Bad customer data can be likened to a bad social media gaffe where a brand gets something wrong and all hell breaks loose. The immediacy is felt and negative brand equity is generated. But typical to Twitter, it is instantaneous—and in most cases, the outrage is short-lived. Often, it’s because a business isn’t quite aware of what audiences it is catering to and what they may or may not be interested in hearing.
Social media gaffes could be considered as a cause of bad customer data. The unknown of who exactly you are talking to and what messaging could fall flat. Outside of social media, unreliable or bad customer data can still generate negative reactions. Say you are sending “personalized” emails, but have the wrong first name? Or you send a birthday offer on the wrong day? Although in these cases, the mistakes may seem relatively minor or subtle, in the end, it could end up generating a lot of negative or ambivalent emotions towards your company and its offerings.
Business folks and marketers are familiar with some of the signs. For emails, we see low email open rates, bounced email addresses, poor click-through rates. From a sales outreach perspective, you may see poor lead quality or fewer leads making it through the funnel. From a web perspective, you may see poor user flows, low site engagement metrics. Customer service might be flooded with calls asking why am I seeing this messaging or even calling to cancel services or subscriptions.
The reason usually is that the wrong people are being targeted, or the message got mixed up along the way. That is the pretty straightforward part. What isn’t straightforward is the long-term effects of targeting the wrong people or targeting the right people with the wrong information.
Leveraging unreliable customer data can build bad brand equity over time as your customers can increasingly be on the receiving end of annoying and irrelevant messaging. What good is it to send a set of customers promotional messaging for an event or item that is not available in their area? Or to a set of customers that previously had shown no interest or proclivity to purchase a particular item?
You waste your money and more importantly, the customer/prospect’s time. Time is a premium, so your target needs to be correct the first time. Otherwise you run the risk of generating negative emotions towards your business and even losing customers. Worse yet, those with negative emotions will spread those bad feelings on, as they complain to friends and family members. Bad feelings travel fast and far, and it’s very challenging to overcome a negative impression.
There never is a quick fix but the first step is being proactive with your customer data so you can avoid a lot of negative feelings and customer displeasure. If you have a database of customers, there is often uncertainty about the trustworthiness and accuracy of your data. Taking steps to first profile your data will help you to discover data issues that you currently may not even know you have. There needs to be a starting point before you can clean and match similar records in your data. Profiling your data and identifying issues upfront is the beginning of a build up to reliable and accurate customer data. If you can trust your data and make smart and actionable decisions, your customers will begin to trust that you know them and have taken the time to consider what is in their best interests.
Trust your data by discovering what is wrong so that as time goes on your customers will trust and appreciate all that your business has to offer.