Data Orchestration: The Modern Approach to Business Intelligence 

What is Data Orchestration?

Data orchestration is the practice of acquiring, cleaning, matching, enriching, and making data accessible across technology systems. Effective data orchestration captures data from several sources and unifies it within a centralized system, making it organized and ready for use by revenue professionals. 

Akin to a conductor directing a symphony, data orchestration seeks to create data harmony across a revenue team. It’s part science and part art. 

A critical piece of any data-driven go-to-market strategy, data orchestration is used by marketing and sales operations teams (also known as revenue operations), data engineers, and data analysts to prepare large swaths of actionable data deliver results for their business. 

What are the Steps Involved in Data Orchestration?

Maintaining actionable data is a symbiotic process with several steps: 


Increasing the number of usable records in your database depends on starting with a clean data set. Clean data means it’s formatted correctly, complete, and up to date. This step resolves inconsistencies using normalization tools.


Prevents duplicate data from disrupting sales and marketing teams. Whether it’s data uploaded from trade shows, list buys, or webinar leads, record merging and duplicate prevention logic form an important part of the orchestration process. 


Also referred to as normalizing, data standardization uses rules, templates and field mapping to refine data into standard taxonomies. This ensures that the formatting of any incoming data complies with your systems. For example, you can run a workflow to standardize phone numbers in batches to ensure auto-dialers return a higher contact rate. Standardization makes lead routing more efficient, resulting in fewer lost opportunities. 


Matching is the process of pairing records together to ensure that fields map correctly. When you match inbound leads to accounts, you make a scalable account-based marketing (ABM) strategy possible. By showing lead data in the context of a prospect’s overall account, you reveal key information like customer history, account assignments, and territory planning.


Multi-vendor, real-time enrichment triggers give teams additional information on prospects. As you import a list, any critical data points that are missing (like phone number, region, or job title) can be populated automatically. The enrichment process  of data orchestration results in better lead-to-account matching. 


Segmentation tools increase the ability to execute multi-channel go-to-market strategies by categorizing and filtering data into clear buyer personas, sales territories, scores, job role, industry classification. This empowers teams with precision targeting capabilities to identify new opportunities and run hyper-targeted campaigns.


Once your data is cleaned, deduped, enriched, and segmented it has to be sent somewhere. How effectively it’s routed to the correct people or queues depends on orchestrating the right routing rules. For example, leads for specific industries can be automatically sent to the reps that specialize in their needs. Or if an enterprise-level account comes in, it can be sent to the best rep to handle a customer of that size. 


Data orchestration prevents future data inaccuracies from entering the system by using customizable workflows to automatically identify and resolve duplicates, normalize incoming data, and enrich fields with specific sources.

What Challenges are Solved by Data Orchestration?

The process of merging, cleaning, and updating a database is typically a time-consuming activity for IT and data analyst teams. Even with extensive time investments, their efforts could still result in significant inaccuracies without a system to automate and manage it all.

With proper data orchestration techniques, organizations are creating end-to-end data management processes that help teams quickly access and use information to fuel their job. The modern data orchestration approach solves two overarching challenges: data usability and data access. 

Challenge 1: Unusable data

As you compile data, you’re bound to come up against plenty of inconsistencies: 

  • Dirty data
  • Inconsistent data
  • Too much data
  • Duplicate data
  • Incomplete data
  • Inaccurate data
  • Decaying data
  • Insecure data

Implementing data orchestration resolves these inconsistencies and results in engagement-ready data for go-to-market motions. 

Challenge 2: Siloed data

Organizations often face fragmented data sets sprawled across their tech stack. This siloed data stands in the way of accurately prioritizing and engaging with buyers. It also offers little to no return on investment and no real path to automate the process of data migration or proper data quality management. 

Breaking down data silos and transforming data into usable intelligence requires a unified system of record. The ideal data orchestration system will solve this lack of interconnectivity within your data ecosystem by creating a centralized approach to acquiring, processing, and activating data. 

What are the Business Benefits of Data Orchestration?

The benefits of data orchestration touch almost every part of a data-driven business. Government and industry compliance, sales and marketing alignment, forecasting, and cost savings are only a few. 

