Main points

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.

The content design team can help you to write impactful and user-friendly main points – email

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.


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.

If you want to know more about who uses your bulletin, take a look at our user personas or contact the content design team at

Your text should be concise, in plain English and written with the user in mind. Many may not be experts; 56% of our users access the website from home.

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 900 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.

If you think your analysis will be more than 900 words, we can help structure your content – email

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.

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. 

Preventing misuse of your data

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 and/or method are in development. 

For an example of how to include a warning box, see the Labour market overview, UK monthly bulletin.

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.

Do not

  • 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.

The content design team can help you to write short, effective warnings – contact if you want to discuss a warning you are working on.

We are constantly improving based on research and best practice. Any significant changes to our guidance are available on the Updates page.

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. 

Next section: Data and methodology