It takes more than a wealth of data to transform a company.
In fact, too much data can be a bad thing: Without guidance on what to collect, where to store the findings and what to do with them, companies can find themselves adrift in a sea of numbers and figures.
Despite this danger, over the past several years, we’ve witnessed numerous companies focus on collecting as much data as possible without defining the end game. This deviates from the idea that data is an asset—when, truly, there are real costs associated with collecting it, such as maintenance, storage, training and streamlining processes that turn data into experiences that delight.
The goal of brands shouldn’t be to collect as much data as possible, but rather to collect data with intention—ensuring it is aligned to the company’s business objectives and avoiding attributes and metrics that may be less impactful.
Here’s more on what those intentions might be, what factors are driving changes in data usage and how to capitalize on those trends:
Collect the Right Data
Begin by taking the longest of views. Consider your brand’s objectives for data and begin breaking those down into use cases. This effort will illuminate the intentionality behind the data you will eventually collect: Is the goal to answer a business question, to define a strategy, to interpret a certain type of experience or to amplify the way an experience is currently customized? Then, with the intention in mind, the focus becomes pinpointing what data you need in order to bring that use case to life—anything that doesn't fit into one of those use cases is just superfluous data.
Taking the time to map data’s intention to use cases is of paramount importance even for companies who think they already understand their purpose for data collection. In our experience, even clients who have the infrastructure in place for data collection and management may fall short on activating it to its fullest potential.
Under-utilizing data to derive insights, optimize an experience or deliver personalization is a common shortfall. To combat this, one of the first steps is to develop a data and analytics framework that considers who the end users are internally and their level of maturity with data. With that baseline, human-centered understanding, organizations can begin to develop their data muscles and mature how intentionally data is applied.
How to Use Data
The ability to report on data is certainly important and serves as the foundation of an exceptional customer experience strategy. Beyond reporting, however, is the ability to derive insights within the context of your goals. This shift from passive reporting to active insight generation is one of the primary chasms we see in growing data maturity and adoption across organizations.
One step further than insights is actual data activation. The “insights to action” cycle is where the real power of data manifests itself. With use cases for the customer experience defined, data is the fuel for segmentation, targeting, personalization, digital experiences and marketing automations. In a virtuous cycle of activation, measurement and optimization, data becomes the lynchpin of success.
At Rightpoint, we can’t stress enough the importance of defined use cases and intention for data – including a plan for testing and learning – because this virtuous cycle can quickly become unwieldly due to KPI overload, ill-equipped internal users, analysis paralysis and an abundance of data activations occurring simultaneously without strong orchestration.
The COVID Effect
The impact of COVID can be felt in these discussions, with one major caveat: The digital shift associated with the pandemic isn’t necessarily responsible for increased importance in data intentionality. Rather, it just makes the need for data intentionality more present and has accelerated shifts in behavior among customers.
A couple of reasons for that: Data has proliferated as more consumers move to digital formats—particularly those consumers who may not be as digitally savvy. With the depth and breadth of data available across audiences and sources that capture interactions, there needs to be a stronger strategy around how data is used to customize the experience for a broader, more diverse digital audience. Another critical consideration is to ensure that how data privacy and security protocols are communicated reaches these diverse audiences in a way that resonates
Spreadsheets full of data and infinite BI dashboards look impressive. But without a strategy for how to use the KPIs and insights, much of the data collected, massaged and surfaced will sit unused.
Data intentionality subverts this issue. By understanding precisely which data is required to make informed business decisions or activate customer experiences, your strategies can effectively home in on just those points, avoiding wasted effort in collection, data management and teams trying to extract value. Data intentionality is key to an efficient and effective data ecosystem, and that efficiency directly translates to increased speed in taking action on the data that powers your business.
Learn how to better prioritize data collection by checking out this video featuring Stephanie Bannos, VP of CX Strategic Solutions, and Kathleen Lukasik, Group Director of Analytics, discussing data intentionality—and reach out to Rightpoint today.