BIA/Kelsey Bytes are excerpts from research reports. This is the latest installment from the recently launched report, Call Commerce: A $1 Trillion Economic Engine. It picks up where last week’s post left off.
The report can be downloaded for free here.
Call Analytics: Tying it All Together
Though consumer voice and calling behavior set the foundation for the call commerce opportunity, the real meat is in call analytics. This is the science of tracking, recording, analyzing and optimizing inbound phone leads – a field that’s quickly evolving in the age of big data.
We won’t spend too much time introducing the basics of call analytics, which can be found in our previous report. However, it’s worth a quick explanation for those unfamiliar. The best way to think of it is like Google Analytics — or any ad analytics tool — but for calls instead of clicks.
From a historical viewpoint, as seen in this report’s introduction, most of the foundations for call analytics are in measuring structured data. That includes things like the meta-data of a given inbound business phone call – its source, duration, caller identification, and other binary factors.
The future of call analytics is in the more complex but opportune unstructured data. This includes nuanced and contextual data such as the contents of a call. At basic levels, it’s what was said on the call… at complex levels it’s deeper machine learning and pattern recognition.
This presents challenges because it applies digital analysis to voice, a mode that doesn’t follow the properties of digital media as neatly as click streams or e-commerce. It requires deriving meaning from content that has nuances and variations, such as voice inflection.
But once this meaning is derived, it can be enormously valuable. The outputs and application of such data include insights on ad campaign effectiveness and ROI. High-value leads and conversions can be tied to campaigns, using attribution tactics detailed in the next section.
The benefits of attribution insights include reporting ROI to advertisers. But it is also valuable as an optimization tool. For example, search ad campaigns can iterate and optimize keywords and ad groups based on the knowledge of which tactics are driving the highest-value leads.