Customer Satisfaction, Data & the Post-Pandemic Recovery

digital transformation course with tom goodwin

Customer satisfaction, data & the post-pandemic recovery   1

In order to create winning customer experiences, brands must have a complete understanding of the customers they love, and those they’d love to have.

This has always been at the heart of what data-driven marketing strategies aim to achieve – relevant campaigns built on a complete view of the customer through the unification of data across business silos.

As we emerge from the COVID-19 pandemic, many businesses are still relatively new to having such a large amount of digital data to process, let alone getting insights from it.  Which is further compounded as their in-person interactions with customers have been replaced, in many instances, with digital services.

For the first time, some businesses created digital shop fronts and many experimented with social media as a way to find new connections with customers. Others have lost their typical customers but gained new ones as their business models shifted.

Ultimately, there is a great opportunity for marketers to use data to fuel their post-pandemic recovery – but the question is, where do they start?

Unify data on to a single platform

For most organisations, starting to work with large amounts of data – or “Big Data” – means implementing platforms that can house the increasingly large quantities of data being generated.

The challenge has always been the ability to connect different data sources and turn them into actionable insights and value. Traditionally, data has been siloed across an organisation based on the type of data and which system or platform collects it, whether it’s consumer data or transactional data or digital data.

Data held and managed on a single platform provides obvious benefits – a centralised data repository that contains all the information you’ll need to make informed business decisions and provide insights to inform your long-term roadmap and growth strategies.

In a digital world, data is the language of people, and it’s ultimately how brands understand their customers.  And because data represents people, it must be respected and protected and used in a balanced and ethical way. It must also be used to inform better customer experiences, which ultimately drives ROI for brands.

Understand the value of data

Given the subjective nature of data analysis, it is important to have checks and balances in place around data volume and quality. Businesses should establish specific use cases and identify when data is useful information, i.e. necessary to have, or superfluous.

When assessing data’s usefulness to a business there are a few check-boxes to tick. Firstly, if you are lacking metadata (this is the data that describes your data) then your results may not be actionable and data usage unlawful.

For instance, if you do not know the frequency of collection, the accuracy, the recency or the “completeness” of the data set then you will struggle to assess its value for your brand and activate it in an automated fashion of moment marketing; or if you process using consented data then records of consent are a GDPR requirement.

Secondly, there needs to be clear usage requirements – particularly when it comes to privacy and if personal details need to be pseudonymised. A lack of metrics that describe the status of data over time can become an issue. If usage requirements and data attributes don’t match, then data is either not actionable or at the very best unpredictable.

Finally, brands clearly must adhere to regulations around the use of data and be privacy compliant, but not be dissuaded from creating the most relevant and memorable customer experience.

Adhere to ethical and regulatory guidelines

There are three key pillars to data management best practice:

  1. Data governance
  2. Metadata management
  3. Data quality management

Effective data governance cannot be undervalued. Being data-led means operating under standards, codes and ethics that ensure the rights of people are protected and regulations are adhered to. Businesses must be transparent, and socially and ethically responsible.

Another crucial aspect of best practice – as mentioned earlier – is the management of metadata. The data that is leveraged for business decision-making, needs to be scalable, accurate and unified, and accessible, compliant, and integrated across the organisation’s ecosystem. It must also always be kept secure and used ethically. This cannot be done if the metadata is not maintained and managed.

Finally, ensuring data quality management. For a business to be data-led in its decision making the data it uses needs to be not only legally compliant and ethically sourced but also relevant, up to date and accurate. Data changes quickly. Why? Because people’s lives are always changing, and a business’s operations change at the same pace. Managing the complexity of this change and the fragmented interactions with a customer is essential.

A data driven culture

Creating a data-driven culture means everyone in the organisation who handles customer data is committed to creating that trusted single view of high-quality data, understanding which data is valuable and which isn’t, growing the ability to execute business decisions based solely on data and staying in line with ethical and regulatory guidelines.

It is a complex world and working with trusted partners that can guide you throughout the process is key.  The best partners can teach you how to create ownership internally while ensuring best practices get put into action.