Your Competitive Edge Is Within Your Data–Unseen Nuances and Opportunities
Digital marketing experts are starting to agree that the biggest way to gain an advantage over your competition is to apply strategies that are backed up by analytics. While some companies view the process of collecting and analysing consumer data with scepticism, in actuality, data insights enable you to obtain meaningful information on what your customers need and desire. This allows you to personalise a service or product design with a people-first mindset to improve customer experience and increase sales and customer retention.
How Do Customers Feel About This?
A 2014 Infosys survey of consumers from five countries, including Australia, found that 78% of consumers would be more likely to buy from a retail store again if the offers provided by the retailer matched their interests, needs or desires. Additionally, 86% of the same consumers said they would spend up to 25% more for an improved customer experience. Similarly, Accenture’s 2012 study of consumers from 24 countries revealed that the number of consumers who want companies to provide more relevant offers based on their data was almost double that of those who thought companies should stop tracking their online activity (64% to 36%).
Let’s discuss some of the ways behavioural analytics are being used in action at the moment to transform the business landscape.
Case Studies and Examples
In the healthcare industry, data algorithms are being used to review treatment decisions. Analysing the symptoms of thousands of patients’ clinical data through the aggregation of individual data sets has enabled healthcare providers to accurately identify rare conditions in subpopulations. Previously, this knowledge has been available only through expensive and lengthy clinical research trials of small samples. Thanks to data intelligence, healthcare providers can now react faster and provide better provision of medical services.
Retail goods that feature smart technology are on the rise, including sensors, iBeacons (Apple technology that allows mobile apps to pick up signals from beacons in the physical world and react to them), or wearable devices that transmit data about usage and consumer behaviour back to the retailer and the manufacturer. Cars with computers inside, for example, are now able to transmit data about their operation, location, environment, and performance. This is useful as it allows the manufacturer to maintain an open, continuous relationship with the end user of the product.
Recently, Malaysia Airports Holdings Berhad (MAHB) used social media data relationships to improve their airport experience. MAHB has 80 million passengers visit its airports annually. Tracking feedback, complaints, and suggestions was a challenge so they hired data scientists. Using data obtained from over 45,000 social media real-time updates, MAHB passengers’ perceptions were analysed using relevant keywords. Sentiment analysis and opinion mining was performed on these keywords by machines using learning algorithms that could detect and understand multiple languages. The data led to the creation of a Customer Affairs and Resolution Excellence Team who acted upon the insights of the social media data analysis. Since this time, MAHB has seen a 1,000% increase in the positive sentiments expressed about its airports on social media.
Methods of Interpreting Data
There are different types of data that can be mined to provide insight including:
- Data from site usage
- Real-time location data
- Social media log-ins and posts
- Search history
- Customer demographic data
- Open public data
Some firms even offer discounts to customers who voluntarily provide access to biometric data. However, data collection alone is useless. Without proper interpretation of the data to “connect the dots” of what it all means, it is hard to implement business strategies that improve sales, ROI, or customer experience.
Large, multinational firms often hire data scientists to conduct this analysis for them. However, this is not realistic financially for all businesses, nor is it putting the decision-making in the hands of the key business users. Another solution is to use an intelligent tool such as Latize Ulysses, which helps everyday business owners translate the data gathered into easy to understand related connections and insights that can indicate what steps or business decisions you need to take next.
The Next Generation of Data Analysis and Interpretation
It can be costly, especially for smaller businesses, to go the traditional route of hiring data scientists to translate their data into usable information that can be applied to improve their business outlook. As such, tools like Ulysses are now seen not just as alternatives but also as the primary choice for many companies since they offer the ability to organise your data in an intuitive way according to scientific formulas like:
Fuzzy matching – When consumers search for jobs, cruises, cars, houses, shoes or other goods fuzzy matching can locate results that are similar but not identical (e.g. dark grey carpet instead of black carpet, a hotel on a Caribbean Island close to the island requested). This fuzzy matching can then be used to show consumers other options they might also like.
Counter-dynamic pricing – Consumers are always on the lookout for bargains and last-minute deals. This can often benefit the retailer as well. For example, if hotels have lots of vacant rooms it may be useful to reduce the price to improve occupancy rates. Counter-dynamic pricing can help provide insights based on personal analytics to help determine the best moment to offer a consumer the lowest price.
Fraud detection – Data tracking can also be used by the financial industry to detect fraud or, more accurately, determine the credit risk for big loans. Tools such as Latize Ulysses can infer relationships from data relating to fraud rings, the social media activity of customers, and detect patterns which may indicate risk.
Dynamic forecasting – Dynamic forecasting shows the role external circumstances play in customer behaviour and purchasing patterns. Factors such as traffic, weather conditions or in-store video can be analysed to find correlations that could predict consumer actions.
The future of digital marketing lies in the intersection of technology, customer engagement, and data intelligence. Statistics from consumer research have revealed that a majority of consumers would find value and increase purchases if presented with more targeted advertising or improved digital experiences. Both can be achieved through gathering and applying the intelligence and insights available from scientifically-validated data relationships.
Many Asia-Pacific companies, such as MAHB, have already started using these insights to gain a competitive edge over their competition and have achieved tangible, positive results within a short time frame. One of the huge advantages of proper data interpretation is that it allows for frequent and rapid improvements and more open relationships with end users.
Want to know more about finding useful hidden insights within your data? Find out who we are and learn more about the products we offer.
