Friday 19 August 2022

Spotlight on: Hum

This year, the judges have selected a shortlist of seven for the ALPSP Awards for Innovation in Publishing.  Each finalist will be invited to showcase their innovation to industry peers on 14 September on the opening day of the ALPSP 2022 Conference in Manchester.

In this series, we learn more about each of the finalists. The winners will be announced at the Awards Dinner on Thursday 15 September. 

Hum logo

Tell us about your organization

There are about 20 of us at Hum, and we are a fully remote organization. The idea of Hum developed from Silverchair’s product innovation function. We were set up as a separate company in late 2021 so that we could single-mindedly pursue an idea that we think has the potential to transform publishing.

What is the project/product that you submitted for the Awards?

Hum is the product, as well as the company name. One of the challenges we face in talking about Hum is that there is a lot about it that is new and different. As a class of software, Hum is a ‘Customer Data Platform’ (or CDP), but for most publishers that isn’t that helpful a place to start since they aren’t that familiar with CDPs – although they are going to get familiar with them because my view is that every publisher (and society) will have a CDP as a central part of their tech stacks and – more importantly –business practices, within 5 years.
So what do CDPs do? They integrate with the other systems and databases at an organization and collect all of the relevant data about an audience (defined as everyone who comes into digital contact with that organization, covering user, reader, customer, reviewer, author, librarian, researcher, teacher, and learner, and so on) and then they allow you to manipulate that data for business use. The primary ways that organizations can use CDPs are via vastly improved segmentation and personalization. Sounds simple, but it is the means for organizations to make data-driven decisions about nearly everything they do.
At Hum, in addition to helping the publishing market to understand what CDPs are, we need to highlight Hum’s critical differentiators from the class of generic CDPs. These differentiators come from Hum’s focus as the only CDP built for content-rich organizations (publishing, most obviously).

Tell us a little about how it works and the team behind it

Hum brings together all of the first party data relating to a publisher’s audience and provides that publisher with the tools to generate insights and take actions from that data. The systems integrated with are likely to be publishing platforms, websites, CRMs, commerce systems, marketing systems, and submission and peer review systems, for example. The data is demographic (name, age, location, email, title, university, library); transactional (a purchase made, a campaign email received); and behavioural (reading all or part of a journal article, visiting a blog post, opening an email, clicking on the email content, scrolling, carrying out a search, downloading content, listening to a podcast, watching a video).

It is this final category (behavioural data) where Hum’s differentiation really kicks in. You can generate significant insight and business benefit by understanding how your audience is engaging with your content. Hum tracks at a deep level every audience member’s interaction with content, capturing what is being read, by whom, how deeply, when, etc. When this behavioural data about interests and intent is tied together with other data (eg demographic and transactional), a lot of exciting use cases become possible. But Hum does not just collect up all the data that a publisher is already capturing (and in most cases not using). It generates significant new data. Hum uses AI (and this is genuinely AI, based upon our own proprietary development of Google’s BERT) to automatically tag every piece of content at a publisher. Many publishers have their journal and book content tagged at some level, but Hum automatically tags and assigns key words to ALL content (video, podcast, blog, content marketing, social, marketing pages, etc). So Hum is generating new data about a publisher’s audience’s engagement with a publisher’s entire content set.

This focus on content is a big differentiator. But also very important is that Hum is ‘built for humans’. While Hum is powerful it is also easy to use: data-driven decision making becomes something that everyone in the publisher can do, rather than requiring data scientists.


illustration graphic Hum

Hum is best understood by example. Say you want to market a new webinar. After implementing Hum, you can use Hum’s ‘Audience Explorer’ to build in a matter of seconds a precise segment that you think will be interested in that webinar. That segment of interested people will automatically be reflected in your email and advertising platforms to use for targeted messaging. The segment is live, not static: when people sign up for the webinar, they are removed.

Hum illustration graphic

When new people qualify, they get targeted messages or ads. For your identified users (for whom you have an email), you can promote the webinar ‘off platform’, often via regular communications that are specifically tailored down to the individual and drive 150%+ lift in metrics like opens and click throughs. You can also target anonymous users on your own sites via popup modals, personalized ads and content recommendations (webinars are content too!). And if I had more time, I’d tell you about ‘Content Explorer’ that allows publishers to understand what content is (and is not) working, for whom, where, when, and so on, to help to devise content and product development strategies based not on guesswork but on actual audience interest and behaviour.

The biggest use cases in publishing are: improved marketing via segmentation and personalization; improved ad targeting; author and reviewer acquisition; content strategy; audience building and identification; B2B sales; and new product development. As for the team, we are a mix of technologists, publishers, data scientists, and sales, marketing, and delivery people. We joined Hum for its mission and culture.

In what ways do you think it demonstrates innovation?

Hum is the first CDP purpose-built for publishers. Publishers care a lot about their content. And so do we. Our focus on content as a first-class artifact is a key Hum differentiator amongst the broader CDP category, and it’s an area where much of our innovation is demonstrated. We’re developing a few proprietary features that help publishers evolve their content strategy and deepen their understanding of how readers interact with content.

I’ll highlight a few areas of content innovation:

- Engagement Scoring:


graphic illustrating engagement scoring

- Content & Audience Explorer:

graphic content and audience explorer

What are your plans for the future?

We’re just getting started and we’ve got miles to go! We just launched in 2021 and we’re still working our way towards fully understanding what publishers need and want from the Hum product. Hum’s success and future depends on delivering genuine differentiation and business value for publishers. We’ve had great success with our early customers, but we’re always listening for their feedback as we continue to evolve the product.

Hum uses a proprietary engagement algorithm that gives publishers a sense for their best topics and subtopics by assigning values to various content metrics. It reads each piece for engagement metrics like full and partial reads, visits by segment, overall traffic, etc. It compares these article-level metrics to other pieces in the corpus to share comparative insights on content performance.

- cueBERT: A modified version of Google’s BERT pre-trained model (trained on huge amounts of text), tweaked to read content and understand what it’s about.

- cueBERT uses Natural Language Processing and machine learning to understand the entire body of content, normalize the tagging of that content, and iteratively improve Hum’s recommendations engine.

This feature pulls a lot of what I’ve just described together. It’s an interactive tool that allows you to drill down into your content and audience based on various search parameters. It lets publishers get a real-time look at important trends, answering questions like: What topics are resonating most with x group?; How big is x segment, and more importantly, how can we activate them?; Where are the gaps in our content strategy?; What are readers in x segment most engaged with? 

About the author

Tim Barton, CEO

photo Tim Barton

Tim worked for OUP for 27 years in many different rolesand markets across research, higher education, and dictionaries (in his last role, he ran OUP’s Global Academic Division) before joining Silverchair (as President) in 2018. As CEO, Tim oversees all aspects of Hum growth and operations. Tim splits his time between New York, NY, Charlottesville, VA and Oxford, UK

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