Data Integrity: Chapter 1

Data hygiene issues can hinder decision-making,  go-to-market planning, customer experiences, and operational efficiency.

That’s why maintaining data integrity is key.

This involves minimising inconsistencies and redundancies and ensuring that data remains high quality across revenue-related functions.

The benefits of data integrity

• Clean and reliable data help GTM teams understand their ICP and minimise the risk of failure when expanding into new market segments. They can target the prospects who share the right fit and characteristics with their best customers.

As Sid Kumar, Senior Vice President of Revenue Operations at HubSpot, said:

"Data is really the fuel that drives a relevant and highly targeted go-to-market strategy."

• Accurate data also helps identify the early signals of a customer’s churn. This could allow organisations to be proactive rather than reactive and work to resolve customer’s pain points ahead of the curve.
  
• Data integrity reduces errors and redundant work.
  
• Reliable data allows for effective customer engagement strategies, improving the overall customer experience.
• High-quality data ensures that customers receive relevant and personalised experiences. By maintaining data integrity, GTM teams can accurately segment their customer base, target specific demographics, and tailor their marketing efforts accordingly. 

This ensures that customers receive the right message at the right time, leading to increased engagement and satisfaction.

• Accurate data is essential for predictive analytics, enabling organisations to anticipate customer needs and identify trends.

As Sid Kumar said:

"Data is the foundation of successful revenue operations teams." And indeed, there are several significant benefits that come with maintaining data integrity in RevOps."

• Clean and reliable data provides accurate insights into customer behaviour, buying patterns, and trends. With data integrity, revenue operations teams can make data-driven decisions. They can identify areas of improvement, optimise sales and marketing strategies, and allocate resources effectively. This leads to better decision-making across the organisation.
• Inaccurate or incomplete data can cause operational inefficiencies, leading to wasted time and resources.
• Data integrity ensures that information is accurate and up to date, allowing revenue operations teams to streamline processes and eliminate redundancies.
• With increasing data protection regulations such as the GDPR (General Data Protection Regulation), data integrity becomes crucial in ensuring compliance. By maintaining data accuracy and protection, you can mitigate the risks of fines, reputation damage, and customer attrition due to non-compliance.

How to improve and maintain data integrity

RevOps teams can implement data hygiene strategies to maintain data integrity.

RevOps establishes data governance policies and standards, defining data quality metrics and ownership responsibilities.

RevOps integrates data from various sources and reviews and updates customer information, eliminating duplicates and correcting errors.

1. Review collection process:

Assess and adjust the data collection process to start with clean data. Then, communicate the value of data integrity to all employees.

2.  Structuring your team

Achieving nearly 100% data integrity depends on your team structure and who is responsible for each data point.

Consider designating roles such as an Insights Manager, Pre-Sales, Post-Sales, and Marketing Operations to oversee specific data-related functions.

Each team member should be clear about their responsibilities, including managing data syncing from marketing efforts, tracking spending, and maintaining data integrity.

3. Optimise your tech stack

One of the primary responsibilities is ensuring that all the different tools and systems are connected.
This connectivity is essential to create a unified data ecosystem that enables smoother operations.

Leore Spira, the Director of Revenue Operations at Blink, pointed out:

"You want to make sure that you build a tech stack that is suitable, not just for the sales team, but also for other stakeholders in the process because you don’t want to start bringing too many tools and integrate it with several platforms."

"You need to think outside the box, but you also need to ensure that you’re using your resources smartly and carefully because otherwise you’re damaging the data."

Conduct thorough research into tech stack best practices. Evaluate tools for lead routing, prospecting, data orchestration, data capture, and data suppliers.

4. Check for data errors

Implement multiple checkpoints to validate data correctness and completeness throughout its lifecycle.

5. Define your data’s relevance and importance

Not all data is created equal, and more data doesn’t necessarily equate to better insights.

Instead of being overwhelmed by vast amounts of data, focus on understanding what data truly matters to your business. Take it from Sid Kumar, who said:

"It’s easy to get caught up in data for data’s sake, and more is not necessarily better in this context. I think being targeted and focused about what you’re using your data for and how it’s helping you connect your go-to-market strategy with your customers is essential."

Define how you intend to use this data, whether it’s to understand your Total Addressable Market, achieve a Share of Addressable Market, or ensure product-market fit.

6. Data refinement

Data often has a shelf life, and knowing when data is 70-80% accurate is usually enough to base healthy and conscious decisions on.

As Sid Kumar explained:

"You sometimes have to accept it’s never going to be perfect. There’s no such thing as ‘perfect’ data, and as soon as it becomes perfect, normally it’s outdated and stale."

"So it’s how much data you need in order to get a conviction as a company that you’re taking a calculated set of risks and bets to go after a market."

Restrict data access to necessary users to reduce the risk of data integrity compromise.

7. Error-detection

Utilise error-detection software to identify potential data risks.

Closing thoughts

Data integrity is essential in any effective revenue operations strategy.

Data integrity is not just a nice-to-have aspect of your business operations but a crucial element that can have a significant impact on your revenue growth and customer experiences.

Organisations can improve decision-making, efficiency and scalability by recognising the importance of data integrity and implementing strategies to maintain it.