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Identify Data Opportunities using Public Customer Reviews

Bad reviews tell us where we might have data issues

Lots of Data teams I speak with struggle to get engagement from their business. Often this is because they don’t explain how data drives business value. Their main challenge is typically knowing how to identify data opportunities that a business person cares about. The reason I have written this article is because it’s possible to identify data opportunities inside your business using information in the public domain. Read on to find out how we do it.

Identify Data Opportunities

Firstly, we’ll make the assumption that Customer Data is likely to provide us the greatest value. Without customers we don’t have a business. As a result we need to govern their data well and cherish the valuable insight it provides us.

There are also plenty of studies that show the huge benefit in the bottom line that a company receives from delivering Customer Experience excellence:

It’s not that hard to see how numbers like this will make even the most resistant Exec stand up and take notice.

Secondly we will establish that Customer Journeys are a complex web of interactions. These Customer Journeys are your Business Process for recruiting and retaining Customers. A typical customer journey (at a high level) looks like the sequence below:

Patient journey map
Each team both produces and consumes data on the same customer. In the case of a patient, that data quality could be the difference between Life and Death.
  • First up, your customers have to discover your products and services (Awareness)
  • After that they must understand what you’re offering and decide they want to buy it (Consideration/Purchase)
  • Once you’ve navigated those hurdles you must onboard that Customer. Typically your sales team hands over to a delivery or fulfilment team at this point (Purchase/Retention)
  • Finally your Finance team needs to send out invoices and collect payment from the customer (Retention)
  • If you’ve done a fantastic job, you might move into the hallowed ground of Advocacy, where the customer promotes your products and services and recruits more customers (bringing down your customer acquisition costs).

Let’s Talk Silos

Lastly we must recognise that the Customer Journey crosses multiple business silos. As a result it creates opportunity for Bad Data to wreak havoc. Whenever different teams have different data about the same customer, you run the risk of wrecking the customer experience.

Oddly enough, 78% seems to be the Magic Number. In Salesforce’s “State of the Connected Customer report” they identified:

  • 78% of Customers Expect to solve complex issues by talking to just one person (that person better have some good data!)
  • 78% of Customers prefer different channels depending on what they’re doing (all of your teams need to speak with the same voice)
  • 78% of Customers expect consistent interactions across departments (again, your teams all need to speak with the same voice)
No Customer deserves to be nameless in this day and age. At least address the person not the Entity.

If you have any business process that relies upon different teams using the same information you have a Data Governance requirement.

Where is the Opportunity?

In order to put a price on our Bad Data we need to understand where and how it causes problems in this Customer journey. In the Business Process described above there are plenty of touch points between different silos/teams where Data is being provided, created or shared in order to deliver the Customer Experience. Before we look at a specific example, let’s cover off the basic areas where bad data could cause a problem:


Bad Data about customers causes us to waste money targeting the wrong people, to present the wrong information at the wrong time, and to miss opportunities to cross or up-sell.


Bad Customer data stops sales people from selling. They might be using contact details that are no longer valid. Bad Product Data means the Sales team does not understand their own offering. Bad Customer experiences usually end up in complaints to the person who made the sale, wasting time and causing missed opportunity.


When you have Bad Data flowing out of the Sales Team you are setting your fulfilment team up to fail. This could be wasted cost from sending product to the wrong place. It could be sending the wrong product or amount of product to the customer.


You put in all the work to win the Customer, so now it’s time to get paid. The only hiccup here is that your Finance team has the wrong address to send the invoice to. Worse, the phone number they have doesn’t work. Bummer! Now you’ve delivered your Products for free and have to write off the debt. You also wasted time and money chasing a customer that didn’t exist.

Human Resources.

Dealing with the inefficiency of bad data is a major drain on employee motivation. Imagine turning up to work every day and knowing you were going to get yet another customer complaint. You know you’ll be handling the complaint but you also won’t ever fix the issue – because management never wants to hear about it. So you have staff that know the complaint is entirely preventable if your company got its act together with their data. Think of the poor teams in each department I’ve listed here and realise how miserable bad data is making their daily life. As a result, companies with Bad Data have higher hiring costs and higher costs to train and retain their staff.


The biggest (and hardest to quantify) cost is in your Goodwill. Customers demand good service these days. They vote with their feet.

Get your customer expectations mapped out

So where do the Customer Reviews come in and how do we Identify Data Opportunities?

If you want to understand your customers you have to listen to them. Most companies think they do this well. In my experience, most companies are appalling at hearing what their Customer’s Voice is really saying. Complaints get handled by junior staff with no power to make changes, and no desire to escalate a problem up to management because the complaints never get acted upon. If you think this is unfair, consider some stats from John Goodman:

  • Only 1-5% of customers will escalate their complaint to a local manager or corporate HQ
  • As little as one out of 500 will actually be addressed to a senior executive

Goodman flags this as “the tip of the iceberg phenomenon” where:

  • 50% of your customers encounter a problem but do not complain. They just leave – this is the bit that sinks the Titanic
  • 45% of your customers complain to an agent or a front line rep, but
  • Only 1-5% of them escalate to Management or HQ. As a result your leadership are often Blind to the issues that exist in their business.
  • Like the Captain of the Titanic, management can only see the problem when it’s already too late to do anything about it.

Customer Reviews to the Rescue

Fortunately for us, the internet has made it remarkably easy for your customers to share negative reviews online about your business. There are a ton of sites where these reviews might exist, and I can guarantee that your management won’t be reading any of them (or worse, they’ll be deleting them to avoid the PR). Facebook company pages are usually a pretty good place to start, Trustpilot is useful, or you could just go to more local forums or subreddits if you’re looking for a niche complaint.

Within these customer reviews you will see a wealth of information that can be used to identify Data Opportunities. The complaints linked to service disruption and invoicing issues are often the easiest to focus on. John Goodman’s team found that people tend to complain more when it’s a financial impact and less when it’s just inconvenience, so start looking there:

  • Problems which result in out of pocket monetary loss have high complaint rates (e.g., 50-75%), while;
  • Mistreatment, quality, and incompetence problems evoke only 5-30% complaint rates to the front line.

How To Use The Poor Customer Review to Identify Data Opportunities – A Primer

As we will show in our next post, you can take these negative reviews and break them down to uncover the Root Cause of the bad service or misaligned expectation. In the vast majority of cases I’ve seen, the employees were doing their level best to deliver to the customer. They’re just doing their job with the tools your company has provided. When those tools include dirty, disorganised, untimely information you cannot blame the employee for “dropping the ball” and annoying your customer.

The Review I’ll be breaking down was one for a Telco Customer. The Telco provided a disjointed experience to their customer. Rather than seamlessly traversing between marketing info, sales conversion and customer onboarding/support, the telco treated the customer as though they did not know him.

The GIF below shows a simplified view of the Information Value Chain for this customer. The arrows represent where Information and Data is presented to or captured from the Customer. When Bad Data is fed in to any part of this Value Chain it corrupts the process, causes errors to be made, and incurs cost in re-work, replacement or eroded customer trust.

As information flows from Customer to the Company, it gets out of sync. This leads to frustration for the customer and cost for the Company.

What next?

In the next post I will pull apart a real-world example of a poor customer experience, highlighting where bad data led to the customer complaint. The costs that are known, estimated and unknowable as a result of this bad customer experience will be calculated. We will then project what cost the company is actually facing due to their shoddy data. The aim here will be to use publicly available information wherever possible. If you work inside an organisation and use the same approach you can get more accurate figures from your Finance team. You could use this information to bolster your own Data Governance Business Case.

If any of the points raised in this article are of interest, feel free to get in touch using the form below.

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