Imagine you’re walking into a tech store to purchase a new phone. As you’re browsing through the phones, a salesperson approaches you asking if you need any help. You’re not sure what accessories you need, but the salesperson suggests a phone case and screen protector. The salesperson explains how the accessories are specifically designed to complement the features of the phone, keeping it safe from scratches and drops. They also mention how these accessories can save you money in the long run by preventing costly repairs. Feeling more confident in your decision, you agree to purchase not only the phone but also the phone case and screen protector. As you leave the store, you feel satisfied with your choice of products.
How did the salesperson convince you to buy not just the phone but also the additional items? A recent Journal of Marketing Research study by Jennifer K. D’Angelo and Francesca Valsesia provides an answer. When an individual, such as a salesperson, stylist, waiter, designer, shop assistant, or influencer, suggests combining two products for purchase or use, they are perceived as an expert in the product category. As a result of this higher level of credibility, consumers are more likely to follow such individuals’ recommendations and make a purchase. This effect holds true regardless of whether the combination is encouraged or discouraged, whether the customer requires the advice, or whether it applies to other products in the category. Furthermore, the more explicit the combinatory recommendation, the stronger the effect.
When an individual, such as a salesperson, stylist, waiter, designer, shop assistant, or influencer, suggests combining two products for purchase or use, consumers perceive them as an expert in the product category and are more likely to follow their recommendations and make a purchase.
We had the opportunity to contact the authors, who kindly provided interesting insights into this article. Read on to discover more details about this fascinating research.
Q: Providing combinatory recommendations is a novel cue that consumption advisers can use to signal expertise. What sparked off the initial research idea of combinatory recommendations as being more impactful?
A: Anecdotally, when browsing images of clothing outfits and interior design, we noticed ourselves thinking, “I would never have thought to put those pieces together, but it totally works.” Those observations sparked the idea that people who have the ability to curate such outfits and designs might possess a novel kind of expertise that the lay consumer doesn’t have.
Jennifer has some ongoing work in the customization domain that finds consumers tend to limit their number of choices (e.g., food ingredients) when these choices are to be combined (e.g., mixed together in a dish). Consumers limit themselves less when making choices that are intended to be consumed individually. This led us to suspect that many consumers have difficulty combining things together. The know-how to combine things requires some higher level of expertise. We later discovered through our research that “higher level of expertise” was greater depth of knowledge.
Q: The real-world persuasive value of combinatory recommendations was tested with a field study (Study 6). Did you face any related challenges? How would you advise scholars or practitioners who are thinking of adopting a similar research approach?
A: The biggest challenge was finding a company that offered a suitable context to operationalize both our combinatory and control conditions. We think that smaller, startup stage companies may be more amenable to experimentation, giving researchers more leeway to better operationalize their constructs in a field study. Many business schools host startup venture competitions. One idea would be to attend these competitions to forge partnerships with these companies for future field experiments. On another note, we think it’s important to read up on Facebook Ad Manager’s latest best practices regarding target market specifications, campaign length, ad formats, etc. as the platform’s guidelines are ever-changing.
Q: Can you elaborate on the potential extensions of your research findings? In particular, what would be the effect of recommending more than two products for joint consumption?
A: This is a great question and one that we have thought about ourselves. Based on our theorizing, a person who can recommend many compatible products exhibits a greater ability to process interactions among products, which might signal even greater expertise than only recommending two products for joint consumption. We find initial support for this prediction from Smart Closet, an online platform where users post clothing pieces that one could wear together: the greater the number of clothing pieces in the post, the more likes the post received. It is nonetheless possible that this effect has an upper boundary: consumers might have a hard time believing an advisor who recommends 20, 50, or 100 products for joint consumption. What this upper boundary is exactly might depend on the product category.
Q: What do you think would happen if the recommendations are created by artificial intelligence or algorithms instead of human advisors?
A: Prior research has demonstrated consumers’ resistance to adopting AI recommendations (e.g., algorithm aversion; see Dietvorst et al. 2015). This resistance might translate into consumers having a hard time believing a combinatory recommendation made by nonhuman advisors. This is, of course, if consumers are aware that the recommendation came from artificial intelligence or an algorithm.
Q: What do you think are the key takeaway points of this research that could be of particular interest to practitioners?
A: On the one hand, retailers should consider using personalized communication, such as direct mail, to provide combinatory recommendations. In this vein, fashion retailers like Mango and StitchFix have recently started sending follow-up emails that contain suggestions of clothing pieces to wear with items consumers already own. On the other hand, retailers could also prompt combinatory recommendations when asking consumers to review their products, as well as asking them to post photos of their outfits. Finally, the influencer marketing industry is set to grow to approximately $21.1 billion in 2023. Marketers should encourage influencers they collaborate with to use combinatory recommendations and consider the use of combinatory recommendations as a selection criterion when evaluating influencers with which to collaborate.
Read the Full Study for Complete Details
Read the full article:
Jennifer K. D’Angelo and Francesca Valsesia (2023), “You Should Try These Together: Combinatory Recommendations Signal Expertise and Improve Product Attitudes,” Journal of Marketing Research, 60 (1), 155–69. doi:10.1177/00222437221111344
Berkeley J. Dietvorst, Joseph P. Simmons, and Cade Massey (2015), “Algorithm Aversion: People Erroneously Avoid Algorithms After Seeing Them Err,” Journal of Experimental Psychology: General, 144 (1), 114–26. doi:doi.org/10.1037/xge0000033.