Accurate customer profiling

Clean, consistent, complete data enables accurate segmentation using any mix of criteria unique to your business, including vertical, persona, and company news.  

Capitalization of the total addressable market (TAM)

Identify new growth opportunities, expand into new markets, and deploy multiple go-to-market programs by understanding your TAM, including accounts you might otherwise miss if your matching function is flawed.

Significant cost savings

Eliminate the need to pay for multiple point solutions, reduce MAP storage costs, and create time-saving efficiencies for all go-to-market teams — without having to hire more full-time employees.

More ROI attribution

High-quality data and automated workflows enable more accurate campaign attribution and ROI reporting.

Industry & government compliance

The risk of hefty fines is reduced because all connected systems can be configured to conform to data and privacy regulations, ensuring that not just an individual’s specific email address is opted out, but also their entire profile, across all platforms or instances.

Better conversion rates

Working with clean, complete data improves inbound lead generation, ensures more qualified meetings, and moves prospects through the buyer journey faster.

Data-driven decision-making

With an effective data orchestration solution, every team member has the data they need to make well-informed business choices.

Campaign personalization

Sales and marketing teams can effectively execute targeted sales sequences and nurture campaigns, based on a complete customer view and with tools to create customized campaigns that resonate with the target audience.

Sales & marketing alignment

Go-to-market teams collaborate best together when they can trust what’s inside their CRM. Make sure your team’s database is not a burden, but rather a system of insight that helps each team achieve their goals.

What is the Difference Between Data Integration and Data Orchestration?

Data integration is the process of automatically centralizing data to provide one single source of information. This makes data more accessible to the teams and systems that need it, including a data orchestration system.

Data integration involves connecting different data sets together. It unifies data from different applications, the cloud, or third-party sources, and stores it in a central location like a data warehouse. For example, ZoomInfo’s integration with Google Cloud gives data and IT teams access to reliable, up-to-date data. The ZoomInfo integration with HubSpot does the same for sales and marketing teams.

Data orchestration involves the coordinated, automated process of cleaning, enriching, and routing data based on customizable rules and workflows. It prepares and organizes data in order to extract value. By ensuring data is error-free, formatted properly, and mapped to the right fields in each platform, data orchestration is the multi-step process that gets data ready to fuel more effective GTM execution. 

ZoomInfo’s Data Orchestration Workflow Using RingLead

Use Cases: Examples of Data Orchestration in Action

The way you orchestrate data can look different depending on what you want to do. Here are some real-life examples of how teams use data orchestration in action to achieve their goals.  

Quickly upload a list of leads from a webinar

You’ve conducted a webinar and you need an automated way to clean, normalize, and segment your attendee list and pump it directly into your marketing and sales tools for fast follow up. Using data orchestration to upload and standardize your list accelerates your MQL-to-conversion process by starting your team off with pristine business intelligence.

Enrich your CRM data using multiple sources

You run a data quality report and find that 46% of your records have blank fields. Orchestration tools, like Enrich Premium, can complete your database with custom field mapping tools that automatically enrich each field with the most relevant source of third-party data. 

Fill in missing information about your web visitors

When a visitor arrives on your landing page and completes a form, data orchestration can deploy real-time matching and data enrichment to automatically supplement the form with additional information you want to know about the prospect. Attributes like phone number, address, industry classification, company size, and revenue can be added to each lead record without requiring the web visitor to type it in.

Score and route leads to the best sales team

For most go-to-market teams, speed-to-lead is the name of the game. Qualifying and routing leads to the right rep quickly is a key element for success. When a new visitor comes to your website, data orchestration provides an automatic, rules-based process for identifying, qualifying, and connecting them with the next best step in their journey.

“When you get back to a lead that filled out a form on your website in the first few minutes, you have a 10 times better chance of converting that lead into an opportunity than if you waited an hour or longer,” says Henry Schuck, CEO and founder of ZoomInfo

How to Get Started With Data Orchestration

Data orchestration is a multifaceted process that helps sales and marketing ops teams facilitate the use of data to make better decisions and drive more business opportunities. A successful data orchestration strategy, including deduplication, normalization, enriching, segmenting, and scoring, enables revenue operations teams to manage the quality of data flowing throughout their systems.