Data TransformationText & StringIntermediate

Split HTTP Query

Infoveave Data Automation — Text & String

Every key-value pair in your URL query strings becomes its own named column — UTM parameters, session IDs, filter values, and API parameters all land in structured columns automatically.

Marketing campaigns embed tracking parameters — utm_source, utm_medium, utm_campaign — into links as URL query strings. APIs log request parameters as query strings. Filter states get saved as URL parameters. In all these cases, the analysis-relevant data is encoded inside a single URL column as a compressed key-value list. Split HTTP Query decodes each parameter into its own named column, enabling direct filtering, aggregation, and join operations on individual parameter values without any string parsing logic. Combine with Split URL to handle full URLs, or feed raw query strings directly when the query string is already isolated in a column.

Input:Tabular dataset with a column containing full URLs or raw query strings with key-value parameter pairs in the format key1=value1&key2=value2Output:Tabular dataset with one new column per unique query parameter key, named using the configured prefix followed by the parameter key name

What Split HTTP Query does

Extract individual HTTP query string key-value pairs from URL columns into named columns in Infoveave. Turn raw query strings like id=E001&name=John into Key_id and Key_name columns for campaign tracking, session analysis, and API log parsing.

When to use Split HTTP Query

  • You have a URL column — or a column containing raw query strings — and need to extract specific parameter values like utm_source, session_id, product_id, or page_name into their own columns for analysis or reporting
  • You are processing campaign click data or marketing attribution data where each record includes a landing URL with UTM parameters embedded in the query string
  • You are analyzing API call logs where request parameters are encoded as URL query strings and you need to filter or aggregate by individual parameter values
  • You have already used Split URL to decompose a full URL and now need to parse the isolated Query column into individual key-value columns for further analysis

When to avoid it

  • Your column contains full URLs and you also need the host, path, and protocol components — use Split URL first, then pass the extracted Query column into Split HTTP Query
  • Your column does not contain URL-encoded key-value pairs — for general delimiter-based column splitting use Split Column, and for email address decomposition use Split Email Address
  • Your query strings use non-standard encoding — apply Find and Replace to normalize the encoding format before parsing

Where it fits in your Infoveave automation

Split HTTP Query is one step inside a multi-step Infoveave workflow. Chain it with other activities — no code, no manual hand-offs.

ConnectLoad click tracking data, API logs, or session data containing URL or query string columns into Infoveave
Split URL (optional)If working with full URLs and needing host or path columns too, use Split URL first to extract all URL components including the raw query string
You are hereSplit HTTP QueryParse the URL or query string column to expand each parameter key into a named column with the configured prefix
Filter or AggregateFilter, group, count, and aggregate metrics by individual parameter columns — utm_source, session_id, product_id
AutomateSchedule the pipeline to parse new click and API logs automatically on each data refresh cycle

Build this workflow visually in Infoveave Data Automation — drag, connect, and schedule with no infrastructure setup.

Infoveave — Workflow Builder
● SavedSchedule: Daily 06:00
Data SourceConnectLoad click tracking data, …Split URL (optional)If working with full URLs …YOU ARE HERESplit HTTP QueryParse the URL or query str…Filter or AggregateFilter, group, count, and …AutomateSchedule the pipeline to p…Dashboard

How teams use Split HTTP Query

Real scenarios where this transformation saves hours of manual work.

Marketing

Extract UTM Parameters from Campaign Click URLs

A marketing analytics team processes a campaign performance dataset where each click record includes the full landing URL with embedded UTM tracking parameters. After using Split URL to isolate the query string, Split HTTP Query expands the query into separate Key_utm_source, Key_utm_medium, Key_utm_campaign, Key_utm_content, and Key_utm_term columns. The team can then group click and conversion metrics directly by campaign, medium, and source without any string manipulation.

Technology

Parse API Request Parameters from Gateway Log URLs

A platform team processes API gateway logs where each request record includes the full request URL with query string parameters encoding the request context — user ID, resource type, version, and filter values. Split HTTP Query extracts each parameter into a named column, allowing the team to analyze API usage patterns by user, filter by resource type, group response latency by API version, and identify over-used parameter combinations from column-level aggregation.

Retail

Analyze Search Filter Combinations from E-Commerce Session URLs

A product analytics team analyzes site session data where filter selections are encoded as URL query strings in the page URL column — for example category=electronics&brand=HP&price_range=500-1000. Split HTTP Query extracts each filter parameter into a named column per key. The team can count how often each filter combination is applied, identify which filter combinations correlate with purchase conversion, and rank the most used filter values per category.

See Split HTTP Query in action

Input data (left) is transformed using the configuration below. The output table (right) is ready for dashboards or downstream steps.

Column Name:url
Prefix:Key_
Include Original:Yes

Input Data

Employee IDNameurl
E001John Doehttps://company.com/employee?id=E001&name=John+Doe&department=Sales
E002Marie Duponthttps://marketing.com/employee?id=E002&name=Marie+Dupont&department=Marketing
E003Carlos Gomezhttps://fileserver.com/download?id=E003&name=Carlos+Gomez&department=IT

Output Data

Employee IDNameurlKey_idKey_nameKey_department
E001John Doehttps://company.com/employee?id=E001&name=John+Doe&department=SalesE001John+DoeSales
E002Marie Duponthttps://marketing.com/employee?id=E002...E002Marie+DupontMarketing
E003Carlos Gomezhttps://fileserver.com/download?id=E003...E003Carlos+GomezIT

Configuration

Key fields to configure in the Infoveave workflow builder. Full reference available in the documentation.

Column Name

Select the column that contains either full URLs or raw query strings. Split HTTP Query automatically finds the query string portion of a full URL, so you can pass a full URL column directly without first isolating the query. You can also pass a column that contains only the query string portion — either starting with a question mark or without it — and the parsing works the same way.

Prefix

Define the prefix added to each output column name. The column name for each parameter becomes the prefix followed by the parameter key — for example a prefix of Key_ and parameter id produces column Key_id. Using a consistent prefix prevents naming conflicts with existing dataset columns and makes auto-generated query parameter columns easy to identify and filter in downstream steps.

Include Original

Choose whether to retain the original URL or query string column alongside the newly generated parameter columns. Keep it on if you need the complete URL for debugging, as a display value, or for passing to additional transformations. Disable it to keep the output clean when the original URL column is no longer needed after parameter extraction.

Frequently asked questions

Everything you need to know about Split HTTP Query in Infoveave.

Also in Text & String — and what runs before & after

Transformations in the same family as Split HTTP Query, often chained together in the same Infoveave workflow.

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Split HTTP Query is one of over 80 transformation activities available inside Infoveave workflows. Chain transformations together — no code, no exports, no waiting for IT.

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