Data is key to a Marketing Automation strategy that works. As the old saying goes, “good input means good output”. Put another way, “better data gives us a sounder starting point”. Good data is needed, but it does not guarantee good results.
Think of data as the heart of your Marketing Automation setup. The heart does not work well when it is weak.
Data not only needs to be clean for it to be useful. It also needs to be correct.
Take automation driven by leads. Leads are possible customers, people or businesses, whose contact details you have gathered, for example through a form. The leads data can cause problems if contact names are wrong or arrive in the wrong format. That can cause trouble if you run complex automations that rely on the leads data. You might use it to feed lookalike audiences, which an ad platform builds by finding people similar to an existing group, such as your leads. You might also use it to run automated media campaigns with machine learning. The same is true for any other data point or setup.
This applies to more than the data that comes in or goes out. It also applies at the back end, where you store and process the data. That covers the schema and structure of the databases, data warehouses and data pipelines you set up for this. A schema sets which fields a database has and what type of data each one will accept. A data warehouse brings data from many sources together for analysis. A data pipeline moves data from one system to another and may process it on the way.
Again, data is of no use if it is stored or processed wrongly. A Phone Number that is processed and stored as First Name data by mistake is useless. It should be obvious, but you would be surprised how often this error happens.
Data is often used in the conditions, or rules, that trigger automation. That is why it needs to be precise. If the data is not accurate, the rules you set up to trigger the automation may never be met.
Example:
1. Setup
You have set up your data pipeline to take in form data from a web page or an app. By mistake, you set up your automation so it sends form field data to the wrong columns in the database. You have also set a trigger based on data you would expect to see in one of the database columns (“1. DO THIS when Field Value is X” or “2. DO THIS when data is added to Column X”).
2. Errors
The form data is not only processed wrongly (meaning it may be in the wrong format), but it is also stored wrongly.
Sometimes the database will not store any data at all. This can happen when the schema rejects data of a type it has not been set up to accept.
3. Problem
With the example triggers above, the automation may do one of two things. Trigger 1 may not fire at all, because it never gets the data it expects. Trigger 2 may fire, but the processed data would be wrong.
4. Conclusion
You can see how this could be a showstopper, both for the setup and for the business as a whole. It is a common error, and you would be surprised how often it is left unattended.
Good input means good output
The example above shows why Marketing Automation needs clean data to work well. If you want to get the most out of it, the data needs to be correct right from the start.
You will have to take the time to make sure everything is correct. There are no shortcuts. If you skip your due diligence, you could end up with a mass of errors that may turn out to be very costly.
Implementation starts from a sounder base
Do the legwork upfront, and you will have a sounder base for your automation strategy. Other work still matters too, such as the workflow, the costs, testing, and checking on things as they run.
It can help you make more of your marketing, bring your business into the ’20s and stay relevant to your customers. Whether it helps you beat your rivals depends on the work and its results.
Start now and thank yourself later for having done so.
Reach out to me if you want guidance around best-in-class Marketing Automation strategies for you and your business.
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