continued from part 3
This data type will tell you how successful your campaigns are against a set KPI. You can see how many sales were made using direct online campaigns and how many users took action on your offline sales push by clicking for directions or to navigate. This is generally quantitative data.
This data could be
- Engagements with the navigation/direction ads
- Shares, Likes and Comments
Using performance data you can measure success as a rate based on your KPIs. For example, you may have set a Click Through KPI of 5% but you see that your online sales campaigns got only 2% whereas your offline sales campaigns got 15%. With this information, you can begin to try and understand why this may be and how you could use it to optimize your business.
Qualitative Data (insights)
This data type will help you understand the characteristics of the people you have reached with your product or service. This data can be found in your Facebook insights section for example and could provide you with information such as:
- Top locations
- Age groups
- Product preferences
Using this information, you can begin to create a better view on what a good prospect would look like and then update your messaging, targeting etc.
Personally Identifiable Information (PPI)
Most of your analytics systems online will give you aggregate information. This information is anonymised or pseudonymised and gives you overall metrics rather than user-specific information. This is for good reason, it is imperative that you only collect PPI level data when a user explicitly opts-in. Read more about the risks associated with data collection here
Although regulated, getting PPI data can help your sales efforts dramatically as you collect and identify unique attributes about individuals. This can allow you to engage in personalized marketing and sales efforts which would increase your overall return and performance.
This information would usually be stored in a CRM (Customer Relations Management) system. Depending on the system, a sales or marketing team could query the information to return groups of people who have similar attributes that can then be marketed to.
It is imperative that you have your compliance and legal documentation in place if you are planning on gathering, storing or re-using this information for advanced marketing and advertising such as hyper-personalised marketing, remarketing or data-driven programmatic advertising. This is why your team should include a legal or data compliance representative.
Read more in our next article