Vinton Cerf, the chief Internet evangelist for Google, said in a conference once, “So, for me, working with larger companies has often been very satisfying, precisely because of the ability of bringing critical mass to bear on a given effort.”
On one hand, critical mass may represent the minimal amount of venture capital funding required to launch an enterprise-level endeavor. However, from an analytics lens, critical mass could also represent the minimal focused insights needed for stakeholders to make critical decisions with a high confidence level.
With so much data-oriented noise to sift through, analysts must continually explore innovative ways to identify and communicate relevant, meaningful, and contextual qualitative, and quantitative, stories. In order to maximize analytics efficiency, analysts should be wary of falling into the trap of collecting data just for the sake of data collection. This is best accomplished by working directly with internal and external stakeholders to identify the key questions to solve for, and then through the isolation, extraction, codification, evaluation, and interpretation of related heart beat performance success metrics.
Ultimately, such observation and recommendations for organizations lead toward optimal efficiencies that impact an organization’s bottom line. As a result, analytics professionals must build relationships of trust with stakeholders, assist in defining key performance and revenue indicators, encourage stakeholders to formulate questions and hypothesis that may be measured and tested, and learn how to tell a compelling data-driven story, tell that story right, and tell that story right now.
One emerging story is how consumers are becoming more sophisticated than ever before. Google pointed out that a generational platform shift has occurred towards mobile devices.
Don Dodge, a developer advocate at Google, described that platform shifts tend to occur every decade. He noted that a platform shift happened from mainframes to mini computers, then from mini computers to desktop computers.
On the mobile front, Google provided a glimpse into what such a phenomenological shift looked like. In a slideshow created by the Google analytics developer relations team two pictures were shown from St. Peter’s Square. The first picture, from 2005, showed a large crowd gathered for Pope John Paul II’s funeral. One early adopter could be seen in the bottom-right corner of the picture, holding up a mobile device to capture the moment. The second picture, from 2013, showed a large crowd gathered in the same location for a talk given by Pope Francis. This time, almost every individual in the picture could be seen holding up a mobile device, or tablet, to capture the moment.
Google discovered that for users worldwide, their primary intent was to capture, share, engage, and interact in moments that matter.
Consumers have taken this platform shift a step further. Google conducted a study of 1,611 participants in Boston, Austin, and Los Angeles. In this evaluation, entitled The New Multi-screen World, Google discovered that 90 percent of people employed multiple screens sequentially to accomplish a task over time, and 98 percent of them moved between devices on the same day.
Further, mobile interactions represented the starting point for a majority of online interactions. With mobile device viewing time the lowest of all device types, at an average of 17 minutes per day, the implication is that consumers have not been relying on mobile devices to complete their online interactions.
Google found that people typically reserve complex tasks, such as handling finances or booking travel, for desktops. However, they tend to complete social interactions primarily from their mobile devices, and watch movies or browse from their tablets.
Interacting in moments that matter from multiple devices are typically driven by context. Four primary context points include goal orientation, location, user attitude, and time. While user attitude and goal orientation may be more challenging to determine intent, location may be determined through geographic-mapped coordinates tracked through GPS location monitoring, and time can be isolated and tracked through time-parting.
In any case, optimizing for multi-device interactions is at the acme of conversion goal fulfillment and better understanding the customer journey. It is simply not viable for an organization to attribute marketing spend on generic defaults, such as last click or first click touch points.
With an increasing number of users conducting sequential screening to complete conversions, ranging from online retail transactions to lead generation form completions, attribution must be more carefully considered and accounted for.
ComScore provided a revealing view into device usage in the U.K.
Usage patterns may be differentiated by transatlantic cultural and behavioral norms. However, the intersections and inflection points for multi-device transitions are indicative that organizations must customize their organic and paid search strategies to reach users in order to increase conversions while decreasing their spend.
Google recognized this need through the recent implementation of Enhanced Campaigns for AdWords. Time-parting and location can be accounted for as adjustments to a single campaign. This is a significant shift.
With Google’s legacy product, if a marketer wanted to target a particular advertising campaign that accounted for 50 different geo-locations and 10 different time-parted segments, then 500 individual campaigns would need to have been created, resulting in a campaign management nightmare.
Further, Enhanced Campaigns for AdWords can be integrated directly into Google Analytics, resulting in optimal performance measures for most productive campaign time parts (e.g., hours in a day, or days in a week), conversion tracking through multi-channel funneling, and other reports that enable a telling view into the multiple stages of the consumer purchase life cycle.
The need for analytics experts to track users across multiple devices is increasing. However, the complexity in tagging and accounting for user interactions across multiple devices is increasing as well.
Google now offers universal tags that can account for multi-device usage. This is accomplished through a single cookie that assigns a new unique user ID (UID parameter) across all devices that a consumer engages with, coupled to the legacy client ID (CID parameter).
Through multi-device optimization techniques, such as time-parted look back windows or user outcomes segmentation by device paths, analysts may come one critical step closer to assisting companies in actualizing conversion goals and capturing true acquisition value by device, time, and location. It’s ultimately through these custom tailored fulfillments that we can increase monetization as well as user satisfaction.