Why more SaaS vendors are embedding data quality into their core platforms

Once, data quality was like an afterthought for SaaS providers – a separate validation exercise or something optional. However, today, more builders and vendors than ever are embedding real-time data quality checks (particularly around address, phone, email, and identity) into core platforms. 

So, let's explore why data quality is important at the product level, how and where SaaS vendors are embedding relevant APIs, and benefits of the resultant transformation. 

Data quality's importance for SaaS products 

Despite being the soul of any SaaS application, data can have undesirable consequences if it's inaccurate or unreliable: 

• Problematic Onboarding: Invalid information interferes with the process of signing up. 
• Wasted Operational Expenses: Sending emails to addresses that are invalid or calling phone numbers that are disconnected wastes time, money, and resources. 
• Issues with Compliance: In domains where stringent regulations are the norm, compliance issues might arise if identity verification is not proper or adequate. 
• Unreliable Analytics: Analytics models, when working with subpar data, fail to offer accurate, reliable insights. 

Decoding the meaning of embedded data quality

Embedding data quality is about integrating the process of validation and enrichment with major product workflows directly. It implies: 

• Placing API calls in real time (from the backend or frontend) when any data input happens 
• Normalizing data (standardizing format of phone numbers by region, for instance)
• Putting checks into effect on the client or server side before persistence 
• Using metadata to enhance inputs 

Hence, from the very beginning, your product gathers better data. 

How SaaS vendors embed data quality APIs

Unlike a one-time job, embedding data quality is a part of the execution path of a product. Simply put, data quality works (or runs) every time a user signs up, verifies their identity, updates their profile, or checks out. 

Here's how modern SaaS vendors are accomplishing the same end-to-end. 

Embedding data quality into the onboarding flow directly 

This strategy stops the infiltration of bad data at the source, common during onboarding. Here's what happens: 

• Frontend (Immediate Feedback)

Most SaaS products nowadays integrate lightweight validation at the user interface (UI) layer. Patterns commonly include automatic completion of addresses along with normalization, email syntax checks while the user is typing, and formatting of phone numbers by country. The idea is to encourage users to make valid entries early on, correct data instantly, and improve user experience. 

• Backend (Authoritative Validation) 

Adding a layer of data quality between handling of requests and persistence allows SaaS vendors to enforce trust. If the data cannot be validated, the request gets rejected or is flagged with a quality score or channeled into a remediation flow. 

Transforming chaotic entries into dependable location data with address APIs

Why are street addresses often messy? Generally, misspelling, contractions, and missing fields trigger this. However, you can tackle the problem by embedding address APIs in billing setups, profiles of customers, checkout flows, etc.  

How?

• Autocomplete

Users get to pick from a list of verified addresses, which minimizes mistakes triggered by manual typing. 

• Normalization

Street names are standardized, postal or ZIP codes are validated, and formats specific to different countries are applied. 

• Enrichment 

Adding geocodes, status of the delivery point, and jurisdiction data associated with time zone, region, taxation, etc. enriches data.  

When you embed address APIs, there are fewer instances of failed shipments and invoices. The accuracy of tax calculations improves too and location-dependent analytics becomes more reliable. 

Boosting the reliability of authentication and messaging with phone APIs

Complications associated with phone numbers are often the result of variations in country codes, formatting, etc. Also, unless they are real and accurate, phone numbers cannot support two-factor authentication (2FA), SMS alerts, and workflows. 

Hence, quality checks generally encompass: 

• Detection of line type (voice over internet protocol/VoIP or mobile or landline)
• Country detection and formatting
• Carrier lookups 
• Risk scoring 

SaaS products typically leverage these to flag VoIP numbers for preventing abuse, reject landlines for features that are SMS-only, and route messages depending on the carrier. 

Preventing Dead Accounts and Deliverability Problems with Email APIs

While most SaaS platforms collect email addresses early on, missing @, typos, disposable addresses, and bad domains are common issues that prevail. Hence, vendors are now embedding these quality checks prior to account creation: 

• Syntax validation to confirm that an address is well-formed
• Domain and mail exchanger (MX) record verification to check if an address can receive emails
• Detection of disposable emails and role accounts 
• Simple mail transfer protocol (SMTP) validation to ensure the mailbox exists

These checks run during signup, before verification emails are sent, and before paid plans are enabled. There are fewer abandoned or fake accounts to deal with and email deliverability gets a boost. Infrastructural costs dip as well.  

Growing Trust without Manual Review with Identity APIs

In case of products that are highly regulated, it's essential to verify that a user is who they say they are. And identity APIs can extract identity data and make comparisons, cross-check names against verified sources, and flag fraudulent signups. 

However, verifying identities is something that is often driven by events. So, what's a typical flow? 

• User provides personal information or identity document
• SaaS backend sends the data to identity API
• API returns verified fields, confidence scores, and fraud indicators 
• State of the user account is automatically updated 

Identity verification is an integral part of tiered access (features unlock progressively), fraud prevention, risk-based pricing, and regulatory compliance. So, scaling trust is possible without involving human reviewers.   

Key perks of embedding data quality 

Here's why embedding data quality has emerged as a strategic move for SaaS vendors: 

• Faster and Smoother Onboarding 

Users complete signup forms reliably and go through onboarding with minimal friction. There are fewer abandoned forms and escalations for support. 

• Less Operational Waste

Since fewer mails or messages fail, downstream resources aren't eaten up as much by invalid contacts. 

• Improved Safety

Validation tools for contact information and identity reduce risk and fraud, which is a competitive advantage.  

• Valuable Analytical Insights 

When quality at the source improves, analytics models operate on data that's clean, correct, and confidence-worthy.  

• Enhanced Compliance 

Sticking to regulatory frameworks and keeping penalties and legal issues at bay is easier when identity and contact data are validated. 

Embed data quality to power your developments 

Embedding data quality in core SaaS platforms pays off in multiple ways. Onboarding becomes smooth, inaccuracies decline, safety risks are mitigated, and trust is fostered for the long run. 

You might be developing a Fintech application, marketplace, or CRM – in any case, leverage real-time, automated tools for address, phone number, email, and identity validation. Start at the earliest and make it a regular exercise.