Posted By Will Archer on 22nd November, 2018

Digging deep: Why improving your business starts at the root (cause)

 

Author: William Archer & Mark Bailey

 

The old truism that prevention is better than the cure applies just as much to business as it does to medicine. Understanding the reasons for a customer’s complaint is really useful but once the complaint is made, potentially unnecessary effort is required to undo the damage that has been done. The best outcome for everyone would be if the problem that led to the complaint didn’t exist at all.

 

The obvious solution is to use those complaints that are made to make sure the underlying issue is identified, acted upon and resolved so that it doesn’t occur again. This is easier said than done. This is because understanding complaints to a level to determine the “what do we do?” is very different than understanding the “what happened?”.

 

The Data Science team at Resolver see the understanding of complaints to this level as the key to unlocking the puzzle of business improvement. It is not enough to have a platform that handles customer complaints efficiently and effectively. We are working with organisations to leverage the data from over 3 million cases across multiple market sectors to make improvements, get better outcomes, improve retention, and ultimately, grow revenue.

 

A cornerstone of driving these improvements is by undertaking Root Cause Analysis (RCA), to identify underlying problems and understanding where a fix is required. This is at the heart of what we do at Revolver and we have been working with our Data Science team and external partners to develop the right services, so our clients can discover what's really going on behind their complaint data and to make this insight actionable.

 

“The core idea is that complaints provide a unique set of data because they are independent of any other business metric that a company uses and customers who complain don’t have any incentive to skew that data,” explains Christaan Swart, a data scientist at Resolver.

 

Bubbling to the surface

 

One powerful way Christiaan and his colleagues are using this data is by comparing the complaints received from several companies in the same sector, looking at the content of those complaints and at which points they occur in the customer relationship. This is done by analysing data to auto-classify complaints and compare with the impact of these complaints and using that information to track how good a company’s interventions are. This information is then combined with a data visualisation tool to identify where a company is able to make improvements.

 

In the example below, we can see how often specific issues arise with a bank. The bigger the bubble, the more often the issue arises; the lighter the colour, the more connections it has to other problems.  We can see in the chart, for example, that bank charges are a recurring issue and are strongly linked to financial hardship and difficulty.

 

 

We can also see how these issues are interconnected. For example, complaints about charges might be related to specific local branches or credit card issues. This information can be used to drill down and see if there are structural issues in an organisation so a solution can be found. These insights can then be viewd across a market sector. Once changes are made to drive improvements, the impact of these changes is measured to see how the complaint profile evolves over time and the level of success these changes bring.

 

“We aim to benchmark different companies and identify the segments of their operation, where they are losing money, where they are losing the retention, how that correlates with customer satisfaction and how that relates to churn and the user journey,” adds Christaan.


 

In the chart above we see issue categorisation for a specific telecoms company and how this compares to its industry peers (left) and its own year-on-year performance (right). There has been a marked improvement in the network coverage complaints, which aligns with a technical upgrade in infrastructure, so, whilst still greater than the industry average, performance has improved by over 28%. However this exercise is also about finding the hot spots – where complaint rate of change is highest - and this allows us to provide early warning and to focus on root causes. For the example above, the process around plan changes and cancelling accounts is significantly (27%) higher than the market place and has also increased by 10% over last year.

 

 

We also know how the telecom company performs at the different stages of the customer lifecycle journey.  We observe consistent trends relating to sales and handset issues decreasing during the customer’s contract.  We also see other issues that can have more dire consequences for the company’s bottom line. For this organisation, 40% of customer issues relate to billing and changing plans at the point that they are about to renew or switch supplier, taking their business elsewhere.

 

These examples demonstrate that by putting the data into context, benchmarking against industry peers and driving actionable insight from what we know, companies can drill down to the root causes of issues that are impacting their customers, their organisation and their profits.

 

Complaints are a genuine source of customer feedback and by looking deeper at the complaints you have today, we can work to remove the causes, retain customers and improve efficiency.

 

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