaviour in the presence of network effects" here: https://openresearch-repository.anu.edu.au/bitstream/1885/200952/1/thesis_submission_Felipe_Maldonado.pdf