Blendle clocks up 1M signups for its pay-per-article journalism platform – TechCrunch
Pay-per-article journalism startup Blendle, which aggregates the written work of different publishers onto a single, ad-free platform whereÂ readers canÂ pick and choose which storiesÂ to consume, paying a few cents per article,Â is touting passing one million registered users.
Itâs taken BlendleÂ just over two years to amass this many sign ups. The journalism micropayments platform kick-started itsÂ attempt to reboot digital mediaÂ business models in Europe in April 2014,Â offering an alternative toÂ publishersâ content-gating paywalls.
Itâs not breaking out active users but managing editorÂ MichaÃ«l Jarjour tells TechCrunchÂ thatâs now in the âhundreds of thousandsâ.
The startup began working with publishers in its nativeÂ Netherlands and in Germany, beforeÂ expanding to the U.S. thisÂ March. Itâs grown its business by 300 per cent over the past year, and is projecting that users will have read more than 20 million articles on its platform by the end of this year.
Jarjour says it remains focused on the latter two markets, with no plans to expand its market footprint further as yet. âThe United States and Germany are our largest focus right now. These are tough nuts to crack,â he adds.
On the age front, heÂ notes BlendleâsÂ largest age group is now 30 year olds; previously it was 35-year-olds so the platformÂ isÂ touting a readership thatâs getting younger.
One key feature isÂ the ability of paying readers to get a refund on any story if they didnât like what they read, although theyÂ are required to specify why they want a refund (and presumably refund abusers would soon be kicked off).Â Jarjour says Blendleâs refund rate is just under 10 per cent platform wide at this point, and a bit lower in the US â a rate he says isÂ âbasically unchangedâ.
Blendle alsoÂ manages access so if a user pays for multiple articles from a particular publicationÂ and exceeds the subscription cost for a particular issue the rest of the content is automatically unlocked. Idea beingÂ they wonât be paying more just for the privilege of being choosy.
Unlike social services with news streamsÂ powered byÂ algorithmicÂ popularity alone,Â BlendleÂ touts human curation as core to its appeal, employingÂ a team of in-house editorial staffÂ reading content to surface what they deem âquality journalismâ.
However itâs now testing a content personalization feature, calledÂ the Blendle Premium Feed, thatÂ will pushÂ a tailored feed of stories at each user.Â Â The feedÂ is beingÂ powered by a mix of algorithmicÂ predictions,Â based on analysis of usersâ past behavior and preferences, blended withÂ human selections, via itsÂ own in house team. ItsÂ editorial staff are being used toÂ identify and flag quality content to supplement algorithmic recommendations âÂ with the aim ofÂ avoiding aÂ content filter bubble scenario narrowing the horizons of itsÂ readers.
The feed is majorityÂ algorithmic recommendation, with human choicesÂ comprising around three stories per day â as âanti filter bubble picksâ â vs around 12 machine selected daily picks. Itâs going to be a balancing act for sure, as Blende notes in its blog post announcing the new feature, which it says itâs still testing â adding that the first results are âencouragingâ.
If your USP is âquality not fillerâ then applying any kind of filtering algorithm to generate more content in your app is absolutely going to requireÂ to a softly, softly approach if you want to retain the readers you wooed with promises of your different approach. So it will be interesting to see howÂ Blendleâs personalized predictions fare.
âFor the Blendle Premium Feed we combine learnings weâve collected from past behavior and predict how much youâll like an article based on your preferences (that you tell us), based on what youâve read before, and based on predictions we make. We make those predictions by analyzing each new story (story type, complexity, feel). Over the past few months editors have been training our algorithms to categorize stories better,â saysÂ Jarjour, explaining how the feature works.
âWe avoid the filter bubble by having editors flag certain stories to be sent to all people. In addition, the signals we use are also optimized for surprise, and not only to whatâs most popular or what youâd like the best.â
A purely algorithmic recommendation system is not something in Blendleâs ânear futureâ, he says adding:Â âHuman curation will remain a core component. We employ 15 journalists who read a combined 40 hours a day, seven days a week, to find stories that are especially worth reading, but are hidden on paper or behind paywalls currently.â
TheÂ premium feed is due to be rolled out âin the coming monthsâ.