Overcoming Four Barriers to Data-Driven Marketing
Marketers are drowning in a sea of data and meaningful analysis is becoming ever more elusive. Marketers are overwhelmed and frequently don't know where to start.
Marketing departments are littered with partially executed business intelligence initiatives that fell short of meeting the needs of agile marketing teams. Why? One major roadblock is that these generic BI initiatives are not sufficient for the rapidly evolving, increasingly varied customer engagement landscape. The best marketing data can be extremely difficult to find and use. How can you make sense of this marketing data explosion?
Below are solutions to four core barriers facing teams trying to get actionable value from marketing data.
1. Channel Fragmentation
With the increase of available channels to engage with consumers comes complexity. Channels are changing rapidly and micro-interactions across paid, owned, and earned media are creating unprecedented volumes of diverse data. There are simply too many marketing signals being produced for most marketers to reliably capture and process on their own.
For instance, sentiment data from Facebook is different than audience data from Snapchat, and their formats are incompatible. Add the complexity of marketers using third-party platforms and services to manage their campaigns and the culprits for extremely fragmented marketing data silos become clear.
In a recent survey, we found that over 60 percent of marketers say they are unable to measure and analyze performance across channels as frequently as they would like. This is due to a fragmentation of platforms and disparate systems presenting data in multiple parts and formats instead of delivering one holistic view of all marketing signals. It's clear that ensuring data accuracy and reliability is becoming more challenging, yet it is an essential step before marketers can confidently take any action.
The Solution: To proactively combat this, you need to establish KPIs and a measurement plan that maps back to them. Although that may sound like a no-brainer, there are a surprising number of large enterprises possessing extremely advanced analytics tools but few measurement and analytics experts to actually set goals for using them. What good is a car without a driver and a destination?
When you understand how each new channel contributes to your KPIs, you can focus your measurement implementation efforts accordingly and develop the necessary knowledge to properly cleanse, normalize, transform, and analyze data within and across channels. Organizations that skip these steps will have a hard time delivering great customer experiences across channels.
2. Rapid Change
Along with the increase in channels, data sources are changing rapidly. Third-party platforms make changes often and keeping up with these changes is not a trivial task -- especially if they are accessed programmatically via APIs.
For example, public APIs from Facebook, Twitter, and others are constantly making changes and need to be actively managed to ensure data accuracy and completeness. In addition, each platform has its own set of measurement standards and ways of slicing and dicing information. Making matters even worse, many APIs are not public and require account-by-account authorization and integration.
The Solution: Organizations must invest in people first -- specifically, people who understand marketing technologies and analytics. It is impossible (and economically untenable) for non-specialists to keep pace with all of the available technologies and associated changes. When companies invest in individuals who understand this landscape and how to manage it, they're better equipped to appreciate, diagnose, and enlist the right partners.
If you don't have a marketing technology leader in-house and don't have the budget for a full-time employee, start by leveraging an agency or consultant. No team can be data-driven without fundamental measurement and analytics knowledge. That knowledge leads to success by altering decision making, how teams work together, and the experiences those teams ultimately deliver.
3. Multiple Dimensions
There is no such thing as a universal method of measurement. Unification of data dimensions across platforms and services does not exist. With the different formats, schema, metric definitions, etc., it is difficult to combine data sets for cross-channel analysis or compound metrics. If a marketer is running six campaigns with eight KPIs, delivering 50 ads over 30 days in six countries, analyzing and gaining insights from the resulting marketing signals and performance data can be extremely challenging.
A prime example of inconsistency is that third-party platforms often define the start of the day at different times. Some might have a GMT timestamp. Another example is the ability to make cross-channel data associations. As mentioned, different sources treat assets and metrics differently. This becomes a challenge when looking across social, paid, owned, and earned media data -- especially as the way a platform defines the start of the day could change at any moment.
The Solution: If your organization hasn't invested in a platform to identify, transform, and normalize your marketing data to address issues associated with differing formats, timeframes, and metrics, you'll need to identify where these issues exist.
Ideally, you tackled this step in your initial measurement plan to ensure your marketing data outputs could be used for apples-to-apples comparisons. If not, you'll need to take a step back and investigate where these issues exist before you can methodically prioritize and address them.
This can be disruptive because it will likely alter the current and historical channel data feeding the core marketing reports reviewed by stakeholders. However, it is an absolutely critical step, so be sure to set expectations and inform teams that your efforts will ultimately improve the accuracy and comparability of marketing data.
4. Data Lag
The inability to access APIs can result in significant data gaps, as changes to APIs can be poorly documented and happen without any prior notice. If your organization relies on third-party sources and service providers, gaps in your data can inhibit marketers from taking action and optimizing in-flight campaigns quickly.
Like the other barriers noted above, these circumstances can be difficult to catch. Oftentimes the data gaps are small, but occasionally they can be large and remain unnoticed for weeks because (a) the contribution from a given source isn't big enough to deviate significantly from the mean or (b) the gaps occurred during an event, promotion, or other marketing activity that was incorrectly assumed to have caused the observed dip. Unfortunately, the latter is not an uncommon circumstance, especially in organizations with meager analytics departments.
The Solution: The best way to resolve this problem across an ever-expanding set of channels is to invest in a tool that automatically identifies errors and anomalies and alerts you when they occur. The best marketing data solutions also employ experts who proactively work with scores of APIs to quickly resolve these issues at the source on your behalf. An organization with a winning combination of effective technology solutions and experienced marketing technologists will be able to overcome data lag.
Set up Your Team for Success
Many of the most important marketing signals are often missed because of drastic differences in the makeup of marketing data. Marketing data is inherently inconsistent, so proper measurement and analysis can be extremely difficult. However, although it will never be easy for organizations to unify marketing data, it is a challenge worth tackling.
Putting marketing campaign dollars to effective use depends heavily on accurate and reliable data. The organizations that set up their marketing teams for success will deliver the best data to drive comprehensive (and actionable) analytics.