Spark.re + Improvado: Real Estate Sales Data Automated

Connect Spark.re and let AI agents query contacts, interactions, contracts and registration answers alongside data from 1,350+ sources.

1,350+ data sources
Any warehouse or BI tool

improvado.io/agent · Spark.re

Improvado Agent

Connected to Spark.re

Which registration sources brought the most new contacts this month?

Spark registered 1,240 new contacts this month. The website form brought 41% of them, followed by broker referrals at 18%.

Show contacts who registered this month but have no interaction logged yet.

Found 156 contacts with no interaction since they registered, grouped by registration source and ready for your sales team.

Trusted by data-driven teams

1,350+

Integrations

200+

Spark.re Fields

99.9%

SLA Uptime

<5 min

Setup

SOC 2

Type II

Key Takeaways

Connect Spark.re to your data warehouse

Improvado connects to the Spark API to extract the records of your Spark projects. Pick a resource - contacts, interactions, contracts, registration answers, inventory and more - select its fields, including custom fields, and Improvado loads it on your schedule into BigQuery, Snowflake, Redshift, or any supported destination.

200+ metrics and dimensions Campaigns, ad groups, keywords, audiences, geo, device — all granularity levels from the Spark.re API

15-minute refresh cycles Near real-time sync with 99.9% SLA uptime. No stale dashboards.

Cross-channel normalization Marketing CDM unifies your data with 1,350+ sources into one schema. No manual mapping.

Any warehouse or BI tool Snowflake, BigQuery, Redshift, Databricks, Power BI, Tableau, Looker Studio

AI Agent access via MCP Query, write, and monitor Spark.re through Claude, ChatGPT, Cursor, or any MCP client

Enterprise-grade security SOC 2 Type II, HIPAA, GDPR, CCPA. Raw data never leaves your environment.

OAuth setup in minutes No API keys, no code, no developer setup. Schema changes handled automatically.

Zero ongoing maintenance Pagination, rate limits, API versioning — all managed. Your team focuses on analysis.

Integration Details

New-development sales data next to your marketing data

Land Spark contacts, registration sources and sales activity in the same warehouse as your ad spend and web analytics. Join contacts to their registration source and compare registrations and contract activity across projects in Tableau, Power BI, or Looker.

Spark API v2 · company or project API key · scheduled · incremental by updated time

Schema Overview

Data objects and fields Improvado extracts from Spark.re

Object	Fields
Contacts	id registered_at marketing_source registration_source_id last_interaction_date opted_in_at created_at updated_at
Interactions	id contact_id interaction_type_id team_member_id project_id timestamp created_at updated_at
Contracts	id project_id inventory_id status_id date firm_date completion_date purchase_price total_price
Question Answers	id contact_id project_id question_id question answers
Registration Sources	id name category created_at updated_at

How it works

From connection to autonomous action in three steps

Connect

Connect Spark with an API key created in Spark under Settings > API. A company-level key brings in every project of your company as an account, and a project-level key connects one project.

Ask

Ask questions like 'which registration sources brought the most contacts this quarter' or 'how many contracts went firm last month' or 'which contacts have had no interaction in 30 days'.

Act

The agent builds lead-source and sales reports, schedules digests for your sales and marketing teams, and flags drops in registrations or contract activity per project.

Use Cases

What teams ask their AI agent about Spark.re

Real prompts from enterprise marketing teams. The agent reads your data, answers in seconds, and takes action when you ask.

See how teams use Improvado →

Improvado Agent Analysis

Compare new contacts by registration source across your Spark projects

Your AI agent analyzes Spark.re data and delivers actionable insights — automatically, in seconds.

Manual → auto

Improvado Agent Cross-channel

Report contract volume and value per project next to marketing spend

Your AI agent analyzes Spark.re data and delivers actionable insights — automatically, in seconds.

Manual → auto

Improvado Agent Reporting

Track sales team follow-up from the interactions logged in Spark

Your AI agent analyzes Spark.re data and delivers actionable insights — automatically, in seconds.

Manual → auto

AI Agent Access

Your agent doesn't just read Spark.re - it tracks lead sources and sales activity

AI agents query the Spark records you extract - contacts, interactions, contracts and registration answers. They compare registration sources, flag contacts with no follow-up, and track contract activity per project next to your marketing data.

Explore MCP →

Read

The agent reads the Spark records you extract - contacts, interactions, contracts, registration answers, inventory and their lookup tables - with the custom fields you select.

