Data driven is the foundation of the marketing success of many companies and organizations. Data and tools are important success factors here, as are the organization and the people who work here. In order not to immediately spend a lot of time and budget on extensive change processes, it is advisable to start ‘lean and mean’ with a data audit; an inspection of your existing marketing and sales data and tools. Once that basis is in order, you can start optimizing processes and organization.
Just like with the inspection of your car, a data audit follows a number of checkpoints. These checkpoints lead you to practical points for improvement with which you can optimize your data driven marketing and thus maximize your results. In this article I will take you through the checkpoints of the data audit.
The main checkpoints of a marketing data audit are:
To start, you check your goals and the KPIs derived from them with a data audit; are they present and are they SMART (Specific, Measurable, Acceptable, Realistic and Time-bound)? For a data audit, the S for Specific and the M for Measurable are very important; if KPIs cannot be translated into metrics (measurable or calculated variables), it becomes difficult to ultimately measure your goals and improve them data driven. If there are goals or KPIs to which no metrics can be linked, reconsider them.
Once your goals have been set and set, define the drivers. Drivers are the variables that drive and influence your goals. Examples of drivers are date or periods, channels, campaigns, advertisements, search rankings, content, target groups or personas. Drivers reinforce and weaken each other, which is why it is important to use a key influencer or cluster analysis of, for example, your Google Analytics and/or CRM data to find out which combinations of which drivers, and which values thereof, drive and influence your goals.
Then we come to the collection; collecting and recording data. At checkpoints 1 and 2 you have already defined which targets and driver data you need to collect. At this third checkpoint you check whether and how you actually collect or can start collecting this data, where you collect it, and whether you collect that data correctly. By ‘correctly’ I mean the level (the more detailed and the less summarized or calculated the better), the correct data type (numeric, text, date/time, etc.), the correct frequency (per minute or hour, daily , weekly, monthly, yearly), and the correct location (see checkpoint 4).
For many marketers, tools are the nicest part of this exercise; new glimmers that we add to our collection like magpies. When selecting your martech tools and setting up your martech stack, it is important to make an inventory of whether the data you have inventoried at checkpoints 1 to 3 is processed and stored correctly (do not forget the legislation, such as CCPA and GDPR privacy laws).
For storage you can roughly choose from (combinations of) your web analytics tool such as Google Analytics, campaign tool(s) such as Google/Facebook Ads or a marketing automation tool, CRM system, a database, and your dashboarding or business intelligence tool . In the latter, you calculate and visualize calculated KPIs such as CPS or customer lifetime value, and save them.
In a data model you record the relationships between your goals, drivers, collection and tools. This is important for both the ultimate design of your tools and martech stack (checkpoint 4) and for monitoring (checkpoint 6). The more goals and drivers and/or the more complex your martech stack, the more extensive your data model. This sounds more complicated than it is, but most marketing and sales data models fit on one A4 page. You can find examples of such data models here.
In order to be able to adjust your marketing and sales activities in time, it is important to maintain insight into the status of your goals to be achieved. To do this, you monitor the values of your goals and your drivers in real time, since the latter direct and influence your goals. You have previously determined which goals and drivers you will be monitoring and recorded at checkpoints 1 and 2.
For this monitoring you use dashboarding or business intelligence tools such as Google Data Studio or Power BI. Do not forget to add a data quality report or dashboard in which you measure and visualize any differences between data from different systems, such as the number of measured leads in Google Analytics vs. those in your CRM system.
Back to work
This article gives you an overview of the important first steps you need to take to get your marketing and sales data in order. If you want to get started with this and if you have any questions, contact me for help or support.