Managing the customer experience has become increasingly complicated.  The customer’s journey becomes fragmented across marketing technologies, devices and platforms.  The data needed to create audiences that inform the customer’s experience doesn’t just spread across time, it is spread across different systems.

Without a clear roadmap and process for building audiences, companies become quickly overwhelmed with the sheer amount of data available, and all of the technologies that are capturing the data.  Here are 5 foundational elements teams should consider incorporating into their Audience Building process.

1. Trusting Your Data
2. Data Governance
3. Data Integration
4. Identifying Conversion Points
5. Understanding the Data’s Value

I’ll be discussing these 5 elements in a two part series.  This first part of the series will cover Trusting Your Data and Data Governance.  The second part of the series will cover Data Integration, Identifying Conversion Points, and Understanding the Data’s Value.

Trusting Your Data

One of the most fundamental elements in building audiences, whether it’s for advertising purposes, A/B testing, customized experiences or for the monetary value of selling the audience data, is the accuracy of your data. Can your company firmly trust your current data set? Trust, however, has many facets to look at.  From saying ‘yes’ if someone asks if the data is reporting correctly, to evolving the data you are collecting, a team can arrive at two different answers.

Teams need to ensure the data is accurate from a processing standpoint.

• Is the data being collected what you expect to see?
• Is that the data is always being collected when it’s expected to?
• Are all processes involved in the data collection continuing to function properly?

If your team can’t answer positively to the above questions, how can you trust the data you have will build out reliable, trustworthy audiences you can use to inform your spending on advertising or selling of your audience data?

Not only that, stop and think about the data you are collecting.  Is it still relevant to the audiences you need to build?  Analytics implementations from more than 3 years ago might need to be audited and refreshed before you start utilizing the data to build audiences.  Company processes, marketing efforts, products and sales cycles can all drastically change year of year, so revaluating the data you are reporting on is a necessary step before you head into building audiences.

Data Governance

Before anyone builds a variable, segment or an audience a necessary element to ensuring your data is solid is the process of Data Governance.  It’s not a flashy subject and can get quite into the weeds that it can put any analyst to sleep. However, if a governance process isn’t set in place properly a company can find themselves in a “wild, wild west” situation with their data sooner than the anticipated.

Governance can cover a lot of areas.  For financial institutions or healthcare providers it can revolve around being able to collect certain types of data.  For publishers and content developers, governance tends to revolve around naming schemas and taxonomies.  A process for implementing what can be measured, by whom it can be measured and who implements the measurement should be a foundation governance process set in place by all companies.  

Here are some important ideas to keep in mind when setting up your data governance team and processes:

• People & Process: Who can implement, collect & view data, along with the methods around how that data collection is approved & implemented
• Nomenclature:  Do all team members agree that what is being named for data collection means the same across the company? 
• Taxonomies:  Create a specific taxonomy to clearly delineate variables, segments and audiences that may have different types (Real Time vs Historical), belong to different business units, or reflect a specific marketing initiative, product or tool integration.
• Who Has the “D”:  Who needs to approve or have the decision (“the D”) on the data collection process, the data implementation method, the data analysis, and possible cross tool integrations?
• Contingency Plans:  Is there a plan in place to address changes in national, state or country specific changes in data collection laws?  How will you handle “rouge” data collection by teams or people not adhering to the governance process?

Ensuring that your team has a solid governance process and organizational schema in place moves your company in the direction of keeping a foundation of data integrity in place.  This goes even further when you realize it’s not just about allowing certain data elements to be collected that affects your data integrity. 

Having governance in place for “People” is just as important.  The last thing you want happening is a rouge team member as an administrator who then gives additional administrator rights to others who shouldn’t have those rights.  This presents the potential for data elements enabled for collection that shouldn’t be.  It also presents the issue of documentation of the collection set in place by these rogue admins.  One domino hits another and before you know it, data integrity is lost, and no one can trust the data to create segments and audiences.

People and process governance is vital to ensure your company’s data integrity, but also to ensure that you don’t encounter “knowledge gaps” when people on your teams leave and move onto other positions.  Knowledge gap issues also can creep into not just “how” things were implemented but “why” they were implemented and that becomes key to responding to issues around General Data Privacy Regulations (GDPR) in Europe and the upcoming legislation in California, the California Consumer Privacy Act (CCPA) of 2018.

Part 2 of this series will be focusing on the 3 other elements that are foundational to Audience Building; Data Integration, Identifying Conversion Points, and Understanding the Data’s Value.