Penguin Random House: Can it beat Amazon at its own game?
Book publishing is becoming an increasingly competitive industry with the big players vying for share of a mature market. Penguin Random House is responding by building a competitive edge through data and technology.
Book publishing is becoming an increasingly competitive industry with the big players vying for share of a mature market. The Covid-19 pandemic accelerated the shift toward digital distribution and consumption of books, which has put downward pressure on publisher margins.
Penguin Random House (PRH) is responding to these market trends by building a competitive edge through data and technology. The use of big data in publishing is not as developed as in other industries, but given the digitization trend in the industry, more data is becoming available for big players to capitalize on.
The first step for PRH was to upgrade their data infrastructure and break down analytic silos created by legacy systems that prevented widespread use of data-driven insights across the organization. This required them to invest heavily in data storage, analytics, and visualization systems that could be accessible to those with limited data literacy while still being useful and flexible enough for power users. This has improved the quality of insights used to inform business decisions as well as the time required to unearth these insights. PRH estimates time savings of 5000 work hours per year based on the initial infrastructure upgrades (Source).
Once the foundation was in place, PRH could start collecting and using the data in more innovative ways to create value for readers. Data comes from sales (online and brick-and-mortar), PRH website browsing data (e.g. what books readers are looking at online), other websites (e.g. best seller lists), and social media impressions.
- Understanding what readers want: The wealth of structured and unstructured data enables PRH to understand demand at a granular level. For example, metadata shown on a book listing allows PRH to drill down to which key words can affect a book’s popularity. This helps them optimize for discovering new books as well as for marketing their books.
- Ensuring online visibility: Metadata analysis also comes into play when working to ensure that PRH books are visible to potential buyers. PRH can optimize for keywords to make sure their authors are appearing higher on Amazon and other e-tailer search results (Source).
- Attracting website traffic: PRH mines data across the web to gather a list of the top 5 Penguin Random House titles called “Today’s Top Books” (see below for example). This is used in combination with search engine optimization and daily newsletters to help drive traffic to their website. It also showcases their innovative data practices, which enhance the brand image (Source).
https://www.penguinrandomhouse.com/interactive/todays-top-books, 10/2/2022
These initiatives all create value because they improve the offering available and streamline the content decision process for readers. In the same stroke they help PRH capture value through higher sales.
When it comes to sourcing data, the best quality data comes from first party sources like PRH’s website, where it has control over what types of data it can collect (reader profile, book listing clicks, etc.). However, the largest quantity of data comes from its Amazon sales. This means that better data insight can be generated by increasing traffic to PRH’s own website. In an attempt to collect more first party data, PRH has waddled onto the rewards program trend with Penguin Rewards. The program helps to drive sales, but it also enables PRH to collect data about loyal readers (Source).
Despite these measures, competing with Amazon will continue to be a key challenge, as the behemoth has top tier data analytics abilities and a vast store of data. Attracting tech-skilled talent will be difficult due to the traditional image of the industry. PRH’s parent company, Bertelsmann, is working to mitigate this risk with data science leadership development programs at the holding company level. Additional challenges may arise due to the longstanding way of working in publishing. It may be difficult to instigate structural change from such changes as how books are selected, how the editing process is managed, how many books are released and at what rate, etc.
There are many opportunities to expand the use of big data in book publishing. PRH has barely scratched the surface. Data can be used to improve prospect discovery, content personalization for readers, supply chain, and marketing and sales. Perhaps there is an opportunity to develop a competing book e-tailer to Amazon, which would feature a collaboration with the top 5 book houses such that they could offer readers the widest array of books while ensuring that quality and quantity of data can be maximized. A united front of the top book publishers could be the only way to face the threat of Amazon.
Really interesting! Makes me wonder if there is a world where Penguin Random House or any other book retailers can ever compete with Amazon in the book market. Maybe there’s a possible roll-up investment thesis to merge otherwise underperforming book retailers to get brand and data synergies to rival Amazon.
Thank you for the blog post, Nitya. It’s true – publishers and book retailers are being disrupted by Amazon (as well as, I would argue, streaming services), as brick and mortar bookstores have historically bred connection with the consumer (author signings, author events, etc.) and discoverability. Metadata helps with discoverability and potentially predicting which books / titles will become best sellers, but beyond that, I’d be interested to see PRH and the other Big 4 publishers leverage iterative A / B testing to evaluate which titles or book cover designs would increase book sales. Additionally, it would be great to see PRH run experiments to refine which books they should publish in an ebook, hardcopy and/or audiobook medium. For example, I often buy longer books in ebook form (for convenience) and memoirs in audiobook (to humanize the author). I believe maintaining close relationships with authors to track sales, fan behavior/preferences, etc. will be the key to achieving cross segment sales and gaining market share; readers often remain loyal to an author and/or genre rather than a publisher (in my experience, readers rarely, if ever, set out to buy a book issued by a particular publisher).
I look forward to seeing how the publishing industry evolves to become more data-driven and targeted as the addressable market grows (with global literacy rates increasing) and barriers to entry drop.
Hi Nitya, thanks for the blog post. It’s really fascinating to see how Penguin Random House is using data to improve their reader experience, ensure visibility, and drive traffic to their own site. However, Amazon is a disruption to the traditional book market and it seems like a challenge to beat Amazon. Since PRH already has experience with the data. I’m curious if it would be a better option for those traditional book publishers, like PRH, to try to work with Amazon, or even with their Penguin Rewards system, to get more loyal customer data under a big database to attract more traffic to their own place?
Thanks for the blog post! I find this industry very exciting because it wasn’t built on data from the beginning, but is now making the change from data-less to data-driven.
It seems to me like Random House focuses on the book sales area with their data once the books hit the market. I wonder if it wouldn’t be exciting to write some of the books specifically for the market. To turn the process around, so to speak.
That would have the advantage of bringing users into the process as well. For example, do a survey with loyal customers on which topics they would like to see more in the future. These customers would then have even more incentive to purchase these books and Random House would have a more direct customer relationship. I would identify that as a competitive advantage over Amazon.
In addition, I wonder if it would not be possible to use the individual customer data to create customer profiles. This would allow Random House to make individual recommendations to each customer. Customers would then not have to search for books on Amazon, but would only have to click on buy in their personal mail recommendation. I imagine the lower the search costs for the customer, the higher the NPS would be.
This would give Random House an additional opportunity to understand their entire customer base. This would allow Random House to focus on an open-minded customer group and apply the process described above.
This was fascinating, Nitya. Like others, I wondered how much difficult it will be for PRH to compete with Amazon. But your post also reminded me about an interesting article I read a few years ago about the CEO who turned around the Waterstone’s bookstore chain in the UK. Waterstone’s basically stopped taking money from the publishers, who had dictated which titles would be prioritized in the bookstores. Instead, Waterstone’s started delegating those decisions to local branches and sales took off. The big takeaway for me was that Amazon’s data analytics are “passive” and so while it can tell you what is selling well, “it doesn’t spotlight unknown books that deserve a wide audience. It can’t make a literary star, something Waterstones now does with regularity.” (https://www.nytimes.com/2019/08/08/books/watersones-barnes-and-noble-james-daunt.html)
Thanks for the post Nitya! I’ve always wondered on how we can put an effective strategy against Amazon. Be it in any verticals, Amazon is a threat. One thing I always wondered about in this space is the importance of ‘convenience’. With Amazon offering same day or 2 day deliveries or even books through Kindle, what’s the incentive for me to order a book through PRH? Maybe the answer is that I can utilize PRH for their recommendations and can use Amazon to order the book vs going through PRH which might take additional days for me to get the book? While PRH can utilize the customer data and run models on to understand customer behaviors, create personas and tailor recommendations and future titles to cater to that audience?
Thank you for your post. I wonder if you could maybe give some more flavor into data sourcing as I see that the most sensitive element of the entire data infrastructure and use cases they might have. Amazon not only has their online portal but also the Goodreads app; the number of users on both those platforms, interacting with books from all over the world, irrespective of language, topic and publishing house is enormous and therefore the level of insights Amazon can generate (even for making recommendations) is much more accurate. I wonder in the case of PRH: 1. reliability of data sources and 2. data size as well. And I worry of a vicious circle called “garbage in , garbage out” which might lead to hurting their business even more, if they end up being the victims of their own bias. Would love to get your thoughts on the matter.
Great pun on the penguin waddle!
On a more serious note, it seems like PRH is making the right investments to get back into more control of their future versus being fully dependent on digital behemoths like Amazon — I am concerned though if it might be too late. While initiatives like “ensuring online visibility” (essentially a SEO approach to e-retailers) and “Today’s Top Books” (mining data across the web) may help them improve sales, I am not sure how they can position themselves to retrain the customer to bypass the convenience of Amazon and create a strong 1st party data source for most of their volume. Nonetheless, this new data-driven approach should still help them against competitive publishers at understanding and catering to their customer base.
Very interesting blog post, Nitya! I’m always amazed by how traditional media transformed themselves and embraced the digital world. I wonder if there’s anything that they do that applies the insights of readers’ preferences/behavior to the physical book stores (e.g., bookshelf display, supply chain, etc.) and other partners in the value chain.
Thank you for your post!
It’s interesting how even if they manage to compete on data and analytics, how hard it must be to attract the talent they need to really scale to a significant online penetration and market share. If I think about buying a book the first place I would look it up is on amazon (sadly), not only because of the amount of SKUs but also because of their logistic ability to send it in 48 hours. This sense of immediate satisfaction for customers (a trend that will only get worse) is my biggest concern for PRH. I think their investment in data is a step in the right direction, but they may be far behind in everything that happens after the book is purchased.
I’m rooting for them!