Segment Announces Protocols, a New Way to Streamline Data Governance Across Enterprise Organizations
SAN FRANCISCO, Sept. 21, 2018 — Segment, a customer data infrastructure company, today announced Protocols, a new data governance product that helps enterprises put their customers first by ensuring that first-party customer data is consistent, accurate, and reliable across their entire organization. With Protocols, Segment now offers businesses the complete Customer Data Infrastructure that they need to build better products, create more relevant customer experiences, and make smarter business decisions.
Previously, the process of ensuring that first-party customer data is clean, correct, and trustworthy across enterprises was an arduous and manual process that was prone to human error. Data is often siloed throughout an entire organization and lacks consistent standardization, making it difficult for large companies to meet customer needs and make well-informed business decisions. Most data strategies at enterprise organizations still revolve around a central spreadsheet, internally called “a tracking plan,” that must be followed and verified manually by every department. As a result, ensuring data integrity can require significant engineering resources, hours of manual testing, and constant communication among multiple teams.
With Protocols, companies can ensure that data used throughout an organization is consistently accurate, with automatic detection and prevention of data errors in real-time.
Bad Data: A $3.1 Trillion Problem
Poor data quality costs enterprise organizations $15 million a year on average, according to a recent survey from Gartner, and by some estimates, costs the United States economy a total of $3.1 trillion dollars a year. Enterprises have thousands of different data sets across dozens of departments, and even the smallest data issue can cause unreliable analytics, disjointed customer experiences, and misguided product decisions. Poor data quality can ultimately cost businesses millions of dollars in lost revenue.
For example, the central analytics team at a B2B SaaS company focused on driving leads will decide in the organization’s tracking spreadsheet that the data point about signups for a product demo, in every department, will be named “Lead Captured.” Marketing, sales and product teams will then incorporate this label on every page where a user can sign up for a demo. However, in one department, the team accidentally titles the data point as “Captured Lead.” Following the central tracking plan, the marketing team then analyzes all “Lead Captured” data to engage with leads, but they are unknowingly missing data about a substantial portion of prospects. Unless this error was caught by someone in the company, this data is now lost and could cost hundreds of thousands of dollars in lost business revenue.
“Everything a business does, from product decisions and personalization to planning and investment, depends on accurate and reliable customer data. Any data issue will have a significant business impact, especially if organizations end up making the wrong decisions for their customers,” said Peter Reinhardt, CEO and co-founder at Segment. “By automating data quality assurance, we’re giving companies the infrastructure they need to ensure that they deliver customer-centric products, marketing, and experiences.”
Protocols Ensures Data Is Accurate and Consistent in Real-Time
With Protocols, companies can solve three of the biggest challenges contributing to data quality issues: alignment, validation, and enforcement. Enterprises are able to:
- Standardize customer data collection across an organization. Analytics teams can stop using spreadsheets and instead create a data tracking plan within Segment. This serves as the single source of truth for customer data to maintain accuracy across teams. Protocols will provide industry-specific specs and templates, including for e-commerce, mobile, B2B SaaS, and more.
- Diagnose data quality issues before they impact production. Protocols automates the complex process of detecting invalid data and other data bugs, so that teams can ensure data quality well before that data is activated in marketing campaigns, product decisions, or business strategy.
- Protect critical business tools and data warehouses from bad data. Protocols lets teams configure settings to keep data clean, accurate, and standardized across all marketing tools and data warehouses. This prevents even a minor data issue from affecting an otherwise clean data set.
Typeform, the online SaaS company that specializes in online forms and surveys, has used Protocols to enforce data quality standards at scale and ensure complete consistency in how they track data events. Protocols has allowed the company to drive greater efficiency across the board, consolidating tracked data events by 75 percent and catching data quality issues before they impact production.
“As Typeform scaled, our rate of growth began to outpace our ability to enforce data quality across our business. We needed a solution that could standardize and automate our data governance process to support our product, marketing, and customer success teams,” said Colin Furlong, Business Intelligence Analyst at Typeform. “With Protocols, we now have confidence in our data, no matter how fast we grow. Everything has become much more streamlined and the insights we’ve gained are driving many business benefits, including a 10 percent lift in user conversion to paid customers in one A/B test.”
For additional details on Protocols and Segment, please visit https://segment.com/product/protocols.
Segment provides the customer data infrastructure that businesses use to put their customers first. With Segment, companies can collect, unify, and connect their first-party data to over 200 marketing, analytics, and data warehousing tools. Today, over 19,000 companies across 71 countries use Segment, from fast-growing businesses such as Atlassian, Bonobos, and Instacart to some of the world’s largest organizations like Levi’s, Intuit, and Time. Segment enables these companies to achieve a common understanding of their users and make customer-centric decisions.