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This article dives into the central role of HubSpot data management in maximising CRM potential, key challenges and best practices for data management. We'll also explore common pitfalls and tips for avoiding them when migrating data to HubSpot.

It's easy to get overwhelmed by too much data in your CRM.

Unfortunately, this has serious consequences: 30% or more of sales are lost due to bad data, and an astonishing 33% of executives are unable to trust their own data. Shockingly, only 3% of organisations' data meets basic quality standards.

Effective data management is therefore essential for organisations of all sizes. By focusing on the right data in the right places, organisations can realise the full potential of their CRM systems.

Join us to discuss the central role of data management in maximising CRM potential and learn more about best practices for data management in HubSpot.

Types of data management

With the vast amounts of data being generated and collected on a daily basis, it is essential to have proper systems in place to manage and organise this information effectively. This includes tasks such as creating policies for data handling, setting up processes for data entry and retrieval, and ensuring the security and integrity of all data within the organisation. 

There are several types of data management that organisations may need to employ depending on their specific needs. Some common types include big data management, which focuses on handling large volumes of complex and varied data sets, master data management, which involves creating a single, accurate view of key business information across multiple systems, and metadata management, which deals with organising and categorising data for easy access and retrieval.

Let’s have a look at different types of data management and their use cases.

Data lifecycle management

Data lifecycle management (DLM) is a systematic approach to managing information through the various stages it goes through during its lifetime. This framework outlines the entire journey of data, from its collection, storage, and usage until its ultimate disposal. By creating policies and procedures for each stage, organisations can ensure that their data is effectively managed and utilised throughout its lifecycle.

The primary aim of DLM is to maximise the value and utility of data for an organisation. By properly managing data from the moment it is collected, ensuring secure access to authorised users, and monitoring how it is used, companies can leverage their information assets more effectively. By implementing a comprehensive DLM strategy, businesses can enhance decision-making processes, improve operational efficiency, and reduce risks associated with data loss or misuse.

Data pipelines

Data pipelines are crucial for businesses looking to streamline their data flow processes. By establishing a smooth path for data to move between systems, companies can better manage and analyse their information. Take the example of a HubSpot customer running a Google Ads campaign – integrating these two systems through a data pipeline enables them to consolidate paid ad data from multiple platforms into one central dashboard. This not only simplifies the data analysis process but also allows for easier comparison and decision-making.

In addition to consolidating data, data pipelines also allow for transformations to occur along the way. In the case of matching time zones when transferring paid ad data, this transformation ensures that all information is aligned and accurate for analysis. These modifications can greatly improve the quality and usability of the data being transferred throughout the pipeline, ultimately leading to better insights and more informed business decisions.

ETLs (extract, transform, load)

ETLs, or extract, transform, load processes, have become an essential component for businesses looking to streamline their data processing and analysis.

By effectively pulling data from various sources into a central repository, ETLs enable organisations to access and analyse information more efficiently. The extraction step involves retrieving data from databases, APIs, or other sources. This raw data is then subjected to transformation where it is cleaned, validated, and formatted for consistency before being loaded into the desired destination.

The transformation phase of ETL plays a crucial role in ensuring that the data is optimised for analysis and reporting. Through this process, data can be enriched with additional information, standardised for uniformity across different sources, or aggregated to provide meaningful insights. Once the data has been transformed, it is ready to be loaded into a new location such as a data warehouse or database where it can be accessed by stakeholders for decision-making purposes.

Overall, ETL processes not only simplify the consolidation of disparate data sources but also help businesses make more data-driven decisions based on accurate and well-structured information.

Key challenges in HubSpot data management

Organisations know how important data management is, but many experience a number of challenges while they try to apply best practices.

Let's take a look at some common data management hurdles in HubSpot:

  • Data integration from other platforms: Combining data from various origins is relatively simple thanks to robust APIs, among other factors. However, the true difficulty lies in accurately modelling the data and synchronising the pertinent information effectively.

  • Determining the need for Ops Hub: It can be challenging to determine whether Ops Hub is necessary for your specific business needs. Deciding on its implementation requires careful consideration of operational requirements and strategic objectives.

  • Manual data entry: Manually entering data, especially from sales teams or other sources, can lead to errors and inconsistencies. Streamlining this process while maintaining data accuracy is essential for effective data management in HubSpot.

In the below video, you can watch our Chief Strategy Officer, Amy Dwyer, talk about common challenges with Hubspot data management. The clip is part of our webinar on Mitigating Information Security Risks, you can watch the full webinar for free here.  

 

Overcoming these HubSpot-specific challenges is critical to realising the full potential of the platform and ensuring smooth data management workflows. Let’s explore best practices that will help you to overcome these challenges and optimise your HubSpot data management.

