---
title: Client self-serve data slicing
category: Guides
slug: client-data-slicing
blurb: Let clients filter and explore selected columns inside a published Insight Hub without asking for new cuts.
order: 5
---

# Client self-serve data slicing

**Client self-serve slicing** means your client opens a published Insight Hub and filters or explores data on their own. You choose which columns are available; they do the cuts without a new change order.

This guide combines steps from the dashboard explorable docs and the filter docs. Terminology in the product may say **Story Dashboard** or **Dashboard**; published hubs use the same publish and explorable settings.

## Part 1: Publish and share the link (analyst)

Before clients can slice data, publish your dashboard and send them the link.

1. Open your dashboard
2. Click **Actions → Manage Publishing**
3. Choose **Publish on AddMaple.com** (public) or **Publish with password** (private)
4. Click **Save Changes**
5. Copy the **Public Link** and send it to your client

See [Publish a dashboard](/help/guides/dashboard/publish), [Password protection](/help/guides/dashboard/password), and [Share with clients](/help/guides/share-with-clients).

## Part 2: Enable Data Explorable (analyst)

With the dashboard published, turn on explorable data and choose which columns clients can access.

1. Open your dashboard
2. Click **Actions → Manage Publishing**
3. Turn on **Data Explorable**
4. Select columns to include (required)
5. Click **Save Changes**

Notes from the explorable guide:

- Explorable controls are disabled when the dashboard is **Unpublished** — publish first (Part 1)
- Column choices must exist in your dataset

See [Make data explorable](/help/guides/dashboard/explorable).

**Privacy:** If a hub will be shared widely, avoid selecting columns with personally identifiable information. The older report explorable guide notes that explorable data can be visible at the row level. See [How to make your data explorable](/help/guides/reportexplorable).

## Part 3: What clients see

On a published hub with explorable data enabled, viewers see a notice that the Story Dashboard includes explorable data and an **Explore** button at the top.

When they click **Explore**, they open the selected columns in the full AddMaple interface (the same tools you use to filter and pivot, limited to the columns you chose).

The report explorable guide describes a similar viewer path with an **Analyze this dataset** link for older report publish flows.

## Part 4: How clients slice data (viewer)

Once in explore mode, clients can filter using the same methods documented for analysts:

### Filter button

From the summary, chart, table, or raw data views, click **Filter** at the top (or press **/**).

Choose a column and filter value. AddMaple applies the filter across the dataset instantly.

### From a chart

Hover a bar (or equivalent) and choose **Filter by this value**.

### From table view

Click an MC+ or MC value in a row to filter by it.

See [Filter your data](/help/guides/filter-your-data), [Filter types](/help/guides/filter-types), and [How to pivot your data](/help/guides/how-to-pivot-your-data).

## Subgroup views vs self-serve slicing

- **Subgroup views** (analyst-built): You define the audience or segment and save charts for clients. See [Subgroup views](/help/guides/subgroup-views).
- **Self-serve slicing** (client-built): You expose selected columns; clients filter and pivot on their own. This guide.

Many teams use both: pre-built mini-dashboards for key stories, plus explorable columns for ad hoc follow-ups.

## Related help

- [What is an Insight Hub?](/help/guides/insight-hub)
- [Ask AI questions in a published Insight Hub](/help/guides/ai-questions-in-hubs)
- [Significance testing](/help/guides/significance-testing) (when clients compare segments in explore mode)