Content types on the ONS website Bulletins
A statistical bulletin is a short summary of findings and essential commentary related to a new release of data. It is usually published monthly, quarterly or annually as part of a series but can be published as a one-off.
- open up information to inquiring citizens
- provide easy links to at least one dataset
- include only the most important information
- link to more detailed content for those who need it
- follow a standard structure with standard headings
The Code of Practice says, “Statistics, data and explanatory material should be relevant and presented in a clear, unambiguous way that supports and promotes use by all types of users.”
A bulletin, or set of related bulletins, will always be published alongside datasets as part of a “release”. A release can also include articles relating to the new data.
Bulletins follow a consistent structure, which is designed to meet user needs and priorities. This structure is designed for bulletins and should not be used for articles or methodologies. If you have more to say, are writing about existing data, or need to write something for more technical users, use an article template instead.
A statistical bulletin template is shown by the blue strip at the top of the page. Any related datasets must be linked to the bulletin. This generates the green “View all data used in this bulletin” button on the right-hand side of the page.
What users need from bulletins
Research shows that our users come to bulletins to complete three tasks. These are:
- read analysis of the latest data
- find the latest data, so that they can do their own analysis
- find out about how the data were gathered and understand the methodology
Our bulletin structure has been designed and tested to help users achieve these goals.
The order of the sections reflects user priorities for these tasks. The section headings clearly label the content so that users can find what they need quickly.
The order of the sections reflects what research identified as users’ priorities. The structure is the same for all bulletins to provide users with a consistent experience.
Keeping bulletins focused
Bulletins should reflect the topics that users are interested in, not the source of the data.
For example, it is more meaningful to tell users about the latest data on “migration” than the “International Passenger Survey”.
A bulletin can be one short page covering multiple topics, or – where there is clear user need, supported by research or analytics – split into multiple pages focusing on individual topics.
Consider the length of your bulletin, too. On average, users spend about four minutes looking at a bulletin. That’s long enough to read around 900 words.
We do not expect most users to read every word on every page, but if you are publishing significantly more than this, consider whether you could split your content.
Where a release contains more than one page, some users may still want to read overarching analysis. For example, there are a number of topic bulletins released that report labour market data, but research showed that users still needed a Labour market overview.
Users expect consistency between releases, so it is best to only create new bulletins on topics that you expect to cover regularly.
If there is not enough to say for a full bulletin, or limited user engagement, consider streamlining your content.
If you have something to report on a one-off basis, consider publishing an article
Bulletin sections separate the different types of content on the page. They reflect the user needs and priorities we have identified through research.
|Other pages in this release (optional)||When publishing more than one bulletin in a release, use this section to link to them.|
|Main points||Up to six bullets containing headline figures or trends in the data.|
Can be followed by a statistician’s comment.
|Analysis sections (split into numbered sections by topic)||Commentary on what the majority of your users would find interesting, noteworthy or important about the new data.|
Can include warnings to let users know about something that fundamentally affects the way they use your analysis.
|[Name of bulletin] data||Links to the most relevant datasets referenced in this bulletin.|
|Glossary||Definitions of between three and six terms used in this bulletin.|
|Measuring the data||A short summary of the data sources and collection method.|
Can link to more detailed Quality and Methodology Information (QMI) reports, methodology articles, user guides and planned changes.
|Strengths and limitations||Information to help users correctly interpret the data, including how the data should or should not be used.|
|Related links||Links to in-depth analysis or articles on this subject from the ONS.|
Can include links to associated bulletins, such as revised or mid-year estimates.
Links to related publications or statistics that users might find useful.
Can include links to publications from other organisations.
|Cite this statistical bulletin||Format as:|
Office for National Statistics (ONS), released XX Month 20XX, ONS website, statistical bulletin, Title: edition with link embedded
This will help writers and academics to cite ONS statistical bulletins correctly and consistently. Read more in the citations, references and sources guidance
The bulletin template should only be used for bulletins. This is to make sure users have a consistent experience when they come to a bulletin page; the structure should be clearly defined and different to articles.
Bulletin titles and summaries
Page titles need to be short, clear and reflect the content on the page.
All bulletin titles must include:
- the name of the release
- the geographical coverage
- the date or period the data cover
Baby names in England and Wales: 2018
A title could include other information such as “provisional” or “final” where appropriate. Insert information like this after the colon and the date but avoid using extra words like “results” where possible.
Bulletin titles should not include a statistical designation (such as Experimental Statistics). These should be in the bulletin summary or keywords.
Titles should reflect the words users put into search engines. For example, people are much more likely to search for “baby names” than “annual birth registrations”. We can use analytics to help you choose the best title for your content.
Avoid naming bulletins after surveys. For example, users may search for “gender pay gap”, but are less likely to search for “Annual Survey of Hours and Earnings”.