6 Best practices for HubSpot data management

Step 1. Make a data management plan

Developing a data management plan that is tailored to the HubSpot framework lays the foundation for effective utilisation of the data in your platform.

This includes several important aspects:

  • Identify your research data: Firstly, conduct a comprehensive data inventory. Understand the type of data, its sources, estimated volume and file formats. Prioritise data security considerations to protect sensitive information.

  • Establish clear goals and objectives that align with organisational goals: Define precise goals for data management in HubSpot that align with overall business objectives. This includes defining key metrics, audience segments and desired outcomes as a basis for strategic decisions.

  • Implement data security measures: Integrate strict data security protocols into your strategy to protect sensitive information. Define access controls, encryption methods and storage protocols to minimise the risk of unauthorised access or a data breach. Ensure compliance with regulations such as HIPAA if you are a healthcare provider.

  • Organise your data effectively: Define systematic methods for organising data in HubSpot. Use features such as folders, tags and naming conventions to ensure consistency and accessibility, minimise errors and optimise workflows.

  • Document your data: Provide comprehensive documentation to effectively contextualise your data. Integrate metadata and supplementary files such as data dictionaries to improve understanding and usability, avoid ambiguity and ensure data integrity.

  • Plan for data retention and deletion: Develop a strategy for long-term retention and deletion of research data in HubSpot. Utilise qualified repositories, such as data repositories, to ensure data integrity and accessibility over time and align retention efforts with data sharing requirements.

By carefully planning your data management strategy in HubSpot, you set the stage for smooth operations, informed decision-making and sustainable business growth.

Step 2. Improving data quality in HubSpot

Enhancing data quality within HubSpot is essential for ensuring accurate insights and effective decision-making.

Here are techniques specifically tailored to HubSpot, along with the tools and features within HubSpot to maintain high data quality:

  • Data cleansing and validation techniques: Implement robust data cleansing and validation processes within HubSpot to identify and rectify inaccuracies, inconsistencies, and duplicates in your data - essentially making sure that only good data enters your CRM. Leverage HubSpot's Import Error Handling feature to discover and rectify errors before adding data to your CRM. Additionally, utilise Property Validations to enforce rules for certain properties, ensuring data integrity and reliability.

  • Role of automation: Automation plays a pivotal role in enhancing data quality within HubSpot. With Data Quality Automation recommendations, HubSpot leverages AI to suggest rules for fixing formatting issues within CRM properties, such as capitalisation and spacing. Once accepted and enabled, these automations ensure that your database remains clean and consistent with minimal manual intervention.

HubSpot Tools for data quality management:

  • Data Quality Command Center: Gain at-a-glance insights into the health of your HubSpot data with the Data Quality Command Center. Identify and rectify issues such as unused properties, data sync bottlenecks, formatting inconsistencies, and duplicates.

  • Data sync improvements for health: Keep your teams informed about integration health and quickly diagnose data syncing issues with sync health monitoring. This feature minimises manual data monitoring efforts, allowing more time for customer engagement.

  • Custom Object Builder: Utilise the Custom Object Builder to create unique data models within HubSpot, reflecting the specific needs of your business. No coding required, making it easy to build and maintain custom data structures tailored to your requirements.

By leveraging these techniques and tools provided by HubSpot, businesses can maintain high data quality standards, ensuring the reliability and accuracy of insights derived from the platform.

Step 3. Data segmentation in HubSpot

In HubSpot, effective data segmentation is the key to tailoring your marketing efforts, nurturing leads, and driving conversions.

Here's how you can leverage segmentation strategies to transform your business:

  • Define segmentation criteria: Begin by defining clear segmentation criteria based on demographics, behaviour, interests, and engagement level. This allows you to create targeted segments that resonate with specific audience segments.

  • Utilise contact properties: Leverage HubSpot's contact properties to categorise and segment your contacts effectively. From industry and job title to purchase history and engagement level, utilise these properties to tailor your messaging and content.

  • Implement lead scoring: Implement lead scoring to prioritise and segment leads based on their likelihood to convert. By assigning scores to leads based on their actions and engagement with your content, you can focus your efforts on high-value prospects and tailor your outreach accordingly.

  • Use lists and segments: Create lists and segments within HubSpot to organise your contacts based on predefined criteria. Lists allow you to group contacts with similar characteristics, while segments dynamically update based on specified conditions, ensuring that your targeting remains relevant and up-to-date.

  • Personalise content and messaging: Armed with segmented data, personalise your content and messaging to resonate with each audience segment. Tailor your email campaigns, website content, and advertisements to address the specific needs and interests of each segment, enhancing engagement and driving conversions.

  • Automate workflows: Streamline your marketing efforts by automating workflows based on segmented data. Set up automated email sequences, lead nurturing campaigns, and follow-up processes to deliver timely and relevant communications to each segment, maximising efficiency and effectiveness.

