Data stories

Turn your numbers into
a story people read.

Short chapters scroll past one chart, which changes as you read. Every figure comes from your data, so the story stays right when the data changes.

Style

Supermarket sales

How our first quarter went

Sales totaled —, with daily results ranging from — to —. Branch sales were closely grouped, while — was the strongest shopping hour.

Scroll to read. The chart changes with each chapter.

Daily sales trend

01 · Daily trend

Sales swung between — and —

Daily sales varied across the period. The strongest day was —, at —, while the quietest was —, at —. Sales on the final day (—) were below the opening day's —.

02 · Shopping hours

Hour — led the sales totals

Hour — is — than hour —, contributing — of total sales. Hour — also ranked among the leading hours, while hour — had the smallest total.

03 · Branches

Branch sales were tightly grouped

— led with —, but its total was only — than —. — was also close to —, leaving sales distributed fairly evenly across the branches.

04 · Product lines

Food and beverages leads by a narrow margin

At —, — leads, just — than —, whose sales are —. — is close too at —. The gap from leader to smallest is modest: — is — than —.

05 · Payments

Payment sales were spread across methods

— led with — of sales, just ahead of — at —. — is — than —, so no single payment method dominates the mix.

06 · Customer gender

— transactions outnumbered — transactions

— accounted for — transactions, compared with — for —. This shows a difference in transaction counts by gender, but not how many unique people bought or how customer types differ.

What to check next

  • Investigate what coincided with the sharp daily low before treating it as a recurring pattern.

  • Review staffing and operating patterns around the busiest shopping hour.

  • Keep branch plans flexible: sales were closely grouped rather than concentrated in one location.

  • Use the product-line and customer-type views to check for patterns not exposed in the available figures.

What this data can't tell you

This covers one quarter and does not explain why daily sales varied. The available product-line facts do not identify a leading line, and the customer chart reports transactions by gender rather than unique buyers or a customer-type breakdown.

Data as of Mar 30, 2019.

Sample data. Scroll inside the frame: every number in the text is filled from the chart beside it.

From a file to a story in three steps

You bring the data and the question. The charts, the order and the first draft of the words are done for you.

  1. Step 1

    Pick Data story and ask

    Attach a file or connect a source, then say what you want explained.

  2. Step 2

    Get it as chapters

    Better Analyst finds what matters, writes a short chapter for each point and pins the matching chart beside it.

  3. Step 3

    Make it yours and share

    Edit any sentence where it sits, change the look, then send one link.

Written for the reader, tied to the data

A story is a dashboard with its explanation attached, so the two never drift apart.

  • Numbers that stay right

    Figures in the text are filled from the chart’s own data. When the data refreshes, the figures update with it.

  • Words you can change

    Click a heading or paragraph and type. Change a chart, and one click rewrites its chapter to match.

  • One link to send

    Share a story the same way as a dashboard. On a phone the chart stays on top while the text scrolls under it.

  • Your data, your look

    Stories use the same files and connectors as dashboards, in your brand kit or one of six looks.

What people tell as a story

Anything you would otherwise explain on a call, slide by slide.

  • Monthly client reports

    Walk a client through the month in order: what moved, where it came from and what you would do next.

  • Leadership updates

    Give the people who will not open a dashboard the five things they need, each with its chart.

  • Campaign and launch wrap-ups

    Tell what happened from first spend to final result, with the figures pulled from the data.

  • Explaining a result

    When a number surprises the team, lay out the breakdowns that explain it, one at a time.

Frequently Asked Questions

A data story is a page of short chapters that scroll past one chart. As you read, the chart changes to show what each chapter is about. Better Analyst builds it from your data and writes the chapters for you.
A dashboard shows many charts at once and leaves the reading to the viewer. A story puts the same charts in an order and says what each one shows, so a reader can follow it from top to bottom without knowing the data.
Every figure in a chapter is filled in from the chart beside it, not typed by the AI. If the data refreshes, the figures in the text change with the chart.
Yes. Click any heading or paragraph and type, reorder or delete chapters, add your own, and insert a figure from a chart wherever you need one. You can also change colors, fonts and the layout.
The same data as a dashboard: spreadsheets and CSV files you upload, Google Sheets, and connected sources such as Google Analytics, ad platforms, databases and warehouses.
Yes. You can build a data story on a free account.

Compare your options

Decide with evidence, not a sales pitch.

Open a neutral research prompt in the AI tool you already use. Compare capabilities, limitations, and fit before you choose.

  1. 01ChatGPTOpen a balanced comparison prompt in ChatGPT.
  2. 02ClaudeOpen the same research prompt in Claude.
  3. 03PerplexityResearch the comparison with linked web sources.

AI answers can be incomplete. Check source links, current pricing, and product documentation before deciding.

Tell your next report
as a story.

Attach your data, say what you want explained, and read the first draft in a couple of minutes.