The main reason some businesses aren’t successful is because they choose to do business with customers that actually cost them money. Consistent late payers or non-payers cost businesses money and take time away from attending to more profitable customers.
In the past, it often took a process of trial and error to understand which customers would be profitable and which would be a drain on the company. Now, businesses can use analytics to ensure business success.
There is a huge amount of data that businesses can collect. This includes data on customer payment and collection histories, customer behaviour and drivers, product and service preferences and reviews, and even social media interactions. Aggregating and analysing all this data can deliver insights about customers that can then drive smarter business decisions.
Doing this effectively can safeguard the company against late payments or the need for debt recovery. It can help businesses decide which customers to focus resources on versus which ones to stop doing business with.
However, a key challenge for businesses has been how to combine customer data, which is often fragmented across departments.
This makes it harder to effectively leverage the insights that can be gained from Big Data; if information can’t be combined easily into a single portfolio, then it can’t be analysed as a whole, so any insights derived from it are incomplete.
Addressing this challenge requires a specialised approach that leverages technology to give companies a clear view of where they’re trading and in what volumes, as well as outlining the organisation’s potential exposures and risks.
When businesses have a visual representation of where risk concentration lies and can see areas of higher risk against the portfolio of buyers, they can make smarter decisions, faster.
If you’re trading on credit terms then the tool used should be able to provide an instant decision regarding limits for specific buyers based on their risk profile, so leaders can immediately decide whether to do business with the customer and, if so, how far to extend their credit terms.
Collated and analysed effectively, Big Data delivers visibility across an entire business, so you can easily seek out answers to questions, which then inform business decisions.
You can compare your book from year to year to identify buyers who have improved or deteriorated, which reduces the time and operational cost involved in working with less profitable customers.
This removes the guesswork involved in deciding which businesses to trade with. You can identify opportunities and potential pitfalls and decide how much risk is acceptable.
This insight into payment behaviour lets business leaders plan for the future, protect against unnecessary risks, and make data-driven decisions that lead to growth.