  • Analyse and iterate: Continuously monitor the performance of your segmented campaigns and analyse the data to gain insights into what works and what doesn't. Use this feedback to refine your segmentation criteria, personalise your messaging further, and optimise your marketing strategies for better results.

By implementing these segmentation strategies in HubSpot, you empower your marketing team to deliver highly targeted and personalised campaigns that resonate with your audience. 

Moreover, it allows your sales team to prioritise leads effectively, focus their efforts on high-value prospects, and drive more conversions.

Ultimately, segmentation isn't just about dividing data; it's about unlocking the full potential of your CRM system to drive business growth and success.

Step 4: Establishing a data governance framework for HubSpot

A data governance framework lays the groundwork for maintaining the quality, consistency, and security of data within HubSpot.

It provides guidelines and protocols for managing data throughout its lifecycle, from collection to disposal. By enforcing standardised practices and procedures, data governance enhances transparency, accountability, and trust in your data assets.

Let's explore how you can implement it effectively:

  • Defining roles and responsibilities
    Central to any data governance framework is the clear definition of roles and responsibilities for data handling within HubSpot. Designate individuals or teams responsible for data management, including data administrators, analysts, and compliance officers. Clearly outline their duties, such as data entry, validation, and security enforcement, to ensure accountability and adherence to data governance policies.

  • Creating policies and procedures
    Developing comprehensive policies and procedures for data handling is essential for maintaining data integrity and security within HubSpot. Define protocols for user permissioning, specifying who can access, edit, or modify data within the platform. Utilise HubSpot's user roles and permissions settings to restrict access to sensitive data, ensuring that only authorised personnel can view or manipulate it.

  • Implementing REACT principles
    Building upon the REACT principles introduced during Inbound23, emphasise the concept of "least privilege" access within HubSpot. Restrict access to data to only those individuals who require it for their specific roles or tasks. This ensures that sensitive information remains protected from unauthorised access or misuse, bolstering data security and compliance.

  • Leverage tools for data protection
    Incorporate advanced data protection tools like Nullafi into your data governance framework to enhance data security and privacy within HubSpot. Nullafi allows you to blur out or redact sensitive data, ensuring that only authorised users with explicit permissions can access or view it. By implementing such tools, you can safeguard sensitive information and mitigate the risk of data breaches or unauthorised access.

In conclusion, establishing a robust data governance framework within HubSpot is essential for effective data management.

By defining roles and responsibilities, creating policies and procedures, implementing REACT principles, and leveraging advanced data protection tools like Nullafi, you can ensure data integrity, security, and compliance while maximising the value of your data assets within HubSpot.

Step 5. Implementing effective data management practices in HubSpot

Implementing effective practices within HubSpot is crucial for maximising the utility of your CRM system. Let's explore five key strategies to streamline data management processes and drive success:

  1. Data capture and entry: Establishing clear guidelines and standards for data capture and entry ensures consistency and accuracy in your CRM system. Leverage automation tools such as web forms or integrations to streamline data input processes, reducing manual errors and improving efficiency.

  2. Data cleaning and deduplication: Regularly cleaning and validating CRM data is essential to maintain data quality. Utilise data cleansing tools or deduplication algorithms to identify and merge duplicate records, reducing redundancy and enhancing data accuracy.

  3. Data integration and centralisation: Integrating disparate data sources into a centralised CRM system is paramount for a unified view of customer information. Utilise APIs, connectors, or middleware platforms to automate data synchronisation, ensuring real-time access to relevant customer data across your organisation.

  4. Data security and compliance: Implement robust security measures to protect customer data within HubSpot. Utilise encryption, role-based access controls, and regular audits to mitigate the risk of data breaches. Stay abreast of data protection regulations and ensure compliance to maintain customer trust and confidentiality.

  5. Data analysis and insights: Leverage analytics and reporting tools within HubSpot to derive actionable insights from customer data. Utilise data visualisation techniques to uncover patterns, trends, and opportunities for personalised engagement. Regularly track key performance indicators (KPIs) to measure the effectiveness of CRM initiatives and optimise strategies for better outcomes.

By implementing these strategies, you can improve your data management practices in HubSpot so that you can maximise the value of your data and achieve optimal results for your business.

Step 6. Ensuring compliance and meeting governance demands

Regulatory compliance and the fulfilment of governance requirements are crucial. Let's delve into the specific compliance requirements relevant to HubSpot and explore strategies for achieving and maintaining compliance within the platform:

Data Privacy Compliance requirements on HubSpot:

  • GDPR (General Data Protection Regulation): As a global platform, HubSpot must adhere to GDPR regulations governing the collection, processing, and storage of personal data of individuals within the European Union. This includes obtaining explicit consent for data processing, providing transparency regarding data usage, and ensuring data security and privacy.

