Melissa AU Team | Australia, Data Quality | bad marketing data, customer acquisition, data driven marketing, data quality, marketing campaigns

Data is undoubtedly the backbone of any organization’s strategies and marketing campaigns. Simply put, if the right data is not available, or the quality of data is not up to the mark, analysts will end up making wrong decisions, which would have a trickledown effect from the higher echelons of the management teams, right till the lower levels within an organization.

When one talks about marketing, the first thought that comes in mind is customers. Every business, enterprise and organization out there deals with customers in some form or another. In other words, if customers don’t purchase products or avail the services offered by these organizations, the very purpose of marketing will be lost.

Since marketing is all about customer acquisition, it’s very important to have a well planned marketing campaign, which is backed with endless amounts of well defined analysis. But how does one make sound inferences, which will feed the very essence of strong strategies? Data is the answer to all problems.

Marketing campaigns and how poor quality data can affect the campaigns adversely.

If the data quality is poor, there are very strong chances that all aspects related to lead generation, sales driving opportunities, finance, customer relationships, etc. will go for a toss. On the other hand, if the data quality is good, it would strongly mean better customers who are loyal to the business, lesser time will be spent on prospecting, and the business can successfully generate higher revenues for itself.

How does a business realize the data quality is not up to the mark?

Missing date, inaccurate details, used customer details, are all examples of bad quality data. Imagine a situation wherein you have a data set and some of the prime fields like customer’s address, email id and phone number is missing. In such situations, you would most probably end up at a dead end, since the Internet might not be able to provide the required accuracy while sourcing the data within the missing fields. End result: you lose a customer, which might have ended up becoming a potential customer for your business. Such opportunity cost for the business can be a deterrent, and can affect the marketing efforts adversely.

Let’s take another example of bad data. Companies most of the times use CRMs to manage their customer and other related data. If the source of this CRM has duplicates in it, or has misspelled customer names, addresses, email IDs etc., the CRM might send out wrong mailers to the customers. If the CRM is triggering automated mails, and using the data directly from the CRMs database, chances are, either the mails will not get delivered to the intended recipients, or you will end up harassing the customer with a series of wrong emails. Either way, it will not be a win situation for either of the parties involved.

Effects of bad data on a successful marketing campaign:

So we have established how to check if the data quality is not up to the mark. Now let’s try to understand the impact bad data quality can have on a good, successful marketing campaign:
• Angry customers: If you are sending out emails on wrong email ids, there will be multiple email bounce backs. Such bounce backs will have their own repercussions with the service provider. Apart from that, if the email IDs are correct, but the details of the customers are wrong, chances are you will end up with an annoyed customer, who will not be happy seeing his/her details misspelled. In such situations, it is often advisable to check the source data, before releasing any kind of communication mails.
• Wrong data gives wrong insights about the competition: If the data is not correct, or the numbers are inaccurate, there are high possibilities of driving incorrect insights from the data. If decisions are based on these wrong insights, the business might end up running into losses, or underestimating their customers/marketing strategies.
• Pipelines become slow: Wrong date, missing fields, etc. can dent the whole concept of a marketing campaign. The whole idea of driving accuracy within the organization’s marketing campaigns is to be able to onboard new customers, in a short span of time. However, if the business has to spend endless number of hours manually updating data errors, there will hardly be any time spent on on-boarding new customers.