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How Geo Tagged House Sales Boost Reader Revenues at BT Spotting the Opportunity

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Newsroom automation playbook series How geo tagged house sales boost reader revenues at BT Spotting the opportunity... It’s 2019 and innovation projects are a regular feature at the newsroom at Bergens Tidende in Norway. Then editor-in-chief Øyulf Hjertenes has identified automation as a key area of exploration. Late autumn an idea takes shape. Would it be possible to develop sophisticated robot written articles about house sales and segment them in such a way that they might start to drive subscription sales? There is only one way to find out.... Robots can generate huge volumes of content. They are fast, reliable and accurate. But they are robots. That – in a nutshell – is what newsroom automation is about. Publishers who get real benefits from automation use robots for the stories that can be automated, freeing up reporters to do the investigative, quality, human stories that underpin the journalistic brand. In the case of Bergens Tidende, robots provided an opportunity to launch a Boligsalg (home sales) vertical, filled entirely with automated content and with only one journalist involved. And use it to drive reader revenues to boot. Read on to find out how Bergens Tidende are leveraging newsroom automation. > Top Norwegian regional title Bergens Tidende is one of Scandinavian media group Schibsted’s two large regional titles in Norway – the other one being Stavanger Aftenblad some 200 km further south on the country’s west coast. Bergens Tidende has 45,000 digital only subscribers and 80,000 total subs (Nov 2020). Schibsted also includes Norwegian national titles VG and Aftenposten as well as Aftonbladet and Svenska Dagbladet in Sweden. Cover image: BT’s internal geo tagging map of the very centre of Bergen city. Two key aspects: Quality.... By early 2020, the small, monthly newsroom innovation project at Bergens Tidende set up in late 2019 has turned into the development of an entire new Boligsalg section on the BT site. The strategy behind the publisher’s first foray into automated content is to make it attractive enough and geographically targeted enough to drive digital subscription sales. Project Lead (previously news editor) Jan Stian Vold, the only BT journalist working full time on the project, and the development team at United Robots set out on a journey to expand the automated articles with more data sources, deeper analysis, better visuals. As Bergens Tidende goes live with the Boligsalg vertical in June 2020, it is publishing some of the most sophisticated robot written real estate texts United Robots have ever developed. ...and segmentation In order to put the most relevant articles in front of site visitors, BT have developed a geo tagging system that is more granular than the one used by the real estate industry. In addition to using the tags to segment the content at the point of distribution, the geo tagging is used to generate lists. “In each article, we list the five most expensive sales in the past 12 months at that most granular neighbourhood level, with links to the tag, down to street level, which of course increases the value of our set-up,” says Jan Stian Vold. The granular tagging has been a key factor in driving the value of the content and thus subscription sales. > If there’s data, there can be text Bergens Tidende use the Real Estate robot from United Robots. The texts delivered are generated through an NLG (Natural Language Generation) process applied to structured data sets from Statens Kartverk (public data in Norway) as well as some secondary data sources and Google Streetview + Google Earth. See next page for a look under the hood of what the robot does. BT’s geo tagging system is more granular than the one used by the Norwegian real estate industry. The content – five layers of UX During the spring of 2020, Jan Stian Vold and the United Robots team work in partnership to expand the automated real estate texts. These grow from being stories of a single sale, to providing readers with analysis of the market on neighbourhood, city and national level, coupled with a number of different visuals. #1. The headline & the ”news” The primary data source, Statens Kartverk, is the one that describes the sale that’s taken place — the “news”. It includes street address, type of property, price, seller and geographic coordinates. The headlines have been developed to be long enough to tell a real story – something which helps drive readers through the funnel, towards conversion. To the primary data source a secondary one has been added. This provides additional information about the property, such as size, number of floors / what floor it’s on, whether there’s an elevator, what neighbourhood it’s in etc. All this information makes up the first couple of paragraphs in the text. The robot also has access to historic data, so compares the sales price with the most recent previous sale and calculates the increase/decrease. continues... #2. The neighbourhood scan The second subhead in the article covers sales in the neighbourhood, how many and at what price. Here, the robot also calculates and includes price per square meter. This section has a list of the top five most expensive homes sold in the city area (i e several neighbourhoods combined, e g Bergen West) so far this year. #3. The bigger picture The final subhead is Prices in Bergen Now, which is based on a monthly update, and compares prices with the previous month as well as the same month last year, including a bar graph comparing prices with other Norwegian cities. This data is synched daily so the updates happen automatically. The bar graph is currently produced manually, but is on Jan Stian Vold’s automation-to-do-list. #4. The top ten list As an extra point of interest, BT has a running list of the ten most expensive houses sold in each municipality in the past 30 days, a list published at the beginning of each article. “It’s a kind of gamification of the content in order to create interest – everyone wants to know how their house is doing,” says Vold. #5. The visuals The image of the property sold comes from Google Streetview (United Robots have a global agreement with Google). A new feature for BT is the frame from automatically generated Google Earth “drone” videos. These frames have the property pinpointed and labelled (see below right). Driving reading: Robot editor managing front box A below-the-fold position on the home page of BT.no has a Boligsalg box with three of the top stories. An in-house built algorithm picks out the articles to push, based on a number of predefined keywords such as ”most expensive”. Jan Stian Vold sometimes manually adds a story: ”We need to consider to what extent the Boligbot contributes to the focus on highly priced properties. In order to give a more balanced view, I’ll manually publish some more reasonably priced properties.” ”The key is driving relevance for readers” According to Jan Stian Vold the relevance the automated real estate content drives is twofold. > Quality of information. One aspect is the depth and breadth of information published. “Information about trends in the real estate market is key for anyone owning or aspiring to own a home. By combining specific information about individual sales with general trends in the local region, BT provide readers with a better overview of the market, which means we put them in a better position to make educated choices in that market.” > Geography. The other relevance piece is to do with geography. Thanks to BT’s extensive tagging structure, they serve the most relevant real estate stories to individual readers. They’ve divided the city of Bergen into four sections; north, west, south and central. The next level of tags is by postal code / neighbourhood, and beneath that small and compact geo areas, which means the content reaching the reader is of high value. “There are 15–50 sales of houses or apartments in Bergen every day, and for buyers, sellers, neighbours, or people moving into the neighbourhood these texts are highly relevant. So we assumed they would generate subscription sales – and we’ve been proven right. The high quality of this real estate content, combined with the fact that it’s automatically generated, provides a net value for us – and our readers. But if we’d had to employ 5 journalists to do this job, the gain would have been cancelled out by the cost in newsroom hours,” says Jan Stian Vold. > Immediate effect on subs sales The top KPI for the Boligbot is the number of subscription sales. Since the launch in summer of 2020, this number has stabilised at 60–70 conversions a month. “These are not extremely high numbers, but they play an important part for our overall subscription business.” > Expected Boligbot performance going forward: 10,000 articles published / year 600–800 subscription sales / year (price €24/month) 1 million page views / year The Boligsalg content on desktop > Working with United Robots “A key success factor for the project has been how responsive the United Robots team have been to ideas I’ve had – the route from idea to impact and increased value is short. It’s been fantastic to work with developers who are just as keen to drive innovation as I am. With projects like these, there’s always a risk that you launch and leave, but the United Robots team continue to walk that extra mile to keep improving the Jan Stian Vold content.” Bridging the buzz and the reality A lot of people in the news industry are talking about newsroom automation.
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