With first-party data, Allrecipes is able to bake reader comments into advertisings tools

By Kayleigh Barber

Publisher comment sections are not only seen has hotbeds for toxicity, but historically have been very difficult, if not impossible, to monetize.

Meredith’s Allrecipes is in a unique position to challenge that.

Known at its core for being a home for user-generated content, Allrecipes collects recipes and modifications to recipes from home cooks around the world. But what’s become valuable for the food publisher in just the last couple of years is that it has been able to find a way to make money off of the first-party contextual data from the ingredient substitutions that are noted in users’ comments.

“Allrecipes is over 20-years-old and I’d love to say that we have 20 years worth of review data but we don’t,” that number is closer to a decade’s worth, said Grace Preyapongpisan, vp and chief of business intelligence at Meredith. That translates to about 7 million user submitted recipe reviews and the site continues to receive thousands of new reviews with recipe modifications landing in the comments every week.

Meredith’s Business Intelligence division has been in its current iteration of data collection for the three years and Preyapongpisan said the team started with Allrecipes out of all Meredith’s portfolio of brands because the site “is the best example of utilizing user-generated comments in a way that gives insights that can improve the user experience as well as gives insights to advertising partners,” she said.

Receiving feedback from readers on recipes gives Allrecipes a leg up in being able to decipher insights from those comments because the content is more formulaic in nature.

“Recipes are a great starting point for some of this text-based mining because some of the language tends to be fairly structured,” Preyapongpisan said.

And recently, early on in the pandemic, people were going to the grocery store less and wanting to use the ingredients in their homes, so the number of substitutions and modifications annotated in readers’ comments increased, said Preyapongpisan. That information ended up being very valuable to consumer-packaged goods companies, she added.

“Mayo was being used or substituted in things that you’d never expect to see,” she said. “Our partners were really interested in seeing if there were opportunities to market their products in different ways.”

One salad dressing manufacturer, which Preyapongpisan declined to name, came to Meredith looking for other uses for its condiments and wanted to see if any consumers were talking about possible uses on Allrecipes.

But there are still challenges, she continued, including coding every single word to figure out which are ingredients, which are modification actions and whether or not the action yielded a positive or negative result. Then, her team has to figure out how many people tested that modification and then, of course, cooking the recipe in order to confirm its validity.

Therefore, the process of extracting the contextual data from user-generated content and comments on posts is not easy in it of itself, which is why Preyapongpisan said it’s taken a while for Meredith to get the …read more

Source:: Digiday