Despite data being discussed relentlessly over the past few years, people are still making some basic mistakes. This week’s blog is addressing some of these common blunders that, with a little tweak here and there, can be rectified quite easily.
1. Not collecting data in one unified place
We’re all guilty of this one. Data capture can come from a variety of sources, and as a result be collected in a variety of locations. Making sure this data is all input and kept together can easily get pushed to the bottom of the ‘to-do list’.
Critical data can be left fragmented in: your sales team inbox, the organisations database, the website analytical data, the newsletter sign-up list, and more.
When all this data is collected but not kept together, it makes for skewed results when conducting analysis, as well as lost potential when sending out marketing communications.
2. No consistent data input guidelines
No matter where or when data is input into a file, it needs to be in a consistent format. Mismatched data is a nightmare for data processing and analytical tools. To counter this try implementing mandatory fields of data right from the beginning. This can include: the field structure, the field types and order of the fields in the file. There is no perfect structure; it just has to be consistent.
3. Not segmenting your data
It is important to segment your data to ensure you are not communicating to everyone in the exact same manner. If you look for clusters of similar attributes within your database you can tailor your communications to get the best results.
These clusters may include: location- at the most basic level, or spend and interests at the more granular level.
4. Not coding data segments
Measurement is the key to learning, and coding is the key to measurement. Ensure that when you segment and communicate to your customer base everything is coded and these codes are recorded with their matching descriptors available for all to access. This is such a simple oversight and it is an effective way to measure and to learn for future communications.
5. Not updating your data
Old, outdated data is worse than no data at all. It is a waste of time and resources to communicate to these people and it can result in serious brand damage using outdated information.
A common mistake is to hoard this old data ‘in case it comes in handy one day’. That day may, and will probably, never come. Keep it clean people.
6. Lackluster processes for opt outs/ removals
Apart of updating your data includes ensuring that you remove records that have asked not to be contacted. It may be that you do not even know that these people are trying to opt out of your communications if your procedure and protocols and not working properly. This is something that should be addressed to ensure all opt outs are removed in a timely manner. For assistance with this pain-point, Prime Prospects can to handle the whole process so you don’t have to. Easy-Peasy.
It may be not quite as dramatic as this, but still – addressing the above points when next working with your data will find you in a more comfortable situation than this little guy!