Write

The agent generates lead-source and sales reports, schedules digests for your sales and marketing teams, and summarizes contract activity across projects.

Monitor

The agent monitors registrations, interactions and contract activity per project and alerts your team when a registration source or a project falls behind.

Improvado Agent · Spark.re

You

Show new contacts by registration source this month

New Contacts by Source

Registration Source	Contacts	Share
Website form	508	41%
Broker referral	223	18%
Paid social	198	16%
Walk-in	174	14%
Sales event	137	11%

5 sources · 1,240 new contacts this month

You

Alert me when weekly registrations from any source drop by 25%

Alert Created

Watching 5 registration sources weekly

Works with

ClaudeChatGPTCursorGeminiAny MCP Client

Destinations

Send Spark.re data anywhere

Load normalized data to your preferred warehouse, BI tool, or cloud storage. Click any destination to see its integration guide.

Snowflake → BigQuery → Redshift → Databricks → Power BI → Tableau → Looker Studio → Google Sheets → Domo → Excel → Qlik → Amazon S3 → Metabase → Grafana → PostgreSQL → Azure SQL →

SOC 2 Type II: Certified Security

HIPAA: Health Data Privacy

GDPR: EU Data Protection

CCPA: CA Privacy Standard

Compare

They extract data. Improvado deploys an agent.

Traditional tools move data from A to B. Improvado gives you an AI agent that reads, acts, and monitors — with Spark.re as one of 1,350+ integrated sources.

Feature	Improvado	Supermetrics	Funnel.io	Fivetran
Data fields extracted	200+	~90	~120	~80
Total integrations	1,350+	~150	~500	~300
Cross-channel normalization (CDM)	✓ Built-in	✗ Manual	Basic mapping	✗ Raw only
AI Agent access (MCP)	✓ Read, Write, Monitor	✗	✗	✗
Data warehouse destinations	✓ 16+ warehouses & BI tools	Sheets, Looker, BigQuery	BigQuery, Snowflake, Redshift	✓ Broad warehouse support
Refresh frequency	Every 15 min	Scheduled triggers	Daily / 6hr	Every 15 min (premium)
SOC 2 Type II & HIPAA	✓	✗ SOC 2 only	✓ SOC 2	✓
Best for	Teams that want an AI agent, not a pipeline	Small teams, spreadsheets	Mid-market, data teams	Engineering-led ELT pipelines

Comparison based on publicly available documentation as of April 2026. Feature availability may vary by plan tier.

FAQ

Frequently asked questions

What Spark.re data can Improvado extract?

Improvado extracts one report, Records. In its Resource setting you pick the Spark resource to extract - such as contacts, interactions, contracts, question answers, registration sources, team members or inventory, 30 resources in all - and select its fields, including the custom fields of contacts, contracts, inventory and brokerages. Each Spark project is an account.

What authentication does the Spark.re integration require?

A Spark API key, created in Spark under Settings > API. A company-level key makes one connection with every project of the company as an account and needs read permission for Company and Projects. A project-level key makes one connection for its project and needs read permission for Projects. Either key also needs read permission for each resource you extract.

How often does Spark.re data sync with Improvado?

Spark.re data refreshes on the schedule you set for the extraction. The first load reads all records of the resource, and each scheduled run then reads the records created or changed in Spark during the last few days.

Why are prices and amounts in Spark.re data so large?

Spark returns money values in cents, so a purchase price of 50000000 is 500,000.00 in the project's currency. Divide money fields by 100 in your reports for two-decimal currencies.

Can I extract Spark.re custom fields?

Yes, for contacts, contracts, inventory and brokerages. Each custom field defined in Spark is a separate field you can select. Selected custom fields make the extraction read each record on its own, so the first load of a large resource takes longer.

Which destinations support Spark.re data?

All major platforms including BigQuery, Snowflake, Redshift, Azure, Tableau, Power BI, and Looker. Spark records flow directly to your preferred warehouse or business intelligence environment.

Customer stories

See all customer stories →

“Improvado saves about 90 hours per week and allows us to focus on data analysis rather than routine data aggregation, normalization, and formatting.”

Jeff Lee

Head of Social, Media Buy, Influencer & Marketing Data, ASUS

Read story

“Improvado's reporting tool effortlessly integrates all our marketing data so we can easily track users across their entire digital journey. This saves me and my team countless hours.”

Marc Cerniglio

Insights & Automation Manager, Chacka Marketing

Read story

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