SIR FRANCIS Bacon’s famous saying, “knowledge is power,” still rings true today, and is especially relevant for businesses investing in data analysis.
Traditionally, businesses have used historical sales data to make financial forecasts. With the growth of data available in recent years, businesses now have access to a wide range of customer insights that is a valuable source of business intelligence.
Indeed, Gartner claims 75% of organisations are currently investing in big data analytics, and in the past six months, big data analytics has become one of the top three IT priorities for businesses. But how does a business mine the enormous volume of business intelligence to find the data that can help its business?
This requires a combination of business acumen, analytical creativity and technical expertise. By developing the right processes and culture, businesses can identify where the real value lies within its data.
The good news is that companies do not immediately need to hire teams of data analysts. Most companies will grow into their needs for big data workers. Better news is that most e-commerce companies already have in place employees who are suited to a transition to data mining and analysis. Application developers, database administrators and IT managers all possess the mathematical, statistical, and computer science skills upon which big data knowledge can be built.
To ensure data mining projects are successful, organisations need to assess their existing infrastructure and understand that the way in which data is stored can directly affect the company’s ability to extract meaning. Businesses should also ensure its employees realise the value of managing and using its data.
Cost cutting efficiently
Organisations produce business intelligence data every day, but how many of them convert this data into knowledge they can use effectively?
Payment data is a valuable source of business intelligence. Analysing payment data can help to forecast how customers will behave, which may help businesses to mitigate risks ahead of time.
The regular analysis of payments data can highlight payment issues and reveal valuable business performance insights. For example, authorisation analysis, as just one source of payments data, can provide insight on:
1. Type of cards most used
If one card is a clear leader for one’s business, it could for businesses to create a campaign targeting those card holders.
2. Geo business
Knowing where business comes from means a business may target by location and consider additional currencies.
3. Average spend by card type
When one card type generates higher sales, businesses could customise mailings to cater to different spend levels.
Increasing revenue – what are the tangible results?
Technology is now supporting data-driven businesses in real-time. According to Monetate, companies that invest in analytics see a 49% increase in revenue growth, while our own research has shown that companies that increased profits in 2012 used data to help shape their future multi-channel sales strategy including identifying any payment challenge.
A recent Forrester whitepaper also found big data is now “enterprise-ready” which means it is cheaper to store and process this data, while according to IBM approximately 63 per cent of companies said the use of information and analytics is creating competitive advantage for their organisations.
In order to create and maintain a competitive advantage it may be a wise choice for businesses to invest in the strategic use of its own data.
Shane Fitzpatrick is the President and Managing Director of Chase Paymentech Europe Limited