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B2B Advertising and marketing Instructions: [Research Round-Up] AI vs. People


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(This 12 months, I plan to commit a few of my Analysis Spherical-Up posts to a dialogue of educational analysis papers about synthetic intelligence. A few of these scientific papers will probably give attention to evaluating the capabilities of AI to these of people at performing duties associated to advertising and marketing. This month’s Analysis Spherical-Up options an unpublished paper that compares the efficiency of AI vs. people at producing concepts for brand new merchandise.)

Concepts are Dimes a Dozen:  Massive Language Fashions for Thought Era in Innovation

  • Authors – Karan Girotra, Cornell Tech and Johnson School of Enterprise, Cornell College; Lennart Meincke, Christian Terwiesch, and Karl T. Ulrich, The Wharton College, College of Pennsylvania
  • Date Written – July 10, 2023

This paper describes the outcomes of an experiment designed to check the efficiency of generative AI and people at producing concepts for brand new shopper merchandise.

The duty used within the experiment was to generate concepts for a brand new product for the school pupil market that might promote at retail for lower than $50. The AI software used within the experiment was OpenAI’s ChatGPT-4.

The experiment used three “swimming pools” of recent product concepts.

  • First pool (200 concepts) – Concepts created with out AI help by college students enrolled in a product design course at an elite college.
  • Second pool (100 concepts) – Concepts generated by ChatGPT based mostly on the identical “immediate” as that given to the scholars.
  • Third pool (100 concepts) – Concepts generated by ChatGPT based mostly on the identical immediate and a pattern of highly-rated product concepts. 

All 400 product concepts have been evaluated by a panel of college-age people in the USA. The standard of the product concepts was based mostly on buy intent. Panel members expressed their buy intent by choosing one among 5 choices – undoubtedly wouldn’t buy, most likely wouldn’t buy, would possibly or may not buy, most likely would buy, or undoubtedly would buy.

The Outcomes

The typical high quality of the product concepts produced by ChatGPT was larger than the common high quality of the human-generated concepts. The typical buy likelihood of a human-produced thought was 40.4%, whereas the common for a ChatGPT thought (with out examples) was 46.8%, and the common with examples was 49.3%.

Of the 40 highest-rated concepts within the experiment, 35 (87.5%) have been concepts produced by ChatGPT.

The researchers additionally requested members of the evaluating panel to fee the novelty of the brand new product concepts. On this experiment, the imply novelty worth of the human-generated concepts was larger than that of the concepts generated by ChatGPT. Nonetheless, the researchers famous that novelty didn’t seem like considerably correlated with buy intent.

Implications for Entrepreneurs

The Girotra et al. paper has essential implications for entrepreneurs as a result of it provides to our understanding of the capabilities of AI functions like ChatGPT.

The outcomes of the experiment described within the paper are just like the findings of different current analysis, together with an experiment carried out by Boston Consulting Group (GCG) and students from 4 elite universities. I described this research in a put up I wrote final fall.

Within the BCG research, individuals have been tasked to generate concepts for a brand new shoe for an underserved market. They have been additionally required to develop a listing of the steps wanted to launch the product, create advertising and marketing slogans, and write a press launch for the product. The researchers discovered that individuals who used an AI software to finish the duties outperformed those that did not by 40%.

The outcomes of those research counsel that AI instruments based mostly on massive language fashions could also be higher than people at performing “brainstorming-like” duties the place the target is to generate numerous numerous concepts regarding a subject.

This consequence shouldn’t be that shocking. Massive language fashions are educated on a voluminous quantity of information from extremely numerous sources. The flexibility to generate responses based mostly on such an unlimited repository of coaching knowledge permits an AI software like ChatGPT to excel at brainstorming-like duties.

For entrepreneurs, the findings described within the Girotra et al. paper and comparable findings in different research counsel that AI instruments powered by massive language fashions could be notably nicely suited to carry out content material ideation duties resembling producing potential matters for weblog posts or producing potential social media posts.

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