If the data period is quarterly, use the months rather than the quarter name. Some users may not be familiar with quarters or understand the periods they cover. For example, use January to March 2020 instead of Quarter 1 (Jan to Mar) 2020.
All titles, headings and subheadings must be written in sentence case.
Read more about best practice in our titles and headings guidance
Creating a bulletin series
A series is used to link multiple editions of a bulletin together. We are not able to mix content types in a series. This means if the first edition is created as a bulletin, all future editions must be published as bulletins. It is important we get the content type and title right for the first release.
The series is created using the title of the publication and this cannot be changed once it has been created. Everything in the title before the colon determines the series and everything after the colon forms the edition.
Baby names in England and Wales: 2021
This would be the “2021” edition of the “Baby names in England and Wales” bulletin series.
A new edition of a bulletin should be created in the relevant existing series. This will link the latest release to any previous editions so that users can easily navigate between them.
When adding to an existing series, you will only need to update the edition (the part of the title after the colon).
The summary is the description that follows the title at the top of the page. The summary should:
- tell users what to expect to find in the bulletin
- describe the topic that the page covers
- be under 160 characters
- begin with the most important information (avoid using phrases like “This bulletin covers…”)
- tell users if the bulletin contains Experimental Statistics; include a sentence at the end with “Experimental Statistics”
- not be a technical definition of the topic; we have a glossary for that
Labour market overview, UK: May 2019
Estimates of employment, unemployment, economic inactivity and other employment-related statistics for the UK.
Main points section
Highlight the most important and interesting findings from your bulletin at a glance. Most users read the main points and nothing else.
Rank up to six main points in order of importance for your users.
Each main point should:
- be a single bullet point
- contain one message that is expanded on in the bulletin
- be a single sentence starting with what’s happened, followed by the significance of this; use a semicolon to split up the sentence if necessary
The UK unemployment rate was estimated at 3.8%; it has not been lower since October to December 1974.
Research shows that users want the headline figures quickly, so avoid prefacing your main points with any introduction or warnings. Do not introduce detailed definitions or quality warnings in your main points.
If the data do not change month to month and only provide enough detail for Main points rather than full analysis sections, it may be better to write a headline release, a streamlined version of the bulletin structure.
Some bulletins include a statistician’s comment. It is primarily for the media but should highlight something of interest to all users.
The comment puts the main findings in context; it should not just repeat something that the user can read elsewhere in the bulletin.
The comment should:
- be short; up to 75 words
- be placed in double quote marks
- be followed by the name of the person quoted, their job title and a link to a relevant ONS Statistician’s Twitter profile (if there is one)
The 75-word limit will make sure the comment does not fill an entire mobile phone screen, or most of a desktop browser screen.
Shorter comments will help users with scrolling and getting to the analysis quicker.
“Marriage rates remain at historical lows despite a small increase in the number of people who got married in 2016. Most couples are preferring to do so with a civil ceremony and for the first time ever, less than a quarter of everyone who married had a religious ceremony. Meanwhile, the age at which people are marrying continues to hit new highs as more and more over 50s get married.”
Kanak Ghosh, Vital Statistics Outputs Branch, Office for National Statistics
How to write statistician's comments
Also remember these tips:
- use a conversational tone of voice; imagine you are explaining the point to an intelligent but non-specialist friend in a friendly chat
- avoid jargon and technical language; use everyday plain English
- do not just wrap speech marks around your main points; explain the significance of what the bulletin reveals in words, ideally avoiding numbers altogether
- use well-chosen adjectives; for example “a sharp rise” rather than a “15% increase”
- be careful when using metaphors or figures of speech and avoid clichés (like the plague!)
- make sure the comment addresses the main angle or issue that the media story is likely to focus on – the can help with this
- never make predictions, chase headlines or sensationalise the numbers; public trust in what we do is far more important than a little extra media attention.
When writing about statistics, focus on what is interesting, noteworthy or important to the majority of users. Consider what is the most important information that supports your message. Use the inverted pyramid, putting your most important or interesting information first. Think about the logical reading order of your content also. Learn more about structuring content
Use text and simple charts or tables to give more detail and context. Your written analysis should add to your visuals, not just report what they show. It is not necessary to comment on every trend shown in a chart or table.
Flag concerns about the data using warnings. These should be short and any more detail should go in the Strengths and limitations section.
How much to write
Analytics show that users spend an average of four minutes looking at bulletins. A typical person would read around 800 words during this time. Aim to limit the amount of analysis on the page to be shorter than this.
If you are unsure whether something is going to be useful or interesting, do not include it. Users can still find the data in datasets, and an accompanying article can provide further detail if there is a user need.