  • PDPA (Personal Data Protection Act): For businesses operating in Singapore or dealing with Singaporean data subjects, compliance with the PDPA is essential. HubSpot users must adhere to PDPA requirements, which include obtaining consent for data collection, ensuring data accuracy, and implementing security measures to protect personal data.

  • CCPA (California Consumer Privacy Act): Compliance with the California Consumer Privacy Act (CCPA) is essential for companies dealing with California consumers' data. This includes being transparent about data practices, ensuring consumers have control over their data, and ensuring data security and integrity.

Let’s delve into 5 strategies for achieving and maintaining compliance within HubSpot:

  • 1. Data governance framework: Establish a robust data governance framework within HubSpot to enforce compliance with regulatory requirements. Define roles and responsibilities for data handling, create policies and procedures for data management, and implement controls to ensure adherence to compliance standards.

  • 2. Data protection measures: Implement data protection measures within HubSpot to safeguard personal data and ensure compliance with regulations like the GDPR and PDPA. Utilise encryption, access controls, and audit trails to protect sensitive information and prevent unauthorised access or data breaches.

  • 3. Consent management: Implement comprehensive consent management processes within HubSpot to obtain explicit consent for data processing in compliance with regulations like the GDPR. Utilise features such as consent forms, opt-in checkboxes, and preference centres to provide transparency and empower individuals to control their data.

  • 4. Data retention policies: Define data retention policies within HubSpot to ensure compliance with regulatory requirements regarding the retention and disposal of personal data. Regularly review and purge outdated or unnecessary data to minimise compliance risks and maintain data accuracy.

  • 5. Regular audits and assessments: Conduct regular audits and assessments of data practices within HubSpot to identify compliance gaps and areas for improvement. Utilise compliance management tools and conduct internal audits to ensure ongoing adherence to regulatory requirements.

By implementing these strategies, businesses can achieve and maintain compliance within HubSpot, ensuring the protection of personal data and adherence to regulatory standards such as the GDPR and PDPA.

Migrating data to HubSpot: steps, tips, and common pitfalls

Moving data to a new CRM system like HubSpot is akin to relocating to a new home - it's a significant change that requires careful planning and execution. However, without a well-thought-out strategy, CRM migration can result in severe business disruption.

Let's explore the essential steps involved in migrating data to HubSpot, along with practical tips and common pitfalls to avoid along the way:

Understanding the risks of CRM data migration

Migrating data involves transferring information from one system to another, which entails changes in storage, databases, and software. Without proper processes in place, several risks can arise, including:

  • Data loss: Critical data may be lost or corrupted during migration, impacting sales, marketing, and customer relationships.

  • Non-compliance: Failure to adhere to data privacy regulations like GDPR or PDPA can result in regulatory penalties and reputational damage.

  • Dirty data: Inaccurate, incomplete, or inconsistent data may compromise the integrity of the CRM system, leading to data quality issues.

  • Semantic clashes: Differences in data categorisation and structure between systems can result in data inconsistencies and loss of critical information.

Essential steps for successful data migration to HubSpot:

  1. Write everything down: Document every stage of the data migration process to track errors, fixes, and updates, ensuring transparency and accountability.

  2. Involve key stakeholders: Engage key stakeholders from various departments to gather insights and set expectations and requirements for data migration.

  3. Map the data migration process: Identify and map out all data sources, fields, and technologies involved in the migration process to ensure a smooth transition.

  4. Prepare and clean data: Cleanse and prepare data before migration, ensuring data quality and uniqueness to prevent duplication.

  5. Validation and resting: Move data into a HubSpot sandbox environment for validation and rigorous testing to identify and resolve any migration issues.

  6. Live migration and resting: Migrate data into the live environment and perform usability testing to verify the successful migration of data.

  7. Post-migration support: Implement dashboards to monitor data quality and provide ongoing support to address any post-migration issues.

In the below video, our Head of Solution Architecture, Taryn Reyneke, talks about common pitfalls when migrating data to Hubspot data and how to avoid them. The clip is part of our webinar on Mitigating Information Security Risks.

You can watch the full webinar for free here

While migrating data to HubSpot independently is feasible, engaging a HubSpot solutions provider can offer several benefits. Experienced specialists can speed up the migration process, assist with implementation and provide post-migration support to ensure a seamless transition.

Work with Huble to optimise HubSpot data management

HubSpot data management isn't just a box to tick, it’s fundamental to business success - it's about setting clear goals, implementing robust processes and continually refining your approach to ensure your data remains an asset.

Our team is ready to guide you through the complexities of data management, from crafting a customised strategy to seamlessly migrating your data into HubSpot.

Contact our team today to realise the full potential of your HubSpot data.

 

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