Guest Column | October 24, 2022

Why Do You Need An Effective Data Strategy?

By Zoe Fenwick


Many will have heard talk of taking a data driven approach to Sales and Marketing and having a Data Strategy but what exactly does it mean? Well quite simply it is about using data to help inform your decision making, strategy and tactics, particularly in terms of sales and marketing planning and activity. Many companies will already be in possession of a host of data, possibly without even realising it and may not be leveraging the most return from this asset.

Whatever size company you are working for, having a robust data strategy that helps you to mine your data effectively and develop insights that can help create competitive advantage and identify opportunities for growth and innovation.  Other benefits that could be realised include

  • Operational efficiency
  • Process optimization
  • Faster decision-making
  • Increased revenue streams
  • Improved customer satisfaction

Where do you start?

Like other strategic frameworks used across organisations, developing your data strategy should begin at board level, waterfalling down from the over-arching business strategy developed by your senior leaders. Start by defining your data mission and objectives. These should reflect and align with your corporate vision, mission and objectives.  As with any strategy, setting key performance indicators (KPI) to help measure the success is imperative, and these KPIs should adhere to the principles of SMART, specific, measurable, achievable, relevant, and time-bound.

Conducting a data audit can help establish your company’s position in relation to data maturity - the level at which a company makes the most out of their data - and data literacy - the ability to read, analyze and derive meaningful information and insights from data. 

Data can be captured from a variety of sources, including internal data, such as employee or basic customer data - company size, industry sector and geographic location - to less obvious types such as financial data including customer purchasing history and profitability. External sources of data such as industry market research and competitor intelligence can help further understanding of what factors are affecting markets and any key trends. This is where robust business intelligence comes to the fore.

Once you have established what data you have, think about what data you actually need, including the volume and type of data, identify any potential gaps and how you might bridge those, and how to ensure a balance of quantitative and qualitative data. Your sales team can also be a valuable source of qualitative data – how healthy are customer relationships, what are the common challenges or pain points, consistent topics of conversations and what is actually happening in the marketplace. You might also consider conducting primary research with your key customers through focus groups or surveys to really develop your knowledge and understanding of their perspective.

If you have data that is not being leveraged, think about whether it needs to be collected. If it is of no use, then why bother? It can add unnecessary complexity, risk, and costs when it comes to managing and storing data.

Data Policy, Standards & Governance

This is a key component of your data strategy. What policies and processes already exist to help protect privacy and ensure ethical use of data. Are there any industry regulations or legislation that needs to be adhered to?

One of the most well know pieces of data legislation of recent years is GDPR. Its introduction in 2018 initially caused alarm for many companies and their marketing teams, spooked by the prospect of huge fines if found in breach of regulations for not obtaining proper consent from customers concerning the collection and use of their personal data. Some even went so far as to delete their existing customer databases and start again from scratch. Whilst this may seem somewhat extreme, simple actions such as having clear procedures for unsubscribing and deleting customer data when requested and adopting best practices such as a double opt-in subscription process can help mitigate falling foul of the regulations. The ability to demonstrate an audit trail can often help regulators understand how your processes work and if/how any improvements can be made to help prevent future compliance issues.

Having clear policies that are accessible and relevant to everyone in the organisation is key. This helps them to understand the need for data privacy and protection, as well as the ethical use of any data, the consequences of not following policy, for example, potential data breaches and GDPR related fines, and how they can help ensure due process is followed. It should outline their responsibilities and correct procedures and practical guidance on storing, retaining, and purging data, as well as who owns the data policies and where to seek help and advice if they are unclear or unsure of due process. 

Data security is another key component and goes hand in hand with your data standards, policy, and governance. Consider how your data is being stored – is it in the cloud or on physical servers? Is it backed up and how often? How robust are your IT systems and cybersecurity policies, as well as those of any vendors to help prevent breaches or loss of data? Ensuring your systems and platforms have the appropriate cybersecurity measures in place and demonstrating due diligence will help mitigate any risks. Determine who has access to the data and to how much, and how that data is shared securely across the organisation. For example, some roles may need only basic customer data whilst others may need access to more potentially sensitive data such as financial data.

Consider the lifecycle of your data. How often is data cleansed and checked for quality and accuracy? Having inaccurate or outdated data will be of no use in decision making and simply undermines your efforts to develop an effective data strategy. Good quality, clean and accurate data is paramount if you are using it to help guide decision making. You need to ensure there are internal processes to help maintain data cleanliness and accuracy – this may be the responsibility of one particular team member or department, or can even be periodically outsourced to an external supplier. You will also need to define a time period for storing it and how the data will be purged or deleted once no longer needed.

Technology, Skills, and Capabilities

Naturally a data strategy requires appropriate technology platforms to help capture and store data. Some of this architecture and IT infrastructure may already be in place and its strengths and weaknesses assessed as part of your data audit. For example, how has your CRM been set up to capture customer data, and is it capturing the right data? How does it integrate with other systems such as Finance to help assess customer and product profitability? When assessing any technology platform, automation and integration with other technology platforms will be key to helping ensure data across the organisation is clean and consistent, helping to save on costs and resources by mitigating the need to manually input and update information wherever possible.

You will also need to ensure your people have the appropriate skills and knowledge to help examine and analyse the data, turning information into actionable insights. Define what training and learning support needs to be in place to support digital transformation and improve data literacy within your organisation as it advances towards attaining data maturity. You may also need to hire more expertise and even decide to leverage machine learning and AI to help with data mining and analysis. Here too there is a need to ensure the data is being used ethically and isn’t discriminating against any groups or individuals who may fall into the special characteristics categories defined under GDPR and other data protection legislations.  

Leadership Support and Buy In

Support from your leadership team is crucial to help ensure successful change management, communicating the need for change to the wider organization and implementation of processes or procedures, as well the necessary investment in and deployment of any new technology platforms to help you effectively manage and leverage company data.  Their support will also be critical to drive changes in organisation attitude and culture regarding data usage and management, particularly where existing policies and procedures may require amending or new ones need to be introduced, and as the functions develop as the organisation grows in terms of data literacy and data maturity.

In conclusion there are many factors to consider when mapping out your data strategy and bringing it to life. But the benefits from doing so are many, and can really help to drive organisational efficiency, accelerate growth, and create competitive advantage by developing a better understanding of markets and operating environments and - most crucially - by building a deeper understanding of customers wants, needs, and challenges. Your data strategy will require ongoing review and periodical auditing to help ensure it remains relevant and compliant, and that it continues to meet organisational needs and aids effective decision making.

About the Author

Zoe Fenwick has accumulated over 20 years of experience in B2B Marketing, working for a number of leading brands including Oxford Biomedica, IQVIA and Mitel. She is passionate about leveraging best practices, frameworks, and technology to ensure a customer centric approach to strategic marketing. Zoe has consistently implemented a data driven approach to marketing, utilising customer journey insights and personas to create targeted marketing campaigns that deliver the right message, to the right person, at the right time, through the right channel, optimising campaign success and delivering quantifiable return on investment.