How to structure your analysis
Use section headings to break your analysis into broad themes. This helps users find the information they are looking for in the table of contents. Section headings should be short, descriptive labels that reflect themes users are interested in. Read our guidance on using descriptive headings
For example, the analysis in the Employment in the UK bulletin could be structured around the headings “Employment”, “Unemployment” and “Economic inactivity”.
If your bulletin has a single topic of analysis, include the word “analysis” after the topic in the section heading, for example, Employment analysis. This will avoid duplicating the bulletin title in the section heading.
Include updated or revised figures as the final analysis section with the title “[Topic] revisions”.
Within sections use subheadings and chart titles that summarise the main trends to break up your analysis. These do not appear in the table of contents but research shows that subheadings make it easier for users to:
- get the most important messages at a glance
- find which part of the page contains what they are looking for
- get a feel for what the following text or chart is going to tell them
Use a new subheading every time you discuss a new subject or trend. Put the most important point at the start. Subheadings should be a maximum of 75 characters including spaces to prevent the text wrapping over too many lines, particularly on mobile.
Employment rate for women was 72%, the joint-highest on record
You can use a chart title instead of a subheading to break up your text. Chart titles should follow our guidance and highlight an important trend in the figure. Avoid using subheadings and chart titles that say the same thing one after another.
Use “warnings” to highlight crucial limitations that affect how users interpret the data. They prevent misuse of data, with minimal interruption to the content.
Warnings are designed to stand out from your analysis so that users notice them; using too many, or including too much detail, distracts users. Warnings should only be used at the end of the Main points or in the analysis sections. Avoid using hyperlinks in warnings, unless the link is directing users to more information in the Strengths and limitations section.
If your bulletin contains designated Experimental Statistics, include a standard warning at the end of the Main points section (see Warnings about Experimental Statistics subsection). This is to let users know that the statistics or method are in development.
How to write a warning
- Highlight essential limitations of the data to help users avoid misinterpreting it.
- Keep warnings short and clear; when text is hard to understand, people retain less information.
- Only use warnings when they have a direct effect on how users interpret the content around them.
- Include only relevant information; use the Measuring the data or Strengths and limitations sections, which you can link to in the warning, to add detail.
- Only include warnings at the end of the Main points section, and in the analysis sections.
- Include a standard warning for Experimental Statistics at the end of the Main points section.
- Use warnings too often; it disrupts the reading experience, makes it difficult to understand the content and reduces the effectiveness of each warning.
- Place warnings next to each other as they overwhelm users and get in the way.
- Position warnings before your analysis; testing has shown that users find it confusing to read warnings before commentary.
- Provide definitions in warnings; instead, define terms briefly in your analysis, and use the glossary section to provide more detail.
- Include hyperlinked text to other sections or articles; instead, any further detail should be included in the Strengths and limitations section, or linked to from there.
Warnings should be short
Warnings have a strict character limit of 280 characters. The shorter the warning, the more effective it will be. Presenting too much information to users makes it less likely that they will understand and retain the warning. Long warnings are also problematic for users on mobile devices or with accessibility needs.
If you need to explain the limitations of the data in more detail, expand on it in the Strengths and limitations section.
Warnings about Experimental Statistics
Use a warning box after the Main points to highlight if your bulletin contains Experimental Statistics. These are a type of official statistics that are going through development and evaluation.
For Experimental Statistics, use:
“These are Experimental Statistics. The [method/data source/estimates is/are] currently under [review/development], which means [brief detail about how this affects estimates or data quality]. We advise caution when using the data.”
More information on the methods used and quality limitations of the data can be included in the Strengths and limitations section.
Experimental Statistics should always be primarily published as a bulletin where they are the first release of new data. An article using the data can be published alongside the bulletin if more detailed analysis is needed.
The data section links to the most relevant datasets, for the benefit of users who want to access data but may not know where to find the tables they need.
Provide links to up to five datasets that users are most likely to be interested in.
When deciding which five to pick, consider:
- what tasks users who are interested in this topic might want to achieve, and which data might help them
- which datasets are the most integral to your analysis
- which datasets get the most downloads
For users wanting to access all the datasets used in the bulletin, there is a prominent link at the top right of the page.
You can also include a sentence at the end of the Data section to help users access the datasets. Use the following standard text to link to the related data page:
“View all data used in this statistical bulletin on the Related data page.”
How to format links
Each link should include:
- the title of the dataset
- the type of content (dataset or time series) and release date
- up to 30 words describing the dataset – use the dataset’s summary if appropriate
Dataset | Released 29 November 2018
Migration flows to and from the UK, quarterly tables and charts
If linking to a dataset containing many tables, you can mention the most useful tables alongside the type of content (for example, “Dataset A02 | Released 29 November 2018”).
This section should not provide additional commentary or caveats about the data. Extra content is likely to slow down users’ journeys to the data they need.
