Share this:

Preparing for Marketing Automation – Data Cleanse

Preparing for Marketing Automation – Data Cleanse

September 30, 2014 - Opinion

Yes, I'm sorry, we are going to talk about it! Data cleansing is that fearful task that everyone postpones, hands over or forgets about. However, it is one of the most important aspects for successful marketing automation, and successful business in general.

Recent research from Sirius Decisions (see graphic on the side column) emphasises the importance of data cleansing, and the impact that bad data has on demand creation.

As an example from this report, Sirius Decisions insists that a strong organization (i.e. one where data inaccuracy is only about 10% of the total database size) “realises nearly 70 percent more revenue than an average organization purely based on data quality”.


Data cleansing is serious business

It is a continuous process that should ideally begin when looking at any new marketing automation tool and planning its implementation, and which eventually needs to become second nature to sales and marketing departments – we will get to this later – by including it in a [insert periodicity here]* practice. However, if you have already implemented a marketing automation tool, it is certainly not too late to improve your data either!

In general, people feel overwhelmed by the task, and have difficulty deciding how to prepare for it. The first thing you will need to do is a data audit. From there my advice is to start small and continue building up.

For your data audit you will need to look at what fields are most needed for your marketing segmentation, what fields are not used by people (and whether they should be), what fields you are missing (but perhaps should be included to be able to target better), and what fields have the wrong field type (e.g. you probably do not want to have an open text type field for "country", but instead, use a selection list to be able to normalize data). Once you have identified those criteria to evaluate, you should look at field completeness and also whether the data that the field contains is valid/correctly spelled according to your selection lists. You can easily get full data reports from your marketing automation tool, which you will use later to confirm correct values and replace wrong ones.

Start small – big results!

As mentioned above, after the audit...start small! The results of the audit can be overwhelming, but there is no need to tackle it all at the same time. One area to work on is on data standardization and applying rules if those did not exist before. This data management playbook can be a useful tool to get that started.

So, when do you think you will start cleaning your data? Reach out to me if you have questions or need ideas on how to start your data cleansing exercise.

Happy cleaning!!

Want to receive similar content?






* how often to clean data is a very frequent question posed to consultants. My answer would be: the most frequent the better of course, as you will then guarantee your data quality. But a constant data cleansing exercise is something that very few can afford** So being realistic, this is something that needs to be looked at, at a minimum, once a year, but ideally, quarterly cleansing exercises are recommended.

** then again, that is where Marketing Automation can also help you! Have you heard of the name analyzer or data washing machines?

References:
Sirius Decisions report available here; or here

Zuriñe Garcia

Senior Marketing Automation Consultant

Thank you for reaching out to us, we will be in touch.

Share this: