5 ways you can use data analytics to improve business
Published 2 Dec, 2021 · 5-minute read
Each day, 300 billion emails are sent, 65 billion messages are sent on WhatsApp, and there are 5 billion searches on website search engines – 75% of which are on Google. Data is everywhere, and the amount of data has been doubling every 2 years for the last decade.*
Business information systems expert Dr Ida Asadi Someh from The University of Queensland suggests that as we continue to move towards a more globally connected economy affected heavily by digitalisation, the internet of things and AI, this trajectory will continue to accelerate.
So, what are organisations doing with all the data generated daily?
Ida believes we’re not doing much at all, or – in cases where we are using this data – we’re not doing so systemically.
But we should be.
Because data is knowledge, and knowledge is power.
“The benefit of organisations having access to relevant, valuable data is the ability to make better quality decisions that fuel processes and strategic actions,” says Ida.
Associate Professor Gabby Walters’s research focuses on the tourism industry. In recent years, she has studied the impact of crises like the global pandemic and the devastating Australian bushfires on the tourism and hospitality industries.
Ida and Gabby share their top tips for using data to better understand your business and your customers and to make better decisions that will ultimately improve business processes and outcomes.
5 tips for using data to drive your business
1. Create a data strategy to focus your efforts
Before getting started, consider what the purpose of your data collection and analysis is.
Data is everywhere. Understanding why you’re collecting data and what you hope to learn by analysing it will help you devise a strategy that makes it easier to focus on the data that’s important to you and your business.
Questions to consider include:
What is our vision for organisational data use? Why am I collecting data?
What services and products will benefit from the collection and use of this data?
How/where will I source the information I need?
Who will use the insights from the data collected? And how do we drive organisational adoption of data-driven insights?
How do we use data in acceptable, ethical ways?
How do we measure data’s strategic value?
For example, we know that Australians haven’t been able to travel overseas for 2 years due to the pandemic. Now that the international borders are finally opening up, Gabby was curious to understand how this would affect Australian travel behaviour.
Through her research, Gabby discovered that even though Australia’s international borders were opening up, only 51% of Australians planned to travel overseas. By analysing the data collected in this research, Gabby was able to see that the most risk-adverse populations are baby boomers, seniors, and female. A way these data insights can be used by Australian tourism and hospitality businesses is in marketing efforts, for example, by targeting female baby boomers with messages that tap into the relative safety of domestic travel and measures in place to give them peace of mind.
2. Collect a variety of structured, unstructured and multi-media data for a clear picture of your organisation and to better understand consumer trends
Companies are no longer able to succeed just by relying on internal, transactional data. To develop a complete picture, businesses need to know the pains and joys in the experiences of their customers and employees.
The best way to gain insight into business experiences is by gathering interactional and sensory data. Compared to transactional data, experience-oriented data can be found in unstructured text or audio data that captures perceptions, preferences and sentiments of customers.
For example, Amazon uses collaborative filtering to recommend items to users based on what people from a similar demographic have purchased. To ascertain your demographic, Amazon collects a variety of interactional, transactional and sensory data such as your clicks, what pages you access, the time you spend browsing, what you purchase, your location data, the time of day, and how you read e-books or watch TV and movies.
Amazon then uses this data to create a “360-degree view” of each individual customer. This view is then used to find other people who fit a similar demographic (such as “employed females aged between 18 and 45 with an income over $50,000 who enjoy cooking and action films”) and make recommendations based on what those similar users like.
As a business, you can collect data about:
transactions: including RFM scores, discount levels, and promotions
demographics: can influence customers’ baseline expectations
engagement: can be measured in a variety of ways, from usage patterns, loyalty programs, and email opt-in/opt-out, to social media
choice of service purchased: the variety of choices a customer makes can provide signals for cross-buying, packaging, and changing costs
satisfaction, trust, commitment, and loyalty: the channel a customer uses to interact can provide valuable information for ongoing, engaged relationships with a variety of customers (for instance, customers acquired through digital channels suggest greater loyalty due to self-selection).
3. Evaluate the quality of the data to make the best decisions
If you’re making business decisions based on data you haven’t collected yourself, it’s important to ask:
Who collected it?
How was it collected?
When was it collected?
Where was it collected?
How many responses were there? (Is it representative of the overall cohort?)
Why was it collected?
The answer to these questions will help you determine how current and accurate the information is and if it’s safe or wise to use it to inform important business decisions.
For example, if you have an Australian business, relying on data collected about American customer trends may or may not be relevant, so this should be used with caution when making decisions.
Likewise, it’s useful to understand whether the data you’re using to make decisions is representative of the overall cohort by seeing the total number of people included in the data set compared to the total segment or population, rather than percentages only, which can be misleading.
4. Understand legal requirements and commit to ethical best practice
Organisations need to be cautious that the way they collect and use customer information is lawful to avoid ending up in legal trouble. In practice, this can mean things like communicating to customers why and how their information is being used and providing the opportunity to unsubscribe from marketing materials.
The ethics of data, however, are more open to interpretation and therefore harder to achieve. For example, if people use Google and don’t get the specific, relevant, and local results they’re looking for, they’d stop using the platform. The only way for Google to provide those results is through collecting customer data such as their location. While the ethical analytics debate is evolving, it’s best practice for organisations to give customers the ability to self-manage the amount and types of data being collected.
5. Invest in analytics capabilities to unlock data value
To truly unlock the economic value of data and create value for customers and employees, organisations need a systematic approach to collect, store and analyse data. To do this effectively, organisations need to invest in new processes, technologies, and data analytics skill development.
While many organisations have a wealth of data, they need to grow their capabilities to effectively use data for value creation. This involves investing in an analytically driven workforce, analytics platforms, and scalable data infrastructure. As the amount of data being collected, analysed and stored continues to grow rapidly, analytics functions and roles are becoming more and more important.