Customer churn is a major health metric listed companies tend to share in their annual and other reports with good reason. It’s often a lot cheaper to retain a customer than it is to get a new one. Smaller businesses can also benefit by reducing churn, which is the result of dissatisfaction from any of a number of sources, says Gerrit Olivier, CEO of About IT.

Churn is a bigger problem today than ever before because customers in the digital era expect companies to be smarter about the way they work with them, interact with them, and deliver their service. Advanced analytics helps companies understand what it is that customers want, what they use, where their pain points are, and ultimately provides a radar to beat churn. Advanced analytics used to be the domain of large enterprises with big IT budgets, big business systems, and big administration teams to the run the entire shebang. But that’s no longer the case.

Affordable financial systems for medium and even small businesses today will, for example, provide alerts when a customer passes the 30-days payment period and can trigger an automated e-mail. That type of e-mail can annoy customers to the point where they stop dealing with you.

The customer may pay on 45 days as regularly as Old Faithful erupts – and have done so for years. But a new automated system doesn’t factor in their history. Threatening e-mails or worse, a credit listing, can utterly ruin a relationship.

Modern analytics systems, which are within reach of medium and smaller businesses, will let you know not only that a customer is past the 30-day period but also that they routinely pay on 45 days. There’s no need to annoy them and there’s no need to spend time and money having someone police them. It’s a small thing but it demonstrates that a business understands their customer – without tying up their people to do so and you don’t lose that valuable insight if an employee leaves to work elsewhere or takes a sick day.

These insights are also presented visually – with the ability to drill into the nuts and bolts of the information – so you can make quicker, more accurate decisions. You can even access it from your smartphone these days.

Predictive analytics, machine learning

It’s the kind of system that a big business could have done right a few years ago because they had the techies to fuss around the IT systems. But you don’t need that anymore because the features come part and parcel of the smart new systems. It’s based on machine learning that includes predictive analytics and there’s not even any need to mess around with formulas if your data sources change or the data sets shrink or grow.

Machine learning is streaming into the field and, to a far lesser extent, artificial intelligence (AI). Machine learning is having a huge impact in a number of fields from finance to medical, accounting to engineering, manufacturing and others. Machine learning is essentially creating an algorithm that watches the way people and processes operate then being able to automatically repeat them without human intervention – but with some intelligence so you don’t end up with the 30-days and 45-days scenario I mentioned above.

The impact in the accounting field is so big, in fact, that even here in South Africa the South African Association of Chartered Accountants (SAICA), together with the Independent Regulatory Board for Auditors (IRBA), has initiated a project called CA2025. The project is investigating the competencies that CAs and RAs will need in future and could have a marked impact on the syllabus taught at university. In essence, that means they’re determining what the computers will be able to take over from the CAs and do automatically.

When computers can do that kind of job quickly, accurately, and taking your customers into account then it adds up to some serious competitive advantage. It hasn’t seen widespread adoption in the lower strata of business sizes yet, which means that today it’s a huge competitive advantage but as it becomes more entrenched it will become more of a must have. It also underlines the growing importance of data analysts as valuable company assets.

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