Provide short, understandable definitions for users who may not be familiar with the terms or concepts described on the page.
Briefly explain technical terms in your analysis using plain English. Use the Glossary to give a little more detail about terms and concepts without interrupting your analysis. You do not need to hyperlink each term used in the analysis to the Glossary; the Glossary is in the table of contents and is used consistently across publications.
Include at least three and up to six terms, with a description of up to 50 words for each. List the terms in alphabetical order.
Choose the most relevant terms that are commonly used in the analysis. Include a clear definition of any complex terms to prevent misunderstanding.
If you have a more detailed list of definitions on another page, link to it at the bottom of this section.
Employment measures the number of people in paid work and differs from the number of jobs because some people have more than one job. The employment rate is the proportion of people aged from 16 to 64 years who are in paid work.
Measuring the data
Finding out more about how the data are gathered and measured is an important task for a smaller group of our audience, namely technical users
Providing short and clear explanations of our methodology helps us establish trust and credibility in our statistics.
In fewer than 200 words, provide explanations of the data used in your bulletin, covering the following:
- where we get the data from, for example, the survey or source
- how we measure the data, for example, sample size and collection method
- time periods covered, for example, the time periods and geography covered by the data
If necessary, summarise upcoming changes to the bulletin or methodology. You can also include information on why data revisions may occur; revised data and figures should be included in their own analysis section. If it is not possible to provide enough detail on these topics in this section, link to relevant articles.
Use a clear subheading for each topic to direct users to this information. For example, “Data source”, “Collection method”, “Coverage” and “Upcoming changes”.
For users who need more detail, include links to the Quality and Methodology Information (QMI) report and the user guide under a subheading called “Quality”.
When linking to the QMI, using the following standard text:
“More quality and methodology information on strengths, limitations, appropriate uses, and how the data were created is available in the (name of release) QMI.”
This section should include only text; it should provide summary information and so should not need any charts or tables.
Avoid including formulas or lengthy technical explanations in this section. This can be overwhelming for users and the information is available in the QMI and can be easily linked to.
Strengths and limitations
This section should provide information to help users correctly interpret the data, including how the data should or should not be used.
This may include:
- detail on the data’s accuracy and reliability, for example, if there was a sampling error or gap between collection and publication
- detail about any
- detail about comparability with other sources or countries’ data
- detail on any warnings used
- whether the bulletin contains National Statistics or Experimental Statistics
It should not include any tables or charts. If necessary, you can link to relevant articles so that users can read more about the data’s quality.
How to format National Statistics status information
- the subheading “National Statistics status for [name of statistics]”
- the date the most recent full assessment where National Statistics status was awarded, with a link to the relevant Office for Statistics Regulation page
- the date of its last compliance check, with a link to the relevant Office for Statistics Regulation page
- a short bullet list of any improvements since the last assessment
Provide examples of the improvements that users are most likely to be interested in and will support their interpretation of the statistics. The level of detail should be proportionate. If there are a lot of improvements to highlight, or ones that require detailed explanation, link to a separate methodological page.
National Statistics status for Effects of taxes and benefits on UK
National Statistics status means that our statistics meet the highest standards of trustworthiness, quality and public value, and it is our responsibility to maintain compliance with these standards.
Improvements since last review:
- improved our income inequality statistics by developing new methods to better measure the incomes for the very richest people by using administrative tax data from HMRC
- worked with the Economic Statistics Centre of Excellence to develop new measures exploring the distribution of social transfers-in-kind provided by adult social care, providing new statistics and insight into an important policy area
- responded to user research, moving away from a single large publication to smaller more targeted releases, covering average income, and income inequality separately
Quality and Methodology Information (QMI) reports
If your QMI has a section that clearly explains the strengths and limitations of your data, for example the quality summary section, link to it directly from the bulletin.
If the strengths and limitations from your QMI are crucial to interpreting the data and can be summarised clearly in a few short bullet points, include them under subheadings of “Strengths” and “Limitations”.
Bulletins should include a standard line that links to this page:
Research tells us that users have two separate needs from related links – to go into more detail, or to find broader but related content.
Include between three and six links in this section. These links should be to:
- articles containing deeper analysis of the topic than the bulletin can provide
- the latest release of other related bulletins, including any related bulletins from the same theme day
- analysis of data from multiple sources
- recent ONS publications that also reference this specific topic
- relevant articles that are published by other official organisations
Links should help users get directly to relevant content. Do not link to:
Links to data should sit in the Data section, and links to methodological articles should be in the Measuring the data section. If your release contains more than one bulletin, use the Other pages in this release section to link between them.
Each link should include:
- the title of what you are linking to
- the type of content you are linking to (Bulletin, Article, Methodology, Wep page, Report or User guide)
- the release date
- up to 30 words describing what the link points to – use the summary of that page if appropriate