DotDash Meredith

DotDash Meredith

Largest digital and print publisher in America

About DotDash Meredith

Simplify's Rating
Why DotDash Meredith is rated
B
Rated B on Competitive Edge
Rated B on Growth Potential
Rated B on Rating Differentiation

Industries

Consumer Goods

Entertainment

Company Size

1,001-5,000

Company Stage

Series C

Total Funding

$14.6M

Headquarters

New York City, New York

Founded

1902

Overview

DotDash Meredith is the largest digital and print publisher in America, featuring well-known brands like PEOPLE, Better Homes & Gardens, Allrecipes, Investopedia, and Verywell. The company creates and distributes high-quality content across various platforms, including websites, magazines, and social media, covering categories such as health, finance, food, lifestyle, and beauty. This content attracts a large audience, which in turn draws advertisers looking to reach specific demographics. DotDash Meredith generates revenue mainly through advertising, subscriptions for its print and digital publications, and partnerships with other businesses for co-branded content. The company's goal is to deliver trusted content to a diverse audience, thereby enhancing its appeal to advertisers and subscribers while maintaining a strong market position.

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Simplify's Take

What believers are saying

  • D/Cipher positions Dotdash Meredith for privacy-compliant advertising solutions.
  • AI-driven ad targeting can boost advertising revenue by improving precision.
  • Content licensing to AI firms presents a potential new revenue stream.

What critics are saying

  • Recent layoffs indicate potential instability and challenges in workforce maintenance.
  • Shift away from print media may alienate long-time subscribers and affect revenue.
  • Partnership with OpenAI exposes risks related to AI technology and data privacy.

What makes DotDash Meredith unique

  • Dotdash Meredith is America's largest digital and print publisher with iconic brands.
  • The company offers a unique cookie-less ad targeting tool, D/Cipher.
  • It leverages AI-driven ad targeting to enhance precision in reaching target audiences.

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Funding

Total Funding

$14.6M

Below

Industry Average

Funded Over

2 Rounds

Series C funding is usually for startups that are doing well and are looking for more money to fuel major growth, such as acquiring other companies, expanding into global markets, or launching new product lines. Investors typically include larger venture capital firms and private equity.
Series C Funding Comparison
Below Average

Industry standards

$50M
$12.2M
DotDash Meredith
$40M
Figma
$50M
Medium
$62M
SeatGeek
$100M
Oura

Company News

MarketScreener
Jan 16th, 2025
Investopedia owner Dotdash Meredith to lay off 4% of workforce

(Reuters) - IAC unit Dotdash Meredith will lay off 143 employees, or about 4% of its workforce, under a plan to focus on growing its advertising business, the publisher said on Thursday.

Des Moines Register
Nov 14th, 2024
Dotdash Meredith plans more layoffs but is mum on how many in Des Moines office

Dotdash Meredith announced Thursday it will eliminate 53 jobs, primarily in its print business, but did not respond to a question about how many of those jobs are in Des Moines, the center of its magazine publishing operation.

The Verge
May 7th, 2024
Dotdash Meredith will tap OpenAI's AI models to enhance its ad-targeting product.

Dotdash is the latest news organization to partner with OpenAI.

The Bookseller
Feb 6th, 2024
Ingram announces raft of promotions at Ingram Publisher Services

Ingram Content Group has announced a raft of promotions at Ingram Publisher Services, with Meredith Greenhouse stepping up to vice-president and general manager, Nick Parker moving up to vice-president and Bunmi Western promoted to director of Ingram Publisher Services UK.

PYMNTS
Jan 5th, 2024
Chatgpt Got ‘Lazier’ Before Nyt Lawsuit: What It Means For Enterprise Ai

There are two things to know about artificial intelligence.The first is that it can “learn” from structured datasets, and the second is it needs massive resources, including human labor around tasks like data tagging and labeling, to run the models so that they can do the learning necessary to be trained and perform effectively.These two elements came to a head before the start of the New Year as AI pioneer OpenAI and its Big Tech partner Microsoft were sued Dec. 27 by The New York Times (NYT) for training their models on copyright-protected and paywalled NYT content without disclosing or compensating the NYT.Buried in the complaint was the fact that the news publisher had been working to finalize a licensing deal with OpenAI, but neither side was able to reach an agreement.Some publishers, including the Associated Press and Axel Springer, have already reached commercial agreements to license their content to OpenAI.Now, a Thursday (Jan. 4) report by The Information reveals just how much they have gotten from those deals — somewhere between $1 million and $5 million. The NYT, observers must assume, was probably hoping for more.That amount of money could be considered less than an overwhelming amount for the tech sector’s $90 billion darling to shell out, particularly when compared to the $50 million Apple is reported to be shopping around to other publishing companies like Condé Nast, the publisher of Vogue and The New Yorker, and IAC, which owns People, The Daily Beast and Better Homes and Gardens, to train its own AI systems.But perhaps most importantly, in the run-up to the time before the NYT’s legal complaint went public, OpenAI had started fielding complaints that its flagship ChatGPT products were getting lazier.we’ve heard all your feedback about GPT4 getting lazier! we haven’t updated the model since Nov 11th, and this certainly isn’t intentional. model behavior can be unpredictable, and we’re looking into fixing it ? — ChatGPT (@ChatGPTapp) December 8, 2023A potential culprit? The fact that OpenAI could no longer rely on NYT-based language datasets to train its models, resulted in a decline in capability.OpenAI’s GPT crawler has been blocked from accessing data by Vox Media as well.While OpenAI did not immediately reply to PYMNTS’ request for comment, the fact that today’s commercially available models can dip and rise in performance is an important data point for enterprise businesses to consider when looking to integrate the innovation into their workflows.It represents a potentially crucial point of failure that could derail business-critical processes and have unforeseen consequences across tech stacks.That isn’t to say that AI is too risky to onboard, but rather that firms need to be aware of the AI systems they are turning to, and most importantly the data sources behind them.See also: Walled Garden LLMs Build Enterprise Trust in AITech Platforms Have Always Chased the NewsThe foundational large language models (LLMs) commercialized today are typically trained using deep learning algorithms which are built on a neural network trained using billions of words of ordinary language.The specific sources of data used for training are often undisclosed by the companies behind these models. However, much of the data comes from publicly available information on the web that has been scraped and analyzed by LLMs, whose technical architecture was not designed to verify and attribute the inputs to its system outputs.In light of the use of copyrighted materials for training data, several news media publishers have reportedly met with OpenAI to discuss licensing their content for use in training that firm’s AI models.The publishers meeting with OpenAI included The Wall Street Journal owner News Corp., Dotdash Meredith owner IAC, USA Today owner Gannett and industry trade association News/Media Alliance.“I think [the lawsuit is] going to put a shot across the bow of all platforms on how they’ve trained their data, but also on how they flag data that comes out and package data in such a way that that they can compensate the organizations behind the training data,” Shaunt Sarkissian, founder and CEO at AI-ID, an AI tracking, authentication, source validation and output data management/control platform, told PYMNTS in December

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